logseq/assets/storages/logseq-citation-manager/paperpileDB.json

[{"key":"0_GettingStarted","type":"online","fields":{"title":["0_Getting Started |"],"url":["http://self-star.imag.fr/?page_id=63"],"urldate":["2016-12-02"]},"creators":{}},{"key":"0003BCT23","type":"inproceedings","fields":{"langid":["english"],"author":["Delgado, David","Burgueño, Lola","Cámara, Javier","Troya, Javier"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS 2023 Companion Västerås Swed. Oct. 1-6 2023"],"date":["2023"],"doi":["10.1109/MODELS-C59198.2023.00129"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nA web-based architecture designed to support the definition of domain models and provide translation capabilities to different verification formalisms and it is shown how this tool has been used to verify properties for the public bus management system in the city of Málaga, Spain."],"pages":["806–810"],"publisher":["IEEE"],"timestamp":["Fri, 05 Jan 2024 16:35:45 +0100"],"title":["Towards an extensible architecture and tool support for model-based verification"]},"creators":{"author":[{"lastName":"Delgado","firstName":"David"},{"lastName":"Burgueño","firstName":"Lola"},{"lastName":"Cámara","firstName":"Javier"},{"lastName":"Troya","firstName":"Javier"}]},"sentenceCased":true},{"key":"01_YourFirstComponent","type":"online","fields":{"title":["01_Your first component with the IDE |"],"url":["http://self-star.imag.fr/?page_id=196"],"urldate":["2016-12-02"]},"creators":{},"sentenceCased":true},{"key":"02_UsingComponentProperties","type":"online","fields":{"title":["02_Using component properties to configure instances |"],"url":["http://self-star.imag.fr/?page_id=198"],"urldate":["2016-12-02"]},"creators":{},"sentenceCased":true},{"key":"0223TOSEM20240012Pdf","type":"misc","fields":{"keywords":["⛔ No INSPIRE recid found"],"title":["02-23-TOSEM-2024-0012.Pdf"]},"creators":{}},{"key":"0229TOSEM20230413_Proof_hiPdf","type":"misc","fields":{"note":["<h1>Annotazioni\n (16/3/2024, 17:09:22)</h1> \n\n- “Sarro, Federica” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”) #5fb236 \n\n- “Sharma, Tusha” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”) #5fb236 \n\n- “Energy-Awareness” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 1) #5fb236 \n\n- “FEDERICA SARRO” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 1) #5fb236 \n\n- “Software tool vendors have developed relevant tools, such as Code Carbon [10] and Experiment Impact Tracker [34], to estimate power consumption and carbon emissions during the training of dl models.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 2) #a28ae5 \n\n- “Implementing a generic method and framework, FECoM, to accurately measure energy consumption at a fine-grained level. Such a method has been instantiated for TensorFlow, to show its feasibility in practice” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 3) #a28ae5 \n\n- “ine-grained Energy Consumption Meter (FECoM)” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 3) #a28ae5 \n\n- “static instrumentation we devised for fine-grained energy-consumption measurement.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 3) #5fb236 \n\n- “measure fine-grained energy consumption” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 3) #5fb236 \n\n- “FECoM identifies a set of target API calls and instruments the code around the identified calls.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 3) #ffd400\n <i>According to what criteria such API calls are identified?</i> \n\n- “FECoM’s measurement module” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 3) #a28ae5 \n\n- “the temperature and energy consumption remain stabl” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 4) #5fb236 \n\n- “Patcher operates at both the method and project levels” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 4) #5fb236 \n\n- “This information allows Patcher to locate the API calls corresponding to the specified libraries.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 4) #5fb236 \n\n- “before_execution_INSERTED_INTO_SCRIPT” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 4) #5fb236 \n\n- “records relevant information such as the total execution time and energy consumed” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 4) #a28ae5 \n\n- “The Project-level script Patcher follows a similar approach as the method-level Patcher by inserting the same source code statements before and after the entire script, enabling comprehensive energy-consumption measurement throughout the project’s execution.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 4) #5fb236 \n\n- “efore_execution_INSERTED_INTO_SCRIPT(” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 5) #ffd400\n <i>Can this placed in the middle of an assignment?</i> \n\n- “after_execution_INSERTED_INTO_SCRIPT” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 5) #5fb236 \n\n- “Executability” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 5) #a28ae5 \n\n- “n the first step, we ensure the executability of the generated patches, confirming that they execute without any syntactical errors.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 5) #5fb236 \n\n- “Pylance” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 5) #5fb236 \n\n- “Automated testing” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 5) #a28ae5 \n\n- “Human evaluation” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 5) #a28ae5 \n\n- “it accurately extracts all the argument values for a given API call” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 6) #5fb236 \n\n- “tool accurately identifies all TensorFlow API calls” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 6) #ffd400\n <i>As far as I understood, it's the user that annotate the code with those special tags, isn't it?</i> \n\n- “API calls made via returned TensorFlow objects from user-defined functions.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 6) #5fb236 \n\n- “We perform two kinds of stability checks as part of the FECoM framework—the temperature check and the energy stability check.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 6) #5fb236 \n\n- “With energy stability check functionality, we ensure that CPU, RAM, and GPU energy observations are not fluctuating” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 6) #5fb236 \n\n- “We execute each project (and each API call, in turn) ten times to ensure the reliability of the measurements.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 7) #5fb236 \n\n- “Intel’s Running Average Power Limit (RAPL): is an interface that allows applications to monitor and control the power consumption of various components, such as the CPU and memory, within Intel processors.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 8) #5fb236 \n\n- “The goal of this study is to develop an approach and framework to measure energy consumption at a fine-grained level (e.g., API level) to understand better the energy profile of APIs of dl frameworks so that it can be subsequently used to make their documentation energy-aware.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 8) #5fb236 \n\n- “API level” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 8) #a28ae5 \n\n- “input data size” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 8) #a28ae5 \n\n- “energy consumption?” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 8) #a28ae5 \n\n- “challenges and considerations in developing fine-grained energy measurement tools for dl frameworks” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 9) #a28ae5 \n\n- “Verdecchia et al. [77] emphasized the significant scarcity of tools, for example, to measure energy consumption, in the Green Artificial Intelligence domain.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 9) #5fb236 \n\n- “uncover the key challenges, underlying reasons and considerations that arise when developing tools measuring energy consumption for fine-grained profiling of dl frameworks and models” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 9) #5fb236\n <i> zotero://note/u/X3FCH6DG/</i> \n\n- “Validating the correctness of the measured energy consumption at a fine-grained granularity is a non-trivial challenge due to the lack of existing tools or benchmarks to measure energy consumption at the fine-grained level” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 9) #5fb236 \n\n- “API level and at the project level” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 9) #a28ae5 \n\n- “method calls belonging to a framework like TensorFlow” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 9) #ffd400\n <i>This needs to be clarified. They are measuring the consumption related to the usage of frameworks like TensorFlow, right? (not the framework it self....)</i> \n\n- “Therefore, the sum of the energy consumed by the measured methods must be less than the total energy consumed by the project” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 9) #5fb236 \n\n- “Where methods 𝑚𝑖 for 𝑖 ∈ {1, 2, · · · , 𝑘 } are in the scope of energy measurement (e.g., TensorFlow methods and API calls in the considered project code) representing 𝐸 (𝑀𝑠 ) and, hence, measured by FECoM.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 9) #ffd400\n <i>AN explanatory example to concretely show the different ingredients of the equation would make the paragraph easier to understand.</i> \n\n- “investigating the relationship between energy consumption and execution time at the API level granularity” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 9) #5fb236 \n\n- “Previous research suggests a linear relationship between energy consumption and execution time [11]” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 9) #5fb236\n <i>THis is interesting for the [[PAPERS/MT-ENERGY-CONSUMPTION]] paper.</i> \n\n- “his assumption holds when the power 𝑃 remains constant, as energy consumption 𝐸 is given by 𝐸 = 𝑃 × 𝑡, where 𝑡 represents the time duration.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 9) #5fb236 \n\n- “the relationship between energy consumption and parameter size is not known” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 10) #5fb236 \n\n- “FECoM to determine the concrete relationship between these two aspects” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 10) #a28ae5 \n\n- “we measure energy consumption by an API call multiple times, changing the passed parameters’ data size” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 10) #5fb236 \n\n- “RQ3. This RQ explores and discusses the key considerations as well as challenges that one may face while designing and developing frameworks and tools similar to FECoM for fine-grained energy consumption measurement.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 10) #5fb236 \n\n- “meeting minutes” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 10) #5fb236 \n\n- “(1) Coding process:” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 10) #5fb236 \n\n- “(2) Iterative process:” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 10) #5fb236 \n\n- “(3) Emergent coding:” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 10) #5fb236 \n\n- “(4) Constant comparison:” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 10) #5fb236 \n\n- “The following criteria were used to select a dl project repository for evaluating the RQs.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 11) #ffd400\n <i>Only one DL project has been analyzed? Check if this is in the threats to validity.</i> \n\n- “Additionally, the tutorials are continually updated to work with the latest TensorFlow versions, maintained by a team of more than 800 contributors.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 11) #5fb236 \n\n- “3.4 Experimental Environment” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 11) #5fb236\n <i>THis is interesting for the [[PAPERS/MT-ENERGY-CONSUMPTION]] paper.</i> \n\n- “The GPU exhibits an idle power of 18 Watts and maximum power consumption of 290 Watts.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 11) #5fb236 \n\n- “The frequency at which energy measurement samples are captured and retrieved is an important factor in measuring energy consumption.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 11) #5fb236 \n\n- “However, using a lower frequency sampling interval can also result in situations where energy consumption readings at API granularity cannot be captured precisely.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 11) #5fb236 \n\n- “We adopt best practices from the literature to achieve and maintain stable conditions during measurements” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 12) #ffd400\n <i>How? Reducing the power or what?</i> \n\n- “setting the cpu power policy to performance mode ensures it operates at maximum frequency” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 12) #5fb236 \n\n- “minimize background processes on the machine related to energy measurement.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 12) #5fb236\n <i>THis is interesting for the [[PAPERS/MT-ENERGY-CONSUMPTION]] paper.</i> \n\n- “Stopping unnecessary background processes” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 12) #5fb236 \n\n- “f the sum of energy consumed by the measured APIs is greater than the energy consumed by the entire project, then the proposed approach is falling short of measuring energy consumption at the fine-grained granularity” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 12) #5fb236 \n\n- “Such a variance stems from different amounts of energy consumed by methods not in the scope, i.e., 𝐸 (𝑀𝑜 ).” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 12) #5fb236 \n\n- “𝐸 (𝑃) &gt;&gt; 𝐸 (𝑀𝑠 )” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 12) #5fb236 \n\n- “We perform statistical tests to determine the significance of the observed differences in energy consumption between method-level and project-level measurements.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 12) #5fb236 \n\n- “Based on the results of the one-tailed Wilcoxon signed-rank test, we can conclude that there is a statistically significant difference between the method-level and project-level energy consumption for all energy types (CPU, GPU, and RAM).” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 13) #5fb236 \n\n- “the sum of method-level energy for a project is less than the project-level energy consumption.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 13) #a28ae5 \n\n- “negative average RAM” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 13) #ffd400\n <i>The negative value for RAM energy consumption for some of the considered project is not clear.</i> \n\n- “igure” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 14) #ff6666 \n\n- “FECoM enables drilling down into energy consumption patterns within real dl code, empowering developers to write greener, more efficient AI applications” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 14) #5fb236 \n\n- “Summary of RQ1: The results provide strong evidence of the effectiveness of FECoM energy consumption measurements at a fine granularity” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 15) #ffd400\n <i>This is a good remark. However, I'm missing an explicit discussion about using the output. What is the take away message that we can learn and that we can leverage on?</i> \n\n- “varying input data sizes.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 15) #5fb236 \n\n- “The figure reveals a linear relationship between input data size and energy consumption for both the CPU and GPU, indicating that 𝐸𝐶𝑃𝑈 (𝑛) and 𝐸𝐺𝑃𝑈 (𝑛) are increasing linear functions for this API call.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 15) #5fb236 \n\n- “𝐸𝑅𝐴𝑀 (𝑛) appears to remain constant.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 15) #a28ae5 \n\n- “The extremely small p-values for CPU, and GPU signify the high statistical significance of these correlations.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 16) #a28ae5 \n\n- “RAM plays a role in the execution at the beginning of the API call execution, where the data is copied to the installed GPU.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 16) #a28ae5 \n\n- “after the data is copied the role of RAM gets over and, hence, we observe low energy consumption from the RAM for the rest of the execution” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 16) #a28ae5 \n\n- “The results show that the energy consumption of CPU and GPU exhibits very strong positive correlation with the input data size” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 16) #a28ae5 \n\n- “Fine-grained Energy Measurement” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 16) #5fb236 \n\n- “ssues that hinder effective energy measurement belong to this categor” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 17) #5fb236 \n\n- “calibration processes to calculate stable energy consumption, maximum allowed temperatures, and wait times specific to the used hardware configuration that can be reused.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 17) #5fb236 \n\n- “It is important to consider the granularity of energy attribution, striking a balance between precision and overheads” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 18) #5fb236 \n\n- “RELATED WORK” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 19) #ffd400\n <i>I would move this section earlier in the paper to motivate the work after presenting the state of the art. Before presenting the FECoM approach, it is necessary to explain what are the limitations of existing techniques and what are the challenges that are not addressed yet. Table 2 fairly addresses such points and shows good motivations to support yet another energy measurement technique.  However, presenting such a table in Section 6 is too late. Thus, I suggest moving such a table before the approach section and adding descriptive texts introducing and motivating the considered comparison features. I would also include technologies like Monsoon in the table to present a complete view of the field. Finally, I would also complete RQ3 with a set of criteria that users can consider when she has to select the energy measurement technique that best fits the particular requirement at hand. For instance, if the expected granularity is at the system level, FECoM might not be necessary, or if the acceptable sampling rate is a matter of seconds, CodeCarbon can be a possible choice.</i> \n\n- “Running Average Power Limit (rapl) interface [82],” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 19) #5fb236 \n\n- “Power modeling techniques estimate energy consumption by considering factors such as the energy characteristics of the hardware and run-time information.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 19) #5fb236 \n\n- “Roberto Verdecchia, June Sallou, and Luís Cruz. 2023. A systematic review of Green AI. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery (2023), e1507.” (“02-29-TOSEM-2023-0413_Proof_hi.pdf”, p. 25) #5fb236"],"title":["02-29-TOSEM-2023-0413_Proof_hi.Pdf"]},"creators":{}},{"key":"03_ProvidingUsingServices","type":"online","fields":{"title":["03_Providing and using services |"],"url":["http://self-star.imag.fr/?page_id=204"],"urldate":["2016-12-02"]},"creators":{},"sentenceCased":true},{"key":"04_BuildingApplicationMultiple","type":"online","fields":{"title":["04_Building an application from multiple bundles |"],"url":["http://self-star.imag.fr/?page_id=206"],"urldate":["2016-12-02"]},"creators":{},"sentenceCased":true},{"key":"05_iCasaICasaArchitecture","type":"online","fields":{"title":["05_iCasa iCasa Architecture"],"url":["http://adeleresearchgroup.github.io/iCasa/snapshot/architecture.html"],"urldate":["2016-12-02"]},"creators":{}},{"key":"06_TutorialFollowMe","type":"online","fields":{"title":["06_Tutorial Follow me"],"url":["http://self-star.imag.fr/?page_id=61"],"urldate":["2016-12-02"]},"creators":{},"sentenceCased":true},{"key":"10.1007/11871637_49","type":"inproceedings","fields":{"abstract":["Multinomial naive Bayes (MNB) is a popular method for document classification due to its computational efficiency and relatively good predictive performance. It has recently been established that predictive performance can be improved further by appropriate data transformations [1,2]. In this paper we present another transformation that is designed to combat a potential problem with the application of MNB to unbalanced datasets. We propose an appropriate correction by adjusting attribute priors. This correction can be implemented as another data normalization step, and we show that it can significantly improve the area under the ROC curve. We also show that the modified version of MNB is very closely related to the simple centroid-based classifier and compare the two methods empirically."],"author":["Frank, Eibe","Bouckaert, Remco R."],"booktitle":["Knowl. Discov. Databases PKDD 2006"],"date":["2006"],"editor":["Fürnkranz, Johannes","Scheffer, Tobias","Spiliopoulou, Myra"],"isbn":["978-3-540-46048-0"],"location":["Berlin, Heidelberg"],"pages":["503–510"],"publisher":["Springer Berlin Heidelberg"],"title":["Naive bayes for text classification with unbalanced classes"]},"creators":{"author":[{"lastName":"Frank","firstName":"Eibe"},{"lastName":"Bouckaert","firstName":"Remco R."}],"editor":[{"lastName":"Fürnkranz","firstName":"Johannes"},{"lastName":"Scheffer","firstName":"Tobias"},{"lastName":"Spiliopoulou","firstName":"Myra"}]},"sentenceCased":true},{"key":"10.1007/978-3-030-20948-3_19","type":"inproceedings","fields":{"abstract":["IoT-technologies allow for the connection of miscellaneous devices, thereby creating a platform that sustains rich data sources. Given the circumstances, it is essential to have decent machinery in order to exploit the existing infrastructure and provide users with personalized services. Among others, recommender systems have been widely used to suggest users additional items that best match their needs and expectation. The use of recommender systems has gained considerable momentum in recent years. Nevertheless, the selection of a proper recommendation technique depends much on the input data as well as the domain of applications. In this work, we present an evaluation of two well-known collaborative-filtering (CF) techniques to build an information system for managing and recommending books in the IoT context. To validate the performance, we conduct a series of experiments on two considerably large datasets. The experimental results lead us to some interesting conclusions. In contrast to many existing studies which state that the item-based CF technique outperforms the user-based CF technique, we found out that there is no distinct winner between them. Furthermore, we confirm that the performance of a CF recommender system may be good with regards to some quality metrics, but not to some others."],"author":["Nguyen, Phuong T.","Di Rocco, Juri","Di Ruscio, Davide"],"booktitle":["Adv. Inf. Syst. Eng. Workshop - CAiSE 2019 Int. Workshop Rome Italy June 3-7 2019 Proc."],"date":["2019"],"doi":["10.1007/978-3-030-20948-3_19"],"editor":["Proper, Henderik A.","Stirna, Janis"],"ids":["nguyenBuildingInformationSystems2019a,nguyenBuildingInformationSystems2019b,nguyenBuildingInformationSystems2019c"],"isbn":["978-3-030-20948-3"],"keywords":["Book recommendation","Collaborative-filtering","IoT"],"location":["Cham"],"note":["cited By 2 \n\ncited By 2 \n\nTL;DR \n\nThis work presents an evaluation of two well-known collaborative-filtering techniques to build an information system for managing and recommending books in the IoT context and confirms that the performance of a CF recommender system may be good with regards to some quality metrics, but not to some others."],"pages":["214–226"],"publisher":["Springer International Publishing"],"series":["Lecture Notes in Business Information Processing"],"title":["Building information systems using collaborative-filtering recommendation techniques"],"volume":["349"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"}],"editor":[{"lastName":"Proper","firstName":"Henderik A."},{"lastName":"Stirna","firstName":"Janis"}]},"sentenceCased":true},{"key":"10.1007/978-3-030-49461-2_18","type":"inproceedings","fields":{"abstract":["Recommender systems (RS) play a focal position in modern user-centric online services. Among them, collaborative filtering (CF) approaches have shown leading accuracy performance compared to content-based filtering (CBF) methods. Their success is due to an effective exploitation of similarities/correlations encoded in user interaction patterns, which is computed by considering common items users rated in the past. However, their strength is also their weakness. Indeed, a malicious agent can alter recommendations by adding fake user profiles into the platform thereby altering the actual similarity values in an engineered way."],"author":["Anelli, Vito Walter","Deldjoo, Yashar","Di Noia, Tommaso","Di Sciascio, Eugenio","Merra, Felice Antonio"],"booktitle":["Semantic Web"],"date":["2020"],"isbn":["978-3-030-49461-2"],"location":["Cham"],"pages":["307–323"],"publisher":["Springer International Publishing"],"title":["SAShA: Semantic-aware shilling attacks on recommender systems exploiting knowledge graphs"]},"creators":{"author":[{"lastName":"Anelli","firstName":"Vito Walter"},{"lastName":"Deldjoo","firstName":"Yashar"},{"lastName":"Di Noia","firstName":"Tommaso"},{"lastName":"Di Sciascio","firstName":"Eugenio"},{"lastName":"Merra","firstName":"Felice Antonio"}]},"sentenceCased":true},{"key":"10.1007/978-3-030-64694-3_13","type":"inproceedings","fields":{"abstract":["Android mobile applications (apps) rely heavily on third-party libraries as a means to save time, reduce implementation costs, and increase software quality while offering rich, robust, and up-to-date features to end users. The selection of third-party libraries is an essential element in any software development project, and particularly, in Android apps given the fast-changing and evolving mobile app ecosystem. Indeed, deciding which libraries to choose is a challenging problem, especially with the exponentially increasing number of available libraries in the Android ecosystem. In this paper, we introduce, AndroLib, a novel approach to recommend third-party libraries for Android apps. In particular, we formulate the problem as a multi-objective combinatorial problem and use the non-dominated sorting genetic algorithm (NSGA-II) as a search method to find and recommend relevant libraries. We aim at guiding the search process towards the best trade-off three objectives to be optimized (i) maximize libraries historical co-usage, (ii) maximize libraries functional diversity, and (iii) maximize libraries reuse from highly rated apps. We conduct an empirical experiment to evaluate our approach on a benchmark of real-world Android apps libraries. Results show the effectiveness of AndroLib compared with three recent state-of-the-art library recommendation approaches."],"author":["Chouchen, Moataz","Ouni, Ali","Mkaouer, Mohamed Wiem"],"booktitle":["Reuse Emerg. Softw. Eng. Pract. 19th Int. Conf. Softw. Syst. Reuse ICSR 2020 Hammamet Tunis. Dec. 2–4 2020 Proc."],"date":["2020"],"doi":["10.1007/978-3-030-64694-3_13"],"isbn":["978-3-030-64693-6"],"keywords":["Android apps","Search based software engineering","Software reuse","Third-party Software Library"],"location":["Berlin, Heidelberg"],"pages":["208–225"],"pagetotal":["18"],"publisher":["Springer-Verlag"],"title":["AndroLib: Third-party software library recommendation for android applications"]},"creators":{"author":[{"lastName":"Chouchen","firstName":"Moataz"},{"lastName":"Ouni","firstName":"Ali"},{"lastName":"Mkaouer","firstName":"Mohamed Wiem"}]},"sentenceCased":true},{"key":"10.1007/978-3-031-00126-0_26","type":"inproceedings","fields":{"abstract":["Third-party libraries have become an indispensable part of the software. The function provided by well-tested third-party libraries can be reused through their programming interfaces, significantly increasing developers' software quality and productivity of developers. However, the vast number of third-party libraries and the complex dependencies are the main obstacles to efficiently exploiting the available resources. So, advanced methods are needed to explore the dependencies between projects and third-party libraries to make meaningful recommendations. This paper proposes GELibRec, which combines graph embedding and collaborative filtering to recommend libraries to developers. We extract a dataset from the open-source dataset libraries.io, and the experimental results show that GELibRec outperforms these methods concerning various quality metrics."],"author":["Zou, Chengming","Fan, Zhenfeng"],"booktitle":["Database Syst. Adv. Appl."],"date":["2022"],"editor":["Bhattacharya, Arnab","Lee Mong Li, Janice","Agrawal, Divyakant","Reddy, P. Krishna","Mohania, Mukesh","Mondal, Anirban","Goyal, Vikram","Uday Kiran, Rage"],"isbn":["978-3-031-00126-0"],"location":["Cham"],"pages":["332–340"],"publisher":["Springer International Publishing"],"title":["GELibRec: Third-party libraries recommendation using graph neural network"]},"creators":{"author":[{"lastName":"Zou","firstName":"Chengming"},{"lastName":"Fan","firstName":"Zhenfeng"}],"editor":[{"lastName":"Bhattacharya","firstName":"Arnab"},{"lastName":"Lee Mong Li","firstName":"Janice"},{"lastName":"Agrawal","firstName":"Divyakant"},{"lastName":"Reddy","firstName":"P. Krishna"},{"lastName":"Mohania","firstName":"Mukesh"},{"lastName":"Mondal","firstName":"Anirban"},{"lastName":"Goyal","firstName":"Vikram"},{"lastName":"Uday Kiran","firstName":"Rage"}]},"sentenceCased":true},{"key":"10.1007/978-3-319-19069-3_17","type":"inproceedings","fields":{"author":["Khelladi, Djamel Eddine","Hebig, Regina","Bendraou, Reda","Robin, Jacques","Gervais, Marie-Pierre"],"booktitle":["Adv. Inf. Syst. Eng."],"date":["2015"],"editor":["Zdravkovic, Jelena","Kirikova, Marite","Johannesson, Paul"],"isbn":["978-3-319-19069-3"],"location":["Cham"],"note":["TL;DR \n\nThis paper proposes a detection engine of complex changes that simultaneously addresses these two challenges of variability and overlap, and introduces three ranking heuristics to help users to decide which overlapping complex changes are likely to be correct."],"pages":["263–278"],"publisher":["Springer International Publishing"],"title":["Detecting complex changes during metamodel evolution"]},"creators":{"author":[{"lastName":"Khelladi","firstName":"Djamel Eddine"},{"lastName":"Hebig","firstName":"Regina"},{"lastName":"Bendraou","firstName":"Reda"},{"lastName":"Robin","firstName":"Jacques"},{"lastName":"Gervais","firstName":"Marie-Pierre"}],"editor":[{"lastName":"Zdravkovic","firstName":"Jelena"},{"lastName":"Kirikova","firstName":"Marite"},{"lastName":"Johannesson","firstName":"Paul"}]},"sentenceCased":true},{"key":"10.1007/978-3-319-60438-1_47","type":"inproceedings","fields":{"abstract":["Document clustering plays an important role in several applications. K-Medoids and CLARA are among the most notable algorithms for clustering. These algorithms together with their relatives have been employed widely in clustering problems. In this paper we present a solution to improve the original K-Medoids and CLARA by making change in the way they assign objects to clusters. Experimental results on various document datasets using three distance measures have shown that the approach helps enhance the clustering outcomes substantially as demonstrated by three quality metrics, i.e. Entropy, Purity and F-Measure."],"author":["Nguyen, Phuong T.","Eckert, Kai","Ragone, Azzurra","Di Noia, Tommaso"],"booktitle":["Found. Intell. Syst."],"date":["2017"],"editor":["Kryszkiewicz, Marzena","Appice, Annalisa","Ślęzak, Dominik","Rybinski, Henryk","Skowron, Andrzej","Raś, Zbigniew W."],"ids":["nguyen_modification_2017"],"isbn":["978-3-319-60438-1"],"location":["Cham"],"note":["TL;DR \n\nA solution to improve the original K-Medoids and CLARA by making change in the way they assign objects to clusters by demonstrating three quality metrics, i.e. Entropy, Purity and F-Measure."],"pages":["481–491"],"publisher":["Springer International Publishing"],"title":["Modification to K-medoids and CLARA for effective document clustering"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Eckert","firstName":"Kai"},{"lastName":"Ragone","firstName":"Azzurra"},{"lastName":"Di Noia","firstName":"Tommaso"}],"editor":[{"lastName":"Kryszkiewicz","firstName":"Marzena"},{"lastName":"Appice","firstName":"Annalisa"},{"lastName":"Ślęzak","firstName":"Dominik"},{"lastName":"Rybinski","firstName":"Henryk"},{"lastName":"Skowron","firstName":"Andrzej"},{"lastName":"Raś","firstName":"Zbigniew W."}]},"sentenceCased":true},{"key":"10.1007/978-3-319-74730-9_33","type":"inproceedings","fields":{"abstract":["Deciding if an OSS project meets the required standards for adoption is hard, and keeping up-to-date with a rapidly evolving project is even harder. Making decisions about quality and adoption involves analysing code, documentation, online discussions, and issue trackers. There is too much information to process manually and it is common that uninformed decisions have to be made with detrimental effects. CROSSMINER aims to remedy this by automatically extracting the required knowledge and injecting it into the developers' Integrated Development Environments (IDE), at the time they need it to make design decisions. This allows them to reduce their effort in knowledge acquisition and to increase the quality of their code. CROSSMINER uniquely combines advanced software project analyses with online IDE monitoring. Developers will be monitored to infer which information is timely, based on readily available knowledge stored earlier by a set of advanced offline deep analyses of related OSS projects."],"author":["Bagnato et. al., Alessandra"],"booktitle":["Softw. Technol. Appl. Found."],"date":["2018"],"isbn":["978-3-319-74730-9"],"noaddress":["Cham"],"note":["TL;DR \n\nCROSSMINER uniquely combines advanced software project analyses with online IDE monitoring and automatically extracting the required knowledge and injecting it into the developers’ Integrated Development Environments (IDE), at the time they need it to make design decisions."],"pages":["375–384"],"publisher":["Springer International Publishing"],"title":["Developer-centric knowledge mining from large open-source software repositories (CROSSMINER)"]},"creators":{"author":[{"lastName":"Bagnato et. al.","firstName":"Alessandra"}]},"sentenceCased":true},{"key":"10.1007/978-3-540-30549-1_43","type":"inproceedings","fields":{"abstract":["This paper presents empirical results for several versions of the multinomial naive Bayes classifier on four text categorization problems, and a way of improving it using locally weighted learning. More specifically, it compares standard multinomial naive Bayes to the recently proposed transformed weight-normalized complement naive Bayes classifier (TWCNB) [1], and shows that some of the modifications included in TWCNB may not be necessary to achieve optimum performance on some datasets. However, it does show that TFIDF conversion and document length normalization are important. It also shows that support vector machines can, in fact, sometimes very significantly outperform both methods. Finally, it shows how the performance of multinomial naive Bayes can be improved using locally weighted learning. However, the overall conclusion of our paper is that support vector machines are still the method of choice if the aim is to maximize accuracy."],"author":["Kibriya, Ashraf M.","Frank, Eibe","Pfahringer, Bernhard","Holmes, Geoffrey"],"booktitle":["AI 2004 Adv. Artif. Intell."],"date":["2005"],"editor":["Webb, Geoffrey I.","Yu, Xinghuo"],"isbn":["978-3-540-30549-1"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nIt is shown how the performance of multinomial naive Bayes can be improved using locally weighted learning, and that support vector machines are still the method of choice if the aim is to maximize accuracy."],"pages":["488–499"],"publisher":["Springer Berlin Heidelberg"],"title":["Multinomial naive bayes for text categorization revisited"]},"creators":{"author":[{"lastName":"Kibriya","firstName":"Ashraf M."},{"lastName":"Frank","firstName":"Eibe"},{"lastName":"Pfahringer","firstName":"Bernhard"},{"lastName":"Holmes","firstName":"Geoffrey"}],"editor":[{"lastName":"Webb","firstName":"Geoffrey I."},{"lastName":"Yu","firstName":"Xinghuo"}]},"sentenceCased":true},{"key":"10.1007/978-3-540-87875-9_22","type":"inproceedings","fields":{"abstract":["Models are becoming increasingly important in the software process. As a consequence, the number of models being used is increasing, and so is the need for efficient mechanisms to search them. Various existing search engines could be used for this purpose, but they lack features to properly search models, mainly because they are strongly focused on text-based search. This paper presents Moogle, a model search engine that uses metamodeling information to create richer search indexes and to allow more complex queries to be performed. The paper also presents the results of an evaluation of Moogle, which showed that the metamodel information improves the accuracy of the search."],"author":["Lucrédio, Daniel","family=M. Fortes, given=Renata P., prefix=de, useprefix=true","Whittle, Jon"],"booktitle":["Model Driven Eng. Lang. Syst."],"date":["2008"],"editor":["Czarnecki, Krzysztof","Ober, Ileana","Bruel, Jean-Michel","Uhl, Axel","Völter, Markus"],"isbn":["978-3-540-87875-9"],"keywords":["/unread","⛔ No INSPIRE recid found"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nMoogle is presented, a model search engine that uses metamodeling information to create richer search indexes and to allow more complex queries to be performed and to improve the accuracy of the search."],"pages":["296–310"],"publisher":["Springer Berlin Heidelberg"],"title":["MOOGLE: A model search engine"]},"creators":{"author":[{"lastName":"Lucrédio","firstName":"Daniel"},{"lastName":"M.Fortes","firstName":"RenataP.","prefix":"de","useprefix":true},{"lastName":"Whittle","firstName":"Jon"}],"editor":[{"lastName":"Czarnecki","firstName":"Krzysztof"},{"lastName":"Ober","firstName":"Ileana"},{"lastName":"Bruel","firstName":"Jean-Michel"},{"lastName":"Uhl","firstName":"Axel"},{"lastName":"Völter","firstName":"Markus"}]},"sentenceCased":true},{"key":"10.1007/978-3-642-03013-0_15","type":"inproceedings","fields":{"author":["Zhong, Hao","Xie, Tao","Zhang, Lu","Pei, Jian","Mei, Hong"],"booktitle":["23rd Eur. Conf. Object-Oriented Program."],"date":["2009"],"ids":["Zhong2009MAPO"],"isbn":["978-3-642-03012-3"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nThe results show that using MAPO, programmers produce code with fewer bugs when facing relatively complex API usages, comparing with using the two state-of-the-art code search tools."],"pages":["318–343"],"publisher":["Springer"],"title":["MAPO: Mining and recommending API usage patterns"]},"creators":{"author":[{"lastName":"Zhong","firstName":"Hao"},{"lastName":"Xie","firstName":"Tao"},{"lastName":"Zhang","firstName":"Lu"},{"lastName":"Pei","firstName":"Jian"},{"lastName":"Mei","firstName":"Hong"}]},"sentenceCased":true},{"key":"10.1007/978-3-642-37456-2_14","type":"inproceedings","fields":{"abstract":["We propose a theoretically and practically improved density-based, hierarchical clustering method, providing a clustering hierarchy from which a simplified tree of significant clusters can be constructed. For obtaining a “flat” partition consisting of only the most significant clusters (possibly corresponding to different density thresholds), we propose a novel cluster stability measure, formalize the problem of maximizing the overall stability of selected clusters, and formulate an algorithm that computes an optimal solution to this problem. We demonstrate that our approach outperforms the current, state-of-the-art, density-based clustering methods on a wide variety of real world data."],"author":["Campello, Ricardo J. G. B.","Moulavi, Davoud","Sander, Joerg"],"booktitle":["Adv. Knowl. Discov. Data Min."],"date":["2013"],"editor":["Pei, Jian","Tseng, Vincent S.","Cao, Longbing","Motoda, Hiroshi","Xu, Guandong"],"isbn":["978-3-642-37456-2"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nThis work proposes a theoretically and practically improved density-based, hierarchical clustering method, providing a clustering hierarchy from which a simplified tree of significant clusters can be constructed, and proposes a novel cluster stability measure. \n\nTL;DR \n\nThis work proposes a theoretically and practically improved density-based, hierarchical clustering method, providing a clustering hierarchy from which a simplified tree of significant clusters can be constructed, and proposes a novel cluster stability measure."],"pages":["160–172"],"publisher":["Springer Berlin Heidelberg"],"title":["Density-based clustering based on hierarchical density estimates"]},"creators":{"author":[{"lastName":"Campello","firstName":"Ricardo J. G. B."},{"lastName":"Moulavi","firstName":"Davoud"},{"lastName":"Sander","firstName":"Joerg"}],"editor":[{"lastName":"Pei","firstName":"Jian"},{"lastName":"Tseng","firstName":"Vincent S."},{"lastName":"Cao","firstName":"Longbing"},{"lastName":"Motoda","firstName":"Hiroshi"},{"lastName":"Xu","firstName":"Guandong"}]},"sentenceCased":true},{"key":"10.1007/s10462-012-9364-9","type":"article","fields":{"abstract":["Online vendors employ collaborative filtering algorithms to provide recommendations to their customers so that they can increase their sales and profits. Although recommendation schemes are successful in e-commerce sites, they are vulnerable to shilling or profile injection attacks. On one hand, online shopping sites utilize collaborative filtering schemes to enhance their competitive edge over other companies. On the other hand, malicious users and/or competing vendors might decide to insert fake profiles into the user-item matrices in such a way so that they can affect the predicted ratings on behalf of their advantages. In the past decade, various studies have been conducted to scrutinize different shilling attacks strategies, profile injection attack types, shilling attack detection schemes, robust algorithms proposed to overcome such attacks, and evaluate them with respect to accuracy, cost/benefit, and overall performance. Due to their popularity and importance, we survey about shilling attacks in collaborative filtering algorithms. Giving an overall picture about various shilling attack types by introducing new classification attributes is imperative for further research. Explaining shilling attack detection schemes in detail and robust algorithms proposed so far might open a lead to develop new detection schemes and enhance such robust algorithms further, even propose new ones. Thus, we describe various attack types and introduce new dimensions for attack classification. Detailed description of the proposed detection and robust recommendation algorithms are given. Moreover, we briefly explain evaluation of the proposed schemes. We conclude the paper by discussing various open questions."],"author":["Gunes, Ihsan","Kaleli, Cihan","Bilge, Alper","Polat, Huseyin"],"date":["2014-12"],"doi":["10.1007/s10462-012-9364-9"],"issn":["0269-2821"],"issue_date":["December 2014"],"journaltitle":["Artif. Intell. Rev."],"keywords":["Attack detection","Collaborative filtering","Profile injection","Push/nuke attacks","Robustness","Shilling"],"location":["USA"],"note":["TL;DR \n\nVarious attack types are described and new dimensions for attack classification are introduced and detailed description of the proposed detection and robust recommendation algorithms are given."],"number":["4"],"pages":["767–799"],"pagetotal":["33"],"publisher":["Kluwer Academic Publishers"],"title":["Shilling attacks against recommender systems: A comprehensive survey"],"volume":["42"]},"creators":{"author":[{"lastName":"Gunes","firstName":"Ihsan"},{"lastName":"Kaleli","firstName":"Cihan"},{"lastName":"Bilge","firstName":"Alper"},{"lastName":"Polat","firstName":"Huseyin"}]},"sentenceCased":true},{"key":"10.1007/s10664-018-9657-y","type":"article","fields":{"abstract":["Third-party libraries are an integral part of many software projects. It often happens that developers need to find analogical libraries that can provide comparable features to the libraries they are already familiar with for different programming languages or different mobile platforms. Existing methods to find analogical libraries are limited by the community-curated list of libraries, blogs, or Q&amp;A posts, which often contain overwhelming or out-of-date information. In this paper, we present a new approach to recommend analogical libraries based on a knowledge base of analogical libraries mined from tags of millions of Stack Overflow questions. The novelty of our approach is to solve analogical-library questions by combining state-of-the-art word embedding technique and domain-specific relational and categorical knowledge mined from Stack Overflow. Given a library and a recommended analogical library, our approach further extracts questions and answer snippets in Stack Overflow about comparison of analogical libraries, which can potentially offer useful information scents for developers to further their investigation of the recommended analogical libraries. We implement our approach in a proof-of-concept web application and more than 34.8 thousands of users visited our website from November 2015 to August 2017. Our evaluation shows that our approach can make accurate recommendation of analogical libraries. We also demonstrate the usefulness of our analogical-library recommendations by using them to answer analogical-library questions in Stack Overflow. Google Analytics of our website traffic and analysis of the visitors' interaction with website contents provide the insights into the usage patterns and the system design of our web application."],"author":["Chen, Chunyang","Xing, Zhenchang","Liu, Yang"],"date":["2019-06"],"doi":["10.1007/s10664-018-9657-y"],"issn":["1382-3256"],"issue_date":["Jun 2019"],"journaltitle":["Empir. Softw Engg"],"keywords":["Analogical libraries","Categorical knowledge","Knowledge graph","Relational knowledge","Word embedding"],"location":["USA"],"number":["3"],"pages":["1155–1194"],"pagetotal":["40"],"publisher":["Kluwer Academic Publishers"],"title":["What's spain's paris? Mining analogical libraries from Q&A discussions"],"volume":["24"]},"creators":{"author":[{"lastName":"Chen","firstName":"Chunyang"},{"lastName":"Xing","firstName":"Zhenchang"},{"lastName":"Liu","firstName":"Yang"}]},"sentenceCased":true},{"key":"10.1109/COMPSAC.2015.241","type":"inproceedings","fields":{"abstract":["As information technology improves, the Internet is involved in every area in our daily life. When the mobile devices and cloud computing technology start to play important parts of our life, they have become more susceptible to attacks. In recent years, phishing and malicious websites have increasingly become serious problems in the field of network security. Attackers use many approaches to implant malware into target hosts in order to steal significant data and cause substantial damage. The growth of malware has been very rapid, and the purpose has changed from destruction to penetration. The signatures of malware have become more difficult to detect. In addition to static signatures, malware also tries to conceal dynamic signatures from anti-virus inspection. In this research, we use hooking techniques to trace the dynamic signatures that malware tries to hide. We then compare the behavioural differences between malware and benign programs by using data mining techniques in order to identify the malware. The experimental results show that our detection rate reaches 95% with only 80 attributes. This means that our method can achieve a high detection rate with low complexity."],"author":["Fan, Chun-I","Hsiao, Han-Wei","Chou, Chun-Han","Tseng, Yi-Fan"],"booktitle":["Proc. 2015 IEEE 39th Annu. Comput. Softw. Appl. Conf. - Vol. 03"],"date":["2015"],"doi":["10.1109/COMPSAC.2015.241"],"isbn":["978-1-4673-6564-2"],"keywords":["API","Classification","Data Mining","Malware","System Call"],"location":["USA"],"note":["TL;DR \n\nThis research uses hooking techniques to trace the dynamic signatures that malware tries to hide, and compares the behavioural differences between malware and benign programs by using data mining techniques in order to identify the malware."],"pages":["255–260"],"pagetotal":["6"],"publisher":["IEEE Computer Society"],"series":["COMPSAC '15"],"title":["Malware detection systems based on API log data mining"]},"creators":{"author":[{"lastName":"Fan","firstName":"Chun-I"},{"lastName":"Hsiao","firstName":"Han-Wei"},{"lastName":"Chou","firstName":"Chun-Han"},{"lastName":"Tseng","firstName":"Yi-Fan"}]},"sentenceCased":true},{"key":"10.1109/ICSM.2011.6080776","type":"inproceedings","fields":{"abstract":["Class names represent the concepts implemented in object-oriented source code and are key elements in program comprehension and, thus, software maintenance. Programming conventions often state that class names should be noun-phrases, but there is little further guidance for developers on the composition of class names. Other researchers have observed that the majority of Java class identifier names are composed of one or more nouns preceded, optionally, by one or more adjectives. However, no detailed analysis of class identifier name structure has been undertaken that could be leveraged to support program comprehension activities."],"author":["Butler, Simon","Wermelinger, Michel","Yu, Yijun","Sharp, Helen"],"booktitle":["Proc. 2011 27th IEEE Int. Conf. Softw. Maint."],"date":["2011"],"doi":["10.1109/ICSM.2011.6080776"],"isbn":["978-1-4577-0663-9"],"location":["USA"],"pages":["93–102"],"pagetotal":["10"],"publisher":["IEEE Computer Society"],"series":["ICSM '11"],"title":["Mining java class naming conventions"]},"creators":{"author":[{"lastName":"Butler","firstName":"Simon"},{"lastName":"Wermelinger","firstName":"Michel"},{"lastName":"Yu","firstName":"Yijun"},{"lastName":"Sharp","firstName":"Helen"}]},"sentenceCased":true},{"key":"10.1109/SANER.2017.7884605","type":"article","fields":{"address":["Los Alamitos, CA, USA"],"author":["Zhang, Yun","Lo, David","Kochhar, Pavneet Singh","Xia, Xin","Li, Quanlai","Sun, Jianling"],"date":["2017"],"journaltitle":["2017 IEEE 24th Int. Conf. Softw. Anal. Evol. Reengineering SANER"],"nodoi":["doi.ieeecomputersociety.org/10.1109/SANER.2017.7884605"],"note":["TL;DR \n\nThis paper proposes a novel approach that can effectively detect similar repositories on GitHub called RepoPal based on three heuristics leveraging two data sources (i.e., GitHub stars and readme files) which are not considered in previous works and compares it to a prior state-of-the-art approach CLAN."],"pages":["13–23"],"publisher":["IEEE Computer Society"],"title":["Detecting similar repositories on GitHub"],"volume":["00"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Yun"},{"lastName":"Lo","firstName":"David"},{"lastName":"Kochhar","firstName":"Pavneet Singh"},{"lastName":"Xia","firstName":"Xin"},{"lastName":"Li","firstName":"Quanlai"},{"lastName":"Sun","firstName":"Jianling"}]},"sentenceCased":true},{"key":"10.1145/1097047.1097061","type":"inproceedings","fields":{"abstract":["Collaborative filtering techniques have been successfully employed in recommender systems in order to help users deal with information overload by making high quality personalized recommendations. However, such systems have been shown to be vulnerable to attacks in which malicious users with carefully chosen profiles are inserted into the system in order to push the predictions of some targeted items. In this paper we propose several metrics for analyzing rating patterns of malicious users and evaluate their potential for detecting such shilling attacks. Building upon these results, we propose and evaluate an algorithm for protecting recommender systems against shilling attacks. The algorithm can be employed for monitoring user ratings and removing shilling attacker profiles from the process of computing recommendations, thus maintaining the high quality of the recommendations."],"author":["Chirita, Paul-Alexandru","Nejdl, Wolfgang","Zamfir, Cristian"],"booktitle":["Proc. 7th Annu. ACM Int. Workshop Web Inf. Data Manag."],"date":["2005"],"doi":["10.1145/1097047.1097061"],"isbn":["1-59593-194-5"],"keywords":["collaborative filtering","recommender systems","shilling attacks","web applications"],"location":["New York, NY, USA"],"note":["TL;DR \n\nSeveral metrics for analyzing rating patterns of malicious users are proposed and an algorithm for protecting recommender systems against shilling attacks is evaluated that can be employed for monitoring user ratings and removing shilling attacker profiles from the process of computing recommendations, thus maintaining the high quality of the recommendations."],"pages":["67–74"],"pagetotal":["8"],"publisher":["Association for Computing Machinery"],"series":["WIDM '05"],"title":["Preventing shilling attacks in online recommender systems"]},"creators":{"author":[{"lastName":"Chirita","firstName":"Paul-Alexandru"},{"lastName":"Nejdl","firstName":"Wolfgang"},{"lastName":"Zamfir","firstName":"Cristian"}]},"sentenceCased":true},{"key":"10.1145/1167473.1167508","type":"inproceedings","fields":{"abstract":["It is common practice for software developers to use examples to guide development efforts. This largely unwritten, yet standard, practice of \"develop by example\" is often supported by examples bundled with library or framework packages, provided in textbooks, and made available for download on both official and unofficial web sites. However, the vast number of examples that are embedded in the billions of lines of already developed library and framework code are largely untapped. We have developed XSnippet, a context-sensitive code assistant framework that allows developers to query a sample repository for code snippets that are relevant to the programming task at hand. In particular, our work makes three primary contributions. First, a range of queries is provided to allow developers to switch between a context-independent retrieval of code snippets to various degrees of context-sensitive retrieval for object instantiation queries. Second, a novel graph-based code mining algorithm is provided to support the range of queries and enable mining within and across method boundaries. Third, an innovative context-sensitive ranking heuristic is provided that has been experimentally proven to provide better ranking for best-fit code snippets than context-independent heuristics such as shortest path and frequency. Our experimental evaluation has shown that XSnippet has significant potential to assist developers, and provides better coverage of tasks and better rankings for best-fit snippets than other code assistant systems."],"author":["Sahavechaphan, Naiyana","Claypool, Kajal"],"booktitle":["Proc. 21st Annu. ACM SIGPLAN Conf. Object-Oriented Program. Syst. Lang. Appl."],"date":["2006"],"doi":["10.1145/1167473.1167508"],"isbn":["1-59593-348-4"],"keywords":["code assistants","code mining","code reuse","ranking code samples"],"location":["New York, NY, USA"],"note":["TL;DR \n\nXSnippet is developed, a context-sensitive code assistant framework that allows developers to query a sample repository for code snippets that are relevant to the programming task at hand and provides better coverage of tasks and better rankings for best-fit snippets than other code assistant systems."],"pages":["413–430"],"pagetotal":["18"],"publisher":["Association for Computing Machinery"],"series":["OOPSLA '06"],"title":["XSnippet: Mining for sample code"]},"creators":{"author":[{"lastName":"Sahavechaphan","firstName":"Naiyana"},{"lastName":"Claypool","firstName":"Kajal"}]},"sentenceCased":true},{"key":"10.1145/1454008.1454012","type":"inproceedings","fields":{"abstract":["The paper studies the Long Tail problem of recommender systems when many items in the Long Tail have only few ratings, thus making it hard to use them in recommender systems. The approach presented in the paper splits the whole itemset into the head and the tail parts and clusters only the tail items. Then recommendations for the tail items are based on the ratings in these clusters and for the head items on the ratings of individual items. If such partition and clustering are done properly, we show that this reduces the recommendation error rates for the tail items, while maintaining reasonable computational performance."],"author":["Park, Yoon-Joo","Tuzhilin, Alexander"],"booktitle":["Proc. 2008 ACM Conf. Recomm. Syst."],"date":["2008"],"doi":["10.1145/1454008.1454012"],"isbn":["978-1-60558-093-7"],"keywords":["clustering","data mining","long tail","recommendation"],"location":["New York, NY, USA"],"note":["TL;DR \n\nThis paper splits the whole itemset into the head and the tail parts and clusters only the tail items, and shows that this reduces the recommendation error rates for the Tail items, while maintaining reasonable computational performance."],"pages":["11–18"],"pagetotal":["8"],"publisher":["Association for Computing Machinery"],"series":["RecSys '08"],"title":["The long tail of recommender systems and how to leverage it"]},"creators":{"author":[{"lastName":"Park","firstName":"Yoon-Joo"},{"lastName":"Tuzhilin","firstName":"Alexander"}]},"sentenceCased":true},{"key":"10.1145/170035.170072","type":"inproceedings","fields":{"abstract":["We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an efficient algorithm that generates all significant association rules between items in the database. The algorithm incorporates buffer management and novel estimation and pruning techniques. We also present results of applying this algorithm to sales data obtained from a large retailing company, which shows the effectiveness of the algorithm."],"author":["Agrawal, Rakesh","Imieliński, Tomasz","Swami, Arun"],"booktitle":["Proc. 1993 ACM SIGMOD Int. Conf. Manag. Data"],"date":["1993"],"doi":["10.1145/170035.170072"],"isbn":["0-89791-592-5"],"location":["New York, NY, USA"],"note":["TL;DR \n\nAn efficient algorithm is presented that generates all significant association rules between items in the database of customer transactions and incorporates buffer management and novel estimation and pruning techniques."],"pages":["207–216"],"pagetotal":["10"],"publisher":["Association for Computing Machinery"],"series":["SIGMOD '93"],"title":["Mining association rules between sets of items in large databases"]},"creators":{"author":[{"lastName":"Agrawal","firstName":"Rakesh"},{"lastName":"Imieliński","firstName":"Tomasz"},{"lastName":"Swami","firstName":"Arun"}]},"sentenceCased":true},{"key":"10.1145/1772690.1772780","type":"inproceedings","fields":{"abstract":["When a Web user's underlying information need is not clearly specified from the initial query, an effective approach is to diversify the results retrieved for this query. In this paper, we introduce a novel probabilistic framework for Web search result diversification, which explicitly accounts for the various aspects associated to an underspecified query. In particular, we diversify a document ranking by estimating how well a given document satisfies each uncovered aspect and the extent to which different aspects are satisfied by the ranking as a whole. We thoroughly evaluate our framework in the context of the diversity task of the TREC 2009 Web track. Moreover, we exploit query reformulations provided by three major Web search engines (WSEs) as a means to uncover different query aspects. The results attest the effectiveness of our framework when compared to state-of-the-art diversification approaches in the literature. Additionally, by simulating an upper-bound query reformulation mechanism from official TREC data, we draw useful insights regarding the effectiveness of the query reformulations generated by the different WSEs in promoting diversity."],"author":["Santos, Rodrygo L.T.","Macdonald, Craig","Ounis, Iadh"],"booktitle":["Proc. 19th Int. Conf. World Wide Web"],"date":["2010"],"doi":["10.1145/1772690.1772780"],"isbn":["978-1-60558-799-8"],"keywords":["diversity","relevance","web search"],"location":["New York, NY, USA"],"note":["TL;DR \n\nA novel probabilistic framework for Web search result diversification, which explicitly accounts for the various aspects associated to an underspecified query, is introduced and diversify a document ranking by estimating how well a given document satisfies each uncovered aspect and the extent to which different aspects are satisfied by the ranking as a whole."],"pages":["881–890"],"pagetotal":["10"],"publisher":["Association for Computing Machinery"],"series":["WWW '10"],"title":["Exploiting query reformulations for web search result diversification"]},"creators":{"author":[{"lastName":"Santos","firstName":"Rodrygo L.T."},{"lastName":"Macdonald","firstName":"Craig"},{"lastName":"Ounis","firstName":"Iadh"}]},"sentenceCased":true},{"key":"10.1145/1835449.1835482","type":"inproceedings","fields":{"abstract":["The vector space model (VSM) is a popular and widely applied model in information retrieval (IR). VSM creates vector spaces whose dimensionality is usually high (e.g., tens of thousands of terms). This may cause various problems, such as susceptibility to noise and difficulty in capturing the underlying semantic structure, which are commonly recognized as different aspects of the \"curse of dimensionality.\" In this paper, we investigate a novel aspect of the dimensionality curse, which is referred to as hubness and manifested by the tendency of some documents (called hubs) to be included in unexpectedly many search result lists. Hubness may impact VSM considerably since hubs can become obstinate results, irrelevant to a large number of queries, thus harming the performance of an IR system and the experience of its users. We analyze the origins of hubness, showing it is primarily a consequence of high (intrinsic) dimensionality of data, and not a result of other factors such as sparsity and skewness of the distribution of term frequencies. We describe the mechanisms through which hubness emerges by exploring the behavior of similarity measures in high-dimensional vector spaces. Our consideration begins with the classical VSM (tf-idf term weighting and cosine similarity), but the conclusions generalize to more advanced variations, such as Okapi BM25. Moreover, we explain why hubness may not be easily mitigated by dimensionality reduction, and propose a similarity adjustment scheme that takes into account the existence of hubs. Experimental results over real data indicate that significant improvement can be obtained through consideration of hubness."],"author":["Radovanović, Milos","Nanopoulos, Alexandros","Ivanović, Mirjana"],"booktitle":["Proc. 33rd Int. ACM SIGIR Conf. Res. Dev. Inf. Retr."],"date":["2010"],"doi":["10.1145/1835449.1835482"],"isbn":["978-1-4503-0153-4"],"keywords":["cosine similarity","curse of dimensionality","hubs","nearest neighbors","similarity concentration","text retrieval","vector space model"],"location":["New York, NY, USA"],"note":["TL;DR \n\nThe origins of hubness are analyzed, showing it is primarily a consequence of high (intrinsic) dimensionality of data, and not a result of other factors such as sparsity and skewness of the distribution of term frequencies."],"pages":["186–193"],"pagetotal":["8"],"publisher":["Association for Computing Machinery"],"series":["SIGIR '10"],"title":["On the existence of obstinate results in vector space models"]},"creators":{"author":[{"lastName":"Radovanović","firstName":"Milos"},{"lastName":"Nanopoulos","firstName":"Alexandros"},{"lastName":"Ivanović","firstName":"Mirjana"}]},"sentenceCased":true},{"key":"10.1145/2579991","type":"article","fields":{"langid":["english"],"articleno":["11"],"author":["Bislimovska, Bojana","Bozzon, Alessandro","Brambilla, Marco","Fraternali, Piero"],"date":["2014"],"doi":["10.1145/2579991"],"issn":["1559-1131"],"issue_date":["March 2014"],"journaltitle":["ACM Trans, Web"],"keywords":["/unread","⛔ No INSPIRE recid found","domain-specific language","Information retrieval","search","Web application"],"location":["New York, NY, USA"],"note":["TL;DR \n\nThis article examines two different techniques for indexing and searching model repositories, with a focus on Web development projects encoded in a domain-specific language."],"number":["2"],"pages":["1–47"],"pagetotal":["47"],"publisher":["Association for Computing Machinery"],"title":["Textual and Content-Based Search in Repositories of Web Application Models"],"volume":["8"]},"creators":{"author":[{"lastName":"Bislimovska","firstName":"Bojana"},{"lastName":"Bozzon","firstName":"Alessandro"},{"lastName":"Brambilla","firstName":"Marco"},{"lastName":"Fraternali","firstName":"Piero"}]}},{"key":"10.1145/2766462.2767823","type":"inproceedings","fields":{"abstract":["It is known that memory-based collaborative filtering systems are vulnerable to shilling attacks. In this paper, we demonstrate that hubness, which occurs in high dimensional data, is exploited by the attacks. Hence we explore methods for reducing hubness in user-response data to make these systems robust against attacks. Using the MovieLens dataset, we empirically show that the two methods for reducing hubness by transforming a similarity matrix(i) centering and (ii) conversion to a commute time kernel-can thwart attacks without degrading the recommendation performance."],"author":["Hara, Kazuo","Suzuki, Ikumi","Kobayashi, Kei","Fukumizu, Kenji"],"booktitle":["Proc. 38th Int. ACM SIGIR Conf. Res. Dev. Inf. Retr."],"date":["2015"],"doi":["10.1145/2766462.2767823"],"isbn":["978-1-4503-3621-5"],"keywords":["collaborative filtering","hubness","shilling attack"],"location":["New York, NY, USA"],"pages":["815–818"],"pagetotal":["4"],"publisher":["Association for Computing Machinery"],"series":["SIGIR '15"],"title":["Reducing hubness: A cause of vulnerability in recommender systems"]},"creators":{"author":[{"lastName":"Hara","firstName":"Kazuo"},{"lastName":"Suzuki","firstName":"Ikumi"},{"lastName":"Kobayashi","firstName":"Kei"},{"lastName":"Fukumizu","firstName":"Kenji"}]},"sentenceCased":true},{"key":"10.1145/2827872","type":"article","fields":{"abstract":["The MovieLens datasets are widely used in education, research, and industry. They are downloaded hundreds of thousands of times each year, reflecting their use in popular press programming books, traditional and online courses, and software. These datasets are a product of member activity in the MovieLens movie recommendation system, an active research platform that has hosted many experiments since its launch in 1997. This article documents the history of MovieLens and the MovieLens datasets. We include a discussion of lessons learned from running a long-standing, live research platform from the perspective of a research organization. We document best practices and limitations of using the MovieLens datasets in new research."],"articleno":["19"],"author":["Harper, F. Maxwell","Konstan, Joseph A."],"date":["2015-12"],"doi":["10.1145/2827872"],"issn":["2160-6455"],"issue_date":["January 2016"],"journaltitle":["ACM Trans. Interact. Intell. Syst."],"keywords":["Datasets","MovieLens","ratings","recommendations"],"location":["New York, NY, USA"],"number":["4"],"pagetotal":["19"],"publisher":["Association for Computing Machinery"],"title":["The MovieLens datasets: History and context"],"volume":["5"]},"creators":{"author":[{"lastName":"Harper","firstName":"F. Maxwell"},{"lastName":"Konstan","firstName":"Joseph A."}]},"sentenceCased":true},{"key":"10.1145/2976749.2978333","type":"inproceedings","fields":{"abstract":["Third-party libraries on Android have been shown to be security and privacy hazards by adding security vulnerabilities to their host apps or by misusing inherited access rights. Correctly attributing improper app behavior either to app or library developer code or isolating library code from their host apps would be highly desirable to mitigate these problems, but is impeded by the absence of a third-party library detection that is effective and reliable in spite of obfuscated code. This paper proposes a library detection technique that is resilient against common code obfuscations and that is capable of pinpointing the exact library version used in apps. Libraries are detected with profiles from a comprehensive library database that we generated from the original library SDKs. We apply our technique to the top apps on Google Play and their complete histories to conduct a longitudinal study of library usage and evolution in apps. Our results particularly show that app developers only slowly adapt new library versions, exposing their end-users to large windows of vulnerability. For instance, we discovered that two long-known security vulnerabilities in popular libs are still present in the current top apps. Moreover, we find that misuse of cryptographic APIs in advertising libs, which increases the host apps' attack surface, affects 296 top apps with a cumulative install base of 3.7bn devices according to Play. To the best of our knowledge, our work is first to quantify the security impact of third-party libs on the Android ecosystem."],"author":["Backes, Michael","Bugiel, Sven","Derr, Erik"],"booktitle":["Proc. 2016 ACM SIGSAC Conf. Comput. Commun. Secur."],"date":["2016"],"doi":["10.1145/2976749.2978333"],"isbn":["978-1-4503-4139-4"],"keywords":["android","third-party library detection"],"location":["New York, NY, USA"],"note":["TL;DR \n\nThis paper proposes a library detection technique that is resilient against common code obfuscations and that is capable of pinpointing the exact library version used in apps, and is first to quantify the security impact of third-party libs on the Android ecosystem."],"pages":["356–367"],"pagetotal":["12"],"publisher":["Association for Computing Machinery"],"series":["CCS '16"],"title":["Reliable third-party library detection in android and its security applications"]},"creators":{"author":[{"lastName":"Backes","firstName":"Michael"},{"lastName":"Bugiel","firstName":"Sven"},{"lastName":"Derr","firstName":"Erik"}]},"sentenceCased":true},{"key":"10.1145/3172871.3172891","type":"inproceedings","fields":{"abstract":["There has been a long history of applying AI technologies to address software engineering problems especially on tool automation. On the other hand, given the increasing importance and popularity of AI software, recent research efforts have been on exploring software engineering solutions to improve the productivity of developing AI software and the dependability of AI software. The emerging field of intelligent software engineering is to focus on two aspects: (1) instilling intelligence in solutions for software engineering problems; (2) providing software engineering solutions for intelligent software. This extended abstract shares perspectives on these two aspects of intelligent software engineering."],"articleno":["1"],"author":["Xie, Tao"],"booktitle":["Proc. 11th Innov. Softw. Eng. Conf."],"date":["2018"],"doi":["10.1145/3172871.3172891"],"isbn":["978-1-4503-6398-3"],"keywords":["artificial intelligence","Intelligent software engineering","software dependability"],"location":["New York, NY, USA"],"pagetotal":["1"],"publisher":["Association for Computing Machinery"],"series":["ISEC '18"],"title":["Intelligent software engineering: Synergy between AI and software engineering"]},"creators":{"author":[{"lastName":"Xie","firstName":"Tao"}]},"sentenceCased":true},{"key":"10.1145/3180155.3180220","type":"inproceedings","fields":{"abstract":["Recent advances in Deep Neural Networks (DNNs) have led to the development of DNN-driven autonomous cars that, using sensors like camera, LiDAR, etc., can drive without any human intervention. Most major manufacturers including Tesla, GM, Ford, BMW, and Waymo/Google are working on building and testing different types of autonomous vehicles. The lawmakers of several US states including California, Texas, and New York have passed new legislation to fast-track the process of testing and deployment of autonomous vehicles on their roads.However, despite their spectacular progress, DNNs, just like traditional software, often demonstrate incorrect or unexpected corner-case behaviors that can lead to potentially fatal collisions. Several such real-world accidents involving autonomous cars have already happened including one which resulted in a fatality. Most existing testing techniques for DNN-driven vehicles are heavily dependent on the manual collection of test data under different driving conditions which become prohibitively expensive as the number of test conditions increases.In this paper, we design, implement, and evaluate DeepTest, a systematic testing tool for automatically detecting erroneous behaviors of DNN-driven vehicles that can potentially lead to fatal crashes. First, our tool is designed to automatically generated test cases leveraging real-world changes in driving conditions like rain, fog, lighting conditions, etc. DeepTest systematically explore different parts of the DNN logic by generating test inputs that maximize the numbers of activated neurons. DeepTest found thousands of erroneous behaviors under different realistic driving conditions (e.g., blurring, rain, fog, etc.) many of which lead to potentially fatal crashes in three top performing DNNs in the Udacity self-driving car challenge."],"author":["Tian, Yuchi","Pei, Kexin","Jana, Suman","Ray, Baishakhi"],"booktitle":["Proc. 40th Int. Conf. Softw. Eng."],"date":["2018"],"doi":["10.1145/3180155.3180220"],"isbn":["978-1-4503-5638-1"],"keywords":["autonomous vehicle","deep learning","deep neural networks","neuron coverage","self-driving cars","testing"],"location":["New York, NY, USA"],"note":["TL;DR \n\nDeepTest is a systematic testing tool for automatically detecting erroneous behaviors of DNN-driven vehicles that can potentially lead to fatal crashes and systematically explore different parts of the DNN logic by generating test inputs that maximize the numbers of activated neurons."],"pages":["303–314"],"pagetotal":["12"],"publisher":["Association for Computing Machinery"],"series":["ICSE '18"],"title":["DeepTest: Automated testing of deep-neural-network-driven autonomous cars"]},"creators":{"author":[{"lastName":"Tian","firstName":"Yuchi"},{"lastName":"Pei","firstName":"Kexin"},{"lastName":"Jana","firstName":"Suman"},{"lastName":"Ray","firstName":"Baishakhi"}]},"sentenceCased":true},{"key":"10.1145/3183440.3195011","type":"inproceedings","fields":{"abstract":["Developing modern mobile applications often require the uses of many libraries specific for the mobile platform, which can be overwhelmingly too many for application developers to find what are needed for a functionality and where and how to use them properly. This paper presents a tool, named LibraryGuru, to recommend suitable Android APIs for given functionality descriptions. It not only recommends functional APIs that can be invoked for implementing the functionality, but also recommends event callback APIs that are inherent in the Android framework and need to be overridden in the application. LibraryGuru internally builds correlation databases among various functionality descriptions and Android APIs. These correlations are extracted from Android development tutorials and SDK documents with domain-specific code parsing and natural language processing techniques adapted for functional APIs and event callback APIs separately, and are matched against functionality queries to recommend relevant APIs for developers. LibraryGuru is publicly accessible at http://libraryguru.info, and a demo video is available at https://youtu.be/f7MtjliUM-4."],"author":["Yuan, Weizhao","Nguyen, Hoang H.","Jiang, Lingxiao","Chen, Yuting"],"booktitle":["Proc. 40th Int. Conf. Softw. Eng. Companion Proceeedings"],"date":["2018"],"doi":["10.1145/3183440.3195011"],"isbn":["978-1-4503-5663-3"],"location":["New York, NY, USA"],"note":["TL;DR \n\nA tool, named LibraryGuru, to recommend suitable Android APIs for given functionality descriptions, which not only recommends functional APIs that can be invoked for implementing the functionality, but also recommends event callback APIs that are inherent in the Android framework and need to be overridden in the application."],"pages":["364–365"],"pagetotal":["2"],"publisher":["Association for Computing Machinery"],"series":["ICSE '18"],"title":["LibraryGuru: API recommendation for android developers"]},"creators":{"author":[{"lastName":"Yuan","firstName":"Weizhao"},{"lastName":"Nguyen","firstName":"Hoang H."},{"lastName":"Jiang","firstName":"Lingxiao"},{"lastName":"Chen","firstName":"Yuting"}]},"sentenceCased":true},{"key":"10.1145/3196398.3196401","type":"inproceedings","fields":{"abstract":["Security vulnerabilities are among the most pressing problems in open source software package libraries. It may take a long time to discover and fix vulnerabilities in packages. In addition, vulnerabilities may propagate to dependent packages, making them vulnerable too. This paper presents an empirical study of nearly 400 security reports over a 6-year period in the npm dependency network containing over 610k JavaScript packages. Taking into account the severity of vulnerabilities, we analyse how and when these vulnerabilities are discovered and fixed, and to which extent they affect other packages in the packaging ecosystem in presence of dependency constraints. We report our findings and provide guidelines for package maintainers and tool developers to improve the process of dealing with security issues."],"author":["Decan, Alexandre","Mens, Tom","Constantinou, Eleni"],"booktitle":["Proc. 15th Int. Conf. Min. Softw. Repos."],"date":["2018"],"doi":["10.1145/3196398.3196401"],"isbn":["978-1-4503-5716-6"],"keywords":["dependency network","security vulnerability","semantic versioning","software ecosystem","software repository mining"],"location":["New York, NY, USA"],"pages":["181–191"],"pagetotal":["11"],"publisher":["Association for Computing Machinery"],"series":["MSR '18"],"title":["On the impact of security vulnerabilities in the npm package dependency network"]},"creators":{"author":[{"lastName":"Decan","firstName":"Alexandre"},{"lastName":"Mens","firstName":"Tom"},{"lastName":"Constantinou","firstName":"Eleni"}]},"sentenceCased":true},{"key":"10.1145/3236024.3264838","type":"inproceedings","fields":{"abstract":["A goal of software engineering research is advancing software quality and the success of the software engineering process. However, while recent studies have demonstrated a new kind of defect in software related to its ability to operate in fair and unbiased manner, software engineering has not yet wholeheartedly tackled these new kinds of defects, thus leaving software vulnerable. This paper outlines a vision for how software engineering research can help reduce fairness defects and represents a call to action by the software engineering research community to reify that vision. Modern software is riddled with examples of biased behavior, from automated translation injecting gender stereotypes, to vision systems failing to see faces of certain races, to the US criminal justice sytem relying on biased computational assessments of crime recidivism. While systems may learn bias from biased data, bias can also emerge from ambiguous or incomplete requirement specification, poor design, implementation bugs, and unintended component interactions. We argue that software fairness is analogous to software quality, and that numerous software engineering challenges in the areas of requirements, specification, design, testing, and verification need to be tackled to solve this problem."],"author":["Brun, Yuriy","Meliou, Alexandra"],"booktitle":["Proc. 2018 26th ACM Jt. Meet. Eur. Softw. Eng. Conf. Symp. Found. Softw. Eng."],"date":["2018"],"doi":["10.1145/3236024.3264838"],"isbn":["978-1-4503-5573-5"],"keywords":["software bias","Software fairness","software process"],"location":["New York, NY, USA"],"note":["TL;DR \n\nIt is argued that software fairness is analogous to software quality, and that numerous software engineering challenges in the areas of requirements, specification, design, testing, and verification need to be tackled to solve this problem."],"pages":["754–759"],"pagetotal":["6"],"publisher":["Association for Computing Machinery"],"series":["ESEC/FSE 2018"],"title":["Software fairness"]},"creators":{"author":[{"lastName":"Brun","firstName":"Yuriy"},{"lastName":"Meliou","firstName":"Alexandra"}]},"sentenceCased":true},{"key":"10.1145/3301285","type":"article","fields":{"abstract":["The advent of the Android system has brought smartphone technology to the doorsteps of the masses. The latest technologies have made it affordable for every section of the society. However, the emergence of the Android platform has also escalated the growth of cybercrime through the mobile platform. Its open source operating system has made it a center of attraction for the attackers. This article provides a comprehensive study of the state of the Android Security domain. This article classifies the attacks on the Android system in four categories (i) hardware-based attacks, (ii) kernel-based attacks, (iii) hardware abstraction layer-based attacks, and (iv) application-based attacks. The study deals with various threats and security measures relating to these categories and presents an in-depth analysis of the underlying problems in the Android security domain. The article also stresses the role of Android application developers in realizing a more secure Android environment. This article attempts to provide a comparative analysis of various malware detection techniques concerning their methods and limitations. The study can help researchers gain knowledge of the Android security domain from various aspects and build a more comprehensive, robust, and efficient solution to the threats that Android is facing."],"articleno":["21"],"author":["Bhat, Parnika","Dutta, Kamlesh"],"date":["2019-02"],"doi":["10.1145/3301285"],"issn":["0360-0300"],"issue_date":["February 2019"],"journaltitle":["ACM Comput. Surv."],"keywords":["Android","intra library collusion","malware","malware detection","privilege escalation"],"location":["New York, NY, USA"],"note":["TL;DR \n\nThis article classifies the attacks on the Android system in four categories and presents an in-depth analysis of the underlying problems in the Android security domain and stresses the role of Android application developers in realizing a more secure Android environment."],"number":["1"],"pagetotal":["35"],"publisher":["Association for Computing Machinery"],"title":["A survey on various threats and current state of security in android platform"],"volume":["52"]},"creators":{"author":[{"lastName":"Bhat","firstName":"Parnika"},{"lastName":"Dutta","firstName":"Kamlesh"}]},"sentenceCased":true},{"key":"10.1145/3357384.3357971","type":"inproceedings","fields":{"abstract":["Online developer communities like GitHub provide services such as distributed version control and task management, which allow a massive number of developers to collaborate online. However, the openness of the communities makes themselves vulnerable to different types of malicious attacks, since the attackers can easily join and interact with legitimate users. In this work, we formulate the malicious account detection problem in online developer communities, and propose GitSec, a deep learning-based solution to detect malicious accounts. GitSec distinguishes malicious accounts from legitimate ones based on the account profiles as well as dynamic activity characteristics. On one hand, GitSec makes use of users' descriptive features from the profiles. On the other hand, GitSec processes users' dynamic behavioral data by constructing two user activity sequences and applying a parallel neural network design to deal with each of them, respectively. An attention mechanism is used to integrate the information generated by the parallel neural networks. The final judgement is made by a decision maker implemented by a supervised machine learning-based classifier. Based on the real-world data of GitHub users, our extensive evaluations show that GitSec is an accurate detection system, with an F1-score of 0.922 and an AUC value of 0.940."],"author":["Gong, Qingyuan","Zhang, Jiayun","Chen, Yang","Li, Qi","Xiao, Yu","Wang, Xin","Hui, Pan"],"booktitle":["Proc. 28th ACM Int. Conf. Inf. Knowl. Manag."],"date":["2019"],"doi":["10.1145/3357384.3357971"],"isbn":["978-1-4503-6976-3"],"keywords":["deep learning","malicious account detection","online developer community","social networks"],"location":["New York, NY, USA"],"pages":["1251–1260"],"pagetotal":["10"],"publisher":["Association for Computing Machinery"],"series":["CIKM '19"],"title":["Detecting malicious accounts in online developer communities using deep learning"]},"creators":{"author":[{"lastName":"Gong","firstName":"Qingyuan"},{"lastName":"Zhang","firstName":"Jiayun"},{"lastName":"Chen","firstName":"Yang"},{"lastName":"Li","firstName":"Qi"},{"lastName":"Xiao","firstName":"Yu"},{"lastName":"Wang","firstName":"Xin"},{"lastName":"Hui","firstName":"Pan"}]},"sentenceCased":true},{"key":"10.1145/3359591.3359732","type":"inproceedings","fields":{"abstract":["Software applications have grown increasingly complex to deliver the features desired by users. Software modularity has been used as a way to mitigate the costs of developing such complex software. Active learning-based program inference provides an elegant framework that exploits this modularity to tackle development correctness, performance and cost in large applications. Inferred programs can be used for many purposes, including generation of secure code, code re-use through automatic encapsulation, adaptation to new platforms or languages, and optimization. We show through detailed examples how our approach can infer three modules in a representative application. Finally, we outline the broader paradigm and open research questions."],"author":["Cambronero, José P.","Dang, Thurston H. Y.","Vasilakis, Nikos","Shen, Jiasi","Wu, Jerry","Rinard, Martin C."],"booktitle":["Proc. 2019 ACM SIGPLAN Int. Symp. New Ideas New Paradig. Reflect. Program. Softw."],"date":["2019"],"doi":["10.1145/3359591.3359732"],"isbn":["978-1-4503-6995-4"],"keywords":["active learning","program inference","program modeling"],"location":["New York, NY, USA"],"pages":["62–78"],"pagetotal":["17"],"publisher":["Association for Computing Machinery"],"series":["Onward! 2019"],"title":["Active learning for software engineering"]},"creators":{"author":[{"lastName":"Cambronero","firstName":"José P."},{"lastName":"Dang","firstName":"Thurston H. Y."},{"lastName":"Vasilakis","firstName":"Nikos"},{"lastName":"Shen","firstName":"Jiasi"},{"lastName":"Wu","firstName":"Jerry"},{"lastName":"Rinard","firstName":"Martin C."}]},"sentenceCased":true},{"key":"10.1145/3360578","type":"article","fields":{"langid":["english"],"abstract":["Programmers often write code that has similarity to existing code written somewhere. A tool that could help programmers to search such similar code would be immensely useful. Such a tool could help programmers to extend partially written code snippets to completely implement necessary functionality, help to discover extensions to the partial code which are commonly included by other programmers, help to cross-check against similar code written by other programmers, or help to add extra code which would fix common mistakes and errors. We propose Aroma, a tool and technique for code recommendation via structural code search. Aroma indexes a huge code corpus including thousands of open-source projects, takes a partial code snippet as input, searches the corpus for method bodies containing the partial code snippet, and clusters and intersects the results of the search to recommend a small set of succinct code snippets which both contain the query snippet and appear as part of several methods in the corpus. We evaluated Aroma on 2000 randomly selected queries created from the corpus, as well as 64 queries derived from code snippets obtained from Stack Overflow, a popular website for discussing code. We implemented Aroma for 4 different languages, and developed an IDE plugin for Aroma. Furthermore, we conducted a study where we asked 12 programmers to complete programming tasks using Aroma, and collected their feedback. Our results indicate that Aroma is capable of retrieving and recommending relevant code snippets efficiently."],"articleno":["152"],"author":["Luan, Sifei","Yang, Di","Barnaby, Celeste","Sen, Koushik","Chandra, Satish"],"date":["2018-12"],"doi":["10.1145/3360578"],"issue":["OOPSLA"],"issue_date":["October 2019"],"journaltitle":["Proc. ACM Program. Lang."],"keywords":["clone detection","clustering","code recommendation","Computer Science - Software Engineering","feature-based code representation","structural code search"],"location":["New York, NY, USA"],"note":["arXiv: 1812.01158 \n\narXiv: 1812.01158"],"pagetotal":["28"],"publisher":["Association for Computing Machinery"],"shorttitle":["Aroma"],"title":["Aroma: Code Recommendation via Structural Code Search"],"volume":["3"]},"creators":{"author":[{"lastName":"Luan","firstName":"Sifei"},{"lastName":"Yang","firstName":"Di"},{"lastName":"Barnaby","firstName":"Celeste"},{"lastName":"Sen","firstName":"Koushik"},{"lastName":"Chandra","firstName":"Satish"}]}},{"key":"10.1145/3368089.3409745","type":"inproceedings","fields":{"abstract":["The Android ecosystem offers different facilities to enable communication among app components and across apps to ensure that rich services can be composed through functionality reuse. At the heart of this system is the Inter-component communication (ICC) scheme, which has been largely studied in the literature. Less known in the community is another powerful mechanism that allows for direct inter-app code invocation which opens up for different reuse scenarios, both legitimate or malicious. This paper exposes the general workflow for this mechanism, which beyond ICCs, enables app developers to access and invoke functionalities (either entire Java classes, methods or object fields) implemented in other apps using official Android APIs. We experimentally showcase how this reuse mechanism can be leveraged to “plagiarize\" supposedly-protected functionalities. Typically, we were able to leverage this mechanism to bypass security guards that a popular video broadcaster has placed for preventing access to its video database from outside its provided app. We further contribute with a static analysis toolkit, named DICIDer, for detecting direct inter-app code invocations in apps. An empirical analysis of the usage prevalence of this reuse mechanism is then conducted. Finally, we discuss the usage contexts as well as the implications of this studied reuse mechanism."],"author":["Gao, Jun","Li, Li","Kong, Pingfan","Bissyandé, Tegawendé F.","Klein, Jacques"],"booktitle":["Proc. 28th ACM Jt. Meet. Eur. Softw. Eng. Conf. Symp. Found. Softw. Eng."],"date":["2020"],"doi":["10.1145/3368089.3409745"],"isbn":["978-1-4503-7043-1"],"keywords":["Android","DICI","Java Reflection"],"location":["New York, NY, USA"],"pages":["939–951"],"pagetotal":["13"],"publisher":["Association for Computing Machinery"],"series":["ESEC/FSE 2020"],"title":["Borrowing your enemy’s arrows: The case of code reuse in android via direct inter-app code invocation"]},"creators":{"author":[{"lastName":"Gao","firstName":"Jun"},{"lastName":"Li","firstName":"Li"},{"lastName":"Kong","firstName":"Pingfan"},{"lastName":"Bissyandé","firstName":"Tegawendé F."},{"lastName":"Klein","firstName":"Jacques"}]},"sentenceCased":true},{"key":"10.1145/3379597.3387478","type":"inproceedings","fields":{"abstract":["Background: Some developer activity traditionally performed manually, such as making code commits, opening, managing, or closing issues is increasingly subject to automation in many OSS projects. Specifically, such activity is often performed by tools that react to events or run at specific times. We refer to such automation tools as bots and, in many software mining scenarios related to developer productivity or code quality, it is desirable to identify bots in order to separate their actions from actions of individuals. Aim: Find an automated way of identifying bots and code committed by these bots, and to characterize the types of bots based on their activity patterns. Method and Result: We propose BIMAN, a systematic approach to detect bots using author names, commit messages, files modified by the commit, and projects associated with the commits. For our test data, the value for AUC-ROC was 0.9. We also characterized these bots based on the time patterns of their code commits and the types of files modified, and found that they primarily work with documentation files and web pages, and these files are most prevalent in HTML and JavaScript ecosystems. We have compiled a shareable dataset containing detailed information about 461 bots we found (all of which have more than 1000 commits) and 13,762,430 commits they created."],"author":["Dey, Tapajit","Mousavi, Sara","Ponce, Eduardo","Fry, Tanner","Vasilescu, Bogdan","Filippova, Anna","Mockus, Audris"],"booktitle":["Proc. 17th Int. Conf. Min. Softw. Repos."],"date":["2020"],"doi":["10.1145/3379597.3387478"],"isbn":["978-1-4503-7517-7"],"keywords":["automated commits","bots","ensemble model","random forest","social coding platforms","software engineering"],"location":["New York, NY, USA"],"note":["TL;DR \n\nBIMAN is proposed, a systematic approach to detect bots using author names, commit messages, files modified by the commit, and projects associated with the commits to find an automated way of identifying bots and code committed by these bots."],"pages":["209–219"],"pagetotal":["11"],"publisher":["Association for Computing Machinery"],"series":["MSR '20"],"title":["Detecting and characterizing bots that commit code"]},"creators":{"author":[{"lastName":"Dey","firstName":"Tapajit"},{"lastName":"Mousavi","firstName":"Sara"},{"lastName":"Ponce","firstName":"Eduardo"},{"lastName":"Fry","firstName":"Tanner"},{"lastName":"Vasilescu","firstName":"Bogdan"},{"lastName":"Filippova","firstName":"Anna"},{"lastName":"Mockus","firstName":"Audris"}]},"sentenceCased":true},{"key":"10.1145/3468264.3468552","type":"inproceedings","fields":{"abstract":["The mobile app marketplace has fierce competition for mobile app developers, who need to develop and update their apps as soon as possible to gain first mover advantage. Third-party libraries (TPLs) offer developers an easier way to enhance their apps with new features. However, how to find suitable candidates among the high number and fast-changing TPLs is a challenging problem. TPL recommendation is a promising solution, but unfortunately existing approaches suffer from low accuracy in recommendation results. To tackle this challenge, we propose GRec, a graph neural network (GNN) based approach, for recommending potentially useful TPLs for app development. GRec models mobile apps, TPLs, and their interactions into an app-library graph. It then distills app-library interaction information from the app-library graph to make more accurate TPL recommendations. To evaluate GRec’s performance, we conduct comprehensive experiments based on a large-scale real-world Android app dataset containing 31,432 Android apps, 752 distinct TPLs, and 537,011 app-library usage records. Our experimental results illustrate that GRec can significantly increase the prediction accuracy and diversify the prediction results compared with state-of-the-art methods. A user study performed with app developers also confirms GRec's usefulness for real-world mobile app development."],"author":["Li, Bo","He, Qiang","Chen, Feifei","Xia, Xin","Li, Li","Grundy, John","Yang, Yun"],"booktitle":["Proc. 29th ACM Jt. Meet. Eur. Softw. Eng. Conf. Symp. Found. Softw. Eng."],"date":["2021"],"doi":["10.1145/3468264.3468552"],"isbn":["978-1-4503-8562-6"],"keywords":["app-library graph","graph neural network","mobile app development","recommendation","third-party library"],"location":["New York, NY, USA"],"note":["TL;DR \n\nGRec, a graph neural network (GNN) based approach, is proposed for recommending potentially useful TPLs for app development and results illustrate that GRec can significantly increase the prediction accuracy and diversify the prediction results compared with state-of-the-art methods."],"pages":["466–477"],"pagetotal":["12"],"publisher":["Association for Computing Machinery"],"series":["ESEC/FSE 2021"],"title":["Embedding app-library graph for neural third party library recommendation"]},"creators":{"author":[{"lastName":"Li","firstName":"Bo"},{"lastName":"He","firstName":"Qiang"},{"lastName":"Chen","firstName":"Feifei"},{"lastName":"Xia","firstName":"Xin"},{"lastName":"Li","firstName":"Li"},{"lastName":"Grundy","firstName":"John"},{"lastName":"Yang","firstName":"Yun"}]},"sentenceCased":true},{"key":"10.1145/3468264.3468571","type":"inproceedings","fields":{"abstract":["With the rise of open-source software and package hosting platforms, reusing 3rd-party libraries has become a common practice. Due to various failures during software evolution, a project may remove a used library and replace it with another library, which we call library migration. Despite substantial research on dependency management, the understanding of how and why library migrations occur is still lacking. Achieving this understanding may help practitioners optimize their library selection criteria, develop automated approaches to monitor dependencies, and provide migration suggestions for their libraries or software projects. In this paper, through a fine-grained commit-level analysis of 19,652 Java GitHub projects, we extract the largest migration dataset to-date (1,194 migration rules, 3,163 migration commits). We show that 8,065 (41.04%) projects having at least one library removal, 1,564 (7.96%, lower-bound) to 5,004 (25.46%, upper-bound) projects have at least one migration, and a median project with migrations has 2 to 4 migrations in total. We discover that library migrations are dominated by several domains (logging, JSON, testing and web service) presenting a long tail distribution. Also, migrations are highly unidirectional in that libraries are either mostly abandoned or mostly chosen in our project corpus. A thematic analysis on related commit messages, issues, and pull requests identifies 14 frequently mentioned migration reasons (e.g., lack of maintenance, usability, integration, etc), 7 of which are not discussed in previous work. Our findings can be operationalized into actionable insights for package hosting platforms, project maintainers, and library developers. We provide a replication package at ¡a¿https://doi.org/10.5281/zenodo.4816752¡/a¿."],"author":["He, Hao","He, Runzhi","Gu, Haiqiao","Zhou, Minghui"],"booktitle":["Proc. 29th ACM Jt. Meet. Eur. Softw. Eng. Conf. Symp. Found. Softw. Eng."],"date":["2021"],"doi":["10.1145/3468264.3468571"],"isbn":["978-1-4503-8562-6"],"keywords":["empirical software engineering","evolution and maintenance","library migration","mining software repositories"],"location":["New York, NY, USA"],"pages":["478–490"],"pagetotal":["13"],"publisher":["Association for Computing Machinery"],"series":["ESEC/FSE 2021"],"title":["A large-scale empirical study on java library migrations: Prevalence, trends, and rationales"]},"creators":{"author":[{"lastName":"He","firstName":"Hao"},{"lastName":"He","firstName":"Runzhi"},{"lastName":"Gu","firstName":"Haiqiao"},{"lastName":"Zhou","firstName":"Minghui"}]},"sentenceCased":true},{"key":"10.1145/3485275","type":"article","fields":{"articleno":["32"],"author":["Watson, Cody","Cooper, Nathan","Palacio, David Nader","Moran, Kevin","Poshyvanyk, Denys"],"date":["2022-03"],"doi":["10.1145/3485275"],"issn":["1049-331X"],"issue_date":["April 2022"],"journaltitle":["ACM Trans. Softw. Eng. Methodol."],"keywords":["Deep learning","literature review","machine learning","neural networks","software engineering"],"location":["New York, NY, USA"],"note":["TL;DR \n\nA systematic literature review of research at the intersection of SE &amp; DL, from its modern inception to the present, that delineates the foundations of DL techniques applied to SE research and highlights likely areas of fertile exploration for the future."],"number":["2"],"pagetotal":["58"],"publisher":["Association for Computing Machinery"],"title":["A systematic literature review on the use of deep learning in software engineering research"],"volume":["31"]},"creators":{"author":[{"lastName":"Watson","firstName":"Cody"},{"lastName":"Cooper","firstName":"Nathan"},{"lastName":"Palacio","firstName":"David Nader"},{"lastName":"Moran","firstName":"Kevin"},{"lastName":"Poshyvanyk","firstName":"Denys"}]},"sentenceCased":true},{"key":"10.1145/3487571","type":"article","fields":{"abstract":["Identifying and optimizing open participation is essential to the success of open software development. Existing studies highlighted the importance of worker recommendation for crowdtesting tasks in order to improve bug detection efficiency, i.e., detect more bugs with fewer workers. However, there are a couple of limitations in existing work. First, these studies mainly focus on one-time recommendations based on expertise matching at the beginning of a new task. Second, the recommendation results suffer from severe popularity bias, i.e., highly experienced workers are recommended in almost all the tasks, while less experienced workers rarely get recommended. This article argues the need for context- and fairness-aware in-process crowdworker recommendation in order to address these limitations. We motivate this study through a pilot study, revealing the prevalence of long-sized non-yielding windows, i.e., no new bugs are revealed in consecutive test reports during the process of a crowdtesting task. This indicates the potential opportunity for accelerating crowdtesting by recommending appropriate workers in a dynamic manner, so that the non-yielding windows could be shortened. Besides, motivated by the popularity bias in existing crowdworker recommendation approach, this study also aims at alleviating the unfairness in recommendations.Driven by these observations, this article proposes a context- and fairness-aware in-process crowdworker recommendation approach, iRec2.0, to detect more bugs earlier, shorten the non-yielding windows, and alleviate the unfairness in recommendations. It consists of three main components: (1) the modeling of dynamic testing context, (2) the learning-based ranking component, and (3) the multi-objective optimization-based re-ranking component. The evaluation is conducted on 636 crowdtesting tasks from one of the largest crowdtesting platforms, and results show the potential of iRec2.0 in improving the cost-effectiveness of crowdtesting by saving the cost, shortening the testing process, and alleviating the unfairness among workers. In detail, iRec2.0 could shorten the non-yielding window by a median of 50%–66% in different application scenarios, and consequently have potential of saving testing cost by a median of 8%–12%. Meanwhile, the recommendation frequency of the crowdworker drop from 34%–60% to 5%–26% under different scenarios, indicating its potential in alleviating the unfairness among crowdworkers."],"articleno":["35"],"author":["Wang, Junjie","Yang, Ye","Wang, Song","Hu, Jun","Wang, Qing"],"date":["2022-03"],"doi":["10.1145/3487571"],"issn":["1049-331X"],"issue_date":["July 2022"],"journaltitle":["ACM Trans. Softw. Eng. Methodol."],"keywords":["Crowdsourced testing","fair recommendation","multi-objective optimization","worker recommendation"],"location":["New York, NY, USA"],"number":["3"],"pagetotal":["31"],"publisher":["Association for Computing Machinery"],"title":["Context- and fairness-aware in-Process crowdworker recommendation"],"volume":["31"]},"creators":{"author":[{"lastName":"Wang","firstName":"Junjie"},{"lastName":"Yang","firstName":"Ye"},{"lastName":"Wang","firstName":"Song"},{"lastName":"Hu","firstName":"Jun"},{"lastName":"Wang","firstName":"Qing"}]},"sentenceCased":true},{"key":"10.1145/3564284","type":"article","fields":{"abstract":["While recent years have witnessed a rapid growth of research papers on recommender system (RS), most of the papers focus on inventing machine learning models to better fit user behavior data. However, user behavior data is observational rather than experimental. This makes various biases widely exist in the data, including but not limited to selection bias, position bias, exposure bias, and popularity bias. Blindly fitting the data without considering the inherent biases will result in many serious issues, e.g., the discrepancy between offline evaluation and online metrics, hurting user satisfaction and trust on the recommendation service, etc. To transform the large volume of research models into practical improvements, it is highly urgent to explore the impacts of the biases and perform debiasing when necessary. When reviewing the papers that consider biases in RS, we find that, to our surprise, the studies are rather fragmented and lack a systematic organization. The terminology “bias” is widely used in the literature, but its definition is usually vague and even inconsistent across papers. This motivates us to provide a systematic survey of existing work on RS biases. In this paper, we first summarize seven types of biases in recommendation, along with their definitions and characteristics. We then provide a taxonomy to position and organize the existing work on recommendation debiasing. Finally, we identify some open challenges and envision some future directions, with the hope of inspiring more research work on this important yet less investigated topic. The summary of debiasing methods reviewed in this survey can be found at https://github.com/jiawei-chen/RecDebiasing."],"author":["Chen, Jiawei","Dong, Hande","Wang, Xiang","Feng, Fuli","Wang, Meng","He†, Xiangnan"],"date":["2022-10"],"doi":["10.1145/3564284"],"issn":["1046-8188"],"journaltitle":["ACM Trans. Inf. Syst."],"keywords":["Adaption","Efficiency","Recommendation","Sampling"],"location":["New York, NY, USA"],"note":["Just Accepted \n\nTL;DR \n\nThis paper summarizes seven types of biases in recommendation, along with their definitions and characteristics, and provides a taxonomy to position and organize the existing work on recommendation debiasing."],"publisher":["Association for Computing Machinery"],"title":["Bias and debias in recommender system: A survey and future directions"]},"creators":{"author":[{"lastName":"Chen","firstName":"Jiawei"},{"lastName":"Dong","firstName":"Hande"},{"lastName":"Wang","firstName":"Xiang"},{"lastName":"Feng","firstName":"Fuli"},{"lastName":"Wang","firstName":"Meng"},{"lastName":"He†","firstName":"Xiangnan"}]},"sentenceCased":true},{"key":"10.1145/963770.963772","type":"article","fields":{"abstract":["Recommender systems have been evaluated in many, often incomparable, ways. In this article, we review the key decisions in evaluating collaborative filtering recommender systems: the user tasks being evaluated, the types of analysis and datasets being used, the ways in which prediction quality is measured, the evaluation of prediction attributes other than quality, and the user-based evaluation of the system as a whole. In addition to reviewing the evaluation strategies used by prior researchers, we present empirical results from the analysis of various accuracy metrics on one content domain where all the tested metrics collapsed roughly into three equivalence classes. Metrics within each equivalency class were strongly correlated, while metrics from different equivalency classes were uncorrelated."],"author":["Herlocker, Jonathan L.","Konstan, Joseph A.","Terveen, Loren G.","Riedl, John T."],"date":["2004-01"],"doi":["10.1145/963770.963772"],"issn":["1046-8188"],"issue_date":["January 2004"],"journaltitle":["ACM Trans. Inf. Syst."],"keywords":["Collaborative filtering","evaluation","metrics","recommender systems"],"location":["New York, NY, USA"],"note":["TL;DR \n\nThe key decisions in evaluating collaborative filtering recommender systems are reviewed: the user tasks being evaluated, the types of analysis and datasets being used, the ways in which prediction quality is measured, the evaluation of prediction attributes other than quality, and the user-based evaluation of the system as a whole."],"number":["1"],"pages":["5–53"],"pagetotal":["49"],"publisher":["Association for Computing Machinery"],"title":["Evaluating collaborative filtering recommender systems"],"volume":["22"]},"creators":{"author":[{"lastName":"Herlocker","firstName":"Jonathan L."},{"lastName":"Konstan","firstName":"Joseph A."},{"lastName":"Terveen","firstName":"Loren G."},{"lastName":"Riedl","firstName":"John T."}]},"sentenceCased":true},{"key":"10.5555/1577069.1755883","type":"article","fields":{"abstract":["Recommender systems are now popular both commercially and in the research community, where many algorithms have been suggested for providing recommendations. These algorithms typically perform differently in various domains and tasks. Therefore, it is important from the research perspective, as well as from a practical view, to be able to decide on an algorithm that matches the domain and the task of interest. The standard way to make such decisions is by comparing a number of algorithms offline using some evaluation metric. Indeed, many evaluation metrics have been suggested for comparing recommendation algorithms. The decision on the proper evaluation metric is often critical, as each metric may favor a different algorithm. In this paper we review the proper construction of offline experiments for deciding on the most appropriate algorithm. We discuss three important tasks of recommender systems, and classify a set of appropriate well known evaluation metrics for each task. We demonstrate how using an improper evaluation metric can lead to the selection of an improper algorithm for the task of interest. We also discuss other important considerations when designing offline experiments."],"author":["Gunawardana, Asela","Shani, Guy"],"date":["2009-12"],"issn":["1532-4435"],"issue_date":["12/1/2009"],"journaltitle":["J. Mach. Learn. Res."],"note":["TL;DR \n\nThis paper reviews the proper construction of offline experiments for deciding on the most appropriate algorithm, and discusses three important tasks of recommender systems, and classify a set of appropriate well known evaluation metrics for each task."],"pages":["2935–2962"],"pagetotal":["28"],"publisher":["JMLR.org"],"title":["A survey of accuracy evaluation metrics of recommendation tasks"],"volume":["10"]},"creators":{"author":[{"lastName":"Gunawardana","firstName":"Asela"},{"lastName":"Shani","firstName":"Guy"}]},"sentenceCased":true},{"key":"10.5555/3001460.3001507","type":"inproceedings","fields":{"abstract":["Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases. The well-known clustering algorithms offer no solution to the combination of these requirements. In this paper, we present the new clustering algorithm DBSCAN relying on a density-based notion of clusters which is designed to discover clusters of arbitrary shape. DBSCAN requires only one input parameter and supports the user in determining an appropriate value for it. We performed an experimental evaluation of the effectiveness and efficiency of DBSCAN using synthetic data and real data of the SEQUOIA 2000 benchmark. The results of our experiments demonstrate that (1) DBSCAN is significantly more effective in discovering clusters of arbitrary shape than the well-known algorithm CLAR-ANS, and that (2) DBSCAN outperforms CLARANS by a factor of more than 100 in terms of efficiency."],"author":["Ester, Martin","Kriegel, Hans-Peter","Sander, Jörg","Xu, Xiaowei"],"booktitle":["Proc. Second Int. Conf. Knowl. Discov. Data Min."],"date":["1996"],"keywords":["arbitrary shape of clusters","clustering algorithms","efficiency on large spatial databases","handling nlj4-275oise"],"location":["Portland, Oregon"],"pages":["226–231"],"pagetotal":["6"],"publisher":["AAAI Press"],"series":["KDD'96"],"title":["A density-based algorithm for discovering clusters in large spatial databases with noise"]},"creators":{"author":[{"lastName":"Ester","firstName":"Martin"},{"lastName":"Kriegel","firstName":"Hans-Peter"},{"lastName":"Sander","firstName":"Jörg"},{"lastName":"Xu","firstName":"Xiaowei"}]},"sentenceCased":true},{"key":"11697_100182","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","Etzlstorfer, Juergen","Iovino, Ludovico","Pierantonio, Alfonso","Schwinger, Wieland"],"booktitle":["Model. Found. Appl. 12th Eur. Conf. ECMFA 2016 Held Part STAF 2016 Vienna Austria July 6-7 2016 Proc."],"date":["2016"],"doi":["10.1007/978-3-319-42061-5_15"],"ids":["diruscioSupportingVariabilityExploration2016,diruscioSupportingVariabilityExploration2016a,ruscioSupportingVariabilityExploration2016,ruscioSupportingVariabilityExploration2016a"],"isbn":["978-3-319-42060-8"],"keywords":["Computer Science (all)","Theoretical Computer Science"],"note":["cited By 9 \n\ncited By 9"],"pages":["231–246"],"publisher":["Springer Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Supporting variability exploration and resolution during model migration"],"volume":["9764"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Etzlstorfer","firstName":"Juergen"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Schwinger","firstName":"Wieland"}]},"sentenceCased":true},{"key":"11697_100188","type":"inproceedings","fields":{"author":["Di Rocco, Juri","Di Ruscio, Davide","Pierantonio, Alfonso","Iovino, Ludovico"],"booktitle":["DSM 2015 - Proc. Workshop Domain-Specif. Model."],"date":["2015"],"doi":["10.1145/2846696.2846703"],"ids":["diroccoSupportingUsersManage2015,diroccoSupportingUsersManage2015a,roccoSupportingUsersManage2015,roccoSupportingUsersManage2015a"],"isbn":["978-1-4503-3903-2"],"keywords":["Breaking unresolvable changes","Code generators","Coupled evolution","MDE","Modeling and Simulation"],"note":["cited By 3 \n\ncited By 3 \n\nTL;DR \n\nThis paper proposes an approach supporting users during the adaptation steps that cannot be fully automated, applied to cope with the coupled evolution of metamodels and model-to-text transformations."],"pages":["47–54"],"publisher":["Association for Computing Machinery, Inc"],"title":["Supporting users to manage breaking and unresolvable changes in coupled evolution"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Iovino","firstName":"Ludovico"}]},"sentenceCased":true},{"key":"11697_100190","type":"article","fields":{"langid":["english"],"author":["Di Rocco, Juri","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2015"],"doi":["10.1109/MS.2015.61"],"ids":["RoccoRIP15,diroccoCollaborativeRepositoriesModeldriven2015,roccoCollaborativeRepositoriesModelDriven2015"],"journaltitle":["IEEE Softw,"],"keywords":["/unread","⛔ No INSPIRE recid found","MDE","MDEForge","model repositories","model-driven engineering","Software","software development","software engineering"],"note":["cited By 59"],"number":["3"],"pages":["28–34"],"timestamp":["Mon, 08 Jun 2020 22:31:48 +0200"],"title":["Collaborative repositories in model-driven engineering"],"volume":["32"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_10461","type":"article","fields":{"author":["Ruscio, Davide Di","Pelliccione","P","Alfonso, Pierantonio"],"date":["2012"],"ids":["ruscioManagingEvolutionFOSS2012"],"journaltitle":["ERCIM NEWS"],"pages":["319–342"],"title":["Managing the evolution of FOSS systems"],"url":["http://ercim-news.ercim.eu/en88/special/managing-the-evolution-of-foss-systems"],"volume":["88"]},"creators":{"author":[{"lastName":"Ruscio","firstName":"Davide Di"},{"literal":"Pelliccione"},{"literal":"P"},{"lastName":"Alfonso","firstName":"Pierantonio"}]},"sentenceCased":true},{"key":"11697_106779","type":"article","fields":{"author":["Ciccozzi, Federico","Crnkovic, Ivica","DI RUSCIO, Davide","Malavolta, Ivano","Pelliccione, Patrizio","Spalazzese, Romina"],"date":["2017"],"doi":["10.1109/MS.2017.1"],"ids":["ciccozziModelDrivenEngineeringMissionCritical2017,ciccozziModelDrivenEngineeringMissionCritical2017a,ciccozziModeldrivenEngineeringMissionCritical2017"],"journaltitle":["IEEE Softw."],"keywords":["internet of things","IoT","Mission critical systems","mission-critical systems","model-driven engineering","software development","software engineering"],"note":["cited By 69 \n\nTL;DR \n\nModel-driven engineering can potentially meet the challenges of mission-critical Internet of Things systems and better enable the adoption of MC-IoTs."],"pages":["46–53"],"title":["Model-driven engineering for mission-critical IoT systems"],"volume":["34"]},"creators":{"author":[{"lastName":"Ciccozzi","firstName":"Federico"},{"lastName":"Crnkovic","firstName":"Ivica"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Pelliccione","firstName":"Patrizio"},{"lastName":"Spalazzese","firstName":"Romina"}]},"sentenceCased":true},{"key":"11697_107894","type":"inproceedings","fields":{"author":["Basciani, Francesco","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"booktitle":["Model-Driven Eng. Lang. Syst. - 17th Int. Conf. MODELS 2014 Valencia Spain Sept. 28 - Oct. 3 2014 Proc."],"date":["2014"],"doi":["10.1007/978-3-319-11653-2_37"],"ids":["bascianiAutomatedChainingModel2014,bascianiAutomatedChainingModel2014a,bascianiAutomatedChainingModel2014b,bascianiAutomatedChainingModel2014c,inproceedings"],"keywords":["Computer Science (all)","Theoretical Computer Science"],"note":["cited By 26 \n\ncited By 26 \n\nTL;DR \n\nIn Model-Driven Engineering models are first-class entities that are manipulated by means of model transformations and the development of complex and large transformations can benefit from the reuse of smaller ones that can be composed according to user requirements."],"pages":["602–618"],"publisher":["Springer Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Automated chaining of model transformations with incompatible metamodels"],"volume":["8767"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_107911","type":"inproceedings","fields":{"author":["Di Rocco, Juri","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"booktitle":["6th Int. Workshop Model. Softw. Eng. MiSE 2014 - Proc."],"date":["2014"],"doi":["10.1145/2593770.2593774"],"ids":["diroccoMiningMetricsUnderstanding2014,diroccoMiningMetricsUnderstanding2014a,roccoMiningMetricsUnderstanding2014"],"isbn":["978-1-4503-2849-4"],"keywords":["Computer Science Applications1707 Computer Vision and Pattern Recognition","Electrical and Electronic Engineering","Metamodel metrics","Metamodeling","Model driven engineering","Software"],"note":["cited By 39 \n\ncited By 39 \n\nTL;DR \n\nA number of metrics are used to quantify and measure metamodels and cross-link different aspects in order to provide additional information about how meetamodel characteristics are related."],"pages":["55–60"],"publisher":["Association for Computing Machinery, Inc"],"title":["Mining metrics for understanding metamodel characteristics"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_107914","type":"inproceedings","fields":{"author":["Di Rocco, Juri","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"booktitle":["Proc. - 7th Int. Workshop Model. Softw. Eng. MiSE 2015"],"date":["2015"],"doi":["10.1109/MiSE.2015.17"],"ids":["diroccoMiningCorrelationsATL2015,diroccoMiningCorrelationsATL2015a,roccoMiningCorrelationsATL2015"],"isbn":["978-1-4799-1934-5"],"keywords":["Modeling and Simulation","Software"],"note":["cited By 10 \n\ncited By 10 \n\nTL;DR \n\nThis paper proposes a process to analyze model transformations with the aim of identifying to what extent their characteristics depend on the corresponding input and target met models."],"pages":["54–59"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Mining correlations of ATL model transformation and metamodel metrics"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_107917","type":"inproceedings","fields":{"author":["Di Rocco, Juri","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"booktitle":["Proc. 2nd Workshop Graph. Model. Lang. Dev. GMLD 2013 - Conjunction Eur. Conf. Model. Found. Appl. ECMFA 2013"],"date":["2013"],"doi":["10.1145/2489820.2489824"],"ids":["diroccoTraceabilityVisualizationMetamodel2013,roccoTraceabilityVisualizationMetamodel2013,roccoTraceabilityVisualizationMetamodel2013a"],"isbn":["978-1-4503-2044-3"],"keywords":["Computer Science Applications1707 Computer Vision and Pattern Recognition","Modeling and Simulation","Software"],"note":["cited By 10 \n\ncited By 10 \n\nTL;DR \n\nHow to generate and visualize traceability information about the dependencies between artifacts in a ecosystem and their related metamodel and how this affects the ecosystem by means of intuitive and straightforward visualization techniques is discussed."],"pages":["51–62"],"title":["Traceability visualization in metamodel change impact detection"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_110621","type":"inproceedings","fields":{"author":["Autili, Marco","Di Ruscio, Davide","Di Salle, Amleto","Perucci, Alexander"],"booktitle":["Proc. 22nd ACM SIGSOFT Int. Symp. Found. Softw. Eng. FSE-22 Hong Kong China Novemb. 16 - 22 2014"],"date":["2014"],"doi":["10.1145/2635868.2661667"],"ids":["autiliCHOReOSyntEnforcingChoreography2014,autiliCHOReOSyntEnforcingChoreography2014a,autiliCHOReOSyntEnforcingChoreography2014b"],"isbn":["978-1-4503-3056-5"],"keywords":["Choreography synthesis","Distributed coordination","Software"],"note":["cited By 13 \n\ncited By 13 \n\nTL;DR \n\nThis paper describes the CHOReOSynt tool, which has been conceived to deal with an additional problem, namely, automated choreography enforcement, and solves this problem by automatically synthesizing additional software entities that, when interposed among the services, allow for preventing undesired interactions."],"pages":["723–726"],"publisher":["Association for Computing Machinery"],"title":["CHOReOSynt: Enforcing choreography realizability in the future internet"],"volume":["16-21-November-2014"]},"creators":{"author":[{"lastName":"Autili","firstName":"Marco"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Di Salle","firstName":"Amleto"},{"lastName":"Perucci","firstName":"Alexander"}]},"sentenceCased":true},{"key":"11697_110934","type":"article","fields":{"author":["Di Ruscio, Davide","family=Lara, given=Juan, prefix=de, useprefix=true","Pierantonio, Alfonso"],"date":["2017"],"doi":["10.1016/j.cl.2016.12.003"],"ids":["diruscioSpecialIssueFlexible2017,diruscioSpecialIssueFlexible2017a,ruscioSpecialIssueFlexible2017"],"journaltitle":["Comput. Lang. Syst. Struct."],"keywords":["Computer Networks and Communications","Software"],"note":["cited By 4 \n\ncited By 4"],"title":["Special issue on flexible model driven engineering"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_111412","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","Kolovos, Dimitrios S.","Korkontzelos, Yannis","Matragkas, Nicholas","Vinju, Jurgen"],"booktitle":["10th Int. Conf. Qual. Inf. Commun. Technol. QUATIC 2016 Lisbon Port. Sept. 6-9 2016"],"date":["2016"],"doi":["10.1109/QUATIC.2016.026"],"ids":["diruscioSupportingCustomQuality2016,diruscioSupportingCustomQuality2017,diruscioSupportingCustomQuality2017a,ruscioSupportingCustomQuality2016,ruscioSupportingCustomQuality2016a"],"isbn":["978-1-5090-3581-6"],"keywords":["Computer Networks and Communications","Information Systems","Management of Technology and Innovation","Reliability and Quality","Risk","Safety","Software"],"note":["cited By 1 \n\ncited By 1"],"pages":["94–99"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Supporting custom quality models to analyse and compare open-source software"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"Korkontzelos","firstName":"Yannis"},{"lastName":"Matragkas","firstName":"Nicholas"},{"lastName":"Vinju","firstName":"Jurgen"}]},"sentenceCased":true},{"key":"11697_111413","type":"inproceedings","fields":{"author":["Basciani, Francesco","Di Rocco, Juri","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"booktitle":["10th Int. Conf. Qual. Inf. Commun. Technol. QUATIC 2016 Lisbon Port. Sept. 6-9 2016"],"date":["2016"],"doi":["10.1109/QUATIC.2016.025"],"ids":["bascianiCustomizableApproachAutomated2016,bascianiCustomizableApproachAutomated2017,bascianiCustomizableApproachAutomated2017a"],"isbn":["978-1-5090-3581-6"],"keywords":["Artefact Quality","Computer Networks and Communications","Information Systems","Management of Technology and Innovation","MDE","Model Quality","Reliability and Quality","Risk","Safety","Software"],"note":["cited By 15 \n\ncited By 15"],"pages":["88–93"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["A customizable approach for the automated quality assessment of modelling artifacts"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_111414","type":"inproceedings","fields":{"author":["Atlee, Joanne","Baillargeon, Robert","Di Ruscio, Davide","Rumpe, Bernhard"],"booktitle":["Proc. - 8th Int. Workshop Model. Softw. Eng. MiSE 2016"],"date":["2016"],"ids":["atleeMessageWorkshopChairs2016,atleeMessageWorkshopChairs2016a"],"isbn":["978-1-4503-4164-6"],"keywords":["Modeling and Simulation","Software"],"note":["cited By 0 \n\ncited By 0 \n\nTL;DR \n\nThe workshop serves a central purpose in helping to define a research community that is really just beginning to emerge in the field of “hardware/software co-design”."],"pages":["vii"],"publisher":["Association for Computing Machinery, Inc"],"title":["Message from the workshop chairs"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973488172&partnerID=40&md5=4c53454d1905560dc7e0f2a62805c560"]},"creators":{"author":[{"lastName":"Atlee","firstName":"Joanne"},{"lastName":"Baillargeon","firstName":"Robert"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Rumpe","firstName":"Bernhard"}]},"sentenceCased":true},{"key":"11697_111418","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","De Lara, Juan","Pierantonio, Alfonso"],"booktitle":["CEUR Workshop Proc."],"date":["2016"],"ids":["diruscioCEURWorkshopProceedings2016,diruscioCEURWorkshopProceedings2016a"],"keywords":["Computer Science (all)"],"note":["cited By 0 \n\ncited By 0"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["CEUR workshop proceedings: Preface"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992533486&partnerID=40&md5=bd42da7c52ba8ecd02ca81bcc01132c9"],"volume":["1694"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"De Lara","firstName":"Juan"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_111420","type":"inproceedings","fields":{"author":["Osman, Haidar","Di Ruscio, Davide","Zaytsev, Vadim","Lungu, Mircea","Bagge, Anya Helene"],"booktitle":["CEUR Workshop Proc."],"date":["2016"],"ids":["osmanSATToSE2016Postproceedings2016,osmanSATToSE2016Postproceedings2016a"],"keywords":["Computer Science (all)"],"note":["cited By 0 \n\ncited By 0"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["SATToSE 2016: The post-proceedings editorial"],"url":["http://ceur-ws.org/"],"volume":["1791"]},"creators":{"author":[{"lastName":"Osman","firstName":"Haidar"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Zaytsev","firstName":"Vadim"},{"lastName":"Lungu","firstName":"Mircea"},{"lastName":"Bagge","firstName":"Anya Helene"}]},"sentenceCased":true},{"key":"11697_111424","type":"inproceedings","fields":{"author":["Basciani, Francesco","DI RUSCIO, Davide","DI ROCCO, Juri","Pierantonio, Alfonso","Iovino, Ludovico"],"booktitle":["Proc. MoDELS 2015 Demo Poster Sess. Co-Located ACMIEEE 18th Int. Conf. Model Driven Eng. Lang. Syst. MoDELS 2015 Ott. Can. Sept. 27 2015"],"date":["2015"],"ids":["bascianiToolClusteringMetamodel2015,bascianiToolClusteringMetamodel2015a,bascianiToolClusteringMetamodel2015b,bascianiToolClusteringMetamodel2015c"],"keywords":["Computer Science (all)"],"note":["cited By 0 \n\ncited By 0 \n\nTL;DR \n\nA clustering tool for automatically organizing stored metamodels and provide users with repository overviews as, for instance, the application domains covered by the available metamadels, which has been implemented and integrated in the MDEForge repository."],"pages":["1–4"],"publisher":["CEUR-WS.org"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["A tool for clustering metamodel repositories"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963641639&partnerID=40&md5=5a37aa0781d1f0fa404c48ce51c2b26b"],"volume":["1554"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Iovino","firstName":"Ludovico"}]},"sentenceCased":true},{"key":"11697_111425","type":"article","fields":{"author":["Van Den Brand, Mark","Di Ruscio, Davide","Kolovos, Dimitrios S.","Rose, Louis M."],"date":["2015"],"doi":["10.1016/j.scico.2014.11.001"],"ids":["brandGuestEditorsIntroduction2015,vandenbrandGuestEditorsIntroduction2015"],"journaltitle":["Sci. Comput. Program."],"keywords":["Software"],"note":["cited By 1"],"pages":["1–2"],"title":["Guest editors' introduction to the fifth issue of Experimental Software and Toolkits (EST): A special issue on Academics Modelling with Eclipse (ACME2012)"],"volume":["98"]},"creators":{"author":[{"lastName":"Van Den Brand","firstName":"Mark"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"Rose","firstName":"Louis M."}]},"sentenceCased":true},{"key":"11697_111428","type":"inproceedings","fields":{"author":["Basciani, Francesco","DI ROCCO, Juri","DI RUSCIO, Davide","Pierantonio, Alfonso","Iovino, Ludovico"],"booktitle":["CEUR Workshop Proc."],"date":["2015"],"ids":["bascianiModelRepositoriesWill2015,bascianiModelRepositoriesWill2015a,bascianiModelRepositoriesWill2015b"],"keywords":["Computer Science (all)"],"note":["cited By 10 \n\ncited By 10"],"pages":["37–42"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["Model repositories: Will they become reality? A position statement"],"url":["http://ceur-ws.org/"],"volume":["1563"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Iovino","firstName":"Ludovico"}]},"sentenceCased":true},{"key":"11697_111431","type":"inproceedings","fields":{"author":["Osman, Haidar","Di Ruscio, Davide","Zaytsev, Vadim","Lungu, Mircea","Bagge, Anya Helene"],"booktitle":["CEUR Workshop Proc."],"date":["2015"],"ids":["osmanSATToSE2015Postproceedings2015,osmanSATToSE2015Postproceedings2015a"],"keywords":["Computer Science (all)"],"note":["cited By 0 \n\ncited By 0"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["SATToSE 2015: The post-proceedings editorial"],"url":["http://ceur-ws.org/"],"volume":["1820"]},"creators":{"author":[{"lastName":"Osman","firstName":"Haidar"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Zaytsev","firstName":"Vadim"},{"lastName":"Lungu","firstName":"Mircea"},{"lastName":"Bagge","firstName":"Anya Helene"}]},"sentenceCased":true},{"key":"11697_111432","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","Kolovos, Dimitrios S.","Korkontzelos, Ioannis","Matragkas, Nicholas","Vinju, Jurgen J."],"booktitle":["2015 10th Jt. Meet. Eur. Softw. Eng. Conf. ACM SIGSOFT Symp. Found. Softw. Eng. ESECFSE 2015 - Proc."],"date":["2015"],"doi":["10.1145/2786805.2803186"],"ids":["diruscioOSSMETERSoftwareMeasurement2015,diruscioOSSMETERSoftwareMeasurement2015a,ruscioOSSMETERSoftwareMeasurement2015"],"isbn":["978-1-4503-3675-8"],"keywords":["Open source software","Software","Source code analysis","Text mining techniques"],"note":["cited By 7 \n\ncited By 7 \n\nTL;DR \n\nOSSMETER is an extensible and scalable platform that can monitor and incrementally analyse a large number of OSS projects and can directly compare different O SS projects with each other."],"pages":["970–973"],"publisher":["Association for Computing Machinery, Inc"],"title":["OSSMETER: A software measurement platform for automatically analysing open source software projects"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"Korkontzelos","firstName":"Ioannis"},{"lastName":"Matragkas","firstName":"Nicholas"},{"lastName":"Vinju","firstName":"Jurgen J."}]},"sentenceCased":true},{"key":"11697_111433","type":"inproceedings","fields":{"author":["Almeida, Bruno","Ananiadou, Sophia","Bagnato, Alessandra","Berreteaga Barbero, Alberto","Di Rocco, Juri","Di Ruscio, Davide","Kolovos, Dimitrios S.","Korkontzelos, Ioannis","Hansen, Scott","Maló, Pedro","Matragkas, Nicholas","Paige, Richard F.","Vinju, Jurgen"],"booktitle":["Proc. Proj. Showc. Part Softw. Technol. Appl. Found. 2015 Fed. Conf. STAF 2015 Aquila Italy July 22 2015"],"date":["2015"],"ids":["almeidaOSSMETERAutomatedMeasurement2015,almeidaOSSMETERAutomatedMeasurement2015a,almeidaOSSMETERAutomatedMeasurement2015b"],"keywords":["Computer Science (all)"],"note":["cited By 4 \n\ncited By 4"],"pages":["36–43"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["OSSMETER: Automated measurement and analysis of open source software"],"url":["http://ceur-ws.org/"],"volume":["1400"]},"creators":{"author":[{"lastName":"Almeida","firstName":"Bruno"},{"lastName":"Ananiadou","firstName":"Sophia"},{"lastName":"Bagnato","firstName":"Alessandra"},{"lastName":"Berreteaga Barbero","firstName":"Alberto"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"Korkontzelos","firstName":"Ioannis"},{"lastName":"Hansen","firstName":"Scott"},{"lastName":"Maló","firstName":"Pedro"},{"lastName":"Matragkas","firstName":"Nicholas"},{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Vinju","firstName":"Jurgen"}]},"sentenceCased":true},{"key":"11697_111437","type":"inproceedings","fields":{"author":["DI RUSCIO, Davide","Malavolta, Ivano","Pelliccione, Patrizio"],"booktitle":["Softw. Eng. Resilient Syst. - 6th Int. Workshop SERENE 2014 Bp. Hung. Oct. 15-16 2014 Proc."],"date":["2014"],"doi":["10.1007/978-3-319-12241-0_3"],"ids":["diruscioRolePartsSystem2014,diruscioRolePartsSystem2014a,ruscioRolePartsSystem2014,ruscioRolePartsSystem2014a"],"isbn":["978-3-319-12240-3"],"keywords":["Computer Science (all)","Theoretical Computer Science"],"note":["cited By 3 \n\ncited By 3 \n\nTL;DR \n\nIn today’s world, the authors are surrounded by software-based systems that control so many critical activities and there is an unavoidable shift from stand-alone systems to systems of systems, to ecosystems, to cyber-physical systems and in general to systems that are composed of various independent parts that collaborate and cooperate to realise the desired goal."],"pages":["24–39"],"publisher":["Springer Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["The role of parts in the system behaviour"],"volume":["8785"]},"creators":{"author":[{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Pelliccione","firstName":"Patrizio"}]},"sentenceCased":true},{"key":"11697_111440","type":"inproceedings","fields":{"author":["DI ROCCO, Juri","DI RUSCIO, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"booktitle":["Proc. Workshop Models Evol. Co-Located ACMIEEE 17th Int. Conf. Model Driven Eng. Lang. Syst. MoDELS 2014 Valencia Spain Sept 28 2014"],"date":["2014"],"ids":["diroccoDealingCoupledEvolution2014,diroccoDealingCoupledEvolution2014a,diroccoDealingCoupledEvolution2014b,roccoDealingCoupledEvolution2014"],"keywords":["Computer Science (all)"],"note":["cited By 12 \n\ncited By 12 \n\nTL;DR \n\nThis paper presents an approach for the coupled evolution of Acceleo-based templating including the OCL embedded in its notation and has been implemented and illustrated by means of a running example."],"pages":["22–31"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["Dealing with the coupled evolution of metamodels and model-to-text transformations"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84923248919&partnerID=40&md5=a2f6518f21c8ff28ac3dd68889891a80"],"volume":["1331"]},"creators":{"author":[{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_111441","type":"inproceedings","fields":{"author":["DI ROCCO, Juri","DI RUSCIO, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"booktitle":["CEUR Workshop Proc."],"date":["2014"],"ids":["diroccoDescribingCorrelationsMetamodels2014,diroccoDescribingCorrelationsMetamodels2014a,roccoDescribingCorrelationsMetamodels2014"],"keywords":["Computer Science (all)","Metamodel metrics","Metamodeling","Model driven engineering","Transformation metrics"],"note":["cited By 1 \n\ncited By 1"],"pages":["90–101"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["Describing the correlations between metamodels and transformations aspects"],"url":["http://ceur-ws.org/"],"volume":["1354"]},"creators":{"author":[{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_111450","type":"inproceedings","fields":{"author":["Cicchetti, Antonio","Di Ruscio, Davide","Eramo, Romina"],"booktitle":["Tenth IEEE Int. Enterp. Distrib. Object Comput. Conf. EDOC 2006 16-20 Oct. 2006 Hong Kong China Workshop"],"date":["2006"],"doi":["10.1109/EDOCW.2006.68"],"ids":["cicchettiPropagationChangesModel2006,cicchettiPropagationChangesModel2006a,cicchettiPropagationChangesModel2006b"],"isbn":["0-7695-2558-X"],"keywords":["Computer Science Applications1707 Computer Vision and Pattern Recognition","Software"],"note":["cited By 14 \n\ncited By 14"],"pages":["24–24"],"title":["Towards propagation of changes by model approximations"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"Antonio"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Eramo","firstName":"Romina"}]},"sentenceCased":true},{"key":"11697_111452","type":"inproceedings","fields":{"author":["Cicchetti, Antonio","Di Ruscio, Davide","Di Salle, Amleto"],"booktitle":["Proc. 2007 ACM Symp. Appl. Comput. SAC Seoul Korea March 11-15 2007"],"date":["2007"],"doi":["10.1145/1244002.1244224"],"ids":["cicchettiSoftwareCustomizationModel2007,cicchettiSoftwareCustomizationModel2007a,cicchettiSoftwareCustomizationModel2007b"],"keywords":["Model driven development","Model transformation","Model-view-controller","Software","Software customization","Web application"],"note":["cited By 15 \n\ncited By 15 \n\nTL;DR \n\nThis paper discusses and attempt to hand-tune the generated code by providing an approach supporting its merging with hand written modifications by considering the behaviour model of the system under study to graphically specify the injection points where the modifications have to occur."],"pages":["1025–1030"],"title":["Software customization in model driven development of web applications"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"Antonio"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Di Salle","firstName":"Amleto"}]},"sentenceCased":true},{"key":"11697_111454","type":"inproceedings","fields":{"author":["Williams, James R.","Di Ruscio, Davide","Matragkas, Nicholas","Di Rocco, Juri","Kolovos, Dimitrios S."],"booktitle":["11th Work. Conf. Min. Softw. Repos. MSR 2014 Proc. May 31 - June 1 2014 Hyderabad India"],"date":["2014"],"doi":["10.1145/2597073.2597132"],"ids":["williamsModelsOSSProject2014,williamsModelsOSSProject2014a"],"isbn":["978-1-4503-2863-0"],"keywords":["Computer Science Applications1707 Computer Vision and Pattern Recognition","Data mining","Software"],"note":["cited By 7 \n\ncited By 7"],"pages":["408–411"],"publisher":["Association for Computing Machinery, Inc"],"title":["Models of OSS project meta-information: A dataset of three forges"]},"creators":{"author":[{"lastName":"Williams","firstName":"James R."},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Matragkas","firstName":"Nicholas"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Kolovos","firstName":"Dimitrios S."}]},"sentenceCased":true},{"key":"11697_111455","type":"inproceedings","fields":{"author":["DI RUSCIO, Davide","Malavolta, Ivano","Pelliccione, Patrizio"],"booktitle":["Proc. 1st Int. Workshop Model-Driven Robot Softw. Eng. Co-Located Int. Conf. Softw. Technol. Appl. Found. MORSESTAF 2014 York UK July 21 2014"],"date":["2014"],"ids":["diruscioFamilyDomainspecificLanguages2014,diruscioFamilyDomainspecificLanguages2014a,ruscioFamilyDomainSpecificLanguages2014"],"keywords":["Computer Science (all)"],"note":["cited By 12 \n\ncited By 12"],"pages":["16–29"],"publisher":["CEUR-WS.org"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["A family of domain-specific languages for specifying civilian missions of multi-robot systems"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84926288188&partnerID=40&md5=9ac6fd0d7810025bceb1feb3800231fc"],"volume":["1319"]},"creators":{"author":[{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Pelliccione","firstName":"Patrizio"}]},"sentenceCased":true},{"key":"11697_111464","type":"inproceedings","fields":{"author":["family=Lara, given=Juan, prefix=de, useprefix=true","DI ROCCO, Juri","DI RUSCIO, Davide","Guerra, Esther","Iovino, Ludovico","Pierantonio, Alfonso","Cuadrado, Jesús Sánchez"],"booktitle":["Fundam. Approaches Softw. Eng. - 20th Int. Conf. FASE 2017 Held Part Eur. Jt. Conf. Theory Pract. Softw. ETAPS 2017 Upps. Swed. April 22-29 2017 Proc."],"date":["2017"],"doi":["10.1007/978-3-662-54494-5_15"],"ids":["delaraReusingModelTransformations2017,delaraReusingModelTransformations2017a,delaraReusingModelTransformations2017b,laraReusingModelTransformations2017"],"isbn":["978-3-662-54494-5"],"keywords":["Computer Science (all)","Theoretical Computer Science"],"note":["cited By 12 \n\ncited By 12"],"pages":["264–282"],"publisher":["Springer Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Reusing model transformations through typing requirements models"],"volume":["10202"]},"creators":{"author":[{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true},{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Cuadrado","firstName":"Jesús Sánchez"}]},"sentenceCased":true},{"key":"11697_111465","type":"inproceedings","fields":{"author":["Basciani, Francesco","DI ROCCO, Juri","DI RUSCIO, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"booktitle":["Post-Proc. Seventh Semin. Adv. Tech. Tools Softw. Evol. SATToSE 2014 Aquila Italy 9-11 July 2014"],"date":["2014"],"ids":["bascianiQualifyingChainsTransformation2014,bascianiQualifyingChainsTransformation2014a"],"keywords":["Computer Science (all)"],"note":["cited By 0 \n\ncited By 0 \n\nTL;DR \n\nThis paper proposes an approach to classify these suitable chains with respect to the coverage of the metamodels involved in the transformation with an evaluation criteria which gives as an indication of how much information a transformation chain covers over another."],"pages":["79–89"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["Qualifying chains of transformation with coverage based evaluation criteria"],"url":["http://ceur-ws.org/"],"volume":["1354"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_119338","type":"article","fields":{"author":["Franzago, MIRCO GIOVANNI UMBERTO","DI RUSCIO, Davide","Malavolta, Ivano","Muccini, Henry"],"date":["2017"],"doi":["10.1109/TSE.2017.2755039"],"ids":["franzagoCollaborativeModelDrivenSoftware2018,franzagoCollaborativeModelDrivenSoftware2018a,franzagoCollaborativeModeldrivenSoftware2018"],"journaltitle":["IEEE Trans. Softw. Eng."],"keywords":["Collaborative Software Engineering","model-driven engineering","Model-Driven Engineering","Systematic Mapping study"],"note":["cited By 49 \n\nTL;DR \n\nResearchers and practitioners can use the results for identifying existing research/technical gaps to attack, better scoping their own contributions, or understanding existing ones for identifying, classifying, and understanding existing collaborative MDSE approaches."],"number":["12"],"pages":["1146–1175"],"title":["Collaborative model-driven software engineering: A classification framework and a research map"],"volume":["44"]},"creators":{"author":[{"lastName":"Franzago","firstName":"MIRCO GIOVANNI UMBERTO"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Muccini","firstName":"Henry"}]},"sentenceCased":true},{"key":"11697_119347","type":"inproceedings","fields":{"author":["DI RUSCIO, Davide","Franzago, MIRCO GIOVANNI UMBERTO","Malavolta, Ivano","Muccini, Henry"],"booktitle":["Proc. - 2017 IEEEACM 39th Int. Conf. Softw. Eng. Companion ICSE-C 2017"],"date":["2017"],"doi":["10.1109/ICSE-C.2017.143"],"ids":["diruscioEnvisioningFutureCollaborative2017,diruscioEnvisioningFutureCollaborative2017a,ruscioEnvisioningFutureCollaborative2017"],"isbn":["978-1-5386-1589-8"],"keywords":["Collaborative MDSE","Collaborative Software Engineering","model-driven engineering","Model-Driven Engineering","Reliability and Quality","Risk","Safety","Software"],"note":["cited By 16 \n\ncited By 16 \n\nTL;DR \n\nThe adoption of Model-driven Software Engineering to develop complex software systems in application domains like automotive and aerospace is being supported by the maturation of model-driven platforms and tools, but empirical studies show that a wider adoption is still an issue."],"pages":["219–221"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Envisioning the future of collaborative model-driven software engineering"]},"creators":{"author":[{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Franzago","firstName":"MIRCO GIOVANNI UMBERTO"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Muccini","firstName":"Henry"}]},"sentenceCased":true},{"key":"11697_121392","type":"incollection","fields":{"author":["Chechik, Marsha","Di Ruscio, Davide","Rumpe, Bernhard"],"booktitle":["Proceedings - 2017 IEEE/ACM 9th international workshop on modelling in software engineering, MiSE 2017"],"date":["2017"],"doi":["10.1109/MiSE.2017.11"],"ids":["chechikMessageWorkshopChairs2017,chechikMessageWorkshopChairs2017a"],"isbn":["978-1-5386-0426-7"],"keywords":["Modeling and Simulation","Software"],"note":["cited By 0 \n\ncited By 0"],"pages":["vii-vii"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Message from the workshop chairs MiSE 2017"]},"creators":{"author":[{"lastName":"Chechik","firstName":"Marsha"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Rumpe","firstName":"Bernhard"}]},"sentenceCased":true},{"key":"11697_121393","type":"incollection","fields":{"author":["Di Ruscio, Davide","Chechik, Marsha","Rumpe, Bernhard"],"booktitle":["9th IEEE/ACM International Workshop on Modelling in Software Engineering, MiSE@ICSE 2017, Buenos Aires, Argentina, May 21-22, 2017"],"date":["2017"],"doi":["10.1109/MiSE.2017.15"],"ids":["diruscio9thWorkshopModelling2017,diruscio9thWorkshopModelling2017a,diruscio9thWorkshopModelling2017b,diruscio9thWorkshopModelling2017c,ruscio9thWorkshopModelling2017"],"isbn":["978-1-5386-0426-7"],"keywords":["Modeling and Simulation","Software"],"note":["cited By 0 \n\ncited By 0"],"pages":["1–1"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["9th workshop on modelling in software engineering (MiSE 2017)"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Chechik","firstName":"Marsha"},{"lastName":"Rumpe","firstName":"Bernhard"}]},"sentenceCased":true},{"key":"11697_121394","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","Etzlstorfer, Juergen","Iovino, Ludovico","Pierantonio, Alfonso","Schwinger, Wieland"],"booktitle":["Model. Found. Appl. - 13th Eur. Conf. ECMFA 2017 Held Part STAF 2017 Marburg Ger. July 19-20 2017 Proc."],"date":["2017"],"doi":["10.1007/978-3-319-61482-3_5"],"ids":["diruscioFeaturebasedApproachVariability2017,diruscioFeaturebasedApproachVariability2017a,ruscioFeatureBasedApproachVariability2017"],"isbn":["978-3-319-61481-6"],"keywords":["Computer Science (all)","Theoretical Computer Science"],"note":["cited By 7 \n\ncited By 7"],"pages":["71–89"],"publisher":["Springer Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["A feature-based approach for variability exploration and resolution in model transformation migration"],"volume":["10376 LNCS"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Etzlstorfer","firstName":"Juergen"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Schwinger","firstName":"Wieland"}]},"sentenceCased":true},{"key":"11697_121395","type":"incollection","fields":{"author":["Kolovos, Dimitris","Di Ruscio, Davide","Matragkas, Nicholas","Cuadrado, Jesus Sanchez","Rath, Istvan","Tisi, Massimo"],"booktitle":["CEUR workshop proceedings"],"date":["2015"],"keywords":["Computer Science (all)"],"publisher":["CEUR-WS"],"title":["Proceedings of the 3rd Workshop on Scalable Model Driven Engineering part of the Software Technologies: Applications and Foundations (STAF 2015) federation of conferences"],"url":["http://ceur-ws.org/"],"volume":["1406"]},"creators":{"author":[{"lastName":"Kolovos","firstName":"Dimitris"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Matragkas","firstName":"Nicholas"},{"lastName":"Cuadrado","firstName":"Jesus Sanchez"},{"lastName":"Rath","firstName":"Istvan"},{"lastName":"Tisi","firstName":"Massimo"}]},"sentenceCased":true},{"key":"11697_121396","type":"inproceedings","fields":{"author":["Ciccozzi, Federico","Di Ruscio, Davide","Malavolta, Ivano","Pelliccione, Patrizio","Tumova, Jana"],"booktitle":["Proc. - 2017 IEEEACM 39th Int. Conf. Softw. Eng. Companion ICSE-C 2017"],"date":["2017"],"doi":["10.1109/ICSE-C.2017.167"],"ids":["ciccozziEngineeringSoftwareRobotic2017,ciccozziEngineeringSoftwareRobotic2017a,ciccozziEngineeringSoftwareRobotic2017b"],"isbn":["978-1-5386-1589-8"],"keywords":["model-driven engineering","Model-Driven Engineering","Reliability and Quality","Risk","Robotics","Safety","Software","software engineering","Software Engineering"],"note":["cited By 13 \n\ncited By 13"],"pages":["507–508"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Engineering the software of robotic systems"]},"creators":{"author":[{"lastName":"Ciccozzi","firstName":"Federico"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Pelliccione","firstName":"Patrizio"},{"lastName":"Tumova","firstName":"Jana"}]},"sentenceCased":true},{"key":"11697_121397","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","De Lara, Juan","Kolovos, Dimitris","Matragkas, Nicholas","Rath, Istvan","Tisi, Massimo"],"booktitle":["CEUR Workshop Proc."],"date":["2014"],"ids":["diruscioProceedings2ndWorkshop2014"],"keywords":["Computer Science (all)"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["Proceedings of the 2nd workshop on scalability in model driven engineering co-located with the software technologies: Applications and foundations conference, BigMDE@STAF2014"],"url":["http://ceur-ws.org/"],"volume":["1206"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"De Lara","firstName":"Juan"},{"lastName":"Kolovos","firstName":"Dimitris"},{"lastName":"Matragkas","firstName":"Nicholas"},{"lastName":"Rath","firstName":"Istvan"},{"lastName":"Tisi","firstName":"Massimo"}]},"sentenceCased":true},{"key":"11697_121399","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","Zaytsev, Vadim"],"booktitle":["CEUR Workshop Proc."],"date":["2014"],"ids":["diruscioSATToSE2014Postproceedings2014,diruscioSATToSE2014Postproceedings2014a"],"keywords":["Computer Science (all)"],"note":["cited By 0 \n\ncited By 0 \n\nTL;DR \n\nAn approach to understand structural characteristics of metamodels by looking at how model transformations depend on metamodels of their source and target models is presented."],"pages":["1–5"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["SATToSE 2014: The post-proceedings editorial"],"url":["http://ceur-ws.org/"],"volume":["1354"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Zaytsev","firstName":"Vadim"}]},"sentenceCased":true},{"key":"11697_121401","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","Kolovos, Dimitrios","Matragkas, Nicholas"],"booktitle":["Proc. Workshop Scalability Model Driven Eng. Bp. Hung. June 17 2013"],"date":["2013"],"doi":["10.1145/2487766.2487767"],"ids":["diruscioScalabilityModelDriven2013,diruscioScalabilityModelDriven2013a,ruscioScalabilityModelDriven2013,ruscioScalabilityModelDriven2013a"],"isbn":["978-1-4503-2165-5"],"keywords":["1707","BigMDE","Computer Networks and Communications","Human-Computer Interaction","MDE","Scalability","Software"],"note":["cited By 1 \n\ncited By 1"],"pages":["1–2"],"title":["Scalability in model driven engineering - BigMDE'13 workshop summary"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Kolovos","firstName":"Dimitrios"},{"lastName":"Matragkas","firstName":"Nicholas"}]},"sentenceCased":true},{"key":"11697_121402","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","Kolovos, Dimitrios","Rose, Louis","Al-Hilank, Samir"],"booktitle":["Proc. Workshop Acad. Tool. Eclipse ACMEECOOP 2013 Montp. Fr. July 2 2013"],"date":["2013"],"doi":["10.1145/2491279.2491280"],"ids":["diruscioACadeMicsToolingEclipse2013,diruscioACadeMicsToolingEclipse2013a,diruscioACadeMicsToolingEclipse2013b,ruscioACadeMicsToolingEclipse2013"],"isbn":["978-1-4503-2036-8"],"keywords":["Software"],"note":["cited By 0 \n\ncited By 0 \n\nTL;DR \n\nThe Eclipse platform has played a very significant role in the evolution of software engineering research over the last few years as it has provided mature infrastructure for the development of orthogonal but interoperable prototypes in areas including model driven engineering, code analysis, data visualisation, software measurement and testing and language development."],"pages":["1:1–1:2"],"publisher":["ACM"],"title":["ACadeMics tooling with Eclipse: ACME 2013 workshop summmary"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Kolovos","firstName":"Dimitrios"},{"lastName":"Rose","firstName":"Louis"},{"lastName":"Al-Hilank","firstName":"Samir"}]},"sentenceCased":true},{"key":"11697_121403","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","Jackson, Ethan"],"booktitle":["Jt. Proc. Model. Invit. Talks Demonstr. Sess. Poster Sess. ACM Stud. Res. Compet. Co-Located 16th Int. Conf. Model Driven Eng. Lang. Syst. MODELS 2013"],"date":["2013"],"ids":["diruscioACMStudentResearch2013,diruscioACMStudentResearch2013a,diruscioACMStudentResearch2013b"],"keywords":["Computer Science (all)"],"note":["cited By 0 \n\ncited By 0"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["ACM student research competition at MoDELS 2013"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921919454&partnerID=40&md5=03f4a0df3c070c47a6f17cca8571698b"],"volume":["1115"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Jackson","firstName":"Ethan"}]},"sentenceCased":true},{"key":"11697_121404","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","Pierantonio, Alfonso","De Lara, Juan"],"booktitle":["2012 Extreme Model. Workshop XM 2012 - Post-Proc. Satell. Event IEEEACM 15th Int. Conf. Model Driven Eng. Lang. Syst. MODELS 2012"],"date":["2012"],"doi":["10.1145/2467307.2467308"],"ids":["diruscioSummaryExtremeModeling2012,diruscioSummaryExtremeModeling2012a,ruscioSummaryExtremeModeling2012"],"isbn":["978-1-4503-1804-4"],"keywords":["Information Systems","Modeling and Simulation","Software"],"note":["cited By 0 \n\ncited By 0 \n\nTL;DR \n\nThis volume includes 8 papers from the Extreme Modeling workshop (XM'2012), a satellite event of MoDELS 2012 held on October, 1st 2012, in Innsbruck, Austria."],"pages":["1–2"],"title":["Summary of the extreme modeling workshop (XM'12)"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"De Lara","firstName":"Juan"}]},"sentenceCased":true},{"key":"11697_121405","type":"incollection","fields":{"author":["Di Ruscio, Davide","Kolovos, Dimitris"],"booktitle":["ACM international conference proceeding series"],"date":["2011"],"isbn":["978-1-4503-0668-3"],"keywords":["1707","Computer Networks and Communications","Human-Computer Interaction","Software"],"title":["Proceedings of the 2nd international workshop on model comparison in practice"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Kolovos","firstName":"Dimitris"}]},"sentenceCased":true},{"key":"11697_121406","type":"incollection","fields":{"author":["Di Ruscio, Davide","Kolovos, Dimitris"],"booktitle":["ACM international conference proceeding series"],"date":["2010"],"isbn":["978-1-60558-960-2"],"keywords":["1707","Computer Networks and Communications","Human-Computer Interaction","Software"],"note":["TL;DR \n\nThe number of submitted and accepted papers indicates that the field of model comparison is an important and actively-researched field within the community and it is hoped that this workshop will trigger useful discussions and help with establishing a deeper understanding - and potentially new collaborations - between researchers."],"title":["Proceedings of the 1st international workshop on model comparison in practice"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Kolovos","firstName":"Dimitris"}]},"sentenceCased":true},{"key":"11697_121408","type":"article","fields":{"author":["Chechik, Marsha","DI RUSCIO, Davide"],"date":["2017"],"doi":["10.1145/3149485.3149520"],"ids":["chechikReport9thWorkshop2017,chechikReport9thWorkshop2017a,chechikReport9thWorkshop2017b"],"journaltitle":["Softw. Eng. NOTES"],"note":["TL;DR \n\nThe 9th edition of the MiSE workshop provided a forum to discuss successful applications of software-modeling techniques and to gain insights into challenging modeling techniques, including uncertainty management, model heterogeneity, model reuse and evolution, testing, and the adoption of mod- els in critical application domains like self-adaptive and real-time systems."],"pages":["21–24"],"title":["Report from the 9th workshop on modelling in software Engineering(MiSE 2017)"],"volume":["42"]},"creators":{"author":[{"lastName":"Chechik","firstName":"Marsha"},{"lastName":"DI RUSCIO","firstName":"Davide"}]},"sentenceCased":true},{"key":"11697_121412","type":"inproceedings","fields":{"author":["DI ROCCO, Juri","DI RUSCIO, Davide","Heinz, Marcel","Iovino, Ludovico","Laemmel, Ralf","Pierantonio, Alfonso"],"booktitle":["Proc. MODELS 2017 Satell. Event Workshop ModComp ME EXE COMMitMDE MRT MULTI GEMOC MoDeVVa MDETools FlexMDE MDEbug Posters Dr. Symp. Educ. Symp. ACM Stud. Res. Compet. Tools Demonstr. Co-Located ACMIEEE 20th Int. Conf. Model Driven Eng. Lang. Syst. MODELS 2017 Austin TX USA Sept. 17 2017"],"date":["2017"],"ids":["roccoConsistencyRecoveryInteractive2017,roccoConsistencyRecoveryInteractive2017a,roccoConsistencyRecoveryInteractive2017b"],"note":["cited By 4 \n\ncited By 4 \n\nTL;DR \n\nThis paper captures the types of artifacts and the relevant relationships in a megamodelingbased manner for the purpose of monitoring and recovering a MDE project’s consistency in response to changes that users may apply to the project within an interactive modeling platform."],"pages":["116–122"],"publisher":["CEUR-WS.org"],"series":["CEUR Workshop Proceedings"],"title":["Consistency recovery in interactive modeling"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041451947&partnerID=40&md5=af32ec5dad9d2b3a5a174631d0ac6972"],"volume":["2019"]},"creators":{"author":[{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Heinz","firstName":"Marcel"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Laemmel","firstName":"Ralf"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_121413","type":"inproceedings","fields":{"author":["Bagnato, Alessandra","Barmpis, Konstantinos","Bessis, Nik","Adrian Cabrera-Diego, Luis","DI ROCCO, Juri","DI RUSCIO, Davide","Gergely, Tamas","Hansen, Scott","Kolovos, Dimitris S.","Krief, Philippe","Korkontzelos, Ioannis","Lauriere, Stephane","Manrique Lopez de la Fuente, Jose","Malo, Pedro","Paige, Richard F.","Spinellis, Diomidis","Thomas, Cedric","Vinju, Jurgen J."],"booktitle":["Softw. Technol. Appl. Found. - STAF 2017 Collocated Workshop Marburg Ger. July 17-21 2017 Revis. Sel. Pap."],"date":["2017"],"doi":["10.1007/978-3-319-74730-9"],"isbn":["978-3-319-74729-3"],"note":["TL;DR \n\nCROSSMINER uniquely combines advanced software project analyses with online IDE monitoring and automatically extracting the required knowledge and injecting it into the developers’ Integrated Development Environments (IDE), at the time they need it to make design decisions."],"publisher":["Springer"],"title":["Developer-centric knowledge mining from large open-source software repositories (CROSSMINER)"],"volume":["10748"]},"creators":{"author":[{"lastName":"Bagnato","firstName":"Alessandra"},{"lastName":"Barmpis","firstName":"Konstantinos"},{"lastName":"Bessis","firstName":"Nik"},{"lastName":"Adrian Cabrera-Diego","firstName":"Luis"},{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Gergely","firstName":"Tamas"},{"lastName":"Hansen","firstName":"Scott"},{"lastName":"Kolovos","firstName":"Dimitris S."},{"lastName":"Krief","firstName":"Philippe"},{"lastName":"Korkontzelos","firstName":"Ioannis"},{"lastName":"Lauriere","firstName":"Stephane"},{"lastName":"Manrique Lopez de la Fuente","firstName":"Jose"},{"lastName":"Malo","firstName":"Pedro"},{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Spinellis","firstName":"Diomidis"},{"lastName":"Thomas","firstName":"Cedric"},{"lastName":"Vinju","firstName":"Jurgen J."}]},"sentenceCased":true},{"key":"11697_126147","type":"article","fields":{"author":["Basciani, Francesco","Demidio, Mattia","Di Ruscio, Davide","Frigioni, Daniele","Iovino, Ludovico","Pierantonio, Alfonso"],"date":["2018"],"entrysubtype":["magazine"],"journaltitle":["IEEE TRANSACTIONS ON SOFTWARE ENGINEERING"],"keywords":["Adaptation models","Analytical models","Bridges","Ecosystems","Graph Algorithms","Model driven engineering","Model Transformation Composition","model-driven engineering","Model-driven engineering","Shortest Paths","Software","Unified modeling language"],"note":["TL;DR \n\nThis paper proposes an approach, based on well-established algorithms, to support modellers when multiple transformation chains are available to bridge a source metamodel with a target one."],"pages":["251–279"],"title":["Automated Selection of Optimal Model Transformation Chains via Shortest-Path Algorithms"],"url":["http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=32"],"volume":["46"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"Demidio","firstName":"Mattia"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Frigioni","firstName":"Daniele"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]}},{"key":"11697_128217","type":"book","fields":{"abstract":["Nowadays, collaborative modeling performed by multiple stakeholders is gaining a growing interest in both academia and practice. However, it poses a set of research challenges, such as large and complex models management, support for multi-user modeling environments, and synchronization mechanisms like models migration and merging, conflicts management, models versioning and rollback support. A body of knowledge in the scientific literature about collaborative model-driven software engineering (MDSE) exists. Still, those studies are scattered across different independent research areas, such as software engineering, model-driven engineering languages and systems, model integrated computing, etc., and a study classifying and comparing the various approaches and methods for collaborative MDSE is still missing. Under this perspective, a systematic mapping study (SMS) can help researchers and practitioners in (i) having a complete, comprehensive and valid picture of the state of the art about collaborative MDSE, and (ii) identifying potential gaps in current research and future research directions."],"author":["Franzago, MIRCO GIOVANNI UMBERTO","DI RUSCIO, Davide","Malavolta, Ivano","Muccini, Henry"],"date":["2016"],"eprint":["1611.02619"],"eprinttype":["arxiv"],"ids":["franzagoProtocolSystematicMapping2016,franzagoProtocolSystematicMapping2016a"],"journaltitle":["CoRR"],"keywords":["Computer Science - Software Engineering"],"note":["TL;DR \n\nA systematic mapping study (SMS) can help researchers and practitioners in having a complete, comprehensive and valid picture of the state of the art about collaborative MDSE, and identifying potential gaps in current research and future research directions."],"publisher":["arXiv"],"title":["Protocol for a systematic mapping study on collaborative model-driven software engineering"],"url":["http://arxiv.org/abs/1611.02619v1"],"volume":["abs/1611.02619"]},"creators":{"author":[{"lastName":"Franzago","firstName":"MIRCO GIOVANNI UMBERTO"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Muccini","firstName":"Henry"}]},"sentenceCased":true},{"key":"11697_128309","type":"article","fields":{"author":["Afzal, Wasif","Bruneliere, Hugo","Di Ruscio, Davide","Sadovykh, Andrey","Mazzini, Silvia","Cariou, Eric","Truscan, Dragos","Cabot, Jordi","Gómez, Abel","Gorroñogoitia, Jesús","Pomante, Luigi","Smrz, Pavel"],"date":["2018"],"doi":["10.1016/j.micpro.2018.05.010"],"ids":["11697_121409,afzalMegaMRt2ECSEL2017,afzalMegaMRt2ECSEL2017a,afzalMegaMRt2ECSEL2017b,afzalMegaMRt2ECSEL2018,afzalMegaMRt2ECSEL2018a,afzalMegaMRt2ECSEL2018b"],"isbn":["978-1-5386-2146-2"],"journaltitle":["Microprocess. Microsyst."],"keywords":["Artificial Intelligence","Computer Networks and Communications","Design time","Hardware and Architecture","Megamodelling","model-driven engineering","Model-driven engineering","Runtime","Software"],"note":["cited By 6 \n\ncited By 6 \n\ncited By 25"],"pages":["86–95"],"publisher":["IEEE Computer Society"],"title":["The MegaM@Rt2 ECSEL project: MegaModelling at Runtime – Scalable model-based framework for continuous development and runtime validation of complex systems"],"volume":["61"]},"creators":{"author":[{"lastName":"Afzal","firstName":"Wasif"},{"lastName":"Bruneliere","firstName":"Hugo"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Sadovykh","firstName":"Andrey"},{"lastName":"Mazzini","firstName":"Silvia"},{"lastName":"Cariou","firstName":"Eric"},{"lastName":"Truscan","firstName":"Dragos"},{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Gómez","firstName":"Abel"},{"lastName":"Gorroñogoitia","firstName":"Jesús"},{"lastName":"Pomante","firstName":"Luigi"},{"lastName":"Smrz","firstName":"Pavel"}]},"sentenceCased":true},{"key":"11697_128310","type":"inproceedings","fields":{"author":["Di Rocco, Juri","Di Ruscio, Davide","Narayanankutty, Hrishikesh","Pierantonio, Alfonso"],"booktitle":["Proc. MODELS 2018 Workshop ModComp MRT OCL FlexMDE EXE COMMitMDE MDETools GEMOC MORSE MDE4IoT MDEbug MoDeVVa ME MULTI HuFaMo AMMoRe PAINS Co-Located ACMIEEE 21st Int. Conf. Model Driven Eng. Lang. Syst. MODELS 2018 Cph. Den. Oct. 14 2018"],"date":["2018"],"ids":["diroccoResilienceSiriusEditors2018,diroccoResilienceSiriusEditors2018a,diroccoResilienceSiriusEditors2018b,roccoResilienceSiriusEditors2018a,roccoResilienceSiriusEditors2018b"],"keywords":["Co-evolution","Computer Science (all)","model-driven engineering","Model-Driven Engineering","Sirius Editors"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 3 \n\ncited By 3 \n\nTL;DR \n\nA study is presented that analyzes the impact of meta-model changes over visual editors based on the Sir-ius framework to provide designers with the possibility to perform an early assessment of the early assessment of the editor consistency needed to restore the editor consistency."],"pages":["620–630"],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"title":["Resilience in sirius editors: Understanding the impact of meta-model changes"],"url":["http://ceur-ws.org/"],"volume":["2192"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Narayanankutty","firstName":"Hrishikesh"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_128311","type":"inproceedings","fields":{"author":["Di Rocco, Juri","Di Ruscio, Davide","Härtel, Johannes","Iovino, Ludovico","Lämmel, Ralf","Pierantonio, Alfonso"],"booktitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"date":["2018"],"doi":["10.1007/978-3-319-93317-7_5"],"ids":["diroccoSystematicRecoveryMDE2018,diroccoSystematicRecoveryMDE2018a,diroccoSystematicRecoveryMDE2018b,roccoSystematicRecoveryMDE2018"],"isbn":["978-3-319-93316-0"],"keywords":["Computer Science (all)","Theoretical Computer Science"],"note":["cited By 4 \n\ncited By 4"],"pages":["110–126"],"publisher":["Springer Verlag"],"series":["LECTURE NOTES IN ARTIFICIAL INTELLIGENCE"],"title":["Systematic recovery of MDE technology usage"],"volume":["10888"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Härtel","firstName":"Johannes"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Lämmel","firstName":"Ralf"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_128312","type":"inproceedings","fields":{"author":["Nguyen, Phuong T.","Di Rocco, Juri","Rubei, Riccardo","Di Ruscio, Davide"],"booktitle":["44th Euromicro Conf. Softw. Eng. Adv. Appl. SEAA 2018 Prague Czech Repub. August 29-31 2018"],"date":["2018"],"doi":["10.1109/SEAA.2018.00069"],"ids":["8498236,nguyenCrossSimExploitingMutual2018,nguyenCrossSimExploitingMutual2018a,nguyenCrossSimExploitingMutual2018b"],"isbn":["978-1-5386-7383-6"],"keywords":["Computational modeling","Ecosystems","Libraries","Mining software repositories","Open source software","Semantics","SimRank","software similarities","Software similarities","Software systems"],"note":["cited By 15 \n\ncited By 15 \n\nTL;DR \n\nCrossSim is proposed as a novel approach to model open source software projects and related artifacts and to compute similarities among them and shows that CrossSim outperforms an existing technique, which has been proven to have a good performance in detecting similar GitHub repositories."],"pages":["388–395"],"title":["CrossSim: Exploiting mutual relationships to detect similar OSS projects"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Rubei","firstName":"Riccardo"},{"lastName":"Di Ruscio","firstName":"Davide"}]},"sentenceCased":true},{"key":"11697_128313","type":"inproceedings","fields":{"author":["Basciani, Francesco","Di Ruscio, Davide","D'Emidio, Mattia","Frigioni, Daniele","Pierantonio, Alfonso","Iovino, Ludovico"],"booktitle":["Proc. 21st ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion Proc. MODELS 2018 Cph. Den. Oct. 14-19 2018"],"date":["2018"],"doi":["10.1145/3270112.3270123"],"ids":["bascianiToolAutomaticallySelecting2018,bascianiToolAutomaticallySelecting2018a,bascianiToolAutomaticallySelecting2018b"],"isbn":["978-1-4503-5965-8"],"note":["cited By 1 \n\ncited By 1 \n\nTL;DR \n\nThe CITRIC tool is presented as a solution to mitigate the problem of characterizing the multitude of transformation chains that can be defined by composing existing model transformations to bridge source and target metamodels that are of interest for the modeler."],"pages":["2–6"],"publisher":["ACM"],"title":["A tool for automatically selecting optimal model transformation chains"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"D'Emidio","firstName":"Mattia"},{"lastName":"Frigioni","firstName":"Daniele"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Iovino","firstName":"Ludovico"}]},"sentenceCased":true},{"key":"11697_132211","type":"article","fields":{"langid":["english"],"abstract":["In Model Driven Engineering (MDE), analogously to any software development practice, metamodel design must be accurate and performed by considering relevant quality factors including maintainability, reusability, and understandability. The quality of metamodels might be compromised by the introduction of smells that can be the result of inappropriate design decisions. Detecting and resolving metamodel smells is a complex task. Existing approaches deal with this problem by supporting the identification and resolution of smells without providing the means to explicitly trace them with the quality attributes that can be potentially affected. In this paper, we present an approach to defining extensible catalogues of metamodel smells. Each smell can be linked to corresponding quality attributes. Such links are exploited to automatically select only those smells that have to be necessarily resolved for enhancing the quality factors that are of interest for the modeler. The implementation of the approach is based on the Edelta language and it has been validated on a corpus of metamodels retrieved from a publicly available repository."],"author":["Bettini, Lorenzo","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"date":["2019"],"doi":["10.1109/ACCESS.2019.2891357"],"entrysubtype":["magazine"],"ids":["8632659,bettiniQualityDrivenDetectionResolution2019,bettiniQualityDrivenDetectionResolution2019a"],"issn":["2169-3536"],"journaltitle":["IEEE Access"],"keywords":["Analytical models","Companies","Computer Science (all)","Containers","Customer relationship management","domain-specific languages","Domain-specific languages","Edelta language","Engineering (all)","formal specification","maintainability","Materials Science (all)","metamodel design","metamodel smells resolution","model-driven engineering","Object oriented modeling","Quality assurance","quality-driven detection","reusability","Software","software development practice","software metrics","software quality","software quality engineering","systems analysis","understandability"],"note":["cited By 21 \n\nTL;DR \n\nThis paper presents an approach to defining extensible catalogues of metamodel smells that automatically select only those smells that have to be necessarily resolved for enhancing the quality factors that are of interest for the modeler."],"pages":["16364–16376"],"title":["Quality-driven Detection and Resolution of Metamodel Smells"],"volume":["7"]},"creators":{"author":[{"lastName":"Bettini","firstName":"Lorenzo"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_132481","type":"article","fields":{"langid":["english"],"author":["Carver, Jeffrey C.","Minku, Leandro L.","Penzenstadler, Birgit","undefined","undefined","undefined","undefined"],"date":["2017-01"],"entrysubtype":["magazine"],"ids":["bozhinoskiSafetyMobileRobotic2019a"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["duplicate-citation-key"],"note":["TL;DR \n\nThis issue's column reports on papers from the 24th International Requirements Engineering Conference, 38th International Conference on Software Engineering, and the 10th International Symposium on Empirical Software Engineering and Measurement, which discuss performance and security requirements, injecting human values into software engineering, and mapping the software development technology landscape."],"number":["1"],"pages":["150–179"],"title":["Requirements, Human Values, and the Development Technology Landscape"],"url":["http://ieeexplore.ieee.org/document/7819412/"],"volume":["151"]},"creators":{"author":[{"lastName":"Carver","firstName":"Jeffrey C."},{"lastName":"Minku","firstName":"Leandro L."},{"lastName":"Penzenstadler","firstName":"Birgit"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"11697_132481","type":"article","fields":{"langid":["english"],"abstract":["Robotic research is making huge progress. However, existing solutions are facing a number of challenges preventing them from being used in our everyday tasks: (i) robots operate in unknown environments, (ii) robots collaborate with each other and even with humans, and (iii) robots shall never injure people or create damages. Researchers are targeting those challenges from various perspectives, producing a fragmented research landscape."],"author":["Bozhinoski, Darko","Ruscio, Davide Di","Malavolta, Ivano","Pelliccione, Patrizio","Crnkovic, Ivica"],"date":["2019"],"entrysubtype":["magazine"],"ids":["bozhinoskiSafetyMobileRobotic2019a"],"issue":["to appear"],"journaltitle":["Elsevier Journal of Systems and Software (JSS)"],"keywords":["duplicate-citation-key","Hardware and Architecture","Information Systems","Safety for mobile robots","Software","Systematic mapping study"],"pages":["150–179"],"title":["Safety for Mobile Robotic System: A Systematic Mapping Study from a Software Engineering Perspective"],"url":["http://people.disim.univaq.it/diruscio/pubs/JSS_ROB_2019.pdf"],"volume":["151"]},"creators":{"author":[{"lastName":"Bozhinoski","firstName":"Darko"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Pelliccione","firstName":"Patrizio"},{"lastName":"Crnkovic","firstName":"Ivica"}]}},{"key":"11697_134269","type":"inproceedings","fields":{"author":["Di Ruscio, Davide","Franzago, Mirco","Muccini, Henry","Malavolta, Ivano"],"booktitle":["Proc. 40th Int. Conf. Softw. Eng. ICSE 2018 Gothenbg. Swed. May 27 - June 03 2018"],"date":["2018"],"doi":["10.1145/3180155.3182543"],"ids":["diruscioCollaborativeModeldrivenSoftware2018,ruscioCollaborativeModeldrivenSoftware2018"],"isbn":["978-1-4503-5638-1"],"note":["TL;DR \n\nResearchers and practitioners can use the results for identifying existing research/technical gaps to attack, better scoping their own contributions, or understanding existing ones for identifying, classifying, and understanding existing collaborative MDSE approaches."],"pages":["535–535"],"title":["Collaborative model-driven software engineering: A classification framework and a research map"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Franzago","firstName":"Mirco"},{"lastName":"Muccini","firstName":"Henry"},{"lastName":"Malavolta","firstName":"Ivano"}]},"sentenceCased":true},{"key":"11697_135647","type":"article","fields":{"author":["DE LARA, Juan","Guerra, Esther","DI RUSCIO, Davide","DI ROCCO, Juri","SANCHEZ CUADRADO, Jesus","Iovino, Ludovico","Pierantonio, Alfonso"],"date":["9999"],"journaltitle":["ACM Trans. Softw. Eng. Methodol."],"title":["Automated reuse of model transformations through typing requirements models"]},"creators":{"author":[{"lastName":"DE LARA","firstName":"Juan"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"SANCHEZ CUADRADO","firstName":"Jesus"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_136218","type":"article","fields":{"author":["DI ROCCO, Juri","DI RUSCIO, Davide","Härtel, Johannes","Iovino, Ludovico","Lämmel, Ralf","Pierantonio, Alfonso"],"date":["2019"],"doi":["10.1007/s10270-019-00748-7"],"ids":["DDHILP19,di2019understanding,diroccoUnderstandingMDEProjects2019,diroccoUnderstandingMDEProjects2020,roccoUnderstandingMDEProjects2020"],"journaltitle":["Softw. Syst. Model."],"keywords":["Architecture recovery","Code generator","MDE","Megamodeling","Megamodeling Reverse engineering Architecture recovery MDE Code generator Model transformation","Model transformation","Reverse engineering"],"note":["cited By 7"],"pages":["1–23"],"publisher":["Springer"],"title":["Understanding MDE projects: Megamodels to the rescue for architecture recovery"]},"creators":{"author":[{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Härtel","firstName":"Johannes"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Lämmel","firstName":"Ralf"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_13879","type":"article","fields":{"author":["Di Ruscio, D","Pelliccione, P"],"date":["2014"],"ids":["diruscioSimulatingUpgradesComplex2014,ruscioSimulatingUpgradesComplex2014,ruscioSimulatingUpgradesComplex2014a"],"journaltitle":["Inf. Softw. Technol."],"note":["cited By 7"],"pages":["438–462"],"title":["Simulating upgrades of complex systems: The case of Free and Open Source Software"],"volume":["56"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pelliccione","firstName":"P"}]},"sentenceCased":true},{"key":"11697_19479","type":"article","fields":{"abstract":["The adoption of Model-Driven Engineering (MDE) in the development of Web Applications permitted to decouple the functional description of applications from the underlying implementation platform. This is of paramount relevance for preserving the intellectual property encoded in models and making applications, languages and processes resilient to technological changes. This paper proposes a model-driven approach for supporting the migration and evolution of data-intensive Web applications. In particular, model differencing techniques are considered to realize a migration facility capable of detecting the modifications a model underwent during its lifecycle and to automatically derive from them the programs that are capable of migrating/adapting also those aspects which are not directly derivable from the source models, as for instance the data persistently stored in a database and the page layout usually written using graphic templates. The approach is validated by considering applications described with the beContent and WebML modeling languages."],"author":["Cicchetti, A","DI RUSCIO, Davide","Iovino, L","Pierantonio, Alfonso"],"date":["2012"],"doi":["10.1007/s10270-011-0193-0"],"ids":["cicchettiManagingEvolutionDataintensive2013a"],"journaltitle":["Softw. Syst. Model."],"keywords":["LOGSEQ"],"note":["“echnological changes” (Cicchetti et al., 2012, p. 53) \n\nTL;DR \n\nA model-driven approach for supporting the migration and evolution of data-intensive Web applications and is validated by considering applications described with the beContent and WebML modeling languages."],"pages":["1–31"],"title":["Managing the evolution of data-intensive Web applications by model-driven techniques"],"volume":["12"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"A"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Iovino","firstName":"L"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_26169","type":"incollection","fields":{"author":["ANTONIO","BUCCHIARONE","RUSCIO, DAVIDE DI","family=HENRY, given=MUCCINI, given-i=MUCCINI","family=PELLICCIONE, given=PATRIZIO, given-i=PATRIZIO"],"booktitle":["From requirements to Java code: An architecture-centric approach for producing quality systems"],"date":["2008"],"doi":["10.4018/978-1-60566-006-6.ch011"],"ids":["bucchiaroneRequirementsJavaCode2008,bucchiaroneRequirementsJavaCode2008a"],"isbn":["978-1-60566-006-6"],"note":["cited By 4 \n\ncited By 4"],"title":["From requirements to Java code: An architecture-centric approach for producing quality systems"],"volume":["abs/0910.0493"]},"creators":{"author":[{"literal":"ANTONIO"},{"literal":"BUCCHIARONE"},{"lastName":"RUSCIO","firstName":"DAVIDE DI"},{"lastName":"HENRY","firstName":"MUCCINI","initial":"MUCCINI"},{"lastName":"PELLICCIONE","firstName":"PATRIZIO","initial":"PATRIZIO"}]},"sentenceCased":true},{"key":"11697_287","type":"article","fields":{"author":["Balzerani, L","Di Ruscio, D","Pierantonio, A","De Angelis, G"],"date":["2006"],"ids":["balzeraniSupportingWebApplications2006b"],"journaltitle":["J. WEB Eng."],"pages":["25–42"],"title":["Supporting Web applications development with a product line architecture"],"volume":["5"]},"creators":{"author":[{"lastName":"Balzerani","firstName":"L"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pierantonio","firstName":"A"},{"lastName":"De Angelis","firstName":"G"}]},"sentenceCased":true},{"key":"11697_29795","type":"inproceedings","fields":{"author":["Ruscio, Davide Di","Ivano","Malavolta","Muccini, H","Patrizio, Pelliccione","Alfonso, Pierantonio"],"booktitle":["4th Eur. Conf. Softw. Archit. ECSA 2010"],"date":["2010"],"ids":["diruscioByADLMDEFramework2010,diruscioByADLMDEFramework2010a,ruscioByADLMDEFramework2010"],"isbn":["978-3-642-15113-2"],"location":["BERLIN HEIDELBERG"],"note":["cited By 3 \n\ncited By 3 \n\nTL;DR \n\nThe BYADL (Build Your ADL), a framework which allows software architects to extend existent ADLs with domain specificities, new architectural views, or analysis aspects, and integrate an ADL with development processes and methodologies, is presented."],"pages":["527–531"],"publisher":["Springer"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["ByADL: An MDE framework for building extensible architecture description languages"],"volume":["Lecture Notes in Computer Science 6285"]},"creators":{"author":[{"lastName":"Ruscio","firstName":"Davide Di"},{"literal":"Ivano"},{"literal":"Malavolta"},{"lastName":"Muccini","firstName":"H"},{"lastName":"Patrizio","firstName":"Pelliccione"},{"lastName":"Alfonso","firstName":"Pierantonio"}]},"sentenceCased":true},{"key":"11697_30086","type":"inproceedings","fields":{"author":["Cicchetti, A","Di Ruscio, D","Pierantonio, A"],"booktitle":["Proc. 2006 ACM Symp. Appl. Comput. SAC Dijon Fr. April 23-27 2006"],"date":["2006"],"doi":["10.1145/1141277.1141571"],"ids":["cicchettiWeavingConcernsModel2006,cicchettiWeavingConcernsModel2006a,cicchettiWeavingConcernsModel2006b"],"note":["cited By 4 \n\ncited By 4 \n\nTL;DR \n\nThis paper proposes explicit weaving models to define rigorous connections between the different artifacts produced during a system development, in order to enhance their reuse and maintenance and perform operations based on the connection semantics."],"pages":["1256–1261"],"title":["Weaving concerns in model based development of data-intensive Web applications"],"volume":["2"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"A"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_30601","type":"inproceedings","fields":{"author":["ANTONIO","CICCHETTI","RUSCIO, DAVIDE DI","PIERANTONIO, A"],"booktitle":["Model Driven Eng. Lang. Syst. 11th Int. Conf. MoDELS 2008 Toulouse Fr. Sept. 28 - Oct. 3 2008 Proc."],"date":["2008"],"doi":["10.1007/978-3-540-87875-9_23"],"ids":["cicchettiManagingModelConflicts2008,cicchettiManagingModelConflicts2008a,cicchettiManagingModelConflicts2008b"],"note":["cited By 70 \n\ncited By 70 \n\nTL;DR \n\nA domain specific language able to define and manage conflicts caused by cooperative updates over the same model elements is proposed, which relies on a model-based representation of model differences and enables the specification and the detection of both syntactical and semantic conflicts."],"pages":["311–325"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Managing model conflicts in distributed development"],"volume":["5301 LNCS"]},"creators":{"author":[{"literal":"ANTONIO"},{"literal":"CICCHETTI"},{"lastName":"RUSCIO","firstName":"DAVIDE DI"},{"lastName":"PIERANTONIO","firstName":"A"}]},"sentenceCased":true},{"key":"11697_30610","type":"inproceedings","fields":{"author":["Balzerani, L","Di Ruscio, D","Pierantonio, A","De Angelis, G"],"booktitle":["Proc ACM Symp. Appl. Comput. SAC 2005 Spec. Track Web Technol. Appl. ACM Press"],"date":["2005"],"doi":["10.1145/1066677.1067059"],"ids":["balzeraniProductLineArchitecture2005,balzeraniProductLineArchitecture2005a,balzeraniProductLineArchitecture2005b,balzeraniProductLineArchitecture2005c"],"note":["cited By 15 \n\ncited By 15"],"pages":["1689–1693"],"publisher":["ACM"],"title":["A product line architecture for web applications"],"volume":["2"]},"creators":{"author":[{"lastName":"Balzerani","firstName":"L"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pierantonio","firstName":"A"},{"lastName":"De Angelis","firstName":"G"}]},"sentenceCased":true},{"key":"11697_30657","type":"inproceedings","fields":{"author":["CICCHETTI, A.","DI RUSCIO, D.","PIERANTONIO, A"],"booktitle":["1st Eur. Workshop Compos. Model Transform. - CMT 2006"],"date":["2006"],"note":["TL;DR \n\nThis paper illustrates how to deal with conflicting modifications of the same model elements by conceiving the composition of difference models as a particular kind of model transformation composition."],"title":["Composition of model differences"]},"creators":{"author":[{"lastName":"CICCHETTI","firstName":"A."},{"lastName":"DI RUSCIO","firstName":"D."},{"lastName":"PIERANTONIO","firstName":"A"}]},"sentenceCased":true},{"key":"11697_31176","type":"inproceedings","fields":{"author":["Cicchetti, A","Di Ruscio, D","Pelliccione, P","Pierantonio, A","Zacchiroli, S"],"booktitle":["ENASE 2009 - Proc. 4th Int. Conf. Eval. Nov. Approaches Softw. Eng. Milan Italy May 2009"],"date":["2009"],"ids":["cicchettiModelDrivenApproach2009,cicchettiModelDrivenApproach2009a,cicchettiModelDrivenApproach2009c,cicchettiModelDrivenApproach2009d"],"isbn":["978-989-8111-98-2"],"note":["cited By 4 \n\ncited By 4"],"pages":["121–133"],"publisher":["Elsevier B.V."],"title":["Towards a model driven approach to upgrade complex software systems"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-74549219557&partnerID=40&md5=f7acf18ff5b0fba5602bf87ec029e353"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"A"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pelliccione","firstName":"P"},{"lastName":"Pierantonio","firstName":"A"},{"lastName":"Zacchiroli","firstName":"S"}]},"sentenceCased":true},{"key":"11697_32865","type":"inproceedings","fields":{"abstract":["The current practice of software architecture modeling and analysis would benefit of using different architectural languages, each specialized on a particular view and each enabling specific analysis. Thus, it is fundamental to pursue architectural language interoperability. An approach for enabling interoperability consists in defining a transformation from each single notation to a pivot language, and vice versa. When the pivot assumes the form of a small and abstract kernel, extension mechanisms are required to compensate the loss of information. The aim of this paper is to enhance architectural languages interoperability by means of hierarchies of pivot languages obtained by systematically extending a root pivot language. Model-driven techniques are employed to support the creation and the management of such hierarchies and to realize the interoperability by means of model transformations. Even though the approach is applied to the software architecture domain, it is completely general."],"author":["Ruscio, Davide Di","Ivano","Malavolta","Muccini, H","Patrizio, Pelliccione","Alfonso, Pierantonio"],"booktitle":["15th Int. Conf. Fundam. Approaches Softw. Eng. FASE"],"date":["2012"],"doi":["10.1007/978-3-642-28872-2_2"],"ids":["diruscioModeldrivenTechniquesEnhance2012,diruscioModeldrivenTechniquesEnhance2012a,ruscioModelDrivenTechniquesEnhance2012"],"isbn":["978-3-642-28871-5"],"location":["BERLIN HEIDELBERG"],"note":["cited By 14 \n\ncited By 14"],"pages":["26–42"],"publisher":["Springer-Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Model-driven techniques to enhance architectural languages interoperability"],"volume":["7212"]},"creators":{"author":[{"lastName":"Ruscio","firstName":"Davide Di"},{"literal":"Ivano"},{"literal":"Malavolta"},{"lastName":"Muccini","firstName":"H"},{"lastName":"Patrizio","firstName":"Pelliccione"},{"lastName":"Alfonso","firstName":"Pierantonio"}]},"sentenceCased":true},{"key":"11697_34038","type":"incollection","fields":{"author":["Cicchetti, A","Di Ruscio, D","Kolovos, D","Pierantonio, A"],"booktitle":["Emerging technologies for the evolution and maintenance of software models"],"date":["2012"],"doi":["10.4018/978-1-61350-438-3.ch012"],"ids":["cicchettiTestdrivenApproachMetamodel2011,cicchettiTestdrivenApproachMetamodel2011a"],"location":["NEY YORK"],"note":["cited By 13 \n\ncited By 13"],"pages":["319–342"],"publisher":["IGI Global"],"title":["A test-driven approach for metamodel development"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"A"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Kolovos","firstName":"D"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_35267","type":"inproceedings","fields":{"author":["Caporuscio, M","DI RUSCIO, D","Inverardi, P","Pelliccione, P","Pierantonio, A"],"booktitle":["Softw. Archit. 2nd Eur. Workshop EWSA 2005 Pisa Italy June 13-14 2005 Proc."],"date":["2005"],"doi":["10.1007/11494713_9"],"ids":["caporuscioEngineeringMDACompositional2005,caporuscioEngineeringMDACompositional2005a,caporuscioEngineeringMDACompositional2005b"],"isbn":["3-540-26275"],"note":["cited By 2 \n\ncited By 2 \n\nTL;DR \n\nThis paper engineer the architectural decomposability theorem to the analysis of middleware-based applications by automatically generating the proxies needed by the components in order to properly interact with each other via the middleware."],"pages":["130–145"],"publisher":["Springer - LNCS series"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Engineering MDA into compositional reasoning for analyzing middleware-based applications"],"volume":["3527"]},"creators":{"author":[{"lastName":"Caporuscio","firstName":"M"},{"lastName":"DI RUSCIO","firstName":"D"},{"lastName":"Inverardi","firstName":"P"},{"lastName":"Pelliccione","firstName":"P"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_37088","type":"inproceedings","fields":{"abstract":["Increasingly, recording the various kinds of design-level structural evolution that a system undergoes throughout its entire life-cycle is gaining relevance in software modeling and development. In this respect, an interesting and useful operation between subsequent system versions is model difference consisting in calculation, representation, and visualization. This work shows how to generalize the application of differences, represented as first-class artefacts, in order to abstract from persistent identifiers and enable more flexibility. Then, modifications can be applied as model patches to arbitrary models according to weaving specifications."],"author":["Cicchetti, A","DI RUSCIO, Davide","Pierantonio, Alfonso"],"booktitle":["Models Softw. Eng. Workshop Symp. MODELS 2009 Denver CO USA Oct. 4-9 2009 Rep. Revis. Sel. Pap."],"date":["2010"],"doi":["10.1007/978-3-642-12261-3_19"],"ids":["cicchettiModelPatchesModelDriven2009,cicchettiModelPatchesModeldriven2010,cicchettiModelPatchesModeldriven2010a"],"isbn":["978-3-642-12260-6"],"note":["cited By 14 \n\ncited By 14 \n\nTL;DR \n\nThis work shows how to generalize the application of differences, represented as first-class artefacts, in order to abstract from persistent identifiers and enable more flexibility."],"pages":["190–204"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Model patches in model-driven engineering"],"volume":["6002 LNCS"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"A"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_37099","type":"inproceedings","fields":{"abstract":["Despite the flourishing of languages to describe software architectures, existing Architecture Description Languages (ADLs) are still far away from what it is actually needed. In fact, while they support a traditional perception of a Software Architecture (SA) as a set of constituting elements (such as components, connectors and interfaces), they mostly fail to capture multiple stakeholders concerns and their design decisions that represent a broader view of SA being accepted today. Next generation ADLs must cope with various and ever evolving stakeholder concerns by employing semantic extension mechanisms. In this paper we present a framework, called BYADL – Build Your ADL, for developing a new generation of ADLs. BYADL ex- ploits model-driven techniques that provide the needed technologies to allow a software architect, starting from existing ADLs, to define its own new generation ADL by: i) adding domain specificities, new architectural views, or analysis aspects, ii) integrating ADLs with development processes and methodologies, and iii) customizing ADLs by fine tuning them. The framework is put in practice in different scenarios showing the incremental extension and customization of the Darwin ADL."],"author":["Di Ruscio, D","Malavolta, I","Muccini, H","Pelliccione, P","Pierantonio, A"],"booktitle":["Proc. 32nd ACMIEEE Int. Conf. Softw. Eng. - Vol. 1 ICSE 2010 Cape Town South Afr. 1-8 May 2010"],"date":["2010"],"doi":["10.1145/1806799.1806816"],"ids":["diruscioDevelopingNextGeneration2010,diruscioDevelopingNextGeneration2010a,ruscioDevelopingNextGeneration2010"],"isbn":["978-1-60558-719-6"],"location":["NEW YORK, NY, USA"],"note":["cited By 33 \n\ncited By 33"],"pages":["85–94"],"publisher":["Association for Computing Machinery, Inc. (ACM)"],"series":["PROCEEDINGS - INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING"],"title":["Developing next generation ADLs through MDE techniques"],"volume":["1"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Malavolta","firstName":"I"},{"lastName":"Muccini","firstName":"H"},{"lastName":"Pelliccione","firstName":"P"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_37101","type":"inproceedings","fields":{"author":["Cicchetti, A","Di Ruscio, D","Pierantonio, A"],"booktitle":["Theory Pract. Model Transform. - 2nd Int. Conf. ICMTTOOLS 2009 Zurich Switz. June 29-30 2009 Proc."],"date":["2009"],"doi":["10.1007/978-3-642-02408-5_4"],"ids":["cicchettiManagingDependentChanges2009,cicchettiManagingDependentChanges2009a,cicchettiManagingDependentChanges2009b,cicchettiManagingDependentChanges2009c"],"isbn":["978-3-642-02407-8"],"note":["cited By 60 \n\ncited By 60 \n\nTL;DR \n\nThe paper illustrates a dependency analysis, classifies such dependencies, and proposes a metamodeling language driven resolution which enables a decomposition and consequent scheduling of the adaptation steps allowing the full automation of the process."],"pages":["35–51"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Managing dependent changes in coupled evolution"],"volume":["5563 LNCS"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"A"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_37103","type":"inproceedings","fields":{"author":["Cicchetti, A","Di Ruscio, D","Eramo, R","Maccarrone, F","Pierantonio, A"],"booktitle":["Web Eng. 9th Int. Conf. ICWE 2009"],"date":["2009"],"doi":["10.1007/978-3-642-02818-2_52"],"ids":["cicchettiBeContentModelDrivenPlatform2009,cicchettiBeContentModeldrivenPlatform2009,cicchettiBeContentModeldrivenPlatform2009a"],"note":["cited By 5 \n\ncited By 5"],"pages":["518–522"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["BeContent: A model-driven platform for designing and maintaining web applications"],"volume":["5648"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"A"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Eramo","firstName":"R"},{"lastName":"Maccarrone","firstName":"F"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_37139","type":"inproceedings","fields":{"author":["Cicchetti, A","Di Ruscio, D","Eramo, R","Pierantonio, A"],"booktitle":["Softw. Lang. Eng. - Third Int. Conf. SLE 2010 Eindh. Neth. Oct. 12-13 2010 Revis. Sel. Pap."],"date":["2010"],"doi":["10.1007/978-3-642-19440-5_11"],"ids":["cicchettiJTLBidirectionalChange2010,cicchettiJTLBidirectionalChange2011,cicchettiJTLBidirectionalChange2011a"],"isbn":["978-3-642-19439-9"],"note":["cited By 119 \n\ncited By 119 \n\nTL;DR \n\nThe Janus Transformation Language (JTL) is presented, a bidirectional model transformation language specifically designed to support nonbijective transformations and change propagation and its expressivity and applicability are validated against a reference benchmark."],"pages":["183–202"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["JTL: A bidirectional and change propagating transformation language"],"volume":["6563 LNCS"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"A"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Eramo","firstName":"R"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_37543","type":"inproceedings","fields":{"author":["Di Ruscio, D","Pierantonio, A"],"booktitle":["Adv. Inf. Syst. Eng. 17th Int. Conf. CAiSE 2005 Porto Port. June 13-17 2005 Proc."],"date":["2005"],"doi":["10.1007/11431855_33"],"ids":["diruscioModelTransformationsDevelopment2005,diruscioModelTransformationsDevelopment2005a,ruscioModelTransformationsDevelopment2005"],"note":["cited By 6 \n\ncited By 6 \n\nTL;DR \n\nThis paper presents model-driven transformations between platform-independent (conceptual descriptions of Web applications) and platform-specific (Model-View-Controller conformant) models."],"pages":["475–490"],"series":["Lecture Notes in Computer Science"],"title":["Model transformations in the development of data-intensive web applications"],"volume":["3520"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_37559","type":"inproceedings","fields":{"author":["Di Ruscio, D","Muccini, H","Pierantonio, A","Pelliccione, P"],"booktitle":["Proc. Jt. Meet. Fourth Workshop Model-Based Dev. Comput.-Based Syst. Third Int. Workshop Model-Based Methodol. Pervasive Embed. Softw. MBDMOMPES 2006 Potsdam Ger. March 30 2006 Proc."],"date":["2006"],"doi":["10.1109/MBD-MOMPES.2006.24"],"ids":["diruscioWeavingSoftwareArchitecture2006,diruscioWeavingSoftwareArchitecture2006a,diruscioWeavingSoftwareArchitecture2006b,ruscioTowardsWeavingSoftwareArchitecture2006,ruscioTowardsWeavingSoftwareArchitecture2006a"],"isbn":["0-7695-2538-5"],"location":["NEW YORK"],"note":["cited By 4 \n\ncited By 4 \n\nTL;DR \n\nThe coexistence and integration of different analysis techniques at the architectural level is reduced to the problem of enriching multi-view descriptions with proper UML elements by means of directed weaving operations."],"pages":["103–112"],"publisher":["IEEE Computer Society"],"title":["Towards weaving software architecture models"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Muccini","firstName":"H"},{"lastName":"Pierantonio","firstName":"A"},{"lastName":"Pelliccione","firstName":"P"}]},"sentenceCased":true},{"key":"11697_38176","type":"inproceedings","fields":{"author":["Di Ruscio, D","Pelliccione, P","Pierantonio, A","Zacchiroli, S"],"booktitle":["IWOCE09 - Proc. 1st Int. Workshop Open Compon. Ecosyst."],"date":["2009"],"doi":["10.1145/1595800.1595803"],"eprint":["0909.5087"],"eprinttype":["arxiv"],"ids":["diruscioMaintainerScriptModernization2009,diruscioMaintainerScriptModernization2009a,ruscioMaintainerScriptModernization2009"],"isbn":["978-1-60558-677-9"],"location":["NEW YORK, NY, USA"],"note":["cited By 10 \n\ncited By 10 \n\nTL;DR \n\nThis paper presents a process to define meta-models that enable dealing with upgrade failures and help rolling back from them, taking into account maintainer scripts, applied to FOSS distributions."],"pages":["11–20"],"publisher":["Association for Computing Machinery, Inc. (ACM)"],"title":["Towards maintainer script modernization in FOSS distributions"],"volume":["abs/0909.5087"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pelliccione","firstName":"P"},{"lastName":"Pierantonio","firstName":"A"},{"lastName":"Zacchiroli","firstName":"S"}]},"sentenceCased":true},{"key":"11697_40934","type":"inproceedings","fields":{"abstract":["Choreographies are an emergent Service Engineering approach to compose together and coordinate distributed services. They represent a global specication of the interactions between the participant services. BPMN2 provides a dedicated notation, called Choreography Diagrams, to dene choreographies. This paper presents a model transformation to automatically transform a BPMN2 choreography speci cation into an automata-based representation called Choreography LTS (CLTS). The latter is a LTS suitably extended to, on one side model the complex interactions that can be specied by choreography diagrams, on the other provide modelers with a means to precisely extract the not-easy-to-grasp coordination logic \" into BPMN2 Choreography Diagrams. Dedicated Eclipse plugins, within the CHOReOSynt tool, have been developed to support the presented transformation."],"author":["Autili, Marco","DI RUSCIO, Davide","DI SALLE, Amleto","Inverardi, Paola"],"booktitle":["Proc. 1st Int. Workshop Model-Driven Eng. Compon.-Based Softw. Syst. Co-Located ACMIEEE 17th Int. Conf. Model Driven Eng. Lang. Syst. MoDELS 2014 Valencia Spain Sept. 29 2014"],"date":["2014"],"ids":["autiliSynthesizingAutomatabasedRepresentation2014,autiliSynthesizingAutomatabasedRepresentation2014a,autiliSynthesizingAutomatabasedRepresentation2014b"],"keywords":["choreography","service engineering"],"location":["AACHEN"],"note":["cited By 1 \n\ncited By 1"],"pages":["67–77"],"publisher":["CEUR-WS.org"],"series":["CEUR Workshop Proceedings"],"title":["Synthesizing an automata-based representation of BPMN2 choreography diagrams"],"url":["http://ceur-ws.org/Vol-1281/7.pdf"],"volume":["1281"]},"creators":{"author":[{"lastName":"Autili","firstName":"Marco"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"DI SALLE","firstName":"Amleto"},{"lastName":"Inverardi","firstName":"Paola"}]},"sentenceCased":true},{"key":"11697_4393","type":"article","fields":{"author":["DI RUSCIO, Davide","Paige, R","Pierantonio, Alfonso"],"date":["2014"],"doi":["10.1016/j.scico.2013.12.006"],"ids":["diruscioGuestEditorialSpecial2014,ruscioGuestEditorialSpecial2014"],"journaltitle":["Sci. Comput. Program."],"note":["cited By 24"],"title":["Guest editorial to the special issue on Success Stories in Model Driven Engineering"]},"creators":{"author":[{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Paige","firstName":"R"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"11697_89156","type":"inproceedings","fields":{"abstract":["This paper overviews Mancoosi, an European project in the 7th Research Framework Programme (FP7) of the European Commission, on managing software complexity. The focus of the project has been on managing the evolution of Free and Open Source Software distributions. Evolution of these distributions is realized through the upgrade, the addition, and the removal of software packages. The project has two main objectives: (i) develop a model-based approach to safely support the upgrade of FOSS systems, (ii) develop better algorithms and tools to plan upgrade paths based on various information sources about software packages and on optimization criteria. The paper focuses on the first objective of the project. The main result of this objective is an approach that promotes the simulation of upgrades to predict failures before affecting the real system. Both fine-grained static aspects (e.g., configuration incoherences) and dynamic aspects (e.g., the execution of configuration scripts) are taken into account, improving over the state of the art of package managers."],"author":["Di Ruscio, D","Pelliccione, P"],"booktitle":["Softw. Eng. Resilient Syst. - 5th Int. Workshop Proc."],"date":["2013"],"doi":["10.1007/978-3-642-40894-6_5"],"ids":["diruscioSupportingEvolutionFree2013,diruscioSupportingEvolutionFree2013a,ruscioSupportingEvolutionFree2013,ruscioSupportingEvolutionFree2013a"],"isbn":["978-3-642-40893-9"],"location":["BERLIN HEIDELBERG"],"note":["cited By 0 \n\ncited By 0"],"pages":["56–63"],"publisher":["Springer-Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Supporting the evolution of free and open source software distributions"],"volume":["8166 LNCS"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pelliccione","firstName":"P"}]},"sentenceCased":true},{"key":"11697_89171","type":"inproceedings","fields":{"abstract":["Identifying and removing the causes of poor performance in software systems are complex problems, and these issues are usually tackled after software deployment only with human-based means. Performance antipatterns can be used to harness these problems since they capture design patterns that are known leading to performance problems, and they suggest refactoring actions that can solve the problems. This paper introduces an approach to automate software model refactoring based on performance antipatterns. A Role-Based Modeling Language is used to model antipattern problems as Source Role Models (SRMs), and antipattern solutions as Target Role Models (TRMs). Each (SRM, TRM) pair is represented by a difference model that encodes refactoring actions to be operated on a software model to remove the corresponding antipattern. Differences are applied to software models through a model transformation automatically generated by a higher-order transformation. The approach is shown at work on an example in the e-commerce domain."],"author":["Arcelli, D","Cortellessa, Vittorio","DI RUSCIO, Davide"],"booktitle":["Comput. Perform. Eng. - 10th Eur. Workshop EPEW 2013 Venice Italy Sept. 16-17 2013 Proc. Lect. Notes Comput. Sci."],"date":["2013"],"doi":["10.1007/978-3-642-40725-3_24"],"ids":["arcelliApplyingModelDifferences2013,arcelliApplyingModelDifferences2013a,arcelliApplyingModelDifferences2013b,arcelliApplyingModelDifferences2013c"],"isbn":["978-3-642-40724-6"],"keywords":["Computer Science (all)","Theoretical Computer Science"],"note":["cited By 6 \n\ncited By 6 \n\nTL;DR \n\nThis paper introduces an approach to automate software model refactoring based on performance antipatterns, and shows the approach at work on an example in the e-commerce domain."],"pages":["312–324"],"publisher":["Springer"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Applying model differences to automate performance-driven refactoring of software models"],"volume":["8168 LNCS"]},"creators":{"author":[{"lastName":"Arcelli","firstName":"D"},{"lastName":"Cortellessa","firstName":"Vittorio"},{"lastName":"DI RUSCIO","firstName":"Davide"}]},"sentenceCased":true},{"key":"11697_89209","type":"inproceedings","fields":{"author":["DI RUSCIO, Davide","Malavolta, Ivano","Pelliccione, Patrizio"],"booktitle":["Softw. Eng. Resilient Syst. 5th Int. Workshop SERENE 2013 Kiev Ukr. Oct. 3-4 2013 Proc. Lect. Notes Comput. Sci."],"date":["2013"],"doi":["10.1007/978-3-642-40894-6_3"],"ids":["diruscioEngineeringPlatformMission2013,diruscioEngineeringPlatformMission2013a,ruscioEngineeringPlatformMission2013"],"isbn":["978-3-642-40893-9"],"keywords":["open source software"],"location":["BERLIN HEIDELBERG"],"note":["cited By 10 \n\ncited By 10 \n\nTL;DR \n\nQuadrotors and UAVs in general are becoming as attractive instruments to safely and efficiently perform environmental monitoring missions and in professional use, quadrotors are manually controlled by expert operators via a remote controller."],"pages":["33–47"],"publisher":["Springer-Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Engineering a platform for mission planning of autonomous and resilient quadrotors"],"volume":["8166"]},"creators":{"author":[{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Pelliccione","firstName":"Patrizio"}]},"sentenceCased":true},{"key":"11697_89217","type":"inproceedings","fields":{"abstract":["Model-Driven Engineering is a software discipline that relies on (meta) models as first class entities and that aims to develop, maintain and evolve software by exploiting model transformations. Analogously to software, metamodels are subject to evolutionary pressures which might compromise a wide range of artefacts including transformations. In contrast with the problem of metamodel/model co-evolution, the problem of adapting model transformations according to the changes operated on the corresponding metamodels is to a great extent unexplored. This is largely due to its intricacy but also to the difficulty in having a mature process which on one hand is able to evaluate the cost and benefits of adaptations, and on the other hand ensures that consistent methods are used to maintain quality and design integrity during the adaptation. This paper proposes a methodological approach to the coupled evolution of ATL transformations aiming at evaluating its sustainability prior to any adaptation step based on the assessment of change impact significance."],"author":["Di Ruscio, D","Iovino, L","Pierantonio, A"],"booktitle":["Theory Pract. Model Transform. - 6th Int. Conf. ICMTSTAF 2013 Bp. Hung. June 18-19 2013 Proc."],"date":["2013"],"doi":["10.1007/978-3-642-38883-5_9"],"ids":["diruscioMethodologicalApproachCoupled2013,diruscioMethodologicalApproachCoupled2013a,diruscioMethodologicalApproachCoupled2013b,ruscioMethodologicalApproachCoupled2013"],"isbn":["978-3-642-38882-8"],"location":["BERLIN HEIDELBERG"],"note":["cited By 25 \n\ncited By 25"],"pages":["60–75"],"publisher":["Springer-Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["A methodological approach for the coupled evolution of metamodels and ATL transformations"],"volume":["7909 LNCS"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Iovino","firstName":"L"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_89297","type":"inproceedings","fields":{"author":["Di Ruscio, D","Iovino, L","Pierantonio, A"],"booktitle":["Proc. 2nd Int. Workshop Model Comp. Pract."],"date":["2011"],"doi":["10.1145/2000410.2000416"],"ids":["10.1145/2000410.2000416,diruscioWhatNeededManaging2011,diruscioWhatNeededManaging2011a,ruscioWhatNeededManaging2011"],"isbn":["978-1-4503-0668-3"],"keywords":["metamodel co-evolution","model differences","model driven engineering"],"location":["Zurich, Switzerland"],"note":["cited By 45 \n\ncited By 45"],"numpages":["9"],"pages":["30–38"],"title":["What is needed for managing co-evolution in MDE?"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Iovino","firstName":"L"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_89302","type":"inproceedings","fields":{"abstract":["In this paper we briefly describe a case study, i.e. the Mobile eHealth (MeH), developed in the context of the IST PLASTIC project aimed at supporting self-adapting and context-aware services. The goal of the case study is to show how to model a service-based application and to demonstrate that model-based solutions are suitable to generate Quality of Service (QoS) models and adaptable code from service models."],"author":["Autili, Marco","Berardinelli, Luca","Di Ruscio, Davide","Trubiani, Catia"],"booktitle":["4th Int. ICSE Workshop Princ. Eng. Serv.-Oriented Syst. PESOS 2012 June 4 2012 Zurich Switz."],"date":["2012"],"doi":["10.1109/PESOS.2012.6225946"],"ids":["autiliProvidingLightweightAdaptable2012,autiliProvidingLightweightAdaptable2012a,autiliProvidingLightweightAdaptable2012b"],"isbn":["978-1-4673-1754-2"],"keywords":["Software"],"location":["NEW YORK"],"note":["cited By 2 \n\ncited By 2 \n\nTL;DR \n\nThe goal of the case study is to show how to model a service-based application and to demonstrate that model-based solutions are suitable to generate Quality of Service (QoS) models and adaptable code from service models."],"pages":["69–70"],"publisher":["IEEE Computer Society"],"title":["Providing lightweight and adaptable service technology for information and communication (PLASTIC) in the mobile eHealth case study"]},"creators":{"author":[{"lastName":"Autili","firstName":"Marco"},{"lastName":"Berardinelli","firstName":"Luca"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Trubiani","firstName":"Catia"}]},"sentenceCased":true},{"key":"11697_89303","type":"inproceedings","fields":{"abstract":["Model-to-model transformations are often employed to establish translational semantics of Domain-Specific Languages (DSLs) by mapping high-level models into more concrete ones. Such semantics are also executable when there exists a target platform able to execute the target models. Conceiving a transformation that targets a low-level language still remains arduous due to the large semantic gap between the DSL and the corresponding target language. In this respect, depending on the domain of the DSL, this task can be made easier by reusing an existing platform and bytecode language for that domain, as for instance the EMF Transformation Virtual Machine (EMFTVM) for the domain of model transformation. This paper defines executable semantics for EMFMigrate, a model transformation language specifically designed for managing the coupled evolution in model-driven development. To this end, the approach considers EMFTVM as the runtime engine targeted by the proposed semantic mappings."],"author":["Wagelaar, D","Iovino, L","Di Ruscio, D","Pierantonio, A"],"booktitle":["Theory Pract. Model Transform."],"date":["2012"],"doi":["10.1007/978-3-642-30476-7_13"],"ids":["wagelaarTranslationalSemanticsCoevolution2012,wagelaarTranslationalSemanticsCoevolution2012a,wagelaarTranslationalSemanticsCoevolution2012b"],"isbn":["978-3-642-30475-0"],"note":["cited By 41 \n\ncited By 41 \n\nTL;DR \n\nThis paper defines executable semantics for EMFMigrate, a model transformation language specifically designed for managing the coupled evolution in model-driven development, and considers EMFTVM as the runtime engine targeted by the proposed semantic mappings."],"pages":["192–207"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Translational semantics of a co-evolution specific language with the EMF transformation virtual machine"],"volume":["7307"]},"creators":{"author":[{"lastName":"Wagelaar","firstName":"D"},{"lastName":"Iovino","firstName":"L"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_89304","type":"inproceedings","fields":{"author":["Di Ruscio, D","Eramo, R","Pierantonio, A"],"booktitle":["Form. Methods Model-Driven Eng. - 12th Int. Sch. Form. Methods Des. Comput. Commun. Softw. Syst. SFM 2012 Bertinoro Italy June 18-23 2012 Adv. Lect."],"date":["2012"],"doi":["10.1007/978-3-642-30982-3_4"],"ids":["diruscioModelTransformations2012,diruscioModelTransformations2012a,ruscioModelTransformations2012"],"isbn":["978-3-642-30981-6"],"location":["BERLIN HEIDELBERG"],"note":["cited By 12 \n\ncited By 12"],"pages":["91–136"],"publisher":["Springer-Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Model transformations"],"volume":["7320 LNCS"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Eramo","firstName":"R"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_89344","type":"inproceedings","fields":{"abstract":["Software systems increasingly require to deal with continuous evolution. In this paper we present the EVOSS tool that has been defined to support the upgrade of free and open source software systems. EVOSS is composed of a simulator and of a fault detector component. The simulator is able to predict failures before they can affect the real system. The fault detector component has been defined to discover inconsistencies in the system configuration model. EVOSS improves the state of the art of current tools, which are able to predict a very limited set of upgrade faults, while they leave a wide range of faults unpredicted."],"author":["Di Ruscio, D","Pelliccione, P","Pierantonio, A"],"booktitle":["34th Int. Conf. Softw. Eng. ICSE 2012 June 2-9 2012 Zurich Switz."],"date":["2012"],"doi":["10.1109/ICSE.2012.6227234"],"ids":["diruscioEVOSSToolManaging2012,diruscioEVOSSToolManaging2012a,ruscioEVOSSToolManaging2012"],"isbn":["978-1-4673-1066-6"],"location":["NEW YORK"],"note":["cited By 2 \n\ncited By 2"],"pages":["1415–1418"],"publisher":["IEEE Computer Society"],"title":["EVOSS: A tool for managing the evolution of free and open source software systems"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pelliccione","firstName":"P"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"11697_89346","type":"inproceedings","fields":{"abstract":["In Model-Driven Engineering (MDE) metamodels are cornerstones for defining a wide range of related artifacts interlaced with explicit or implicit correspondences. According to this view, models, transformations, editors, and supporting tools can be regarded as a whole pursuing a common scope and therefore constituting an ecosystem. Analogously to software, metamodels are subject to evolutionary pressures too. However, changing a metamodel might compromise the validity of the artifacts in the ecosystem which therefore require to co-evolve as well in order to restore their validity. Different approaches have been proposed to support at different extent the adaptation of artifacts according to the changes operated on the corresponding metamodels. Each technique is specialized in the adaptation of specific kind of artifact (e.g., models, or transformations) by forcing modelers to learn different technologies and languages. This paper discusses the different relations occurring in a typical metamodeling ecosystem among the metamodel and the related artifacts, and identifies the commonalities which can be leveraged to define a unifying and comprehensive adaptation process. A language and corresponding supporting tools are also proposed for the management of metamodel evolution and the corresponding togetherness with the related artifacts."],"author":["Di Ruscio, D","Iovino, L","Pierantonio, A"],"booktitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"date":["2012"],"doi":["10.1007/978-3-642-33654-6_2"],"ids":["diruscioEvolutionaryTogethernessHow2012,diruscioEvolutionaryTogethernessHow2012a,ruscioEvolutionaryTogethernessHow2012"],"isbn":["978-3-642-33653-9"],"location":["BERLIN HEIDELBERG"],"note":["cited By 35 \n\ncited By 35 \n\nTL;DR \n\nThe different relations occurring in a typical meetamodeling ecosystem among the metamodel and the related artifacts are discussed, and the commonalities which can be leveraged to define a unifying and comprehensive adaptation process are identified."],"pages":["20–37"],"publisher":["Springer-Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Evolutionary togetherness: How to manage coupled evolution in metamodeling ecosystems"],"volume":["7562 LNCS"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Iovino","firstName":"L"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"1514443","type":"article","fields":{"author":["Sjoeberg, D.I.K.","Hannay, J.E.","Hansen, O.","Kampenes, V.B.","Karahasanovic, A.","Liborg, N.-K.","Rekdal, A.C."],"date":["2005"],"doi":["10.1109/TSE.2005.97"],"journaltitle":["IEEE Trans. Softw. Eng."],"number":["9"],"pages":["733–753"],"title":["A survey of controlled experiments in software engineering"],"volume":["31"]},"creators":{"author":[{"lastName":"Sjoeberg","firstName":"D.I.K."},{"lastName":"Hannay","firstName":"J.E."},{"lastName":"Hansen","firstName":"O."},{"lastName":"Kampenes","firstName":"V.B."},{"lastName":"Karahasanovic","firstName":"A."},{"lastName":"Liborg","firstName":"N.-K."},{"lastName":"Rekdal","firstName":"A.C."}]},"sentenceCased":true},{"key":"159059","type":"article","fields":{"author":["Carpenter, G. A.","Grossberg, S.","Markuzon, N.","Reynolds, J. H.","Rosen, D. B."],"date":["1992-09"],"doi":["10.1109/72.159059"],"issn":["1045-9227"],"journaltitle":["IEEE Trans. Neural Netw."],"keywords":["adaptive resonance theory","analog multidimensional maps","Computational modeling","fuzzy ARTMAP","fuzzy logic","Fuzzy logic","Fuzzy neural networks","fuzzy set theory","Fuzzy sets","Fuzzy systems","incremental supervised learning","learning systems","Multidimensional systems","neural nets","neural network architecture","Neural networks","pattern recognition","Resonance","Salzberg's NGE systems","Simpson's FMMC system","Subspace constraints","Supervised learning"],"note":["TL;DR \n\nThe fuzzy ARTMAP system is compared with Salzberg's NGE systems and with Simpson's FMMC system, and its performance in relation to benchmark backpropagation and generic algorithm systems."],"number":["5"],"pages":["698–713"],"title":["Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps"],"volume":["3"]},"creators":{"author":[{"lastName":"Carpenter","firstName":"G. A."},{"lastName":"Grossberg","firstName":"S."},{"lastName":"Markuzon","firstName":"N."},{"lastName":"Reynolds","firstName":"J. H."},{"lastName":"Rosen","firstName":"D. B."}]},"sentenceCased":true},{"key":"3rdworkshopFlexibleModel2017","type":"book","fields":{"date":["2017"],"ids":["3rdworkshopFlexibleModel2017a"],"journaltitle":["CEUR Workshop Proceedings"],"pages":["385–386"],"pagetotal":["385–386"],"publisher":["CEUR-WS"],"title":["3rdworkshop on flexible model driven engineering (FlexMDE 2017)"],"volume":["2019"]},"creators":{},"sentenceCased":true},{"key":"4688070","type":"inproceedings","fields":{"author":["Zaier, Zied","Godin, Robert","Faucher, Luc"],"booktitle":["2008 Int. Conf. Autom. Solut. Cross Media Content Multi-Channel Distrib."],"date":["2008"],"doi":["10.1109/AXMEDIS.2008.21"],"note":["TL;DR \n\nThis paper discusses how to compare recommenders based on a set of properties that are relevant for the application, and focuses on comparative studies, where a few algorithms are compared using some evaluation metric, rather than absolute benchmarking of algorithms."],"pages":["211–217"],"title":["Evaluating recommender systems"]},"creators":{"author":[{"lastName":"Zaier","firstName":"Zied"},{"lastName":"Godin","firstName":"Robert"},{"lastName":"Faucher","firstName":"Luc"}]},"sentenceCased":true},{"key":"5279910","type":"inproceedings","fields":{"author":["Klint, P.","family=Storm, given=T., prefix=v. d., useprefix=false","Vinju, J."],"booktitle":["2009 Ninth IEEE Int. Work. Conf. Source Code Anal. Manip."],"date":["2009-09"],"doi":["10.1109/SCAM.2009.28"],"keywords":["ad hoc integration","automated software engineering tool","complex software refactoring","conceptual-syntactic-semantic-technical level","domain specific language","Domain specific languages","Impedance","impedance mismatch","Informatics","Java","Libraries","Logic programming","meta-programming","object-oriented languages","Pattern matching","program diagnostics","RASCAL","Scalability","software engineering","software maintenance","source code analysis","source code manipulation","Storms","transformation"],"note":["TL;DR \n\nRascal is a domain-specific language that takes away most of this boilerplate by integrating source code analysis and manipulation at the conceptual, syntactic, semantic and technical level."],"pages":["168–177"],"title":["RASCAL: A domain specific language for source code analysis and manipulation"]},"creators":{"author":[{"lastName":"Klint","firstName":"P."},{"lastName":"Storm","firstName":"T.","prefix":"v.d.","useprefix":false},{"lastName":"Vinju","firstName":"J."}]},"sentenceCased":true},{"key":"5287006","type":"article","fields":{"author":["Robillard, M. P."],"date":["2009-11"],"doi":["10.1109/MS.2009.193"],"ids":["robillard2009makes"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["API design","API learnability","API usability","application program interface","application program interfaces","Application software","code examples","code reuse","empirical study","Microsoft developers","Programming profession","software development management","software development technologies","software documentation","software reusability","Usability"],"note":["TL;DR \n\nThe article focuses on the obstacles to learning an API and concludes that as APIs keep growing larger, developers will need to learn a proportionally smaller fraction of the whole."],"number":["6"],"pages":["27–34"],"title":["What makes APIs hard to learn? Answers from developers"],"volume":["26"]},"creators":{"author":[{"lastName":"Robillard","firstName":"M. P."}]},"sentenceCased":true},{"key":"5428690","type":"inproceedings","fields":{"author":["Ray, S.","Mahanti, A."],"booktitle":["2010 43rd Hawaii Int. Conf. Syst. Sci."],"date":["2010"],"doi":["10.1109/HICSS.2010.225"],"pages":["1–9"],"title":["Improving prediction accuracy in trust-aware recommender systems"]},"creators":{"author":[{"lastName":"Ray","firstName":"S."},{"lastName":"Mahanti","firstName":"A."}]},"sentenceCased":true},{"key":"6224306","type":"inproceedings","fields":{"author":["Harman, M.","Jia, Y.","Zhang, Y."],"booktitle":["2012 9th IEEE Work. Conf. Min. Softw. Repos. MSR"],"date":["2012-06"],"doi":["10.1109/MSR.2012.6224306"],"issn":["2160-1860"],"keywords":["app download","app store analysis","app store mining","app store MSR","Blackberry app store","Business","business aspect","Clustering algorithms","Correlation","customer aspect","customer rating","customer review","data mining","Data mining","Feature extraction","feature information extraction","Measurement","pricing","Software","software development management","software packages","software repository mining","technical aspect"],"pages":["108–111"],"title":["App store mining and analysis: MSR for app stores"]},"creators":{"author":[{"lastName":"Harman","firstName":"M."},{"lastName":"Jia","firstName":"Y."},{"lastName":"Zhang","firstName":"Y."}]},"sentenceCased":true},{"key":"6233407","type":"inproceedings","fields":{"author":["Zagalsky, A.","Barzilay, O.","Yehudai, A."],"booktitle":["2012 Third Int. Workshop Recomm. Syst. Softw. Eng. RSSE"],"date":["2012-06"],"issn":["2327-0934"],"note":["TL;DR \n\nExamples Overflow is presented, a code search and recommendation tool which brings together social media and code recommendation systems and enables crowd-sourced software development by utilizing both textual and social information, which accompany source code on the Web."],"pages":["38–42"],"title":["Example Overflow: Using social media for code recommendation"]},"creators":{"author":[{"lastName":"Zagalsky","firstName":"A."},{"lastName":"Barzilay","firstName":"O."},{"lastName":"Yehudai","firstName":"A."}]},"sentenceCased":true},{"key":"6233418","type":"inproceedings","fields":{"author":["Cordeiro, J.","Antunes, B.","Gomes, P."],"booktitle":["2012 Third Int. Workshop Recomm. Syst. Softw. Eng. RSSE"],"date":["2012-06"],"doi":["10.1109/RSSE.2012.6233418"],"issn":["2327-0934"],"keywords":["Console View","Context","Context Modelling","context-based recommendation","Data mining","Eclipse","exception occurrence","exception stack traces","IDE","information searching","keyword-based approach","online front-ends","problem solving","Problem Solving","Problem-solving","Programming","question answering (information retrieval)","question-answering Web resources retrieval","recommendation systems","recommender systems","Search engines","Servers","Software","Software Development","software development management","software development process","Web browser","Web pages","Web sites"],"pages":["85–89"],"title":["Context-based recommendation to support problem solving in software development"]},"creators":{"author":[{"lastName":"Cordeiro","firstName":"J."},{"lastName":"Antunes","firstName":"B."},{"lastName":"Gomes","firstName":"P."}]},"sentenceCased":true},{"key":"6671293","type":"inproceedings","fields":{"author":["Thung, F.","Lo, D.","Lawall, J."],"booktitle":["2013 20th Work. Conf Reverse Eng. WCRE"],"date":["2013-10"],"ids":["LibRec"],"issn":["1095-1350"],"keywords":["association rule mining","Association rules","automated library recommendation","Collaboration","collaborative filtering","data mining","Feature extraction","Generators","Itemsets","Libraries","recall rate","software projects","software reliability","third-party libraries"],"note":["TL;DR \n\nA new technique is proposed that automatically recommends libraries to developers based on a set of library usage patterns that an application currently uses, and recommends other libraries that are likely to be relevant."],"pages":["182–191"],"title":["Automated library recommendation"]},"creators":{"author":[{"lastName":"Thung","firstName":"F."},{"lastName":"Lo","firstName":"D."},{"lastName":"Lawall","firstName":"J."}]},"sentenceCased":true},{"key":"6671295","type":"inproceedings","fields":{"author":["Teyton, Cédric","Falleri, Jean-Rémy","Morandat, Floréal","Blanc, Xavier"],"booktitle":["2013 20th Work. Conf. Reverse Eng. WCRE"],"date":["2013-10"],"doi":["10.1109/WCRE.2013.6671295"],"issn":["1095-1350"],"keywords":["Apache HBase project","Communities","data mining","GitHub developers","Indexes","Java","Java libraries","Libraries","Libtic search engine","Prototypes","public domain software","search engines","Software","software development","software maintenance","software repositories mining","third-party libraries"],"pages":["202–211"],"title":["Find your library experts"]},"creators":{"author":[{"lastName":"Teyton","firstName":"Cédric"},{"lastName":"Falleri","firstName":"Jean-Rémy"},{"lastName":"Morandat","firstName":"Floréal"},{"lastName":"Blanc","firstName":"Xavier"}]},"sentenceCased":true},{"key":"6671315","type":"inproceedings","fields":{"author":["Montandon, J. E.","Borges, H.","Felix, D.","Valente, M. T."],"booktitle":["2013 20th Work. Conf. Reverse Eng. WCRE"],"date":["2013-10"],"doi":["10.1109/WCRE.2013.6671315"],"issn":["1095-1350"],"keywords":["Android API","Androids","API documentation","API learning process","APIMiner platform","application program interfaces","application programming interfaces","Computer architecture","data mining","Documentation","field study","Google","Humanoid robots","Instruments","Java","JavaDoc","Measurement","private source code repository","software development","software engineering","source code examples","standard Java-based API documentation format","static slicing algorithm","system documentation"],"pages":["401–408"],"title":["Documenting APIs with examples: Lessons learned with the APIMiner platform"]},"creators":{"author":[{"lastName":"Montandon","firstName":"J. E."},{"lastName":"Borges","firstName":"H."},{"lastName":"Felix","firstName":"D."},{"lastName":"Valente","firstName":"M. T."}]},"sentenceCased":true},{"key":"67OpenSource","type":"online","fields":{"title":["67 open source tools and resources for the Internet of Things (IoT)"],"url":["http://techbeacon.com/67-open-source-tools-resources-iot"],"urldate":["2016-09-27"]},"creators":{},"sentenceCased":true},{"key":"7070485","type":"inproceedings","fields":{"author":["Basten, B.","Hills, M.","Klint, P.","Landman, D.","Shahi, A.","Steindorfer, M. J.","Vinju, J. J."],"booktitle":["2015 IEEE 1st Int. Workshop Softw. Anal. SWAN"],"date":["2015-03"],"doi":["10.1109/SWAN.2015.7070485"],"ids":["Basten2015M3"],"keywords":["Abstracts","Analytical models","code analytics","Computational modeling","general model","Java","M3 framework","Measurement","Object oriented modeling","Rascal meta programming language","software libraries","source code","source code (software)","specification languages","standard library"],"note":["TL;DR \n\nThis short paper introduces M3, a simple and extensible model for capturing facts about source code for future analysis that is a core part of the standard library of the Rascal meta programming language."],"pages":["25–28"],"title":["M3: A general model for code analytics in rascal"]},"creators":{"author":[{"lastName":"Basten","firstName":"B."},{"lastName":"Hills","firstName":"M."},{"lastName":"Klint","firstName":"P."},{"lastName":"Landman","firstName":"D."},{"lastName":"Shahi","firstName":"A."},{"lastName":"Steindorfer","firstName":"M. J."},{"lastName":"Vinju","firstName":"J. J."}]},"sentenceCased":true},{"key":"7332619","type":"inproceedings","fields":{"author":["Maldonado, Everton da S.","Shihab, Emad"],"booktitle":["2015 IEEE 7th Int. Workshop Manag. Tech. Debt MTD"],"date":["2015"],"doi":["10.1109/MTD.2015.7332619"],"note":["TL;DR \n\nThis paper examines code comments to determine the different types of technical debt, and finds that self-admitted technical debt can be classified into five main types - design debt, defect debt, documentation debt, requirement debt and test debt."],"pages":["9–15"],"title":["Detecting and quantifying different types of self-admitted technical Debt"]},"creators":{"author":[{"lastName":"Maldonado","firstName":"Everton da S."},{"lastName":"Shihab","firstName":"Emad"}]},"sentenceCased":true},{"key":"7372018","type":"inproceedings","fields":{"author":["Vargas-Baldrich, S.","Linares-Vásquez, M.","Poshyvanyk, D."],"booktitle":["2015 30th IEEEACM Int. Conf. Autom. Softw. Eng. ASE"],"date":["2015-11"],"doi":["10.1109/ASE.2015.38"],"keywords":["automatic software tagging approach","bytecode","categorization approach","closed source repository group software systems","Data mining","dependency relations","Feature extraction","information retrieval","Internet","Maven-based software projects","online repositories","open source community","open source repository group software systems","project management","public domain software","recommendation systems","Sally","Software algorithms","software assets","software management","Software systems","software tagging","Support vector machines","Tagging","term assignment"],"pages":["289–294"],"title":["Automated tagging of software projects using bytecode and dependencies (n)"]},"creators":{"author":[{"lastName":"Vargas-Baldrich","firstName":"S."},{"lastName":"Linares-Vásquez","firstName":"M."},{"lastName":"Poshyvanyk","firstName":"D."}]},"sentenceCased":true},{"key":"7403546","type":"inproceedings","fields":{"author":["Carbunar, B.","Potharaju, R."],"booktitle":["2015 IEEEACM Int. Conf. Adv. Soc. Netw. Anal. Min. ASONAM"],"date":["2015"],"doi":["10.1145/2808797.2808823"],"pages":["242–249"],"title":["A longitudinal study of the Google app market"]},"creators":{"author":[{"lastName":"Carbunar","firstName":"B."},{"lastName":"Potharaju","firstName":"R."}]},"sentenceCased":true},{"key":"7569018","type":"article","fields":{"langid":["english"],"abstract":["Modeling languages, just as all software artifacts, evolve. This imposes the risk that legacy models of a company get lost, when they become incompatible with the new language version. To address this risk a multitude of approaches for metamodel-model co-evolution was proposed in the last 10 years. However, the high number of solutions makes it difficult for practitioners to choose an appropriate approach."],"author":["Hebig, R.","Khelladi, D. E.","Bendraou, R."],"date":["2017-05"],"doi":["10.1109/TSE.2016.2610424"],"ids":["hebigApproachesCoEvolutionMetamodels2017"],"issn":["2326-3881"],"journaltitle":["IIEEE Trans. Software Eng."],"keywords":["Atmospheric modeling","Biological system modeling","coevolution approaches","Companies","decision support","design notations and documentation","Libraries","metamodel-model coevolution","metamodels","models","Productivity","software engineering","solution technique taxonomy","Survey","Taxonomy","Unified modeling language"],"note":["TL;DR \n\nA survey on 31 approaches to support metamodel-model co-evolution is presented, a taxonomy of solution techniques is introduced and the existing approaches are classified to support researchers and practitioners."],"number":["5"],"pages":["396–414"],"shorttitle":["Approaches to Co-Evolution of Metamodels and Models"],"title":["Approaches to co-evolution of metamodels and models: A survey"],"volume":["43"]},"creators":{"author":[{"lastName":"Hebig","firstName":"R."},{"lastName":"Khelladi","firstName":"D. E."},{"lastName":"Bendraou","firstName":"R."}]},"sentenceCased":true},{"key":"7816479","type":"inproceedings","fields":{"author":["Borges, H.","Hora, A.","Valente, M. T."],"booktitle":["2016 IEEE Int. Conf. Softw. Maint. Evol. ICSME"],"date":["2016-10"],"doi":["10.1109/ICSME.2016.31"],"keywords":["Documentation","GitHub","GitHub projects","GitHub Repositories","HTML","Java","Libraries","open source developers","open source software","Open Source software","Organizations","programming language","project popularity","public domain software","Social coding","Software","software acceptance","software market","Software Popularity","software reviews","software system popularity","source code (software)","stargazers button","time series"],"pages":["334–344"],"title":["Understanding the factors that impact the popularity of GitHub repositories"]},"creators":{"author":[{"lastName":"Borges","firstName":"H."},{"lastName":"Hora","firstName":"A."},{"lastName":"Valente","firstName":"M. T."}]},"sentenceCased":true},{"key":"7884616","type":"inproceedings","fields":{"author":["Xavier, L.","Brito, A.","Hora, A.","Valente, M. T."],"booktitle":["2017 IEEE 24th Int Conf Softw. Anal. Evol. Reengineering SANER"],"date":["2017"],"note":["TL;DR \n\nThe authors' large-scale analysis on 317 real-world Java libraries, 9K releases, and 260K client applications shows that systems with higher frequency of breaking changes are larger, more popular, and more active."],"pages":["138–147"],"title":["Historical and impact analysis of API breaking changes: A large-scale study"]},"creators":{"author":[{"lastName":"Xavier","firstName":"L."},{"lastName":"Brito","firstName":"A."},{"lastName":"Hora","firstName":"A."},{"lastName":"Valente","firstName":"M. T."}]},"sentenceCased":true},{"key":"7884645","type":"inproceedings","fields":{"author":["Zerouali, Ahmed","Mens, Tom"],"booktitle":["2017 IEEE 24th Int. Conf. Softw. Anal. Evol. Reengineering SANER"],"date":["2017"],"doi":["10.1109/SANER.2017.7884645"],"note":["TL;DR \n\nIt is found that some libraries are considerably more popular than their competitors, while some libraries become more popular over time, and many projects tend to use multiple libraries together."],"pages":["417–421"],"title":["Analyzing the evolution of testing library usage in open source Java projects"]},"creators":{"author":[{"lastName":"Zerouali","firstName":"Ahmed"},{"lastName":"Mens","firstName":"Tom"}]},"sentenceCased":true},{"key":"7961519","type":"inproceedings","fields":{"author":["Lam, A. N.","Nguyen, A. T.","Nguyen, H. A.","Nguyen, T. N."],"booktitle":["2017 IEEEACM 25th Int. Conf. Program Comprehension ICPC"],"date":["2017"],"note":["TL;DR \n\nThe new model, DNNLOC, with a combination of the features built from DNN, rVSM, and project'sbug-fixing history, achieves higher accuracy than the state-of-the-artIR and machine learning techniques."],"pages":["218–229"],"title":["Bug localization with combination of deep learning and information retrieval"]},"creators":{"author":[{"lastName":"Lam","firstName":"A. N."},{"lastName":"Nguyen","firstName":"A. T."},{"lastName":"Nguyen","firstName":"H. A."},{"lastName":"Nguyen","firstName":"T. N."}]},"sentenceCased":true},{"key":"7961718","type":"inproceedings","fields":{"author":["Ranjan, R.","Sankaranarayanan, S.","Castillo, C. D.","Chellappa, R."],"booktitle":["2017 12th IEEE Int Conf Autom. Face Gesture Recognit. FG 2017"],"date":["2017-05"],"doi":["10.1109/FG.2017.137"],"keywords":["age estimation","all-in-one convolutional neural network","CNN shared parameters","Face","face alignment","face analysis","Face detection","face recognition","Face recognition","gender recognition","learning (artificial intelligence)","multitask learning framework","neural nets","pose estimation","Pose estimation","Robustness","simultaneous face detection","smile detection","Training"],"pages":["17–24"],"title":["An all-in-one convolutional neural network for face analysis"]},"creators":{"author":[{"lastName":"Ranjan","firstName":"R."},{"lastName":"Sankaranarayanan","firstName":"S."},{"lastName":"Castillo","firstName":"C. D."},{"lastName":"Chellappa","firstName":"R."}]},"sentenceCased":true},{"key":"7985645","type":"inproceedings","fields":{"author":["Guo, J.","Cheng, J.","Cleland-Huang, J."],"booktitle":["2017 IEEEACM 39th Int. Conf. Softw. Eng. ICSE"],"date":["2017"],"pages":["3–14"],"title":["Semantically enhanced software traceability using deep learning techniques"]},"creators":{"author":[{"lastName":"Guo","firstName":"J."},{"lastName":"Cheng","firstName":"J."},{"lastName":"Cleland-Huang","firstName":"J."}]},"sentenceCased":true},{"key":"7985674","type":"inproceedings","fields":{"author":["Li, M.","Wang, W.","Wang, P.","Wang, S.","Wu, D.","Liu, J.","Xue, R.","Huo, W."],"booktitle":["2017 IEEEACM 39th Int. Conf. Softw. Eng. ICSE"],"date":["2017"],"note":["TL;DR \n\nResults show that compared to existing tools, LibD can better handle multi-package third-party libraries in the presence of name-based obfuscation, leading to significantly improved precision without the loss of scalability."],"pages":["335–346"],"title":["LibD: Scalable and precise third-party library detection in android markets"]},"creators":{"author":[{"lastName":"Li","firstName":"M."},{"lastName":"Wang","firstName":"W."},{"lastName":"Wang","firstName":"P."},{"lastName":"Wang","firstName":"S."},{"lastName":"Wu","firstName":"D."},{"lastName":"Liu","firstName":"J."},{"lastName":"Xue","firstName":"R."},{"lastName":"Huo","firstName":"W."}]},"sentenceCased":true},{"key":"8009930","type":"inproceedings","fields":{"author":["Behnamghader, P.","Alfayez, R.","Srisopha, K.","Boehm, B."],"booktitle":["2017 IEEE Int. Conf. Softw. Qual. Reliab. Secur. QRS"],"date":["2017-07"],"doi":["10.1109/QRS.2017.36"],"keywords":["Apache Java software systems","commit-impact analysis","Computer bugs","Measurement","mining software repositories","program compilers","Security","software metrics","software quality","Software quality","software quality evolution","software quality indicator","software quality metrics","Software systems","source code","source code (software)","Tools"],"pages":["251–262"],"title":["Towards better understanding of software quality evolution through commit-impact analysis"]},"creators":{"author":[{"lastName":"Behnamghader","firstName":"P."},{"lastName":"Alfayez","firstName":"R."},{"lastName":"Srisopha","firstName":"K."},{"lastName":"Boehm","firstName":"B."}]},"sentenceCased":true},{"key":"8025917","type":"inproceedings","fields":{"author":["Gilda, S."],"booktitle":["2017 14th Int. Jt. Conf. Comput. Sci. Softw. Eng. JCSSE"],"date":["2017-07"],"doi":["10.1109/JCSSE.2017.8025917"],"keywords":["artificial neural network","Artificial neural network","convolutional neural network","feature extraction","Feature extraction","file extension","HTML","intelligent feature extraction","learning (artificial intelligence)","Multi-layer neural network","multilayer neural network","neural nets","neural networks","pattern classification","programming languages","software development industry","software engineering","source code (software)","source code classification","supervised learning","Supervised learning","Syntactics","Training","word embedding layers"],"pages":["1–6"],"title":["Source code classification using neural networks"]},"creators":{"author":[{"lastName":"Gilda","firstName":"S."}]},"sentenceCased":true},{"key":"8327318","type":"inproceedings","fields":{"author":["Ragkhitwetsagul, C.","Krinke, J.","Marnette, B."],"booktitle":["2018 IEEE 12th Int. Workshop Softw. Clones IWSC"],"date":["2018-03"],"doi":["10.1109/IWSC.2018.8327318"],"issn":["2572-6587"],"keywords":["clone pairs","Cloning","code clone detection technique","code clone detectors","code image blurring","Detectors","Earth","Image color analysis","image conversion","image processing","image similarity","Jaccard similarity","Java","Java clone detection","normalisation technique","pervasive code modifications","public domain software","raw source code text","similarity computation","similarity measures","software maintenance","software systems","source code (software)","syntax highlighting","type-3 clones","Visualization"],"pages":["44–50"],"title":["A picture is worth a thousand words: Code clone detection based on image similarity"]},"creators":{"author":[{"lastName":"Ragkhitwetsagul","firstName":"C."},{"lastName":"Krinke","firstName":"J."},{"lastName":"Marnette","firstName":"B."}]},"sentenceCased":true},{"key":"8595172","type":"inproceedings","fields":{"author":["Geiger, F.","Malavolta, I.","Pascarella, L.","Palomba, F.","Di Nucci, D.","Bacchelli, A."],"booktitle":["2018 IEEEACM 15th Int. Conf. Min. Softw. Repos. MSR"],"date":["2018"],"pages":["30–33"],"title":["A graph-based dataset of commit history of real-world android apps"]},"creators":{"author":[{"lastName":"Geiger","firstName":"F."},{"lastName":"Malavolta","firstName":"I."},{"lastName":"Pascarella","firstName":"L."},{"lastName":"Palomba","firstName":"F."},{"lastName":"Di Nucci","firstName":"D."},{"lastName":"Bacchelli","firstName":"A."}]},"sentenceCased":true},{"key":"8595234","type":"inproceedings","fields":{"author":["Lamothe, M.","Shang, W."],"booktitle":["2018 IEEEACM 15th Int. Conf. Min. Softw. Repos. MSR"],"date":["2018-05"],"ids":["lamothe_exploring_2018"],"issn":["2574-3864"],"keywords":["Android API","Android APIs","API consumers","API documentation","API migration","application program interfaces","automated API migrating techniques","Data mining","Documentation","freely available application program interfaces","historical code changes","historical code-change information","History","Keyword search","migration guidance","migration suggestions","Mining Software Repositories","mobile computing","open source software libraries","public domain software","robust applications","Software","software documentation","Software evolution","software libraries","software maintenance","Task analysis","Tools"],"nopublisher":["ACM Press"],"note":["TL;DR \n\nThe experiences suggest that migration through historical code-changes presents various challenges and that API documentation is undervalued, and that the challenges of API migration lie beyond migration suggestions, in aspects such as coping with parameter type changes in new API."],"nourl":["http://dl.acm.org/citation.cfm?doid=3196398.3196420"],"pages":["503–514"],"title":["Exploring the use of automated API migrating techniques in practice: An experience report on android"]},"creators":{"author":[{"lastName":"Lamothe","firstName":"M."},{"lastName":"Shang","firstName":"W."}]},"sentenceCased":true},{"key":"8630054","type":"article","fields":{"author":["Chen, Chunyang","Xing, Zhenchang","Liu, Yang","Xiong, Kent Ong Long"],"date":["2021"],"doi":["10.1109/TSE.2019.2896123"],"journaltitle":["IEEE Trans. Softw. Eng."],"number":["3"],"pages":["432–447"],"title":["Mining likely analogical APIs across third-party libraries via large-scale unsupervised API semantics embedding"],"volume":["47"]},"creators":{"author":[{"lastName":"Chen","firstName":"Chunyang"},{"lastName":"Xing","firstName":"Zhenchang"},{"lastName":"Liu","firstName":"Yang"},{"lastName":"Xiong","firstName":"Kent Ong Long"}]},"sentenceCased":true},{"key":"9043686","type":"article","fields":{"author":["He, Q.","Li, B.","Chen, F.","Grundy, J.","Xia, X.","Yang, Y."],"date":["2020"],"journaltitle":["IEEE Trans. Softw. Eng."],"pages":["1–1"],"title":["Diversified third-party library prediction for mobile app development"]},"creators":{"author":[{"lastName":"He","firstName":"Q."},{"lastName":"Li","firstName":"B."},{"lastName":"Chen","firstName":"F."},{"lastName":"Grundy","firstName":"J."},{"lastName":"Xia","firstName":"X."},{"lastName":"Yang","firstName":"Y."}]},"sentenceCased":true},{"key":"9054865","type":"inproceedings","fields":{"abstract":["Third-party libraries are crucial to the development of software projects. To get suitable libraries, developers need to search through millions of libraries by filtering, evaluating, and comparing. The vast number of libraries places a barrier for programmers to locate appropriate ones. To help developers, researchers have proposed automated approaches to recommend libraries based on library usage pattern. However, these prior studies can not sufficiently match user requirements and suffer from cold-start problem. In this work, we would like to make recommendations based on requirement descriptions to avoid these problems. To this end, we propose a novel neural approach called Req2Lib which recommends libraries given descriptions of the project requirement. We use a Sequence-to-Sequence model to learn the library linked-usage information and semantic information of requirement descriptions in natural language. Besides, we apply a domain-specific pre-trained word2vec model for word embedding, which is trained over textual corpus from Stack Overflow posts. In the experiment, we train and evaluate the model with data from 5,625 java projects. Our preliminary evaluation demonstrates that Req2Lib can recommend libraries accurately."],"author":["Sun, Z.","Liu, Y.","Cheng, Z.","Yang, C.","Che, P."],"booktitle":["2020 IEEE 27th Int. Conf. Softw. Anal. Evol. Reengineering SANER"],"date":["2020-02"],"doi":["10.1109/SANER48275.2020.9054865"],"issn":["1534-5351"],"keywords":["conferences","deep learning","filtering","java","natural languages","semantics","software libraries"],"location":["Los Alamitos, CA, USA"],"note":["TL;DR \n\nThis work proposes a novel neural approach called Req2Lib which recommends libraries given descriptions of the project requirement, which uses a Sequence-to-Sequence model to learn the library linked-usage information and semantic information of requirement descriptions in natural language."],"pages":["542–546"],"publisher":["IEEE Computer Society"],"title":["Req2Lib: A semantic neural model for software library recommendation"]},"creators":{"author":[{"lastName":"Sun","firstName":"Z."},{"lastName":"Liu","firstName":"Y."},{"lastName":"Cheng","firstName":"Z."},{"lastName":"Yang","firstName":"C."},{"lastName":"Che","firstName":"P."}]},"sentenceCased":true},{"key":"9463106","type":"inproceedings","fields":{"author":["Mashhadi, Ehsan","Hemmati, Hadi"],"booktitle":["2021 IEEEACM 18th Int. Conf. Min. Softw. Repos. MSR"],"date":["2021"],"doi":["10.1109/MSR52588.2021.00063"],"note":["TL;DR \n\nA novel automated program repair approach based on CodeBERT, which is a transformer-based neural architecture pre-trained on large corpus of source code, which can generate varied-length fixes and can fix different types of bugs, even if only a few instances of those types of Bugs exists in the training dataset."],"pages":["505–509"],"title":["Applying CodeBERT for automated program repair of java simple bugs"]},"creators":{"author":[{"lastName":"Mashhadi","firstName":"Ehsan"},{"lastName":"Hemmati","firstName":"Hadi"}]},"sentenceCased":true},{"key":"9474384","type":"inproceedings","fields":{"author":["Golzadeh, Mehdi","Decan, Alexandre","Constantinou, Eleni","Mens, Tom"],"booktitle":["2021 IEEEACM Third Int. Workshop Bots Softw. Eng. BotSE"],"date":["2021"],"doi":["10.1109/BotSE52550.2021.00012"],"note":["TL;DR \n\nA classification model based on natural language processing is proposed for identification of development bots using a combination of the bag of words and TF-IDF techniques to predict the type of comment (human or bot) based on this vector representation."],"pages":["21–25"],"title":["Identifying bot activity in GitHub pull request and issue comments"]},"creators":{"author":[{"lastName":"Golzadeh","firstName":"Mehdi"},{"lastName":"Decan","firstName":"Alexandre"},{"lastName":"Constantinou","firstName":"Eleni"},{"lastName":"Mens","firstName":"Tom"}]},"sentenceCased":true},{"key":"9609135","type":"inproceedings","fields":{"author":["Cassee, Nathan","Kitsanelis, Christos","Constantinou, Eleni","Serebrenik, Alexander"],"booktitle":["2021 IEEE Int. Conf. Softw. Maint. Evol. ICSME"],"date":["2021"],"doi":["10.1109/ICSME52107.2021.00075"],"note":["TL;DR \n\nThis study investigates three comment-level classification models and finds that the best classifiers based on these classification models achieve a precision and recall between 88% and 96% and even the most accurate comment- level classifier cannot accurately detect mixed accounts."],"pages":["654–658"],"title":["Human, bot or both? A study on the capabilities of classification models on mixed accounts"]},"creators":{"author":[{"lastName":"Cassee","firstName":"Nathan"},{"lastName":"Kitsanelis","firstName":"Christos"},{"lastName":"Constantinou","firstName":"Eleni"},{"lastName":"Serebrenik","firstName":"Alexander"}]},"sentenceCased":true},{"key":"9678712","type":"inproceedings","fields":{"author":["Paltenghi, Matteo","Pradel, Michael"],"booktitle":["2021 36th IEEEACM Int. Conf. Autom. Softw. Eng. ASE"],"date":["2021"],"doi":["10.1109/ASE51524.2021.9678712"],"note":["TL;DR \n\nThis paper investigates to what extent the attention weights of effective neural models match the reasoning of skilled humans, and presents a methodology for recording human attention and uses it to gather 1,508 human attention maps, which is the largest such dataset the authors are aware of."],"pages":["867–879"],"title":["Thinking like a developer? Comparing the attention of humans with neural models of code"]},"creators":{"author":[{"lastName":"Paltenghi","firstName":"Matteo"},{"lastName":"Pradel","firstName":"Michael"}]},"sentenceCased":true},{"key":"9825781","type":"inproceedings","fields":{"author":["Nafi, Kawser Wazed","Asaduzzaman, Muhammad","Roy, Banani","Roy, Chanchal K.","Schneider, Kevin A."],"booktitle":["2022 IEEE Int. Conf. Softw. Anal. Evol. Reengineering SANER"],"date":["2022"],"doi":["10.1109/SANER53432.2022.00109"],"note":["TL;DR \n\nAn extensive evaluation show that the proposed XLibRec technique can recommend cross-language analogical libraries with great accuracy and has achieved 8-45% higher precision than the state-of-the-art technique."],"pages":["913–924"],"title":["Mining software information sites to recommend cross-language analogical libraries"]},"creators":{"author":[{"lastName":"Nafi","firstName":"Kawser Wazed"},{"lastName":"Asaduzzaman","firstName":"Muhammad"},{"lastName":"Roy","firstName":"Banani"},{"lastName":"Roy","firstName":"Chanchal K."},{"lastName":"Schneider","firstName":"Kevin A."}]},"sentenceCased":true},{"key":"9825861","type":"inproceedings","fields":{"langid":["english"],"abstract":["During their daily routine, developers often deal with a plethora of resources, attempting to search for relevant artifacts that can be added to the project under development. This kind of information overload may render developers overwhelmed, thus undermining their productivity and efficiency. Recommender systems are an effective means of easing such a burden, providing relevant items for the current programming contexts, e.g., third-party libraries (TPLs), API calls, or code snippets. By focusing on TPLs, there has been no work to allow for the integration of tailored feedback mechanisms with which users can conveniently accept or discard libraries. In this paper, we propose an approach to handle explicit user feedback, including positive, negative, and additive. Thus, further than accepting or discarding the recommended TPLs, users can also endorse libraries that, in their opinion, are relevant for the current context, even though they are not included in the provided recommendations. As a proof of concept, we demonstrate how user feedback generated by the proposed mechanism can change the outcome of a real TPLs recommender system. The results show that our proposed approach helps the considered system retrieve relevant items, under different configurations. © 2022 IEEE."],"author":["Rubei, R.","Di Sipio, C.","Di Rocco, J.","Di Ruscio, D.","Nguyen, P.T."],"booktitle":["Proc. - 2022 IEEE Int. Conf. Softw. Anal. Evol. Reengineering SANER 2022"],"date":["2022"],"doi":["10.1109/SANER53432.2022.00099"],"ids":["rubeiEndowingThirdpartyLibraries2022,rubeiEndowingThirdpartyLibraries2022a,rubeiEndowingThirdpartyLibraries2022b,rubeiEndowingThirdpartyLibraries2022c,rubeiEndowingThirdpartyLibraries2022d"],"isbn":["978-1-66543-786-8"],"keywords":["API calls","Application programming interfaces (API)","Current programming","Daily routines","Feedback control","Feedback mechanisms","Information overloads","Libraries","Library users","Positive/negative","Recommender systems","Third parties","Third-party recommendation","User feedback"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 1 \n\nTL;DR \n\nThis paper proposes an approach to handle explicit user feedback, including positive, negative, and additive, and shows how user feedback generated by the proposed mechanism can change the outcome of a real TPLs recommender system."],"pages":["817–821"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Endowing third-party libraries recommender systems with explicit user feedback mechanisms"]},"creators":{"author":[{"lastName":"Rubei","firstName":"R."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Nguyen","firstName":"P.T."}]},"sentenceCased":true},{"key":"9866550","type":"article","fields":{"author":["Fatima, Sakina","Ghaleb, Taher A.","Briand, Lionel"],"date":["2023"],"doi":["10.1109/TSE.2022.3201209"],"journaltitle":["IEEE Trans. Softw. Eng."],"number":["4"],"pages":["1912–1927"],"title":["Flakify: A black-box, language model-based predictor for flaky tests"],"volume":["49"]},"creators":{"author":[{"lastName":"Fatima","firstName":"Sakina"},{"lastName":"Ghaleb","firstName":"Taher A."},{"lastName":"Briand","firstName":"Lionel"}]},"sentenceCased":true},{"key":"9ae2f829db7d4233bdf77953d5055637","type":"book","fields":{"langid":["english"],"abstract":["Templates are used to generate all kinds of text, including computer code. The last decade, the use of templates gained a lot of popularity due to the increase of dynamic web applications. Templates are a tool for programmers, and implementations of template engines are most times based on practical experience rather than based on a theoretical background. This book reveals the mathematical background of templates and shows interesting findings for improving the practical use of templates. First, a framework to determine the necessary computational power for the template metalanguage is presented. The template metalanguage does not need to be Turing-complete to be useful. A non-Turing-complete metalanguage enforces separation of concerns between the view and model. Second, syntactical correctness of all languages of the templates and generated code is ensured. This includes the syntactical correctness of the template metalanguage and the output language. Third, case studies show that the achieved goals are applicable in practice. It is even shown that syntactical correctness helps to prevent cross-site scripting attacks in web applications. The target audience of this book is twofold. The first group exists of researcher interested in the mathematical background of templates. The second group exists of users of templates. This includes designers of template engines on one side and programmers and web designers using templates on the other side"],"author":["Arnoldus, B.J.","Brand, van den, M.G.J.","Serebrenik, A.","Brunekreef, J.J."],"date":["2012"],"doi":["10.2991/978-94-91216-56-5"],"isbn":["978-94-91216-55-8"],"location":["Netherlands"],"note":["TL;DR \n\nThe mathematical background of templates is revealed, a framework to determine the necessary computational power for the template metalanguage is presented and it is shown that syntactical correctness helps to prevent cross-site scripting attacks in web applications."],"publisher":["Atlantis Press"],"series":["Atlantis studies in computing"],"title":["Code generation with templates"]},"creators":{"author":[{"lastName":"Arnoldus","firstName":"B.J."},{"lastName":"Brand","suffix":"van den","firstName":"M.G.J."},{"lastName":"Serebrenik","firstName":"A."},{"lastName":"Brunekreef","firstName":"J.J."}]},"sentenceCased":true},{"key":"ab.rahimSurveyApproachesVerifying2013","type":"article","fields":{"langid":["english"],"abstract":["As with other software development artifacts, model transformations are not bug-free and so must be systematically verified. Their nature, however, means that transformations require specialist verification techniques. This paper brings together current research on model transformation verification by classifying existing approaches along two dimensions. Firstly, we present a coarse-grained classification based on the technical details of the approach (e.g., testing, theorem proving, model checking). Secondly, we present a finer-grained classification which categorizes approaches according to criteria such as level of formality, transformation language, properties verified. The purpose of the survey is to bring together research in model transformation verification to act as a resource for the community. Furthermore, based on the survey, we identify a number of trends in current and past research on model transformation verification."],"author":["Ab. Rahim, Lukman","Whittle, Jon"],"date":["2013-06-13"],"doi":["10.1007/s10270-013-0358-0"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"keywords":["software engineering"],"note":["TL;DR \n\nA finer-grained classification is presented which categorizes approaches according to criteria such as level of formality, transformation language, properties verified and a number of trends in current and past research on model transformation verification are identified."],"pages":["1–26"],"title":["A survey of approaches for verifying model transformations"]},"creators":{"author":[{"lastName":"Ab. Rahim","firstName":"Lukman"},{"lastName":"Whittle","firstName":"Jon"}]},"sentenceCased":true},{"key":"Abbar09context-awarerecommender","type":"inproceedings","fields":{"author":["Abbar, Sofiane","Bouzeghoub, Mokrane","Lopez, Stéphane"],"booktitle":["VLDB PersDB workshop"],"date":["2009"],"title":["Context-aware recommender systems: A service oriented approach"]},"creators":{"author":[{"lastName":"Abbar","firstName":"Sofiane"},{"lastName":"Bouzeghoub","firstName":"Mokrane"},{"lastName":"Lopez","firstName":"Stéphane"}]},"sentenceCased":true},{"key":"Abdalhadi20221356","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Indones. J. Electrical Eng. Comput. Sci."],"affiliation":["Control and Mechatronics Engineering Division, School of Electrical Engineering, Universiti Teknologi Malaysia, Johor, Malaysia; Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Malaysia"],"author":["Abdalhadi, A.","Wahid, H.","Burhanuddin, D.H."],"correspondence_address1":["Wahid, H.; School of Electrical Engineering, Johor, Malaysia; email: herman@utm.my"],"date":["2022"],"document_type":["Article"],"doi":["10.11591/ijeecs.v25.i3.pp1356-1366"],"issn":["25024752"],"journaltitle":["Indones. J. Electr. Eng. Comput. Sci."],"note":["cited By 0 \n\nTL;DR \n\nA comparative assessment of controllers for the magnetic levitation system using proportional integral derivative (PID) controller based optimal tuning using a Simscape model has been developed and it was found that the model has produced about similar performance as what has been obtained from the MATLAB simulation."],"number":["3"],"pages":["1356–1366"],"publisher":["Institute of Advanced Engineering and Science"],"source":["Scopus"],"title":["An optimal proportional integral derivative tuning for a magnetic levitation system using metamodeling approach"],"volume":["25"]},"creators":{"author":[{"lastName":"Abdalhadi","firstName":"A."},{"lastName":"Wahid","firstName":"H."},{"lastName":"Burhanuddin","firstName":"D.H."}]},"sentenceCased":true},{"key":"abdalkareemCodeReuseStackOverflow2017","type":"article","fields":{"abstract":["Context: Source code reuse has been widely accepted as a fundamental activity in software development. Recent studies showed that StackOverflow has emerged as one of the most popular resources for code reuse. Therefore, a plethora of work proposed ways to optimally ask questions, search for answers and find relevant code on StackOverflow. However, little work studies the impact of code reuse from StackOverflow. Objective: To better understand the impact of code reuse from StackOverflow, we perform an exploratory study focusing on code reuse from StackOverflow in the context of mobile apps. Specifically, we investigate how much, why, when, and who reuses code. Moreover, to understand the potential implications of code reuse, we examine the percentage of bugs in files that reuse StackOverflow code. Method: We perform our study on 22 open source Android apps. For each project, we mine their source code and use clone detection techniques to identify code that is reused from StackOverflow. We then apply different quantitative and qualitative methods to answer our research questions. Results: Our findings indicate that 1) the amount of reused StackOverflow code varies for different mobile apps, 2) feature additions and enhancements in apps are the main reasons for code reuse from StackOverflow, 3) mid-age and older apps reuse StackOverflow code mostly later on in their project lifetime and 4) that in smaller teams/apps, more experienced developers reuse code, whereas in larger teams/apps, the less experienced developers reuse code the most. Additionally, we found that the percentage of bugs is higher in files after reusing code from StackOverflow. Conclusion: Our results provide insights on the potential impact of code reuse from StackOverflow on mobile apps. Furthermore, these results can benefit the research community in developing new techniques and tools to facilitate and improve code reuse from StackOverflow."],"author":["Abdalkareem, Rabe","Shihab, Emad","Rilling, Juergen"],"date":["2017"],"issn":["0950-5849"],"journaltitle":["Inf. Softw. Technol."],"keywords":["Code reuse","Mobile app","StackOverflow"],"nodoi":["https://doi.org/10.1016/j.infsof.2017.04.005"],"pages":["148–158"],"title":["On code reuse from StackOverflow: An exploratory study on Android apps"],"url":["http://www.sciencedirect.com/science/article/pii/S0950584917303610"],"volume":["88"]},"creators":{"author":[{"lastName":"Abdalkareem","firstName":"Rabe"},{"lastName":"Shihab","firstName":"Emad"},{"lastName":"Rilling","firstName":"Juergen"}]},"sentenceCased":true},{"key":"abdeen2014multi","type":"inproceedings","fields":{"langid":["english"],"author":["Abdeen, Hani","Varró, Dániel","Sahraoui, Houari","Nagy, András Szabolcs","Debreceni, Csaba","Hegedüs, Ábel","Horváth, Ákos"],"booktitle":["Proc. 29th ACMIEEE Int. Conf. Autom. Softw. Eng."],"date":["2014"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper proposes to integrate multi-objective optimization techniques by using Non-dominated Sorting Genetic Algorithms (NSGA) to drive rule-based design space exploration using Eclipse framework, preserving both domain independence and a high-level of abstraction."],"pages":["289–300"],"title":["Multi-objective optimization in rule-based design space exploration"]},"creators":{"author":[{"lastName":"Abdeen","firstName":"Hani"},{"lastName":"Varró","firstName":"Dániel"},{"lastName":"Sahraoui","firstName":"Houari"},{"lastName":"Nagy","firstName":"András Szabolcs"},{"lastName":"Debreceni","firstName":"Csaba"},{"lastName":"Hegedüs","firstName":"Ábel"},{"lastName":"Horváth","firstName":"Ákos"}]},"sentenceCased":true},{"key":"abdelbakyComputingContinuumCombining2017","type":"inproceedings","fields":{"author":["AbdelBaky, Moustafa","Zou, Mengsong","Zamani, Ali Reza","Renart, Eduard","Diaz-Montes, Javier","Parashar, Manish"],"booktitle":["2017 IEEE 37th Int. Conf. Distrib. Comput. Syst. ICDCS"],"date":["2017-06"],"doi":["10.1109/ICDCS.2017.323"],"eventtitle":["2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)"],"isbn":["978-1-5386-1792-2"],"keywords":["LOGSEQ"],"location":["Atlanta, GA, USA"],"note":["TL;DR \n\nThis paper presents the vision for enabling an approach for computing in the continuum, i.e., realizing a fluid ecosystem where distributed resources and services are programmatically aggregated on-demand to support emerging data-driven application workflows."],"pages":["1815–1824"],"publisher":["IEEE"],"shorttitle":["Computing in the Continuum"],"title":["Computing in the Continuum: Combining Pervasive Devices and Services to Support Data-Driven Applications"]},"creators":{"author":[{"lastName":"AbdelBaky","firstName":"Moustafa"},{"lastName":"Zou","firstName":"Mengsong"},{"lastName":"Zamani","firstName":"Ali Reza"},{"lastName":"Renart","firstName":"Eduard"},{"lastName":"Diaz-Montes","firstName":"Javier"},{"lastName":"Parashar","firstName":"Manish"}]}},{"key":"abdelhediLogicalUnifiedModeling2017","type":"inproceedings","fields":{"langid":["english"],"abstract":["Big Data, NoSQL, UML Conceptual Model, MDA, QVT."],"author":["Abdelhedi, Fatma","Brahim, Amal Ait","Atigui, Faten","Zurfluh, Gilles"],"date":["2017"],"doi":["10.5220/0006311702490256"],"isbn":["978-989-758-247-9 978-989-758-248-6 978-989-758-249-3"],"note":["TL;DR \n\nThis paper proposes a generic logical model that is compatible with the three types of NoSQL systems (column, document and graph) and proposes transformation rules formalized with QVT to generate NoSQL physical models."],"pages":["249–256"],"publisher":["SCITEPRESS - Science and Technology Publications"],"shorttitle":["Logical Unified Modeling for NoSQL Databases"],"title":["Logical Unified Modeling for NoSQL Databases:"]},"creators":{"author":[{"lastName":"Abdelhedi","firstName":"Fatma"},{"lastName":"Brahim","firstName":"Amal Ait"},{"lastName":"Atigui","firstName":"Faten"},{"lastName":"Zurfluh","firstName":"Gilles"}]}},{"key":"abeywickramaSimSOTAEngineeringSimulating2013","type":"inproceedings","fields":{"author":["Abeywickrama, Dhaminda B.","Hoch, Nicklas","Zambonelli, Franco"],"booktitle":["Proc. Int. C Conf. Comput. Sci. Softw. Eng."],"date":["2013"],"pages":["67–76"],"publisher":["ACM"],"shorttitle":["SimSOTA"],"title":["SimSOTA: Engineering and simulating feedback loops for self-adaptive systems"],"url":["http://dl.acm.org/citation.cfm?id=2494446"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Abeywickrama","firstName":"Dhaminda B."},{"lastName":"Hoch","firstName":"Nicklas"},{"lastName":"Zambonelli","firstName":"Franco"}]},"sentenceCased":true},{"key":"abid_facer_2021","type":"article","fields":{"langid":["english"],"abstract":["To save time, developers often search for code examples that implement their desired software features. Existing code search techniques typically focus on finding code snippets for a single given query, which means that developers need to perform a separate search for each desired functionality. In this paper, we propose FACER (Feature-driven API usagebased Code Examples Recommender), a technique that avoids repeated searches through opportunistic reuse. Specifically, given the selected code snippet that matches the initial search query, FACER finds and suggests related code snippets that represent features that the developer may want to implement next. FACER first constructs a code fact repository by parsing the source code of open-source Java projects to obtain methods’ textual information, call graphs, and Application Programming Interface (API) usages. It then detects unique features by clustering methods based on similar API usages, where each cluster represents a feature or functionality. Finally, it detects frequently co-occurring features across projects using frequent pattern mining and recommends related methods from the mined patterns. To evaluate FACER, we run it on 120 Java Android apps from GitHub. We first manually validate that the detected method clusters represent methods with similar functionality. We then perform an automated evaluation to determine the best parameters (e.g., similarity threshold) for FACER. We recruit 10 professional developers along with 39 experienced students to judge FACER’s recommendation of related methods. Our results show that, on average, FACER’s recommendations are 80% precise. We also survey a total of 20 professional Android and Java developers to understand their code search and reuse experiences, and also to obtain their feedback on the usability and usefulness of FACER. The survey results show that 95% of our surveyed professional developers find the idea of related method recommendations useful during code reuse."],"author":["Abid, Shamsa","Shamail, Shafay","Basit, Hamid Abdul","Nadi, Sarah"],"date":["2021-11"],"doi":["10.1007/s10664-021-10000-w"],"issn":["1382-3256, 1573-7616"],"journaltitle":["Empir. Softw. Eng."],"note":["TL;DR \n\nFACER finds and suggests related code snippets that represent features that the developer may want to implement next and recommends related methods from the mined patterns, a technique that avoids repeated searches through opportunistic reuse."],"number":["6"],"pages":["110"],"shorttitle":["FACER"],"title":["FACER: An API usage-based code-example recommender for opportunistic reuse"],"volume":["26"]},"creators":{"author":[{"lastName":"Abid","firstName":"Shamsa"},{"lastName":"Shamail","firstName":"Shafay"},{"lastName":"Basit","firstName":"Hamid Abdul"},{"lastName":"Nadi","firstName":"Sarah"}]},"sentenceCased":true},{"key":"Abid2019355","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Int. Conf. Softw. Eng. Knowl. Eng., SEKE"],"affiliation":["Model-based Systems Engineering (MbSE) fortiss GmbH, Munich, Germany; Technical University of Munich, Munich, Germany"],"author":["Abid, S.B.","Mahajan, V.","Lucio, L."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.18293/SEKE2019-050"],"isbn":["1-891706-48-9"],"issn":["23259000"],"keywords":["GOAL_Model-Repair","notion","TECHNIQUE_DNN","TECHNIQUE_GENETIC_ALGORITHMS","TECHNIQUE_ILP","TECHNIQUE_MARKOV_DECISION_PROCESS","TECHNIQUE_NN"],"note":["cited By 2 \n\nTL;DR \n\nA machine learning-based recommendation system named M AGNET is described for aiding beginner and intermediate users of AF3 in learning the tool."],"pages":["355–360"],"publisher":["Knowledge Systems Institute Graduate School"],"series":["Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE"],"source":["Scopus"],"title":["Towards machine learning for learnability of MDD tools"],"volume":["2019-July"]},"creators":{"author":[{"lastName":"Abid","firstName":"S.B."},{"lastName":"Mahajan","firstName":"V."},{"lastName":"Lucio","firstName":"L."}]},"sentenceCased":true},{"key":"abrahaoFocusingDevelopersEra2023","type":"article","fields":{"langid":["english"],"author":["Abrahão, Silvia","Staron, Miroslaw","Serebrenik, Alexander","Penzenstadler, Birgit","Prikladnicki, Rafael","Muccini, Henry"],"date":["2023-11"],"doi":["10.1109/MS.2023.3302884"],"ids":["abrahaoFocusingDevelopersEra2023a"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"number":["6"],"pages":["126–129"],"title":["Focusing on Developers in the Era of AI and ML"],"volume":["40"]},"creators":{"author":[{"lastName":"Abrahão","firstName":"Silvia"},{"lastName":"Staron","firstName":"Miroslaw"},{"lastName":"Serebrenik","firstName":"Alexander"},{"lastName":"Penzenstadler","firstName":"Birgit"},{"lastName":"Prikladnicki","firstName":"Rafael"},{"lastName":"Muccini","firstName":"Henry"}]}},{"key":"abrahaoModelDrivenEngineeringLanguages2014","type":"book","fields":{"abstract":["This book constitutes the refereed proceedings of the 17th International Conference on Model Driven Engineering Languages and Systems, MODELS 2014, held in Valencia, Spain, in September/October 2014. The 41 full papers presented in this volume were carefully reviewed and selected from a total of 126 submissions. The scope of the conference series is broad, encompassing modeling languages, methods, tools, and applications considered from theoretical and practical angles and in academic and industrial settings. The papers report on the use of modeling in a wide range of cloud, mobile, and web computing, model transformation behavioral modeling, MDE: past, present, future, formal semantics, specification, and verification, models at runtime, feature and variability modeling, composition and adaptation, practices and experience, modeling for analysis, pragmatics, model extraction, manipulation and persistence, querying, and reasoning"],"date":["2014"],"doi":["10.1007/978-3-319-11653-2"],"edition":["1st ed. 2014"],"editor":["Abrahao, Silvia","Dingel, Juergen","Insfran, Emilio","Ramos, Isidro","Schulte, Wolfram"],"isbn":["978-3-319-11653-2"],"keywords":["Programming Languages, Compilers, Interpreters","Computer logic","Computer science","Computer simulation","Computer system failures","Logics and Meanings of Programs","Management information systems","Management of Computing and Information Systems","Programming languages (Electronic computers)","Simulation and Modeling","Software engineering","Software Engineering","System Performance and Evaluation"],"location":["Cham"],"note":["Cloud, Mobile and Web Computing – Model-Driven Development of Mobile Applications Allowing Role-Driven Variants – A Model-Based System to Automate Cloud Resource Allocation and Optimization – An Evaluation of the Effectiveness of the Atomic Section Model – Model Transformation 1 – Parsing in a Broad Sense – Streaming Model Transformations by Complex Event Processing – On the Use of Signatures for Source Incremental Model-to-text Transformation – Behavioral Modeling – Modeling Systemic Behavior by State-Based Holonic Modular Units – Semantic Model Differencing Utilizing Behavioral Semantics Specifications – Formalizing Execution Semantics of UML Profiles with fUML Models – MDE: Past, Present and Future.-Who Knows/Uses What of the UML: A Personal Opinion Survey – Assessing the State-of-Practice of Model-Based Engineering in the Embedded Systems Domain – The Relevance of Model-Driven Engineering Thirty Years from Now – Formal Semantics, Specification and Verification – Verifying Compilation of Synchronous Distributed Applications – Environment-Centric Contracts for Design of Cyber-Physical Systems – Removing Redundancies and Deducing Equivalences in UML Class Diagrams – Models at Runtime – A Native Versioning Concept to Support Historized Models at Runtime – Modelling Adaptation Policies as Domain-Specific Constraints – Scalable Armies of Model Clones through Data Sharing – Feature and Variability Modeling – Three Cases of Feature-Based Variability Modeling in Industry – Supporting Multiplicity and Hierarchy in Model-Based Configuration: Experiences and Lessons Learned – Propagating Decisions to Detect and Explain Conflicts in a Multi-step Configuration Process – Composition and Adaptation – An MDA Approach for the Generation of Communication Adapters Integrating SW and FW Components from Simulink – A UML Model-Driven Approach to Efficiently Allocate Complex Communication Schemes – Model-Integrating Software Components – Practices and Experience – Experiences in Applying Model Driven Engineering to the Telescope and Instrument Control System Domain – Model Driven Grant Proposal Engineering – Agile Model-Driven Engineering in Mechatronic Systems - An Industrial Case Study – Modeling for Analysis – Using UML for Modeling Procedural Legal Rules: Approach and a Study of Luxembourg's Tax Law – Resolution of Interfering Product Fragments in Software Product Line Engineering – Ontology-Based Modeling of Context-Aware Systems – Pragmatics – Comprehending Feature Models Expressed in CVL – On the Impact of Layout Quality to Understanding UML Diagrams: Size Matters – Enabling the Development of Cognitive Effective Visual DSLs – Model Extraction, Manipulation and Persistence – JUMP-From Java Annotations to UML Profiles – SIGMA: Scala Internal Domain-Specific Languages for Model Manipulations – A Framework to Benchmark NoSQL Data Stores for Large-Scale Model Persistence – Model Transformation 2 – Automated Chaining of Model Transformations with Incompatible Metamodels – Classification of Model Transformation Tools: Pattern Matching Techniques – Learning Implicit and Explicit Control in Model Transformations by Example – Querying and Reasoning IncQuery-D: A Distributed Incremental Model Query Framework in the Cloud – Translating OCL to Graph Patterns"],"number":["8767"],"pagetotal":["1"],"publisher":["Springer International Publishing : Imprint: Springer"],"series":["Programming and Software Engineering"],"shorttitle":["Model-Driven Engineering Languages and Systems"],"title":["Model-Driven Engineering Languages and Systems: 17th International Conference, MODELS 2014, Valencia, Spain, September 283- October 4, 2014. Proceedings"]},"creators":{"editor":[{"lastName":"Abrahao","firstName":"Silvia"},{"lastName":"Dingel","firstName":"Juergen"},{"lastName":"Insfran","firstName":"Emilio"},{"lastName":"Ramos","firstName":"Isidro"},{"lastName":"Schulte","firstName":"Wolfram"}]}},{"key":"abu-elkheirDataManagementInternet2013","type":"article","fields":{"langid":["english"],"author":["Abu-Elkheir, Mervat","Hayajneh, Mohammad","Ali, Najah"],"date":["2013-11-14"],"doi":["10.3390/s131115582"],"issn":["1424-8220"],"journaltitle":["Sensors"],"keywords":["Data analysis","internet of things"],"note":["TL;DR \n\nThis paper surveys the data management solutions proposed for IoT, and proposes a data management framework for IoT that takes into consideration the discussed design elements and acts as a seed to a comprehensive IoT data management solution."],"number":["11"],"pages":["15582–15612"],"shorttitle":["Data Management for the Internet of Things"],"title":["Data Management for the Internet of Things: Design Primitives and Solution"],"volume":["13"]},"creators":{"author":[{"lastName":"Abu-Elkheir","firstName":"Mervat"},{"lastName":"Hayajneh","firstName":"Mohammad"},{"lastName":"Ali","firstName":"Najah"}]}},{"key":"ACMInternationalConference2010","type":"book","fields":{"date":["2010"],"journaltitle":["ACM International Conference Proceeding Series"],"title":["ACM International Conference Proceeding Series: Foreword"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921919454&partnerID=40&md5=03f4a0df3c070c47a6f17cca8571698b"]},"creators":{}},{"key":"acmsigchisymposiumonengineeringinteractivecomputingsystemsEICS13Proceedings2013","type":"book","fields":{"langid":["english"],"author":["ACM SIGCHI Symposium on Engineering Interactive Computing Systems","Forbrig, Peter","Dewan, Prasun","SIGCHI (Group : U.S.)","City University (London, England)","Springer (Firm)","IFIP Working Group 2.7/13.4","Association for Computing Machinery","ACM Digital Library"],"date":["2013"],"shorttitle":["EICS '13"],"title":["EICS '13: Proceedings of the ACM SIGCHI Symposium on Engineering Interactive Computing Systems : June 24-27, 2013, London, United Kingdom"],"url":["http://dl.acm.org/citation.cfm?id=2494603"],"urldate":["2016-09-24"]},"creators":{"author":[{"literal":"ACM SIGCHI Symposium on Engineering Interactive Computing Systems"},{"lastName":"Forbrig","firstName":"Peter"},{"lastName":"Dewan","firstName":"Prasun"},{"literal":"SIGCHI (Group : U.S.)"},{"lastName":"City University (London","firstName":"England)"},{"literal":"Springer (Firm)"},{"literal":"IFIP Working Group 2.7/13.4"},{"literal":"Association for Computing Machinery"},{"literal":"ACM Digital Library"}]}},{"key":"ACMStudentResearch2017","type":"book","fields":{"date":["2017"],"ids":["ACMStudentResearch2017a"],"journaltitle":["CEUR Workshop Proceedings"],"pages":["547–548"],"pagetotal":["547–548"],"publisher":["CEUR-WS"],"title":["ACM student research competition at MoDELS 2017"],"volume":["2019"]},"creators":{},"sentenceCased":true},{"key":"acretoaieHypersonicModelAnalysis2014","type":"article","fields":{"author":["Acretoaie, Vlad","Störrle, Harald"],"date":["2014"],"note":["TL;DR \n\nThis paper investigates the conceptual and technical feasibility of a new software architecture for modeling tools, where certain advanced features are factored out of the client and moved towards the Cloud, by applying standards such as REST and JSON in combination with Prolog as an implementation language."],"title":["Hypersonic: Model Analysis and Checking in the Cloud"]},"creators":{"author":[{"lastName":"Acretoaie","firstName":"Vlad"},{"lastName":"Störrle","firstName":"Harald"}]}},{"key":"Adamopoulos_TIST","type":"article","fields":{"acmid":["2559952"],"address":["New York, NY, USA"],"articleno":["54"],"author":["Adamopoulos, Panagiotis","Tuzhilin, Alexander"],"date":["2014-12"],"issn":["2157-6904"],"issue_date":["January 2015"],"journaltitle":["ACM Trans. Intell. Syst. Technol."],"keywords":["Diversity","evaluation","novelty","recommendation systems","recommender systems","serendipity","unexpectedness","utility theory"],"nodoi":["10.1145/2559952"],"number":["4"],"numpages":["32"],"pages":["54:1-54:32"],"publisher":["ACM"],"title":["On unexpectedness in recommender systems: Or how to better expect the unexpected"],"url":["http://doi.acm.org/10.1145/2559952"],"volume":["5"]},"creators":{"author":[{"lastName":"Adamopoulos","firstName":"Panagiotis"},{"lastName":"Tuzhilin","firstName":"Alexander"}]},"sentenceCased":true},{"key":"addaziSemanticbasedModelMatching2016","type":"article","fields":{"author":["Addazi, L.","Cicchetti, A.","Di Rocco, J.","Di Ruscio, D.","Iovino, L.","Pierantonio, A."],"date":["2016"],"ids":["addaziSemanticbasedModelMatching2016a"],"journaltitle":["Proc. 10th Workshop Models Evol. Co-Located ACMIEEE 19th Int. Conf. Model Driven Eng. Lang. Syst. MODELS 2016 St.-Malo Fr. Oct. 2 2016"],"note":["cited By 12 \n\ncited By 12"],"pages":["40–49"],"series":["CEUR Workshop Proceedings"],"title":["Semantic-based model matching with EMFcompare"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84996671087&partnerID=40&md5=9fbb2fc418eca02b33584050869f35d5"],"volume":["1706"]},"creators":{"author":[{"lastName":"Addazi","firstName":"L."},{"lastName":"Cicchetti","firstName":"A."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Iovino","firstName":"L."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"AddonItem","type":"software","fields":{"note":["9VTMURYV{\"readingTime\":{\"page\":9,\"data\":{\"3\":10}}} \n\nBCYRLKCX{\"readingTime\":{\"page\":32,\"data\":{\"0\":290,\"1\":80,\"30\":80}}} \n\nC6XDG4BZ{\"readingTime\":{\"page\":23,\"data\":{\"0\":90,\"1\":60,\"2\":10,\"4\":10,\"7\":10,\"8\":160}}} \n\nGGSQ77ZG{\"readingTime\":{\"page\":5,\"data\":{\"0\":50}}} \n\nNR6H34GJ{\"readingTime\":{\"page\":3,\"data\":{\"0\":30}}} \n\nRUKHUVV6{\"readingTime\":{\"page\":58,\"data\":{\"1\":160,\"11\":10,\"25\":10,\"39\":10,\"44\":10,\"45\":20,\"46\":20,\"51\":30,\"52\":10}}} \n\nUGUFVGGU{\"readingTime\":{\"page\":85,\"data\":{\"0\":10}}} \n\nWLPPNLMM{\"readingTime\":{\"page\":15,\"data\":{\"0\":10}}}"],"title":["Addon Item"]},"creators":{}},{"key":"AddressingOrganizationalTechnical","type":"misc","fields":{"note":["<h1>Annotazioni\n (12/3/2024, 21:51:28)</h1> \n\n- “Low-Code Adoption for Advancing Digitalization” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 11) #5fb236\n i \n\n- “Construction Industr” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 11) #5fb236\n i \n\n- “optimization of processes” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 11) #5fb236\n i \n\n- “digitalization in a variety of industrial scenarios” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 11) #5fb236\n i \n\n- “there is a lack of scholarly research analysing how the low-code technology paradigm can support digitalization in the construction sector” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 11) #5fb236\n i \n\n- “The objective of this research project is therefore to address the critical organizational and technical barriers to fill current research gaps and derive practical insights to advance low-code technology in construction organizations.” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 11) #a28ae5\n i \n\n- “RQ1) What are the organizational pre-requisites to ensure low-code scalability in the context of a construction enterprise?” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 11) #a28ae5\n i \n\n- “RQ2) How low-code technology can be integrated with Building Information Modelling (BIM)?” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 11) #ffd400\n <i>Why is BIM of interest here? </i> \n\n- “this research will contribute to the body of knowledge in a relatively new field of research by structurally addressing prevailing knowledge gaps and delineating areas for further research” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 11) #5fb236\n i \n\n- “By optimizing resource utilization and streamlining processes, digitalization in the construction industry becomes fundamental to improve overall productivity and support the delivery of a sustainable built environment” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 11) #5fb236\n i \n\n- “inadequate understanding of operations” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 11) #5fb236\n i \n\n- “ow-code technology emerges as a new Information Technology (IT) paradigm having the potential to bridge the gap between technology development and operations.” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 12) #5fb236\n i \n\n- “supporting rapid development of customer-facing applications, requiring minimal hand-coding and enabling productive new development practices” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 12) #5fb236\n i \n\n- “This “democratization” in technology development allows increased participation of subject/domain experts in technology development, facilitating the development process, and ensuring that the final solution meets the requirements of people and their processes” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 12) #5fb236\n i \n\n- “5 to 10 times faster than traditional programming” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 12) #5fb236\n i \n\n- “technical limitations such restricted customization options” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 12) #5fb236\n i \n\n- “Low-code research in industrial setups highlight the need for further research in low-code integration with Industry 4.0, Internet of Things, and Digital Twin” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 12) #5fb236\n i \n\n- “organizational and strategical aspects surrounding the introduction of low-code in corporate environments” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 12) #5fb236\n i \n\n- “organizations need standard processes to channel best practices and guidelines to improve consistency, compliance, and governance throughout the enterprise” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 12) #5fb236\n i \n\n- “70% of business applications will be developed using some sort of low-code technology [27] with the number of “citizen developers” largely surpassing the number of professional developers” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 12) #a28ae5\n i \n\n- “by enabling people closer to construction operations to independently develop digita l solutions, low-code could facilitate the digitalization of a variety of construction processes which are currently run using pen and paper” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 13) #5fb236\n i \n\n- “here is a critical contextual gap and a lack of scholarly research analysing how the low-code technology paradigm can support digitalization in the construction sector” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 13) #ffd400\n <i>What are the challenges in the construction sector? What are the issues that are critical and that require the introduction of low-code technologies? </i> \n\n- “through 3 scholarly articles” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 13) #a28ae5\n i \n\n- “This includes the results of a survey to the construction professionals involved in the case studies to understand to what extent low-code benefits and limitations identified in previous literature resonate to them.” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 13) #5fb236\n i \n\n- “This potential derives from the pivotal role of low-code in bridging the gap between development and operations, empowering individuals with expertise in construction processes and operations to actively engage in the development process” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 13) #5fb236\n i \n\n- “applicant's research results allowed the identification of critical limitations and research gaps essential for a broader understanding of low-code in the construction industry” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 14) #ffd400\n <i>What are such critical limitations? The construction domain is a critical one requiring deep expertise. How can you put \"citizen developer\" in a such a critical domain? This is not clear! </i> \n\n- “Area 1: Organizational/strategical - RQ 1: What are the organizational pre-requisites to ensure low-code scalability in the context of a construction enterprise?” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 14) #5fb236\n i \n\n- “Consequently, understanding the essential competencies of a \"citizen developer\" within the construction industry context becomes critical to expedite low-code” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 14) #ffd400\n <i>What does it mean? </i> \n\n- “low-code, particularly in project-based industries like construction” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 14) #ffd400\n <i>What's the practical implication for this? </i> \n\n- “there is no studies addressing these research gaps in the construction industry” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 14) #ffd400\n i \n\n- “RQ 2: How low -code technology can be integrated with Building Information Modelling (BIM)” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 14) #ffd400\n <i>Before the HOW I would have preferred to read WHY. </i> \n\n- “BIM stands out as the most relevant technology supporting technical activities and collaboration during design, construction, and maintenance of the built assets, and it is cornerstone for Construction industry 4.0” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 14) #ffd400\n i \n\n- “low-code interoperability with BIM is the critical first step to streamline BIM processes and leverage the integrated utility of these technologies on the field.” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 14) #ffd400\n <i>What does it mean? I think it is necessary an example!!!! The discussion so far has been vague. </i> \n\n- “intersection” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 15) #5fb236\n i \n\n- “construction digitalization” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 15) #5fb236\n i \n\n- “low-code” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 15) #5fb236\n i \n\n- “Nevertheless, the results of this inquiry were not conclusive, as we discovered the emerging nature of low-code technology and that the current development of research still does not provide answer to the several gaps we realized” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 15) #ffd400\n <i>What are the gaps you are referring to? </i> \n\n- “a) Introducing and pioneering the use of low-code to the construction industry” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 15) #ffd400\n <i>Already said! </i> \n\n- “Nevertheless, further research in the areas proposed in this project is critical to find alternatives to address prevailing gaps to expand scientific knowledge about how this technology can foster a holistic digital transformation in the construction sector” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 15) #ffd400\n <i>The proposal contains many sentences like this that are vague and they are not precise in presenting the problems and the issues that the applicant aims at solving with this project proposal. In other words so far the project has not presented the problem clearly. </i> \n\n- “in the context of a construction enterprise” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 15) #ffd400\n <i>Concerning this considered application domain I have the following question: - why such a domain requires the usage of low-code platforms?\n - what are the criticalities of currently available systems that instead should be replaced by low-code platforms?\n - why it makes sense and it is really doable considering \"citizen-developers\" in the building construction domain? </i> \n\n- “to understand the available knowledge about organizational and strategical considerations for low-code implementation” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 16) #ffd400\n <i>Some preliminary result of this study are required to justify and support the project proposal. </i> \n\n- “Develop a technical solution to facilitate data interoperability between low -code databases and Industry Foundation Classes (IFC) schema in BIM models (e.g., via low-code development platform connectors or Application Programming Interfaces) [45].” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 17) #ffd400\n <i>It's not clear what the project aims at producing. Is it a study? Is it a software platform / framework? Is it a set of reusable components? What is the goal of the proposed technical solution? </i> \n\n- “use cases where low-code can be integrated with BIM” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 17) #ffd400\n <i>It seems that is something completely new and the applicant has to evaluate if and how the integration of low-code platforms with BIM make sense. The kind of integration that is expected is not clear at all. </i> \n\n- “A representative use case will be selected for the development serving as a baseline to derive the requirements of the technical system.” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 17) #5fb236\n i \n\n- “Validated technical solution” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 18) #ffd400\n <i>Which technical solution? </i> \n\n- “construction sites in Chile” (“Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry”, p. 26) #5fb236\n i"],"title":["Addressing Organizational and Technical Barriers in Low-Code Adoption for Advancing Digitalization in the Construction Industry"]},"creators":{}},{"key":"Adomavicius:2008:CRS:1454008.1454068","type":"inproceedings","fields":{"acmid":["1454068"],"author":["Adomavicius, Gediminas","Tuzhilin, Alexander"],"booktitle":["Proc. 2008 ACM Conf. Recomm. Syst."],"date":["2008"],"isbn":["978-1-60558-093-7"],"keywords":["collaborative filtering","contextual information","personalization","recommender systems","tutorial"],"location":["New York, NY, USA"],"nodoi":["10.1145/1454008.1454068"],"numpages":["2"],"pages":["335–336"],"publisher":["ACM"],"series":["RecSys '08"],"title":["Context-aware recommender systems"],"url":["http://doi.acm.org/10.1145/1454008.1454068"]},"creators":{"author":[{"lastName":"Adomavicius","firstName":"Gediminas"},{"lastName":"Tuzhilin","firstName":"Alexander"}]},"sentenceCased":true},{"key":"Adomavicius:2012:aggrDiv","type":"article","fields":{"acmid":["2197127"],"address":["Piscataway, NJ, USA"],"author":["Adomavicius, Gediminas","Kwon, YoungOk"],"date":["2012-05"],"issn":["1041-4347"],"issue_date":["May 2012"],"journaltitle":["IEEE Trans Knowl Data Eng"],"keywords":["collaborative filtering.","performance evaluation metrics","ranking functions","recommendation diversity"],"nodoi":["10.1109/TKDE.2011.15"],"number":["5"],"numpages":["16"],"pages":["896–911"],"publisher":["IEEE Educational Activities Department"],"title":["Improving aggregate recommendation diversity using ranking-based techniques"],"url":["http://dx.doi.org/10.1109/TKDE.2011.15"],"volume":["24"]},"creators":{"author":[{"lastName":"Adomavicius","firstName":"Gediminas"},{"lastName":"Kwon","firstName":"YoungOk"}]},"sentenceCased":true},{"key":"adomavicius2012impact","type":"article","fields":{"author":["Adomavicius, Gediminas","Zhang, Jingjing"],"date":["2012"],"journaltitle":["ACM Trans. Manag. Inf. Syst. TMIS"],"number":["1"],"pages":["1–17"],"publisher":["ACM New York, NY, USA"],"title":["Impact of data characteristics on recommender systems performance"],"volume":["3"]},"creators":{"author":[{"lastName":"Adomavicius","firstName":"Gediminas"},{"lastName":"Zhang","firstName":"Jingjing"}]},"sentenceCased":true},{"key":"AdversarialMachineLearning","type":"article","fields":{"langid":["english"],"journaltitle":["Mach. Learn."],"keywords":["adversarial machine learning"],"pages":["26"],"title":["Adversarial Machine Learning —An Introduction"]},"creators":{}},{"key":"AgentDrivenAutomaticSoftware2024","type":"article","fields":{"langid":["english"],"date":["2024"],"title":["Agent-Driven Automatic Software Improvement"]},"creators":{}},{"key":"aggarwalNeighborhoodbasedCollaborativeFiltering2016","type":"incollection","fields":{"abstract":["Neighborhood-based collaborative filtering algorithms, also referred to as memory-based algorithms, were among the earliest algorithms developed for collaborative filtering. These algorithms are based on the fact that similar users display similar patterns of rating behavior and similar items receive similar ratings. There are two primary types of neighborhood-based algorithms:"],"author":["Aggarwal, Charu"],"booktitle":["Recommender systems: The textbook"],"date":["2016"],"doi":["10.1007/978-3-319-29659-3₂"],"isbn":["978-3-319-29659-3"],"location":["Cham"],"pages":["29–70"],"publisher":["Springer International Publishing"],"title":["Neighborhood-based collaborative filtering"]},"creators":{"author":[{"lastName":"Aggarwal","firstName":"Charu"}]},"sentenceCased":true},{"key":"AGIRRE10.534","type":"inproceedings","fields":{"langid":["english"],"author":["Agirre, Eneko","Cuadros, Montse","Rigau, German","Soroa, Aitor"],"booktitle":["Proc. Seventh Int. Conf. Lang. Resour. Eval. LREC10"],"editor":["Chair), Nicoletta Calzolari (Conference","Choukri, Khalid","Maegaard, Bente","Mariani, Joseph","Odijk, Jan","Piperidis, Stelios","Rosner, Mike","Tapias, Daniel"],"isbn":["2-9517408-6-7"],"location":["Valletta, Malta"],"publisher":["European Language Resources Association (ELRA)"],"title":["Exploring knowledge bases for similarity"],"year":["19-21, 2010-05"]},"creators":{"author":[{"lastName":"Agirre","firstName":"Eneko"},{"lastName":"Cuadros","firstName":"Montse"},{"lastName":"Rigau","firstName":"German"},{"lastName":"Soroa","firstName":"Aitor"}],"editor":[{"lastName":"Chair)","firstName":"Nicoletta Calzolari (Conference"},{"lastName":"Choukri","firstName":"Khalid"},{"lastName":"Maegaard","firstName":"Bente"},{"lastName":"Mariani","firstName":"Joseph"},{"lastName":"Odijk","firstName":"Jan"},{"lastName":"Piperidis","firstName":"Stelios"},{"lastName":"Rosner","firstName":"Mike"},{"lastName":"Tapias","firstName":"Daniel"}]},"sentenceCased":true},{"key":"agirrePersonalizingPageRankWord2009","type":"inproceedings","fields":{"acmid":["1609070"],"author":["Agirre, Eneko","Soroa, Aitor"],"booktitle":["Proc. 12th Conf. Eur. Chapter Assoc. Comput. Linguist."],"date":["2009"],"location":["Stroudsburg, PA, USA"],"note":["TL;DR \n\nThis paper proposes a new graph-based method that uses the knowledge in a LKB (based on WordNet) in order to perform unsupervised Word Sense Disambiguation, performing better than previous approaches in English all-words datasets."],"numpages":["9"],"pages":["33–41"],"publisher":["Association for Computational Linguistics"],"series":["EACL '09"],"title":["Personalizing PageRank for word sense disambiguation"],"url":["http://dl.acm.org/citation.cfm?id=1609067.1609070"]},"creators":{"author":[{"lastName":"Agirre","firstName":"Eneko"},{"lastName":"Soroa","firstName":"Aitor"}]},"sentenceCased":true},{"key":"agt-rickauerSupportingDomainModeling","type":"article","fields":{"langid":["ngerman"],"author":["Agt-Rickauer, Henning"],"pages":["196"],"title":["Supporting Domain Modeling with Automated Knowledge Acquisition and Modeling Recommendations"]},"creators":{"author":[{"lastName":"Agt-Rickauer","firstName":"Henning"}]}},{"key":"Aha:1991:ILA:104713.104717","type":"article","fields":{"acmid":["104717"],"address":["Hingham, MA, USA"],"author":["Aha, David W.","Kibler, Dennis","Albert, Marc K."],"date":["1991-01"],"issn":["0885-6125"],"issue_date":["Jan. 1991"],"journaltitle":["Mach. Learn."],"keywords":["incremental learning","instance-based concept descriptions","learning theory","noise","similarity","Supervised concept learning"],"nodoi":["10.1023/A:1022689900470"],"note":["TL;DR \n\nThis paper describes how storage requirements can be significantly reduced with, at most, minor sacrifices in learning rate and classification accuracy and extends the nearest neighbor algorithm, which has large storage requirements."],"number":["1"],"numpages":["30"],"pages":["37–66"],"publisher":["Kluwer Academic Publishers"],"title":["Instance-based learning algorithms"],"url":["https://doi.org/10.1023/A:1022689900470"],"volume":["6"]},"creators":{"author":[{"lastName":"Aha","firstName":"David W."},{"lastName":"Kibler","firstName":"Dennis"},{"lastName":"Albert","firstName":"Marc K."}]},"sentenceCased":true},{"key":"ahmad2023humanbot","type":"misc","fields":{"author":["Ahmad, Aakash","Waseem, Muhammad","Liang, Peng","Fehmideh, Mahdi","Aktar, Mst Shamima","Mikkonen, Tommi"],"date":["2023"],"eprint":["2302.14600"],"eprintclass":["cs.SE"],"eprinttype":["arxiv"],"journaltitle":["Proceedings of the 27th international conference on evaluation and assessment in software engineering (EASE)"],"note":["TL;DR \n\nA case study that involves collaboration between a novice software architect and ChatGPT to architect a service-based software and explores socio-technical aspects of architecting with ChatG PT to tackle challenges of ACSE is detail."],"title":["Towards human-bot collaborative software architecting with ChatGPT"]},"creators":{"author":[{"lastName":"Ahmad","firstName":"Aakash"},{"lastName":"Waseem","firstName":"Muhammad"},{"lastName":"Liang","firstName":"Peng"},{"lastName":"Fehmideh","firstName":"Mahdi"},{"lastName":"Aktar","firstName":"Mst Shamima"},{"lastName":"Mikkonen","firstName":"Tommi"}]},"sentenceCased":true},{"key":"ahmadUnifiedPretrainingProgram2021","type":"online","fields":{"abstract":["Code summarization and generation empower conversion between programming language (PL) and natural language (NL), while code translation avails the migration of legacy code from one PL to another. This paper introduces PLBART, a sequence-to-sequence model capable of performing a broad spectrum of program and language understanding and generation tasks. PLBART is pre-trained on an extensive collection of Java and Python functions and associated NL text via denoising autoencoding. Experiments on code summarization in the English language, code generation, and code translation in seven programming languages show that PLBART outperforms or rivals state-of-the-art models. Moreover, experiments on discriminative tasks, e.g., program repair, clone detection, and vulnerable code detection, demonstrate PLBART's effectiveness in program understanding. Furthermore, analysis reveals that PLBART learns program syntax, style (e.g., identifier naming convention), logical flow (e.g., if block inside an else block is equivalent to else if block) that are crucial to program semantics and thus excels even with limited annotations."],"author":["Ahmad, Wasi Uddin","Chakraborty, Saikat","Ray, Baishakhi","Chang, Kai-Wei"],"date":["2021-04-10"],"eprint":["2103.06333"],"eprintclass":["cs"],"eprinttype":["arxiv"],"ids":["Ahmad_Chakraborty_Ray_Chang_2021"],"issue":["arXiv:2103.06333"],"keywords":["Computer Science - Computation and Language","Computer Science - Programming Languages"],"note":["arXiv:2103.06333 [cs] \n\nComment: NAACL 2021 (camera ready) \n\nTL;DR \n\nAnalysis reveals that PLBART learns program syntax, style, logical flow, and style that are crucial to program semantics and thus excels even with limited annotations, and outperforms or rivals state-of-the-art models."],"pubstate":["preprint"],"title":["Unified Pre-training for Program Understanding and Generation"],"url":["http://arxiv.org/abs/2103.06333"],"urldate":["2023-05-04"]},"creators":{"author":[{"lastName":"Ahmad","firstName":"Wasi Uddin"},{"lastName":"Chakraborty","firstName":"Saikat"},{"lastName":"Ray","firstName":"Baishakhi"},{"lastName":"Chang","firstName":"Kai-Wei"}]}},{"key":"AkbarPrePrint","type":"unknown","fields":{"author":["Azeem Akbar, Muhammad","Khan, Arif"],"date":["2023-03"],"title":["Ethical aspects of ChatGPT in software engineering research"]},"creators":{"author":[{"lastName":"Azeem Akbar","firstName":"Muhammad"},{"lastName":"Khan","firstName":"Arif"}]},"sentenceCased":true},{"key":"Al-Azzoni202087","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Int. Conf. Intell. Data Sci. Technol. Appl., IDSTA"],"affiliation":["College of Engineering, Al Ain University, Al Ain, United Arab Emirates"],"art_number":["9264067"],"author":["Al-Azzoni, I."],"correspondence_address1":["Al-Azzoni, I.; College of Engineering, United Arab Emirates; email: issam.alazzoni@aau.ac.ae"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/IDSTA50958.2020.9264067"],"editor":["Alsmirat M., Jararweh Y., Aloqaily M., Lloret Mauri J."],"isbn":["978-1-72818-376-3"],"note":["cited By 0 \n\nTL;DR \n\nNew meta-models for addressing machine learning problems using artificial neural networks can capture the main elements of learning problems and neural networks, and help users to develop solutions with less dependence on a particular set of tools and technologies."],"pages":["87–94"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["2020 International Conference on Intelligent Data Science Technologies and Applications, IDSTA 2020"],"source":["Scopus"],"title":["Model driven approach for neural networks"]},"creators":{"author":[{"lastName":"Al-Azzoni","firstName":"I."}],"editor":[{"lastName":"Alsmirat M.","suffix":"Jararweh Y.","firstName":"Aloqaily M., Lloret Mauri J."}]},"sentenceCased":true},{"key":"al-garadiSurveyMachineDeep2018","type":"article","fields":{"abstract":["The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. It is one of the fastest developing fields in the history of computing, with an estimated 50 billion devices by the end of 2020. On the one hand, IoT play a crucial role in enhancing several real-life smart applications that can improve life quality. On the other hand, the crosscutting nature of IoT systems and the multidisciplinary components involved in the deployment of such systems introduced new security challenges. Implementing security measures, such as encryption, authentication, access control, network security and application security, for IoT devices and their inherent vulnerabilities is ineffective. Therefore, existing security methods should be enhanced to secure the IoT system effectively. Machine learning and deep learning (ML/DL) have advanced considerably over the last few years, and machine intelligence has transitioned from laboratory curiosity to practical machinery in several important applications. Consequently, ML/DL methods are important in transforming the security of IoT systems from merely facilitating secure communication between devices to security-based intelligence systems. The goal of this work is to provide a comprehensive survey of ML /DL methods that can be used to develop enhanced security methods for IoT systems. IoT security threats that are related to inherent or newly introduced threats are presented, and various potential IoT system attack surfaces and the possible threats related to each surface are discussed. We then thoroughly review ML/DL methods for IoT security and present the opportunities, advantages and shortcomings of each method. We discuss the opportunities and challenges involved in applying ML/DL to IoT security. These opportunities and challenges can serve as potential future research directions."],"author":["Al-Garadi, Mohammed Ali","Mohamed, Amr","Al-Ali, Abdulla","Du, Xiaojiang","Guizani, Mohsen"],"date":["2018-07-29"],"eprint":["1807.11023"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv180711023 Cs"],"note":["TL;DR \n\nA comprehensive survey of ML methods and recent advances in DL methods that can be used to develop enhanced security methods for IoT systems and presents the opportunities, advantages and shortcomings of each method."],"title":["A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security"],"url":["http://arxiv.org/abs/1807.11023"],"urldate":["2021-01-10"]},"creators":{"author":[{"lastName":"Al-Garadi","firstName":"Mohammed Ali"},{"lastName":"Mohamed","firstName":"Amr"},{"lastName":"Al-Ali","firstName":"Abdulla"},{"lastName":"Du","firstName":"Xiaojiang"},{"lastName":"Guizani","firstName":"Mohsen"}]}},{"key":"Al-Janan2017686","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Int. J. Autom. Comput."],"affiliation":["Institute of Engineering Science and Technology, National Kaohsiung First University of Science and Technology, Taiwan; Mechanical Engineering Departement, Engineeering Faculty, Semarang State University, Semarang, Center of Java, Indonesia"],"author":["Al-Janan, D.H.","Chang, H.-C.","Chen, Y.-P.","Liu, T.-K."],"correspondence_address1":["Liu, T.-K.; Institute of Engineering Science and Technology, Taiwan; email: tkliu@nkfust.edu.tw"],"date":["2017"],"document_type":["Article"],"doi":["10.1007/s11633-017-1069-8"],"issn":["14768186"],"journaltitle":["Int. J. Autom. Comput."],"note":["cited By 10"],"number":["6"],"pages":["686–695"],"publisher":["Chinese Academy of Sciences"],"source":["Scopus"],"title":["Optimizing the double inverted pendulum’s performance via the uniform neuro multiobjective genetic algorithm"],"volume":["14"]},"creators":{"author":[{"lastName":"Al-Janan","firstName":"D.H."},{"lastName":"Chang","firstName":"H.-C."},{"lastName":"Chen","firstName":"Y.-P."},{"lastName":"Liu","firstName":"T.-K."}]},"sentenceCased":true},{"key":"Al-Subaihin:2016:CMA:2961111.2962600","type":"inproceedings","fields":{"acmid":["2962600"],"articleno":["38"],"author":["Al-Subaihin, A. A.","Sarro, F.","Black, S.","Capra, L.","Harman, M.","Jia, Y.","Zhang, Y."],"booktitle":["Proc. 10th ACMIEEE Int. Symp. Empir. Softw. Eng. Meas."],"date":["2016"],"isbn":["978-1-4503-4427-2"],"location":["New York, NY, USA"],"nodoi":["10.1145/2961111.2962600"],"numpages":["10"],"pages":["38:1-38:10"],"publisher":["ACM"],"series":["ESEM '16"],"title":["Clustering mobile apps based on mined textual features"],"url":["http://doi.acm.org/10.1145/2961111.2962600"]},"creators":{"author":[{"lastName":"Al-Subaihin","firstName":"A. A."},{"lastName":"Sarro","firstName":"F."},{"lastName":"Black","firstName":"S."},{"lastName":"Capra","firstName":"L."},{"lastName":"Harman","firstName":"M."},{"lastName":"Jia","firstName":"Y."},{"lastName":"Zhang","firstName":"Y."}]},"sentenceCased":true},{"key":"Alaa2019","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Adv. neural inf. proces. syst."],"affiliation":["ECE Department UCLA; UCLA, University of Cambridge, Alan Turing Institute, United Kingdom"],"author":["Alaa, A.M.","family=Schaar, given=M., prefix=van der, useprefix=true"],"date":["2019"],"document_type":["Conference Paper"],"issn":["10495258"],"note":["cited By 19 \n\nTL;DR \n\nIt is shown that symbolic metamodeling provides an all-encompassing framework for model interpretation — all common forms of global and local explanations of a model can be analytically derived from its symbolic meetamodel."],"publisher":["Neural information processing systems foundation"],"series":["Advances in Neural Information Processing Systems"],"source":["Scopus"],"title":["Demystifying black-box models with symbolic metamodels"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078483653&partnerID=40&md5=e624a02d5e67fdb84876eed77ec60513"],"volume":["32"]},"creators":{"author":[{"lastName":"Alaa","firstName":"A.M."},{"lastName":"Schaar","firstName":"M.","prefix":"vander","useprefix":true}]},"sentenceCased":true},{"key":"alamin2021empirical","type":"article","fields":{"abstract":["Low-code software development (LCSD) is an emerging paradigm that combines minimal source code with interactive graphical interfaces to promote rapid application development. LCSD aims to democratize application development to software practitioners with diverse backgrounds. Given that LCSD is relatively a new paradigm, it is vital to learn about the challenges developers face during their adoption of LCSD platforms. The online developer forum, Stack Overflow (SO), is popular among software developers to ask for solutions to their technical problems. We observe a growing body of posts in SO with discussions of LCSD platforms. In this paper, we present an empirical study of around 5K SO posts (questions + accepted answers) that contain discussions of nine popular LCSD platforms. We apply topic modeling on the posts to determine the types of topics discussed. We find 13 topics related to LCSD in SO. The 13 topics are grouped into four categories: Customization, Platform Adoption, Database Management, and Third-Party Integration. More than 40% of the questions are about customization, i.e., developers frequently face challenges with customizing user interfaces or services offered by LCSD platforms. The topic \"Dynamic Event Handling\" under the \"Customization\" category is the most popular (in terms of average view counts per question of the topic) as well as the most difficult. It means that developers frequently search for customization solutions such as how to attach dynamic events to a form in low-code UI, yet most (75.9%) of their questions remain without an accepted answer. We manually label 900 questions from the posts to determine the prevalence of the topics' challenges across LCSD phases. We find that most of the questions are related to the development phase, and low-code developers also face challenges with automated testing."],"author":["Alamin, Md Abdullah Al","Malakar, Sanjay","Uddin, Gias","Afroz, Sadia","Haider, Tameem Bin","Iqbal, Anindya"],"date":["2021-05"],"doi":["10.1109/MSR52588.2021.00018"],"eprint":["2103.11429"],"eprintclass":["cs.SE"],"eprinttype":["arxiv"],"journaltitle":["2021 IEEEACM 18th Int. Conf. Min. Softw. Repos. MSR"],"keywords":["Computer Science - Software Engineering"],"note":["TL;DR \n\nAn empirical study of around 5K SO posts that contain discussions of nine popular LCSD platforms finds that most of the questions are related to the development phase, and low-code developers also face challenges with automated testing."],"pages":["46–57"],"title":["An Empirical Study of Developer Discussions on Low-Code Software Development Challenges"]},"creators":{"author":[{"lastName":"Alamin","firstName":"Md Abdullah Al"},{"lastName":"Malakar","firstName":"Sanjay"},{"lastName":"Uddin","firstName":"Gias"},{"lastName":"Afroz","firstName":"Sadia"},{"lastName":"Haider","firstName":"Tameem Bin"},{"lastName":"Iqbal","firstName":"Anindya"}]}},{"key":"aldallalEmpiricalEvaluationImpact2018","type":"article","fields":{"author":["Al Dallal, Jehad","Abdin, Anas"],"date":["2018-01-01"],"doi":["10.1109/TSE.2017.2658573"],"issn":["0098-5589, 1939-3520"],"journaltitle":["IEEE Trans. Softw. Eng."],"note":["TL;DR \n\nIt is indicated that different refactoring scenarios sometimes have opposite impacts on different quality attributes, and it is false thatRefactoring always improves all software quality aspects."],"number":["1"],"pages":["44–69"],"shorttitle":["Empirical Evaluation of the Impact of Object-Oriented Code Refactoring on Quality Attributes"],"title":["Empirical Evaluation of the Impact of Object-Oriented Code Refactoring on Quality Attributes: A Systematic Literature Review"],"volume":["44"]},"creators":{"author":[{"lastName":"Al Dallal","firstName":"Jehad"},{"lastName":"Abdin","firstName":"Anas"}]}},{"key":"AlessioTonioniAutonomousFlightROSSimple","type":"online","fields":{"title":["AlessioTonioni/Autonomous-Flight-ROS: A simple autopilot for a quadrotor realized using MoveIt!. The system use a simulated RGBD sensor to reconstruct the map, then ompl for path generation."],"url":["https://github.com/AlessioTonioni/Autonomous-Flight-ROS"],"urldate":["2016-09-11"]},"creators":{},"sentenceCased":true},{"key":"alexanderCertificationAutonomousSystems2007","type":"inproceedings","fields":{"author":["Alexander, Robert","Hall-May, Martin","Kelly, Tim"],"booktitle":["Proc. 2nd Syst. Eng. Auton. Syst. SEAS Def. Technol. Cent. DTC Annu. Tech. Conf."],"date":["2007"],"note":["TL;DR \n\nThe aim of the project is to show that it is possible to automate the system design validation as well as the verification of the implementation in software so that there is considerably reduced time and cost while still being able to meet certification requirements."],"publisher":["Citeseer"],"title":["Certification of autonomous systems"],"url":["http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.126.7288&rep=rep1&type=pdf"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Alexander","firstName":"Robert"},{"lastName":"Hall-May","firstName":"Martin"},{"lastName":"Kelly","firstName":"Tim"}]},"sentenceCased":true},{"key":"alf","type":"book","fields":{"langid":["english"],"date":["2017"],"keywords":["/unread","⛔ No INSPIRE recid found"],"publisher":["Object Management Group (OMG)"],"title":["Action language for foundational UML (alf)"],"url":["https://www.omg.org/spec/ALF/1.1/PDF"]},"creators":{},"sentenceCased":true},{"key":"alfonsoSelfadaptiveArchitecturesIoT2021","type":"article","fields":{"abstract":["Over the past few years, the relevance of the Internet of Things (IoT) has grown significantly and is now a key component of many industrial processes and even a transparent participant in various activities performed in our daily life. IoT systems are subjected to changes in the dynamic environments they operate in. These changes (e.g. variations in the bandith consumption or new devices joining/leaving) may impact the Quality of Service (QoS) of the IoT system. A number of self-adaptation strategies for IoT architectures to better deal with these changes have been proposed in the literature. Nevertheless, they focus on isolated types of changes. We lack a comprehensive view of the trade-offs of each proposal and how they could be combined to cope with dynamic situations involving simultaneous types of events. In this paper, we identify, analyze, and interpret relevant studies related to IoT adaptation and develop a comprehensive and holistic view of the interplay of different dynamic events, their consequences on the architecture QoS, and the alternatives for the adaptation. To do so, we have conducted a systematic literature review of existing scientific proposals and defined a research agenda for the near future based on the findings and weaknesses identified in the literature."],"author":["Alfonso, Iván","Garcés, Kelly","Castro, Harold","Cabot, Jordi"],"date":["2021-09-07"],"eprint":["2109.03312"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv210903312 Cs"],"keywords":["Computer Science - Networking and Internet Architecture"],"note":["Comment: 18 pages, 3 figures, 8 tables, submitted to Journal of Internet Services and Applications \n\nTL;DR \n\nA comprehensive and holistic view of the interplay of different dynamic events, their consequences on QoS, and the alternatives for the adaptation is developed based on the findings and weaknesses identified in the literature."],"shorttitle":["Self-adaptive Architectures in IoT Systems"],"title":["Self-adaptive Architectures in IoT Systems: A Systematic Literature Review"],"url":["http://arxiv.org/abs/2109.03312"],"urldate":["2021-10-04"]},"creators":{"author":[{"lastName":"Alfonso","firstName":"Iván"},{"lastName":"Garcés","firstName":"Kelly"},{"lastName":"Castro","firstName":"Harold"},{"lastName":"Cabot","firstName":"Jordi"}]},"sentenceCased":true},{"key":"Ali20192979","type":"article","fields":{"abstract":["The work reported in this paper presents a novel hierarchical modular neural network architecture (HMNNA) for automated screening of cervical cancer. HMNNA consists of three neural networks trained specifically on different areas of problem space under consideration, and the trained networks are then arranged in a tree structure forming hierarchical modular neural network architecture. The three specialized neural networks are trained by Levenberg–Maarquardt neural network algorithm. As compared to the standard back propagation algorithm, Levenberg–Maarquardt is fast and stable for convergence with only one drawback, i.e., storage requirement for estimated Hessian Matrix. For training and testing of HMNNA, a huge primary database is created which contains 8091 cervical cell images pertaining to 200 clinical cases collected from two health care institutions of northern India. The raw cases of cervical cancer in the form of Pap smear slides were photographed under a multi-headed digital microscope. Individual cells were manually cropped off from these slide images which were then passed through a feature extraction module for morphological profiling. Each cell was calibrated on the basis of 40 features from both cytoplasm and nucleus. After profiling, these cells were vigilantly assigned cell classes as per the latest 2001-Bethesda system of cervical cancer cell classification, by trained cytotechnicians and histopathologists. HMNNA is also trained and tested on the Herlev Benchmark dataset created by the Denmark University, which consists of 1417 cervical cancer cells. Both the datasets have seven classes of diagnosis, i.e., superficial squamous, intermediate squamous, columnar, mild dysplasia, moderate dysplasia, severe dysplasia, and carcinoma in situ, corresponding to the level of abnormality in cervical cells. These datasets are available in public domain at http://digitalpapsmeardb.in/ and http://mde-lab.aegean.gr/index.php/downloads. The screening potential of the HMNNA is compared with 25 well-known machine learning algorithms available in MatlabR2016 (Machine learning and statistics toolbox 10.2) and monolithic neural network algorithms available in Matlab neural network pattern recognition toolbox. The HMNNA outperformed in all the 25 algorithms for both the datasets. For the Novel Benchmark database, it produced a classification accuracy of 95.32% with an F-value of 0.949310 and classification accuracy of 88.41% with an F-value of 0.89145 for the Herlev dataset. The screening potential of HMNNA was also evaluated and compared with the other diagnostic systems available in the recently published literature and was found to be performing much better than the counterparts on multiple parameters of performance evaluation. © 2017, The Natural Computing Applications Forum."],"author":["Ali, M.","Sarwar, A.","Sharma, V.","Suri, J."],"date":["2019"],"document_type":["Article"],"doi":["10.1007/s00521-017-3246-7"],"issn":["09410643"],"journaltitle":["Neural Comput. Appl."],"note":["cited By 9 \n\nTL;DR \n\nThe screening potential of HMNNA was evaluated and compared with the other diagnostic systems available in the recently published literature and was found to be performing much better than the counterparts on multiple parameters of performance evaluation."],"number":["7"],"pages":["2979–2993"],"publisher":["Springer London"],"source":["Scopus"],"title":["Artificial neural network based screening of cervical cancer using a hierarchical modular neural network architecture (HMNNA) and novel benchmark uterine cervix cancer database"],"volume":["31"]},"creators":{"author":[{"lastName":"Ali","firstName":"M."},{"lastName":"Sarwar","firstName":"A."},{"lastName":"Sharma","firstName":"V."},{"lastName":"Suri","firstName":"J."}]},"sentenceCased":true},{"key":"allenEngineeringAcademicSoftware2017","type":"incollection","fields":{"author":["Allen, Alice","Aragon, Cecilia","Becker, Christoph","Carver, Jeffrey","Chis, Andrei","Combemale, Benoit","Croucher, Mike","Crowston, Kevin","Garijo, Daniel","Gehani, Ashish","others"],"booktitle":["Dagstuhl Manifestos"],"date":["2017"],"number":["1"],"publisher":["Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik"],"title":["Engineering Academic Software (Dagstuhl Perspectives Workshop 16252)"],"url":["http://drops.dagstuhl.de/opus/volltexte/2017/7146/"],"urldate":["2017-05-30"],"volume":["6"]},"creators":{"author":[{"lastName":"Allen","firstName":"Alice"},{"lastName":"Aragon","firstName":"Cecilia"},{"lastName":"Becker","firstName":"Christoph"},{"lastName":"Carver","firstName":"Jeffrey"},{"lastName":"Chis","firstName":"Andrei"},{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Croucher","firstName":"Mike"},{"lastName":"Crowston","firstName":"Kevin"},{"lastName":"Garijo","firstName":"Daniel"},{"lastName":"Gehani","firstName":"Ashish"},{"lastName":"others"}]}},{"key":"allhoffInternetThingsFoundational2018","type":"article","fields":{"langid":["english"],"abstract":["This paper surveys foundational ethical issues that attach to the Internet of Things (IoT). In Section 1, we provide an overview of the technology, indicating both current and future applications. Subsequent sections consider particular ethical issues, including: informed consent (Section 2), privacy (Section 3), information security (Section 4), physical safety (Section 5), and trust (Section 6). Section 7 emphasizes that these ethical issues do not exist in isolation, but converge and intersect in myriad ways. And that these issues are not comprehensive, but rather are foundational starting points that stand to be expanded and further elucidated through future research."],"author":["Allhoff, Fritz","Henschke, Adam"],"date":["2018-09"],"doi":["10.1016/j.iot.2018.08.005"],"issn":["25426605"],"journaltitle":["Internet Things"],"pages":["55–66"],"shorttitle":["The Internet of Things"],"title":["The Internet of Things: Foundational ethical issues"],"volume":["1–2"]},"creators":{"author":[{"lastName":"Allhoff","firstName":"Fritz"},{"lastName":"Henschke","firstName":"Adam"}]},"sentenceCased":true},{"key":"almonte_automating_2021","type":"article","fields":{"langid":["english"],"abstract":["We are witnessing an increasing interest in building recommender systems (RSs) for all sorts of Software Engineering activities. Modelling is no exception to this trend, as modelling environments are being enriched with RSs that help building models by providing recommendations based on previous solutions to similar problems in the same domain. However, building a RS from scratch requires considerable effort and specialized knowledge. To alleviate this problem, we propose an automated approach to the generation of RSs for modelling languages. Our approach is model-based, and we provide a domain-specific language called Droid to configure every aspect of the RS (like the type and features of the recommended items, the recommendation method, and the evaluation metrics). The RS so configured can be deployed as a service, and we offer out-of-the-box integration of this service with the EMF tree editor. To assess the usefulness of our proposal, we present a case study on the integration of a generated RS with a modelling chatbot, and report on an offline experiment measuring the precision and completeness of the recommendations."],"author":["Almonte, Lissette","Pérez-Soler, Sara","Guerra, Esther","Cantador, Iván","family=Lara, given=Juan, prefix=de, useprefix=true"],"date":["2021"],"pages":["14"],"title":["Automating the Synthesis of Recommender Systems for Modelling Languages"]},"creators":{"author":[{"lastName":"Almonte","firstName":"Lissette"},{"lastName":"Pérez-Soler","firstName":"Sara"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Cantador","firstName":"Iván"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true}]}},{"key":"almonteAutomatingConstructionRecommender2020","type":"article","fields":{"langid":["english"],"abstract":["Low-code development platforms allow users with a low technical background to build complete software solutions, typically by means of graphical user interfaces, diagrams or declarative languages. In these platforms, recommender systems play an important role as they can provide users with relevant, personalised suggestions generated according to previously developed software solutions. However, developing recommender systems requires a high investment of time as it implies the selection and implementation of a suitable recommendation method, its configuration for the problem and domain at hand, and its evaluation to assess the accuracy of its recommendations."],"author":["Almonte, Lissette","Cantador, Iván","Guerra, Esther"],"date":["2020"],"note":["TL;DR \n\nThis paper presents the first steps towards a generic model-driven framework capable of generating ad-hoc, task-oriented recommender systems for their integration on low-code platforms and presents some preliminary results obtained from an offline evaluation of the framework."],"pages":["10"],"title":["Towards automating the construction of recommender systems for low-code development platforms"]},"creators":{"author":[{"lastName":"Almonte","firstName":"Lissette"},{"lastName":"Cantador","firstName":"Iván"},{"lastName":"Guerra","firstName":"Esther"}]},"sentenceCased":true},{"key":"almonteRecommenderSystemsModeldriven2021","type":"article","fields":{"langid":["english"],"abstract":["Recommender systems are information filtering systems used in many online applications like music and video broadcasting and e-commerce platforms. They are also increasingly being applied to facilitate software engineering activities. Following this trend, we are witnessing a growing research interest on recommendation approaches that assist with modelling tasks and modelbased development processes. In this paper, we report on a systematic mapping review (based on the analysis of 66 papers) that classifies the existing research work on recommender systems for model-driven engineering (MDE). This study aims to serve as a guide for tool builders and researchers in understanding the MDE tasks that might be subject to recommendations, the applicable recommendation techniques and evaluation methods, and the open challenges and opportunities in this field of research."],"author":["Almonte, Lissette","Guerra, Esther","Cantador, Iván","family=Lara, given=Juan, prefix=de, useprefix=true"],"date":["2021-07-26"],"doi":["10.1007/s10270-021-00905-x"],"ids":["almonte_recommender_2021"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"note":["TL;DR \n\nA systematic mapping review that classifies the existing research work on recommender systems for model-driven engineering (MDE) and serves as a guide for tool builders and researchers in understanding the MDE tasks that might be subject to recommendations, the applicable recommendation techniques and evaluation methods, and the open challenges and opportunities in this field of research."],"shorttitle":["Recommender systems in model-driven engineering"],"title":["Recommender systems in model-driven engineering: A systematic mapping review"]},"creators":{"author":[{"lastName":"Almonte","firstName":"Lissette"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Cantador","firstName":"Iván"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true}]},"sentenceCased":true},{"key":"almorsySuiteDomainspecificVisual2013","type":"inproceedings","fields":{"author":["Almorsy, Mohamed","Grundy, John","Sadus, Richard","family=Straten, given=Willem, prefix=van, useprefix=true","Barnes, David G.","Kaluza, Owen"],"booktitle":["Vis. Lang. Hum.-Centric Comput. VLHCC 2013 IEEE Symp. On"],"date":["2013"],"pages":["91–94"],"publisher":["IEEE"],"title":["A suite of domain-specific visual languages for scientific software application modelling"],"url":["http://ieeexplore.ieee.org/abstract/document/6645249/"],"urldate":["2017-02-23"]},"creators":{"author":[{"lastName":"Almorsy","firstName":"Mohamed"},{"lastName":"Grundy","firstName":"John"},{"lastName":"Sadus","firstName":"Richard"},{"lastName":"Straten","firstName":"Willem","prefix":"van","useprefix":true},{"lastName":"Barnes","firstName":"David G."},{"lastName":"Kaluza","firstName":"Owen"}]},"sentenceCased":true},{"key":"alomranChoosingNLPLibrary2017","type":"inproceedings","fields":{"author":["Al Omran, Fouad Nasser A","Treude, Christoph"],"date":["2017-05"],"doi":["10.1109/MSR.2017.42"],"isbn":["978-1-5386-1544-7"],"pages":["187–197"],"publisher":["IEEE"],"shorttitle":["Choosing an NLP Library for Analyzing Software Documentation"],"title":["Choosing an NLP Library for Analyzing Software Documentation: A Systematic Literature Review and a Series of Experiments"]},"creators":{"author":[{"lastName":"Al Omran","firstName":"Fouad Nasser A"},{"lastName":"Treude","firstName":"Christoph"}]}},{"key":"Alreshedy2018SCCAC","type":"article","fields":{"author":["Alreshedy, Kamel","Dharmaretnam, Dhanush","German, Daniel M.","Srinivasan, Venkatesh","Gulliver, T. Aaron"],"date":["2018"],"journaltitle":["CoRR"],"title":["SCC: Automatic classification of code snippets"],"volume":["abs/1809.07945"]},"creators":{"author":[{"lastName":"Alreshedy","firstName":"Kamel"},{"lastName":"Dharmaretnam","firstName":"Dhanush"},{"lastName":"German","firstName":"Daniel M."},{"lastName":"Srinivasan","firstName":"Venkatesh"},{"lastName":"Gulliver","firstName":"T. Aaron"}]},"sentenceCased":true},{"key":"alrubaye_how_nodate","type":"article","fields":{"langid":["english"],"abstract":["The migration process between different thirdparty software libraries is hard, complex and error-prone. Typically, during a library migration process, developers opt to replace methods from the retired library with other methods from a new library without altering the software behavior. However, the extent to which such a migration process to new libraries will be rewarded with an improved software quality is still unknown. In this paper, we aim at studying and analyzing the impact of library API migration on software quality. We conduct a large-scale empirical study on 9 popular API migrations, collected from a corpus of 57,447 open-source Java projects. We compute the values of commonly-used software quality metrics before and after a migration occurs. The statistical analysis of the obtained results provides evidence that library migrations are likely to improve different software quality attributes including a significantly reduced coupling, increased cohesion, and improved code readability. Furthermore, we release an online portal that helps software developers to understand the pre-impact of a library migration on software quality and recommend migration examples that adopt best design and implementation practices to improve software quality. Finally, we provide the software engineering community with a large scale dataset to foster research in software library migration."],"author":["Alrubaye, Hussein","AlShoaibi, Deema","Mkaouer, Mohamed Wiem","Ouni, Ali"],"note":["TL;DR \n\nAn online portal is released that helps software developers to understand the pre-impact of a library migration on software quality and recommend migration examples that adopt the best design and implementation practices to improve software quality."],"pages":["12"],"title":["How Does API Migration Impact Software Quality and Comprehension? An Empirical Study"]},"creators":{"author":[{"lastName":"Alrubaye","firstName":"Hussein"},{"lastName":"AlShoaibi","firstName":"Deema"},{"lastName":"Mkaouer","firstName":"Mohamed Wiem"},{"lastName":"Ouni","firstName":"Ali"}]}},{"key":"alrubaye2019learning","type":"article","fields":{"author":["Alrubaye, Hussein","Mkaouer, Mohamed Wiem","Khokhlov, Igor","Reznik, Leon","Ouni, Ali","Mcgoff, Jason"],"date":["2020"],"issn":["1568-4946"],"journaltitle":["Appl. Soft Comput."],"pages":["106–140"],"title":["Learning to recommend third-party library migration opportunities at the API level"],"volume":["90"]},"creators":{"author":[{"lastName":"Alrubaye","firstName":"Hussein"},{"lastName":"Mkaouer","firstName":"Mohamed Wiem"},{"lastName":"Khokhlov","firstName":"Igor"},{"lastName":"Reznik","firstName":"Leon"},{"lastName":"Ouni","firstName":"Ali"},{"lastName":"Mcgoff","firstName":"Jason"}]},"sentenceCased":true},{"key":"alrubayeUseInformationRetrieval2019","type":"inproceedings","fields":{"abstract":["The migration process between different third-party libraries is hard, complex and error-prone. Typically, during a library migration, developers need to find methods in the new library that are most adequate in replacing the old methods of the retired library. This process is subjective and time-consuming as developers need to fully understand the documentation of both libraries' Application Programming Interfaces, and find the right matching between their methods, if it exists. In this context, several studies rely on mining existing library migrations to provide developers with by-example approaches for similar scenarios. In this paper, we introduce a novel mining approach that extracts existing instances of library method replacements that are manually performed by developers for a given library migration to automatically generate migration patterns in the method level. Thereafter, our approach combines the mined method-change patterns with method-related lexical similarity to accurately detect mappings between replacing/replaced methods. We conduct a large scale empirical study to evaluate our approach on a benchmark of 57,447 open-source Java projects leading to 9 popular library migrations. Our qualitative results indicate that our approach significantly increases the accuracy of mining method-level mappings by an average accuracy of 12%, as well as increasing the number of discovered method mappings, in comparison with existing state-of-the-art studies. Finally, we provide the community with an open source mining tool along with a dataset of all mined migrations at the method level."],"author":["Alrubaye, Hussein","Mkaouer, Mohamed Wiem","Ouni, Ali"],"booktitle":["2019 IEEEACM 27th Int. Conf. Program Comprehension ICPC"],"date":["2019-05"],"doi":["10.1109/ICPC.2019.00053"],"eventtitle":["2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)"],"ids":["alrubaye_use_2019"],"issn":["2643-7147"],"keywords":["API","API migration","application program interfaces","data mining","information retrieval","Information Retrieval","Java","library method replacements","library migration","method-related lexical similarity","migration patterns","migration process","mined method-change patterns","open source mining tool","open-source Java","public domain software","Software Evolution","software libraries","Third Party Library","third-party Java library migration","third-party libraries"],"note":["ISSN: 2643-7147"],"pages":["347–357"],"title":["On the Use of Information Retrieval to Automate the Detection of Third-Party Java Library Migration at the Method Level"]},"creators":{"author":[{"lastName":"Alrubaye","firstName":"Hussein"},{"lastName":"Mkaouer","firstName":"Mohamed Wiem"},{"lastName":"Ouni","firstName":"Ali"}]}},{"key":"alsrehinIntelligentTransportationControl2019","type":"article","fields":{"langid":["english"],"abstract":["Traffic congestion is becoming the issues of the entire globe. This study aims to explore and review the data mining and machine learning technologies adopted in research and industry to attempt to overcome the direct and indirect traffic issues on humanity and societies. The study’s methodology is to comprehensively review around 165 studies, criticize, and categorize all these studies into a chronological and understandable category. The study is focusing on the traffic management approaches that were depended on data mining and machine learning technologies to detect and predict the traffic only. This study has found that there is no standard traffic management approach that the community of traffic management has agreed on. This study is important to the traffic research communities, traffic software companies, and traffic government officials. It has a direct impact on drawing a clear path for new traffic management propositions. This study is one of the largest studies with respect to the size of its reviewed articles that were focused on data mining and machine learning. Additionally, this study will draw general attention to a new traffic management proposition approach."],"author":["Alsrehin, Nawaf O.","Klaib, Ahmad F.","Magableh, Aws"],"date":["2019"],"doi":["10.1109/ACCESS.2019.2909114"],"issn":["2169-3536"],"journaltitle":["IEEE Access"],"note":["TL;DR \n\nIt is found that there is no standard traffic management approach that the community of traffic management has agreed on and this study will draw general attention to a new traffic management proposition approach."],"pages":["49830–49857"],"shorttitle":["Intelligent Transportation and Control Systems Using Data Mining and Machine Learning Techniques"],"title":["Intelligent Transportation and Control Systems Using Data Mining and Machine Learning Techniques: A Comprehensive Study"],"volume":["7"]},"creators":{"author":[{"lastName":"Alsrehin","firstName":"Nawaf O."},{"lastName":"Klaib","firstName":"Ahmad F."},{"lastName":"Magableh","firstName":"Aws"}]}},{"key":"altulyanRecommenderSystemsInternet2020","type":"article","fields":{"langid":["english"],"abstract":["Recommendation represents a vital stage in developing and promoting the benefits of the Internet of Things (IoT). Traditional recommender systems fail to exploit ever-growing, dynamic, and heterogeneous IoT data. This paper presents a comprehensive review of the state-of-the-art recommender systems, as well as related techniques and application in the vibrant field of IoT. We discuss several limitations of applying recommendation systems to IoT and propose a reference framework for comparing existing studies to guide future research and practices."],"author":["Altulyan, May","Yao, Lina","Wang, Xianzhi","Huang, Chaoran","Kanhere, Salil S.","Sheng, Quan Z."],"date":["2020-07-13"],"eprint":["2007.06758"],"eprintclass":["cs, stat"],"eprinttype":["arxiv"],"journaltitle":["ArXiv200706758 Cs Stat"],"keywords":["internet of things","machine learning","recommendation systems"],"note":["TL;DR \n\nA comprehensive review of the state-of-the-art recommender systems, as well as related techniques and application in the vibrant field of IoT, and proposes a reference framework for comparing existing studies to guide future research and practices."],"shorttitle":["Recommender Systems for the Internet of Things"],"title":["Recommender Systems for the Internet of Things: A Survey"],"url":["http://arxiv.org/abs/2007.06758"],"urldate":["2020-12-14"]},"creators":{"author":[{"lastName":"Altulyan","firstName":"May"},{"lastName":"Yao","firstName":"Lina"},{"lastName":"Wang","firstName":"Xianzhi"},{"lastName":"Huang","firstName":"Chaoran"},{"lastName":"Kanhere","firstName":"Salil S."},{"lastName":"Sheng","firstName":"Quan Z."}]}},{"key":"alurSystemsComputingChallenges2016","type":"article","fields":{"author":["Alur, Rajeev","Berger, Emery","Drobnis, Ann W.","Fix, Limor","Fu, Kevin","Hager, Gregory D.","Lopresti, Daniel","Nahrstedt, Klara","Mynatt, Elizabeth","Patel, Shwetak","others"],"date":["2016"],"eprint":["1604.02980"],"eprinttype":["arxiv"],"journaltitle":["ArXiv Prepr. ArXiv160402980"],"note":["TL;DR \n\nSuccess in developing value-added capabilities around IoT requires a broad approach that includes expertise in sensing and hardware, machine learning, networked systems, human-computer interaction, security, and privacy."],"title":["Systems Computing Challenges in the Internet of Things"],"url":["http://arxiv.org/abs/1604.02980"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Alur","firstName":"Rajeev"},{"lastName":"Berger","firstName":"Emery"},{"lastName":"Drobnis","firstName":"Ann W."},{"lastName":"Fix","firstName":"Limor"},{"lastName":"Fu","firstName":"Kevin"},{"lastName":"Hager","firstName":"Gregory D."},{"lastName":"Lopresti","firstName":"Daniel"},{"lastName":"Nahrstedt","firstName":"Klara"},{"lastName":"Mynatt","firstName":"Elizabeth"},{"lastName":"Patel","firstName":"Shwetak"},{"lastName":"others"}]}},{"key":"alvarezMTCFlowTool2013","type":"article","fields":{"author":["Alvarez, Camilo","Casallas, Rubby"],"date":["2013"],"doi":["10.1145/2491279.2491286"],"journaltitle":["Proc. Workshop Acad. Tool. Eclipse - ACME 13"],"note":["TL;DR \n\nThis paper presents a tool called MTC Flow, which allows model-driven developers to design, develop, test and deploy Model Transformation Chains (MTCs), and offers a graphical DSL for defining MTC workflow models independently of the technologies that support the transformations."],"pages":["1–9"],"title":["MTC Flow: A tool to design, develop and deploy model transformation chains"]},"creators":{"author":[{"lastName":"Alvarez","firstName":"Camilo"},{"lastName":"Casallas","firstName":"Rubby"}]},"sentenceCased":true},{"key":"alvinoLessonsLearnedLarge","type":"article","fields":{"langid":["english"],"author":["Alvino, Chris"],"pages":["22"],"title":["Lessons Learned from Large Scale Real World Recommender Systems"]},"creators":{"author":[{"lastName":"Alvino","firstName":"Chris"}]}},{"key":"AmbitiousPlan","type":"online","fields":{"langid":["british"],"abstract":["A plan for projects and related publications Project Workshops/ Doctoral Symposium Conference Journal Leading role Other members of the group mainly involved Work to be done Note 1 CrossSim SEAA 2018 SQJ Phuong Riccardo Wait for the notification from SQJ Response to revie..."],"organization":["Google Docs"],"shorttitle":["An ambitious plan"],"title":["An ambitious plan :-)"],"url":["https://docs.google.com/document/d/1uWyVw2JEI6A6KcB1kMYx_9sXqTSgy8r5CfWc1xQSHRM/edit?ts=5be56d68&usp=embed_facebook"],"urldate":["2020-02-11"]},"creators":{},"sentenceCased":true},{"key":"amershiSoftwareEngineeringMachine2019","type":"inproceedings","fields":{"langid":["english"],"abstract":["Recent advances in machine learning have stimulated widespread interest within the Information Technology sector on integrating AI capabilities into software and services. This goal has forced organizations to evolve their development processes. We report on a study that we conducted on observing software teams at Microsoft as they develop AI-based applications. We consider a nine-stage workflow process informed by prior experiences developing AI applications (e.g., search and NLP) and data science tools (e.g. application diagnostics and bug reporting). We found that various Microsoft teams have united this workflow into preexisting, well-evolved, Agile-like software engineering processes, providing insights about several essential engineering challenges that organizations may face in creating large-scale AI solutions for the marketplace. We collected some best practices from Microsoft teams to address these challenges. In addition, we have identified three aspects of the AI domain that make it fundamentally different from prior software application domains: 1) discovering, managing, and versioning the data needed for machine learning applications is much more complex and difficult than other types of software engineering, 2) model customization and model reuse require very different skills than are typically found in software teams, and 3) AI components are more difficult to handle as distinct modules than traditional software components — models may be “entangled” in complex ways and experience non-monotonic error behavior. We believe that the lessons learned by Microsoft teams will be valuable to other organizations."],"author":["Amershi, Saleema","Begel, Andrew","Bird, Christian","DeLine, Robert","Gall, Harald","Kamar, Ece","Nagappan, Nachiappan","Nushi, Besmira","Zimmermann, Thomas"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/conf/icse/AmershiBBDGKNN019.bib"],"booktitle":["2019 IEEEACM 41st Int. Conf. Softw. Eng. Softw. Eng. Pract. ICSE-SEIP"],"date":["2019-05"],"doi":["10.1109/ICSE-SEIP.2019.00042"],"eventtitle":["2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)"],"ids":["DBLP:conf/icse/AmershiBBDGKNN019,amershiSoftwareEngineeringMachine2019a"],"isbn":["978-1-72811-760-7"],"location":["Montreal, QC, Canada"],"note":["TL;DR \n\nA study conducted on observing software teams at Microsoft as they develop AI-based applications finds that various Microsoft teams have united this workflow into preexisting, well-evolved, Agile-like software engineering processes, providing insights about several essential engineering challenges that organizations may face in creating large-scale AI solutions for the marketplace."],"pages":["291–300"],"publisher":["IEEE"],"shorttitle":["Software Engineering for Machine Learning"],"timestamp":["Wed, 16 Oct 2019 14:14:49 +0200"],"title":["Software Engineering for Machine Learning: A Case Study"]},"creators":{"author":[{"lastName":"Amershi","firstName":"Saleema"},{"lastName":"Begel","firstName":"Andrew"},{"lastName":"Bird","firstName":"Christian"},{"lastName":"DeLine","firstName":"Robert"},{"lastName":"Gall","firstName":"Harald"},{"lastName":"Kamar","firstName":"Ece"},{"lastName":"Nagappan","firstName":"Nachiappan"},{"lastName":"Nushi","firstName":"Besmira"},{"lastName":"Zimmermann","firstName":"Thomas"}]}},{"key":"Ameur2022","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Intl. J. Mach. Learn. Cybern."],"affiliation":["Multimedia, InfoRmation Systems and Advanced Computing Laboratory, Sfax, Tunisia; Higher Institute of Computer Sciences and Multimedia, University of Sfax, Sfax, Tunisia; Higher Institute of Computer Sciences and Multimedia, University of Gabes, Gabes, Tunisia"],"author":["Ameur, H.","Njah, H.","Jamoussi, S."],"correspondence_address1":["Ameur, H.; Multimedia, Tunisia; email: ameurhanen@gmail.com"],"date":["2022"],"document_type":["Article"],"doi":["10.1007/s13042-022-01577-9"],"issn":["18688071"],"journaltitle":["Int. J. Mach. Learn. Cybern."],"note":["cited By 0"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Merits of Bayesian networks in overcoming small data challenges: A meta-model for handling missing data"]},"creators":{"author":[{"lastName":"Ameur","firstName":"H."},{"lastName":"Njah","firstName":"H."},{"lastName":"Jamoussi","firstName":"S."}]},"sentenceCased":true},{"key":"amine_benelallam_2018_1489120","type":"article","fields":{"author":["Benelallam, Amine","Harrand, Nicolas","Valero, César Soto","Baudry, Benoit","Barais, Olivier"],"date":["2018-11"],"doi":["10.5281/zenodo.1489120"],"note":["The Maven dependency graph is the fruit of a collaboration between the DiverSE team (Inria Rennes, France) and CASTOR project (KTH, Sweden). Instructions on how to use and reproduce the dataset can be found in the dataset's repository on [Github](https://github.com/diverse-project /maven-miner). A complete description of the dataset and usages can be found in the accompanying [paper] (https://arxiv.org/abs/1901.05392). \n\nThe Maven dependency graph is the fruit of a collaboration between the DiverSE team (Inria Rennes, France) and CASTOR project (KTH, Sweden). Instructions on how to use and reproduce the dataset can be found in the dataset's repository on [Github](https://github.com/diverse-project /maven-miner). A complete description of the dataset and usages can be found in the accompanying [paper] (https://arxiv.org/abs/1901.05392). \n\nThe Maven dependency graph is the fruit of a collaboration between the DiverSE team (Inria Rennes, France) and CASTOR project (KTH, Sweden). Instructions on how to use and reproduce the dataset can be found in the dataset's repository on [Github](https://github.com/diverse-project /maven-miner). A complete description of the dataset and usages can be found in the accompanying [paper] (https://arxiv.org/abs/1901.05392). \n\nThe Maven dependency graph is the fruit of a collaboration between the DiverSE team (Inria Rennes, France) and CASTOR project (KTH, Sweden). Instructions on how to use and reproduce the dataset can be found in the dataset's repository on [Github](https://github.com/diverse-project /maven-miner). A complete description of the dataset and usages can be found in the accompanying [paper] (https://arxiv.org/abs/1901.05392). \n\nThe Maven dependency graph is the fruit of a collaboration between the DiverSE team (Inria Rennes, France) and CASTOR project (KTH, Sweden). Instructions on how to use and reproduce the dataset can be found in the dataset's repository on [Github](https://github.com/diverse-project /maven-miner). A complete description of the dataset and usages can be found in the accompanying [paper] (https://arxiv.org/abs/1901.05392)."],"title":["Maven central dependency graph"]},"creators":{"author":[{"lastName":"Benelallam","firstName":"Amine"},{"lastName":"Harrand","firstName":"Nicolas"},{"lastName":"Valero","firstName":"César Soto"},{"lastName":"Baudry","firstName":"Benoit"},{"lastName":"Barais","firstName":"Olivier"}]},"sentenceCased":true},{"key":"Ammar2018247","type":"article","fields":{"abstract":["Automatic planning is a separate discipline of Artificial Intelligence (AI). It aims to formalize the planning problems described by the concept of state space. The Planning Domain Definition Language (PDDL) is a de facto standard language in the field of automatic planning. PDDL-related dynamic analysis tools, namely planners and validators, are insufficient for verifying and validating PDDL descriptions. Such tools make it possible to detect errors a posteriori by means of a test activity. In this article, we recommend a rigorous approach coupling Event-B and PDDL for automatic planning. Event-B is used for formal modeling by stepwise refinement with mathematical proofs of planning problems. A refinement strategy appropriate to planning problems is, then, proposed. The ultimate Event-B model, correct by construction, supposed to be translatable into PDDL, is automatically translated into PDDL using our MDE Event-B2PDDL tool. The obtained PDDL description is submitted to efficient planners for generation of solution plans. © Springer Nature Switzerland AG 2018."],"author":["Ammar, S.","Bhiri, M.T."],"date":["2018"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-02852-7_21"],"editor":["Golfarelli M., Bellatreche L., Nakamatsu K., Ordonez C., Mery D., Benslimane D., Abdelwahed E.H., Jean S."],"isbn":["9783030028510"],"issn":["18650929"],"journaltitle":["Commun. Comput. Inf. Sci."],"note":["cited By 0 \n\nTL;DR \n\nThis article recommends a rigorous approach coupling Event-B and PDDL, and proposes a refinement strategy appropriate to planning problems, which is automatically translated into PDDL using the MDE Event- B2PDDL tool."],"pages":["247–254"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Automatic planning: From event-B to PDDL"],"volume":["929"]},"creators":{"author":[{"lastName":"Ammar","firstName":"S."},{"lastName":"Bhiri","firstName":"M.T."}],"editor":[{"lastName":"Golfarelli M.","suffix":"Bellatreche L.","firstName":"Nakamatsu K., Ordonez C., Mery D., Benslimane D., Abdelwahed E.H., Jean S."}]},"sentenceCased":true},{"key":"Ammar2021261","type":"inproceedings","fields":{"abstract":["In artificial intelligence, the goal of automatic planning is to structure actions in the form of a plan to achieve an expressed goal. The PDDL (Planning Domain Definition Language) was designed to allow the common representation of planning problems during ICAPS (International Conference on Automated Planning and Scheduling) competitions. PDDL has many verification and validation tools allowing the description, resolution and validation of planning problems. But they only allow the reliability of PDDL descriptions a posteriori. In this article, we recommend a rigorous approach coupling Event-B and PDDL favoring obtaining PDDL descriptions deemed correct, a priori, from an ultimate Event-B model. The formal Event-B method allows us to obtain, by successive refinements with mathematical proofs, correct by construction formal models of planning problems. A refinement strategy appropriate to planning problems is, then, proposed. The ultimate Event-B model, correct by construction, is automatically translated into PDDL using our MDE Event-B2PDDL tool. The obtained PDDL description is submitted to efficient planners for generation of correct and efficient plan-solutions. Copyright © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved"],"author":["Ammar, S.","Bhiri, M.T."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.5220/0010577102610268"],"editor":["Fill H.-G., van Sinderen M., Maciaszek L., Maciaszek L."],"isbn":["978-989-758-523-4"],"note":["cited By 0 \n\nTL;DR \n\nA rigorous approach is recommended coupling Event-B and PDDL favoring obtaining PDDL descriptions deemed correct, a priori, from an ultimate Event-Bs model, correct by construction formal models of planning problems."],"pages":["261–268"],"publisher":["SciTePress"],"series":["Proceedings of the 16th International Conference on Software Technologies, ICSOFT 2021"],"source":["Scopus"],"title":["A formal approach combining event-b and pddl for planning problems"]},"creators":{"author":[{"lastName":"Ammar","firstName":"S."},{"lastName":"Bhiri","firstName":"M.T."}],"editor":[{"lastName":"Fill H.-G.","suffix":"van Sinderen M.","firstName":"Maciaszek L., Maciaszek L."}]},"sentenceCased":true},{"key":"Amouzgar201828","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Eng Appl Artif Intell"],"affiliation":["School of Engineering Science, University of Skövde, Skövde, 541 28, Sweden"],"author":["Amouzgar, K.","Bandaru, S.","Ng, A.H.C."],"coden":["EAAIE"],"correspondence_address1":["Amouzgar, K.; School of Engineering Science, Sweden; email: kaveh.amouzgar@his.se"],"date":["2018"],"document_type":["Article"],"doi":["10.1016/j.engappai.2018.02.006"],"issn":["09521976"],"journaltitle":["Eng. Appl. Artif. Intell."],"note":["cited By 16"],"pages":["28–44"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Radial basis functions with a priori bias as surrogate models: A comparative study"],"volume":["71"]},"creators":{"author":[{"lastName":"Amouzgar","firstName":"K."},{"lastName":"Bandaru","firstName":"S."},{"lastName":"Ng","firstName":"A.H.C."}]},"sentenceCased":true},{"key":"amraniTridimensionalApproachStudying2012","type":"inproceedings","fields":{"abstract":["In Model Driven Engineering (MDE), models are first-class citizens, and model transformation is MDE's \"heart and soul\". Since model transformations are executed for a family of conforming models, their validity becomes a crucial issue. This paper proposes to explore the question of the formal verification of model transformation properties through a tri-dimensional approach: the transformation involved, the properties of interest addressed, and the formal verification techniques used to establish the properties. This work allows a better understanding of the expected properties for a particular transformation, and facilitates the identification of the suitable tools and techniques for enabling their verification."],"author":["Amrani, M.","Lucio, L.","Selim, G.","Combemale, B.","Dingel, J.","Vangheluwe, H.","Le Traon, Y.","Cordy, J.R."],"booktitle":["2012 IEEE Fifth Int. Conf. Softw. Test. Verification Valid. ICST"],"date":["2012-04"],"doi":["10.1109/ICST.2012.197"],"eventtitle":["2012 IEEE Fifth International Conference on Software Testing, Verification and Validation (ICST)"],"note":["<b>SPUNTI INTERESSANTI</b> \n\n<ul> <li><b>Idea per il forge</b>: \"we would like to propose the community to contribute for a comprehensive <b>benchmark</b> <b>for FV (Formal Verification) of transformations</b>: it consists of storing pairs constituted by a transformation together with its properties of interest. This benchmark can help researchers as well as practitioners, and could provide a common reference for playing with verification of transformations by easily targeting a technique, a property kind amongthose identified in this paper, and comparing efficiency and scalability of approaches.\" <li>Tra gli approcci di <b>formal verification</b> che ci interessano ci sono quelli che ricascano in \"<i>Type II: Transformation-Dependent and Input-Independent</i>\". Questi sono: <ul> <li><b>Model checking</b> <li><b>Static Analysis</b>: Becker et al. [43 - <i>Symbolic Invariant</i>\n <i>Verification For Systems With Dynamic Structural Adaptation</i>] proposed a static\n analysis technique to check whether a model transformation\n (formalized as graph rewriting) preserved constraints\n expressed as (conditional) forbidden patterns in the output\n model. The study proved that the structural adaptation does\n not transform a safe system state to an unsafe one by verifying\n that the backward application of each rule to each forbidden\n pattern cannot result in a safe state. <li><b>Theorem Proving </b> </ul> <li>Le proprietà che possono essere provate sono: <ul> <li>Language related <ul> <li>at execution-time (termination and determinism) <li>at design-tyme (static semantics) </ul> <li>Transformation related <ul> <li> properties involving transformations’s source and/or target models <ul> <li>per esempio in caso di <b>merging</b>: they enunciate several properties merge\n operators should possess: completeness means no information is lost during the merge; non-redundancy ensures that the\n merge does not duplicate redundant information spread over source models; minimality ensures that the merge produces\n models with information solely originating from sources; totality ensures that the merge can actually be computed\n on any pair of models; idempotency, which ensures that a model merged with itself produces an identical model. </ul> <li>syntax-guided properties <li>properties involving the underlying semantics of models </ul> </ul> </ul> \n\nTL;DR \n\nThis paper proposes to explore the question of the formal verification of model transformation properties through a tri-dimensional approach: the transformation involved, the properties of interest addressed, and the formal verify techniques used to establish the properties."],"pages":["921–928"],"title":["A Tridimensional Approach for Studying the Formal Verification of Model Transformations"]},"creators":{"author":[{"lastName":"Amrani","firstName":"M."},{"lastName":"Lucio","firstName":"L."},{"lastName":"Selim","firstName":"G."},{"lastName":"Combemale","firstName":"B."},{"lastName":"Dingel","firstName":"J."},{"lastName":"Vangheluwe","firstName":"H."},{"lastName":"Le Traon","firstName":"Y."},{"lastName":"Cordy","firstName":"J.R."}]}},{"key":"AnalisiSperimentazioneDi","type":"thesis","fields":{"title":["Analisi e sperimentazione di Algoritmi di Outlier Detection in Sistemi GDO"]},"creators":{},"sentenceCased":true},{"key":"AnalysisLicenseInconsistency","type":"article","fields":{"entrysubtype":["newspaper"],"title":["Analysis of license inconsistency in large collections of open source projects"],"url":["http://rdcu.be/tez8"]},"creators":{},"sentenceCased":true},{"key":"AnalysisMetamodelingPractices","type":"online","fields":{"title":["An analysis of metamodeling practices for MOF and OCL"],"url":["http://www.sciencedirect.com/science/article/pii/S1477842415000068"],"urldate":["2015-06-12"]},"creators":{},"sentenceCased":true},{"key":"AnalyzeUnderstandText","type":"online","fields":{"title":["Analyze and Understand Text: Guide to Natural Language Processing - Strumenta"],"url":["https://tomassetti.me/guide-natural-language-processing/?utm_source=newsletter&utm_medium=email&utm_campaign=onboardingsequence"],"urldate":["2021-02-01"]},"creators":{}},{"key":"AnastasakisBGR10","type":"article","fields":{"langid":["english"],"author":["Anastasakis, Kyriakos","Bordbar, Behzad","Georg, Geri","Ray, Indrakshi"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2010"],"doi":["10.1007/S10270-008-0110-3"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["1"],"pages":["69–86"],"timestamp":["Fri, 18 Sep 2020 11:19:22 +0200"],"title":["On challenges of model transformation from UML to alloy"],"volume":["9"]},"creators":{"author":[{"lastName":"Anastasakis","firstName":"Kyriakos"},{"lastName":"Bordbar","firstName":"Behzad"},{"lastName":"Georg","firstName":"Geri"},{"lastName":"Ray","firstName":"Indrakshi"}]},"sentenceCased":true},{"key":"Anavangot20216314","type":"article","fields":{"abstract":["Classical quantizer design approaches using the Lloyd-Max algorithm (or k-means) have served signal processing applications for more than three decades. With the advent of distributed signal processing and machine learning at edge devices, novel alternatives for quantizers design will be desired to address the energy, communication and hardware constraints. To address these resource challenges, we propose a model-driven approach, termed Approximate Lloyd-Max (ALM) design, based on piecewise linear approximation of the signal-source probability density. From the principles of the ALM design, we develop a data-driven quantizer, or Learning ALM (LALM), using statistical learning methods. By mathematical analysis, we show convergence of the ALM quantizer near the limit of the Lloyd-Max quantizer. Both ALM and LALM quantizers satisfy asymptotic optimality and exponential convergence rate. Simulation performed over smooth signal source distributions validate our mathematical analysis. Experiments for LALM quantizer are implemented on an Android-based edge device, and the proposed quantizer demonstrate improved performance over k-means, in terms of algorithm speedup, energy usage and memory utilization. © 1991-2012 IEEE."],"author":["Anavangot, V.","Kumar, A."],"coden":["ITPRE"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/TSP.2021.3125602"],"issn":["1053587X"],"journaltitle":["IEEE Trans. Signal Process."],"note":["cited By 0 \n\nTL;DR \n\nA model-driven approach, termed Approximate Lloyd-Max (ALM) design, based on piecewise linear approximation of the signal-source probability density is proposed, and a data-driven quantizer is developed, or Learning ALM (LALM), using statistical learning methods."],"pages":["6314–6328"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Signal source distribution approximation to speedup scalar quantizer design"],"volume":["69"]},"creators":{"author":[{"lastName":"Anavangot","firstName":"V."},{"lastName":"Kumar","firstName":"A."}]},"sentenceCased":true},{"key":"Anderson:2006:LTW:1197299","type":"book","fields":{"author":["Anderson, Chris"],"date":["2006"],"isbn":["1-4013-0237-8"],"publisher":["Hyperion"],"title":["The long tail: Why the future of business is selling less of more"]},"creators":{"author":[{"lastName":"Anderson","firstName":"Chris"}]},"sentenceCased":true},{"key":"andSwingSWTBack2010","type":"inproceedings","fields":{"author":["and"],"booktitle":["2010 IEEE Int. Conf. Softw. Maint."],"date":["2010-09"],"doi":["10.1109/ICSM.2010.5610429"],"ids":["thiago_tonelli_swing_2010"],"issn":["1063-6773"],"keywords":["Adaptive arrays","API migration re-engineering","application code","application program interfaces","Containers","graphical user interfaces","Graphical user interfaces","Java","object-oriented API","object-oriented methods","Open source software","open-source GUI wrapper","wrapper-based migration","wrapper-based re-implementation","wrapping","Wrapping","XML"],"note":["ISSN: 1063-6773"],"pages":["1–10"],"title":["Swing to SWT and back: Patterns for API migration by wrapping"]},"creators":{"author":[{"literal":"and"}]},"sentenceCased":true},{"key":"anelliElliotComprehensiveRigorous2021","type":"article","fields":{"abstract":["Recommender Systems have shown to be an effective way to alleviate the over-choice problem and provide accurate and tailored recommendations. However, the impressive number of proposed recommendation algorithms, splitting strategies, evaluation protocols, metrics, and tasks, has made rigorous experimental evaluation particularly challenging. Puzzled and frustrated by the continuous recreation of appropriate evaluation benchmarks, experimental pipelines, hyperparameter optimization, and evaluation procedures, we have developed an exhaustive framework to address such needs. Elliot is a comprehensive recommendation framework that aims to run and reproduce an entire experimental pipeline by processing a simple configuration file. The framework loads, filters, and splits the data considering a vast set of strategies (13 splitting methods and 8 filtering approaches, from temporal training-test splitting to nested K-folds Cross-Validation). Elliot optimizes hyperparameters (51 strategies) for several recommendation algorithms (50), selects the best models, compares them with the baselines providing intra-model statistics, computes metrics (36) spanning from accuracy to beyond-accuracy, bias, and fairness, and conducts statistical analysis (Wilcoxon and Paired t-test). The aim is to provide the researchers with a tool to ease (and make them reproducible) all the experimental evaluation phases, from data reading to results collection. Elliot is available on GitHub (https://github.com/sisinflab/elliot)."],"author":["Anelli, Vito Walter","Bellogín, Alejandro","Ferrara, Antonio","Malitesta, Daniele","Merra, Felice Antonio","Pomo, Claudio","Donini, Francesco Maria","Di Noia, Tommaso"],"date":["2021-03-03"],"eprint":["2103.02590"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv210302590 Cs"],"keywords":["Computer Science - Information Retrieval"],"note":["Comment: 10 pages, 1 figure \n\nTL;DR \n\nElliot is a comprehensive recommendation framework that aims to run and reproduce an entire experimental pipeline by processing a simple configuration file and optimizes hyperparameters for several recommendation algorithms."],"shorttitle":["Elliot"],"title":["Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation"],"url":["http://arxiv.org/abs/2103.02590"],"urldate":["2021-03-09"]},"creators":{"author":[{"lastName":"Anelli","firstName":"Vito Walter"},{"lastName":"Bellogín","firstName":"Alejandro"},{"lastName":"Ferrara","firstName":"Antonio"},{"lastName":"Malitesta","firstName":"Daniele"},{"lastName":"Merra","firstName":"Felice Antonio"},{"lastName":"Pomo","firstName":"Claudio"},{"lastName":"Donini","firstName":"Francesco Maria"},{"lastName":"Di Noia","firstName":"Tommaso"}]}},{"key":"anelliSemanticInterpretationTopN2020","type":"article","fields":{"langid":["english"],"abstract":["Over the years, model-based approaches have shown their effectiveness in computing recommendation lists in different domains and settings. By relying on the computation of latent factors, they can recommend items with a very high level of accuracy. Unfortunately, when moving to the latent space, even if the model embeds content-based information, we miss references to the actual semantics of the recommended item. It makes the interpretation of the recommendation process non-trivial. In this paper, we show how to initialize latent factors in Factorization Machines by using semantic features coming from knowledge graphs to train an interpretable model, which is, in turn, able to provide recommendations with a high level of accuracy. In the presented approach, semantic features are injected into the learning process to retain the original informativeness of the items available in the dataset. By relying on the information encoded in the original knowledge graph, we also propose two metrics to evaluate the semantic accuracy and robustness of knowledge-aware interpretability. An extensive experimental evaluation on six different datasets shows the effectiveness of the interpretable model in terms of both accuracy and diversity of recommendation results and interpretability robustness."],"author":["Anelli, Vito Walter","Di Noia, Tommaso","Di Sciascio, Eugenio","Ragone, Azzurra","Trotta, Joseph"],"date":["2020"],"doi":["10.1109/TKDE.2020.3010215"],"issn":["1041-4347, 1558-2191, 2326-3865"],"journaltitle":["IEEE Trans. Knowl. Data Eng."],"note":["TL;DR \n\nThis paper shows how to initialize latent factors in Factorization Machines by using semantic features coming from knowledge graphs to train an interpretable model, which is, in turn, able to provide recommendations with a high level of accuracy."],"pages":["1–1"],"title":["Semantic Interpretation of Top-N Recommendations"]},"creators":{"author":[{"lastName":"Anelli","firstName":"Vito Walter"},{"lastName":"Di Noia","firstName":"Tommaso"},{"lastName":"Di Sciascio","firstName":"Eugenio"},{"lastName":"Ragone","firstName":"Azzurra"},{"lastName":"Trotta","firstName":"Joseph"}]}},{"key":"angeliniCrackingNutsSledgehammer2022","type":"online","fields":{"abstract":["The recent work “Combinatorial Optimization with Physics-Inspired Graph Neural Networks” [Nat Mach Intell 4 (2022) 367] introduces a physics-inspired unsupervised Graph Neural Network (GNN) to solve combinatorial optimization problems on sparse graphs. To test the performances of these GNNs, the authors of the work show numerical results for two fundamental problems: maximum cut and maximum independent set (MIS). They conclude that \"the graph neural network optimizer performs on par or outperforms existing solvers, with the ability to scale beyond the state of the art to problems with millions of variables.\" In this comment, we show that a simple greedy algorithm, running in almost linear time, can find solutions for the MIS problem of much better quality than the GNN. The greedy algorithm is faster by a factor of $10 ̂4$ with respect to the GNN for problems with a million variables. We do not see any good reason for solving the MIS with these GNN, as well as for using a sledgehammer to crack nuts. In general, many claims of superiority of neural networks in solving combinatorial problems are at risk of being not solid enough, since we lack standard benchmarks based on really hard problems. We propose one of such hard benchmarks, and we hope to see future neural network optimizers tested on these problems before any claim of superiority is made."],"author":["Angelini, Maria Chiara","Ricci-Tersenghi, Federico"],"date":["2022-06-27"],"eprint":["2206.13211"],"eprintclass":["cond-mat"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Machine Learning","Condensed Matter - Disordered Systems and Neural Networks","Mathematics - Optimization and Control"],"note":["Comment: Comment to \"Combinatorial Optimization with Physics-Inspired Graph Neural Networks” [Nat Mach Intell 4 (2022) 367] https://www.nature.com/articles/s42256-022-00468-6"],"pubstate":["preprint"],"shorttitle":["Cracking nuts with a sledgehammer"],"title":["Cracking nuts with a sledgehammer: When modern graph neural networks do worse than classical greedy algorithms"],"url":["http://arxiv.org/abs/2206.13211"],"urldate":["2022-08-03"]},"creators":{"author":[{"lastName":"Angelini","firstName":"Maria Chiara"},{"lastName":"Ricci-Tersenghi","firstName":"Federico"}]},"sentenceCased":true},{"key":"aniculaeseiHolisticSoftwareSystems2018","type":"inproceedings","fields":{"abstract":["Autonomous systems are gaining momentum in various application domains, such as autonomous vehicles, autonomous transport robotics and self-adaptation in smart homes. Product liability regulations impose high standards on manufacturers of such systems with respect to dependability (safety, security and privacy). Today's conventional engineering methods are not adequate for providing guarantees with respect to dependability requirements in a cost-efficient manner, e.g. road tests in the automotive industry sum up millions of miles before a system can be considered sufficiently safe. System engineers will no longer be able to test and respectively formally verify autonomous systems during development time in order to guarantee the dependability requirements in advance. In this vision paper, we introduce a new holistic software systems engineering approach for autonomous systems, which integrates development time methods as well as operation time techniques. With this approach, we aim to give the users a transparent view of the confidence level of the autonomous system under use with respect to the dependability requirements. We present already obtained results and point out research goals to be addressed in the future."],"author":["Aniculaesei, Adina","Grieser, Jörg","Rausch, Andreas","Rehfeldt, Karina","Warnecke, Tim"],"booktitle":["2018 IEEEACM 1st Int. Workshop Softw. Eng. AI Auton. Syst. SEFAIAS"],"date":["2018-05"],"eventtitle":["2018 IEEE/ACM 1st International Workshop on Software Engineering for AI in Autonomous Systems (SEFAIAS)"],"pages":["23–30"],"title":["Toward a Holistic Software Systems Engineering Approach for Dependable Autonomous Systems"],"url":["https://ieeexplore.ieee.org/document/8452726"],"urldate":["2023-09-28"]},"creators":{"author":[{"lastName":"Aniculaesei","firstName":"Adina"},{"lastName":"Grieser","firstName":"Jörg"},{"lastName":"Rausch","firstName":"Andreas"},{"lastName":"Rehfeldt","firstName":"Karina"},{"lastName":"Warnecke","firstName":"Tim"}]}},{"key":"aNoSQLImplementationConceptual2018","type":"article","fields":{"author":["A, Benmakhlouf"],"date":["2018-04-30"],"doi":["10.5121/ijdms.2018.10201"],"issn":["09755985, 09755705"],"journaltitle":["IJDMS"],"number":["2"],"pages":["01–10"],"shorttitle":["NoSQL Implementation of a Conceptual Data Model"],"title":["NoSQL Implementation of a Conceptual Data Model : UML Class Diagram to a Document Oriented Model"],"volume":["10"]},"creators":{"author":[{"lastName":"A","firstName":"Benmakhlouf"}]}},{"key":"Ansari2022190","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Cybern. Inf. Technol."],"affiliation":["CSED, MNNIT, Prayagraj, Allahabad, India"],"author":["Ansari, M.A.","Singh, D.K."],"date":["2022"],"document_type":["Article"],"doi":["10.2478/cait-2022-0012"],"issn":["13119702"],"journaltitle":["Cybern. Inf. Technol."],"note":["cited By 0"],"number":["1"],"pages":["190–200"],"publisher":["Sciendo"],"source":["Scopus"],"title":["ESAR, an expert shoplifting activity recognition system"],"volume":["22"]},"creators":{"author":[{"lastName":"Ansari","firstName":"M.A."},{"lastName":"Singh","firstName":"D.K."}]},"sentenceCased":true},{"key":"AnvikM11","type":"article","fields":{"author":["Anvik, John","Murphy, Gail C."],"date":["2011"],"journaltitle":["ACM Trans. Softw. Eng. Methodol."],"note":["TL;DR \n\nA machine learning approach to create recommenders that assist with a variety of decisions aimed at streamlining the development process and it is shown that recommenders for which developer should fix a bug can be quickly configured with this approach and that the configured recommenders are within 15% precision of hand-tuned developer recommenders."],"number":["3"],"pages":["10:1–10:35"],"title":["Reducing the effort of bug report triage: Recommenders for development-oriented decisions"],"volume":["20"]},"creators":{"author":[{"lastName":"Anvik","firstName":"John"},{"lastName":"Murphy","firstName":"Gail C."}]},"sentenceCased":true},{"key":"apache_log4j_2020","type":"misc","fields":{"author":["Apache"],"date":["2020-06"],"nourl":["https://logging.apache.org/log4j/2.x/"],"title":["Log4j – Apache Log4j 2"]},"creators":{"author":[{"literal":"Apache"}]}},{"key":"app10010012","type":"article","fields":{"abstract":["Currently, enterprises have to make quick and resilient responses to changing market requirements. In light of this, low-code development platforms provide the technology mechanisms to facilitate and automate the development of software applications to support current enterprise needs and promote digital transformation. Based on a theory-building research methodology through the literature and other information sources review, the main contribution of this paper is the current characterisation of the emerging low-code domain following the foundations of the computer-aided software engineering field. A context analysis, focused on the current status of research related to the low-code development platforms, is performed. Moreover, benchmarking among the existing low-code development platforms addressed to manufacturing industry is analysed to identify the current lacking features. As an illustrative example of the emerging low-code paradigm and respond to the identified uncovered features, the virtual factory open operating system (vf-OS) platform is described as an open multi-sided low-code framework able to manage the overall network of a collaborative manufacturing and logistics environment that enables humans, applications, and Internet of Things (IoT) devices to seamlessly communicate and interoperate in the interconnected environment, promoting resilient digital transformation."],"author":["Sanchis, Raquel","García-Perales, Óscar","Fraile, Francisco","Poler, Raul"],"date":["2020"],"doi":["10.3390/app10010012"],"issn":["2076-3417"],"issue":["1"],"journaltitle":["Appl. Sci."],"note":["TL;DR \n\nThe main contribution of this paper is the current characterisation of the emerging low-code domain following the foundations of the computer-aided software engineering field."],"number":["12"],"title":["Low-code as enabler of digital transformation in manufacturing industry"],"volume":["10"]},"creators":{"author":[{"lastName":"Sanchis","firstName":"Raquel"},{"lastName":"García-Perales","firstName":"Óscar"},{"lastName":"Fraile","firstName":"Francisco"},{"lastName":"Poler","firstName":"Raul"}]},"sentenceCased":true},{"key":"ApplicationofAIandMLinIoTPdf","type":"article","fields":{"entrysubtype":["newspaper"],"keywords":["internet of things"],"note":["<b>Green Annotations (17/12/2020, 14:33:13)</b> \n\n\"IoT with AI and ML in industries has the potential to transform their outputs and aid them to yield better results\" (<a href=\"zotero://open-pdf/library/items/RXAEHVFX?page=13\"> :13</a>) \n\n\"he industries may also use connected tools and machinery that eliminate the chances of errors made while setting the parameters manually.\" (<a href=\"zotero://open-pdf/library/items/RXAEHVFX?page=13\"> :13</a>) \n\n\"In the future, it will be nearly impossible to find IoT systems that don't utilize AI services\" (<a href=\"zotero://open-pdf/library/items/RXAEHVFX?page=18\"> :18</a>) \n\n\"the future of IoT is AI\" (<a href=\"zotero://open-pdf/library/items/RXAEHVFX?page=18\"> :18</a>) \n\n\"he main purpose is to make life easier by working smarter and not harder.\" (<a href=\"zotero://open-pdf/library/items/RXAEHVFX?page=18\"> :18</a>) \n\n\"t is expected that in the future, we will have devices that will make our lives more convenient than it is today by performing our tasks timely, even before we think of doing it, and give us real-time data and insights about every aspect of our livesbe it personal, professional or social.\" (<a href=\"zotero://open-pdf/library/items/RXAEHVFX?page=18\"> :18</a>) \n\n\"automation which will bring out the true essence of IoT\" (<a href=\"zotero://open-pdf/library/items/RXAEHVFX?page=18\"> :18</a>)"],"title":["ApplicationofAIandMLinIoT.Pdf"]},"creators":{}},{"key":"aranegaUsingFeatureModel2012","type":"article","fields":{"author":["Aranega, Vincent","Etien, Anne","Mosser, Sebastien"],"date":["2012"],"doi":["10.1007/978-3-642-33666-9_36"],"journaltitle":["Model Driven Eng. Lang. Syst."],"pages":["562–578"],"title":["Using Feature Model to Build Model Transformation Chains"],"volume":["7590"]},"creators":{"author":[{"lastName":"Aranega","firstName":"Vincent"},{"lastName":"Etien","firstName":"Anne"},{"lastName":"Mosser","firstName":"Sebastien"}]}},{"key":"arcainiModelingAnalyzingMAPEK2015","type":"inproceedings","fields":{"langid":["english"],"abstract":["The MAPE-K (Monitor-Analyze-Plan-Execute over a shared Knowledge) feedback loop is the most influential reference control model for autonomic and self-adaptive systems. This paper presents a conceptual and methodological framework for formal modeling, validating, and verifying distributed self-adaptive systems. We show how MAPE-K loops for selfadaptation can be naturally specified in an abstract stateful language like Abstract State Machines. In particular, we exploit the concept of multi-agent Abstract State Machines to specify decentralized adaptation control by using MAPE computations. We support techniques for validating and verifying adaptation scenarios, and getting feedback of the correctness of the adaptation logic as implemented by the MAPE-K loops. In particular, a verification technique based on meta-properties is proposed to allow discovering unwanted interferences between MAPE-K loops at the early stages of the system design. As a proof-ofconcepts, we model and analyze a traffic monitoring system."],"author":["Arcaini, Paolo","Riccobene, Elvinia","Scandurra, Patrizia"],"booktitle":["2015 IEEEACM 10th Int. Symp. Softw. Eng. Adapt. Self-Manag. Syst."],"date":["2015-05"],"doi":["10.1109/SEAMS.2015.10"],"eventtitle":["2015 IEEE/ACM 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)"],"isbn":["978-0-7695-5567-6"],"location":["Florence, Italy"],"pages":["13–23"],"publisher":["IEEE"],"title":["Modeling and Analyzing MAPE-K Feedback Loops for Self-Adaptation"]},"creators":{"author":[{"lastName":"Arcaini","firstName":"Paolo"},{"lastName":"Riccobene","firstName":"Elvinia"},{"lastName":"Scandurra","firstName":"Patrizia"}]}},{"key":"ArchivaDocumentationInstalling","type":"online","fields":{"title":["Archiva Documentation - Installing Apache Archiva"],"url":["http://archiva.apache.org/docs/2.2.0/adminguide/installing.html"],"urldate":["2015-04-16"]},"creators":{}},{"key":"Areferencearchitecturefortheinternetofthings","type":"article","fields":{"keywords":["iot","reference architecture","se4as"],"title":["A-reference-architecture-for-the-internet-of-things"]},"creators":{},"sentenceCased":true},{"key":"arendtEMFMetricsSpecification","type":"article","fields":{"author":["Arendt, Thorsten","Stepien, Pawel","Taentzer, Gabriele"],"note":["TL;DR \n\nEMF Metrics is presented, a prototype Eclipse plug-in providing specification and calculation of metrics wrt."],"title":["EMF Metrics: Specification and Calculation of Model Metrics within the Eclipse Modeling Framework"]},"creators":{"author":[{"lastName":"Arendt","firstName":"Thorsten"},{"lastName":"Stepien","firstName":"Pawel"},{"lastName":"Taentzer","firstName":"Gabriele"}]}},{"key":"arendtIntegrationSmellsRefactorings2012","type":"article","fields":{"author":["Arendt, Thorsten","Taentzer, Gabriele"],"date":["2012"],"doi":["10.1145/2328876.2328878"],"journaltitle":["Proc. Fifth Workshop Refactoring Tools - WRT 12"],"pages":["8–15"],"title":["Integration of smells and refactorings within the Eclipse modeling framework"]},"creators":{"author":[{"lastName":"Arendt","firstName":"Thorsten"},{"lastName":"Taentzer","firstName":"Gabriele"}]},"sentenceCased":true},{"key":"arendtToolEnvironmentQuality2012","type":"article","fields":{"author":["Arendt, Thorsten","Taentzer, Gabriele"],"date":["2012"],"doi":["10.1007/s10515-012-0114-7"],"journaltitle":["Autom. Softw. Eng."],"note":["TL;DR \n\nThis paper presents a tool environment conveniently supporting the proposed model quality assurance process, and presents tools support metrics reporting, smell detection, and refactoring for models being based on the Eclipse Modeling Framework."],"number":["2"],"pages":["141–184"],"title":["A tool environment for quality assurance based on the Eclipse Modeling Framework"],"volume":["20"]},"creators":{"author":[{"lastName":"Arendt","firstName":"Thorsten"},{"lastName":"Taentzer","firstName":"Gabriele"}]},"sentenceCased":true},{"key":"arhippainenUseIntegrationThridparty2003","type":"book","fields":{"langid":["english"],"author":["Arhippainen, Leena"],"date":["2003"],"isbn":["978-951-38-6032-5 978-951-38-6033-2"],"keywords":["software engineering"],"location":["Espoo"],"note":["Internet-Adresse: URL: http://www.inf.vtt.fi/pdf"],"number":["489"],"pagetotal":["68"],"publisher":["VTT"],"series":["VTT publications"],"title":["Use and integration of thrid-party components in software development"]},"creators":{"author":[{"lastName":"Arhippainen","firstName":"Leena"}]},"sentenceCased":true},{"key":"ariasOrccadRobotController2010","type":"inproceedings","fields":{"author":["Arias, Soraya","Boudin, Florine","Pissard-Gibollet, Roger","Simon, Daniel"],"booktitle":["5th Natl. Conf. Control Archit. Robots"],"date":["2010"],"title":["Orccad, robot controller model and its support using eclipse modeling tools"],"url":["https://hal.archives-ouvertes.fr/inria-00482559/"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Arias","firstName":"Soraya"},{"lastName":"Boudin","firstName":"Florine"},{"lastName":"Pissard-Gibollet","firstName":"Roger"},{"lastName":"Simon","firstName":"Daniel"}]},"sentenceCased":true},{"key":"arkinModelDrivenTransformationsMapping2013","type":"article","fields":{"author":["Arkin, Ethem","Tekinerdogan, Bedir"],"date":["2013"],"journaltitle":["MDHPCL MoDELS"],"pages":["63–72"],"title":["Model-Driven Transformations for Mapping Parallel Algorithms on Parallel Computing Platforms."],"url":["http://ceur-ws.org/Vol-1118/08-paper.pdf"],"urldate":["2017-02-23"],"volume":["2013"]},"creators":{"author":[{"lastName":"Arkin","firstName":"Ethem"},{"lastName":"Tekinerdogan","firstName":"Bedir"}]}},{"key":"arlot2010","type":"article","fields":{"added-at":["2017-04-15T09:32:51.000+0200"],"author":["Arlot, Sylvain","Celisse, Alain"],"biburl":["https://www.bibsonomy.org/bibtex/295dfb73fc5adfb8b1c5dba6435132f15/becker"],"date":["2010"],"fjournal":["Statistics Surveys"],"ids":["arlot2010survey"],"interhash":["ce81fa08863c054ec939cc798387b0b8"],"intrahash":["95dfb73fc5adfb8b1c5dba6435132f15"],"journaltitle":["Stat. Surv"],"keywords":["cross validation inthesis diss citedby:scholar:count:1216 citedby:scholar:timestamp:2017-4-15"],"nodoi":["10.1214/09-SS054"],"note":["TL;DR \n\nThis survey intends to relate the model selection performances of cross-validation procedures to the most recent advances of model selection theory, with a particular emphasis on distinguishing empirical statements from rigorous theoretical results."],"pages":["40–79"],"publisher":["The American Statistical Association, the Bernoulli Society, the Institute of Mathematical Statistics, and the Statistical Society of Canada"],"timestamp":["2017-04-15T09:32:51.000+0200"],"title":["A survey of cross-validation procedures for model selection"],"volume":["4"]},"creators":{"author":[{"lastName":"Arlot","firstName":"Sylvain"},{"lastName":"Celisse","firstName":"Alain"}]},"sentenceCased":true},{"key":"article","type":"article","fields":{"author":["Brun, Cédric","Pierantonio, Alfonso"],"date":["2008-01"],"journaltitle":["UPGRADE Eur. J. Inform. Prof."],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["29–34"],"title":["Model differences in the eclipse modelling framework"],"volume":["9"]},"creators":{"author":[{"lastName":"Brun","firstName":"Cédric"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"Aspenberg2013245","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Eng Optim"],"affiliation":["Division of Solid Mechanics, Linköping University, SE-581 83, Linköping, Sweden; Volvo Cars Safety Centre, SE-405 31, Göteborg, Sweden"],"author":["Aspenberg, D.","Jergeus, J.","Nilsson, L."],"coden":["EGOPA"],"correspondence_address1":["Aspenberg, D.; Division of Solid Mechanics, , SE-581 83, Linköping, Sweden; email: david.aspenberg@liu.se"],"date":["2013"],"document_type":["Article"],"doi":["10.1080/0305215X.2012.669380"],"issn":["0305215X"],"journaltitle":["Eng. Optim."],"note":["cited By 14"],"number":["3"],"pages":["245–264"],"source":["Scopus"],"title":["Robust optimization of front members in a full frontal car impact"],"volume":["45"]},"creators":{"author":[{"lastName":"Aspenberg","firstName":"D."},{"lastName":"Jergeus","firstName":"J."},{"lastName":"Nilsson","firstName":"L."}]},"sentenceCased":true},{"key":"assmannReferenceArchitectureRoadmap2014","type":"incollection","fields":{"author":["A\\s smann, Uwe","Götz, Sebastian","Jézéquel, Jean-Marc","Morin, Brice","Trapp, Mario"],"booktitle":["Models@ run. Time"],"date":["2014"],"pages":["1–18"],"publisher":["Springer"],"title":["A reference architecture and roadmap for Models@ run. Time systems"],"url":["http://link.springer.com/chapter/10.1007/978-3-319-08915-7_1"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"A\\s smann","firstName":"Uwe"},{"lastName":"Götz","firstName":"Sebastian"},{"lastName":"Jézéquel","firstName":"Jean-Marc"},{"lastName":"Morin","firstName":"Brice"},{"lastName":"Trapp","firstName":"Mario"}]},"sentenceCased":true},{"key":"atkinson2016demystifying","type":"inproceedings","fields":{"langid":["english"],"author":["Atkinson, Colin","Kühne, Thomas"],"booktitle":["Model. Found. Appl. 12th Eur. Conf. ECMFA 2016 Held Part STAF 2016 Vienna Austria July 6-7 2016 Proc. 12"],"date":["2016"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["83–100"],"publisher":["Springer"],"title":["Demystifying ontological classification in language engineering"]},"creators":{"author":[{"lastName":"Atkinson","firstName":"Colin"},{"lastName":"Kühne","firstName":"Thomas"}]},"sentenceCased":true},{"key":"AtkinsonK03a","type":"article","fields":{"langid":["english"],"author":["Atkinson, Colin","Kühne, Thomas"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2003"],"doi":["10.1109/MS.2003.1231149"],"journaltitle":["IEEE Softw,"],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["5"],"pages":["36–41"],"timestamp":["Mon, 15 Feb 2021 14:16:47 +0100"],"title":["Model-driven development: A metamodeling foundation"],"volume":["20"]},"creators":{"author":[{"lastName":"Atkinson","firstName":"Colin"},{"lastName":"Kühne","firstName":"Thomas"}]},"sentenceCased":true},{"key":"atkinsonUnifyingApproachConnections","type":"article","fields":{"author":["Atkinson, Colin","Gerbig, Ralph","Kühne, Thomas"],"title":["A Unifying Approach to Connections for Multi-Level Modeling"],"url":["http://homepages.ecs.vuw.ac.nz/~tk/publications/papers/deep-connections.pdf"],"urldate":["2015-09-24"]},"creators":{"author":[{"lastName":"Atkinson","firstName":"Colin"},{"lastName":"Gerbig","firstName":"Ralph"},{"lastName":"Kühne","firstName":"Thomas"}]}},{"key":"ATL","type":"article","fields":{"langid":["english"],"author":["Jouault, Frédéric","Allilaire, Freddy","Bézivin, Jean","Kurtev, Ivan"],"date":["2008"],"issn":["0167-6423"],"journaltitle":["Sci. Comput. Program."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["1-2"],"pages":["31–39"],"title":["ATL: A model transformation tool"],"volume":["72"],"x-doi":["DOI: 10.1016/j.scico.2007.08.002"]},"creators":{"author":[{"lastName":"Jouault","firstName":"Frédéric"},{"lastName":"Allilaire","firstName":"Freddy"},{"lastName":"Bézivin","firstName":"Jean"},{"lastName":"Kurtev","firstName":"Ivan"}]},"sentenceCased":true},{"key":"Atouani202155","type":"article","fields":{"langid":["english"],"abbrev_source_title":["GPCE - Proc. ACM SIGPLAN Int. Conf. Gener. Program.: Concepts Exp., co-located SPLASH"],"abstract":["Machine learning is a discipline which has become ubiquitous in the last few years. While the research of machine learning algorithms is very active and continues to reveal astonishing possibilities on a regular basis, the wide usage of these algorithms is shifting the research focus to the integration, maintenance, and evolution of AI-driven systems. Although there is a variety of machine learning frameworks on the market, there is little support for process automation and DevOps in machine learning-driven projects. In this paper, we discuss how metamodels can support the development of deep learning frameworks and help deal with the steadily increasing variety of learning algorithms. In particular, we present a deep learning-oriented artifact model which serves as a foundation for build automation and data management in iterative, machine learning-driven development processes. Furthermore, we show how schema and reference models can be used to structure and maintain a versatile deep learning framework. Feasibility is demonstrated on several state-of-the-art examples from the domains of image and natural language processing as well as decision making and autonomous driving."],"affiliation":["Rwth Aachen University, Germany"],"author":["Atouani, Abdallah","Kirchhof, Jörg Christian","Kusmenko, Evgeny","Rumpe, Bernhard"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1145/3486609.3487199"],"note":["cited By 0 \n\nTL;DR \n\nA deep learning-oriented artifact model is presented which serves as a foundation for build automation and data management in iterative, machine learning-driven development processes and it is shown how schema and reference models can be used to structure and maintain a versatile deep learning framework."],"pages":["55–68"],"series":["GPCE 2021 - Proceedings of the 20th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, co-located with SPLASH 2021"],"source":["Scopus"],"title":["Artifact and Reference Models for Generative Machine Learning Frameworks and Build Systems"]},"creators":{"author":[{"lastName":"Atouani","firstName":"Abdallah"},{"lastName":"Kirchhof","firstName":"Jörg Christian"},{"lastName":"Kusmenko","firstName":"Evgeny"},{"lastName":"Rumpe","firstName":"Bernhard"}]},"sentenceCased":true},{"key":"atzeniDataModelDescriptions2011","type":"article","fields":{"langid":["english"],"author":["Atzeni, Paolo","Gianforme, Giorgio","Cappellari, Paolo"],"date":["2011-12"],"doi":["10.1007/s10472-012-9277-y"],"issn":["1012-2443, 1573-7470"],"journaltitle":["Ann. Math. Artif. Intell."],"note":["TL;DR \n\nAn approach where translations are specified as Datalog-like programs is considered, which shows that the target model of a translation can be completely characterized given the description of the source model and the signatures of the rules."],"number":["3-4"],"pages":["287–315"],"title":["Data model descriptions and translation signatures in a multi-model framework"],"volume":["63"]},"creators":{"author":[{"lastName":"Atzeni","firstName":"Paolo"},{"lastName":"Gianforme","firstName":"Giorgio"},{"lastName":"Cappellari","firstName":"Paolo"}]},"sentenceCased":true},{"key":"atzeniModelindependentSchemaTranslation2008","type":"article","fields":{"langid":["english"],"author":["Atzeni, Paolo","Cappellari, Paolo","Torlone, Riccardo","Bernstein, Philip A.","Gianforme, Giorgio"],"date":["2008-11"],"doi":["10.1007/s00778-008-0105-2"],"issn":["1066-8888, 0949-877X"],"journaltitle":["VLDB J."],"note":["TL;DR \n\nA proposal for the implementation of the model management operator ModelGen, which translates schemas from one model to another, for example from object-oriented to SQL or from SQL to XML schema descriptions, is discussed."],"number":["6"],"pages":["1347–1370"],"title":["Model-independent schema translation"],"volume":["17"]},"creators":{"author":[{"lastName":"Atzeni","firstName":"Paolo"},{"lastName":"Cappellari","firstName":"Paolo"},{"lastName":"Torlone","firstName":"Riccardo"},{"lastName":"Bernstein","firstName":"Philip A."},{"lastName":"Gianforme","firstName":"Giorgio"}]},"sentenceCased":true},{"key":"atzeniModelsNoSQLDatabases2015","type":"incollection","fields":{"langid":["english"],"author":["Atzeni, Paolo"],"booktitle":["Advances in Conceptual Modeling"],"date":["2015"],"doi":["10.1007/978-3-319-25747-1_13"],"editor":["Jeusfeld, Manfred A.","Karlapalem, Kamalakar"],"isbn":["978-3-319-25746-4 978-3-319-25747-1"],"location":["Cham"],"note":["TL;DR \n\nThis talk will discuss how traditional notions related to modeling can be useful in this context as well, both in the search for standardization and uniform access and in the support to generic approaches to logical and physical design."],"pages":["133–133"],"publisher":["Springer International Publishing"],"shorttitle":["Models for NoSQL Databases"],"title":["Models for NoSQL Databases: A Contradiction?"],"volume":["9382"]},"creators":{"author":[{"lastName":"Atzeni","firstName":"Paolo"}],"editor":[{"lastName":"Jeusfeld","firstName":"Manfred A."},{"lastName":"Karlapalem","firstName":"Kamalakar"}]}},{"key":"atzeniRuntimeApproachModelgeneric2012","type":"article","fields":{"langid":["english"],"author":["Atzeni, Paolo","Bellomarini, Luigi","Bugiotti, Francesca","Celli, Fabrizio","Gianforme, Giorgio"],"date":["2012-05"],"doi":["10.1016/j.is.2011.11.003"],"issn":["03064379"],"journaltitle":["Inf. Syst."],"number":["3"],"pages":["269–287"],"title":["A runtime approach to model-generic translation of schema and data"],"volume":["37"]},"creators":{"author":[{"lastName":"Atzeni","firstName":"Paolo"},{"lastName":"Bellomarini","firstName":"Luigi"},{"lastName":"Bugiotti","firstName":"Francesca"},{"lastName":"Celli","firstName":"Fabrizio"},{"lastName":"Gianforme","firstName":"Giorgio"}]},"sentenceCased":true},{"key":"atzeniUniformAccessNoSQL2014","type":"article","fields":{"langid":["english"],"author":["Atzeni, Paolo","Bugiotti, Francesca","Rossi, Luca"],"date":["2014-07"],"doi":["10.1016/j.is.2013.05.002"],"issn":["03064379"],"journaltitle":["Inf. Syst."],"pages":["117–133"],"title":["Uniform access to NoSQL systems"],"volume":["43"]},"creators":{"author":[{"lastName":"Atzeni","firstName":"Paolo"},{"lastName":"Bugiotti","firstName":"Francesca"},{"lastName":"Rossi","firstName":"Luca"}]},"sentenceCased":true},{"key":"atzeniUniversalMetamodelIts2009","type":"incollection","fields":{"langid":["english"],"abstract":["We discuss a universal metamodel aimed at the representation of schemas in a way that is at the same time model-independent (in the sense that it allows for a uniform representation of different data models) and model-aware (in the sense that it is possible to say to whether a schema is allowed for a data model). This metamodel can be the basis for the definition of a complete model-management system. Here we illustrate the details of the metamodel and the structure of a dictionary for its representation. Exemplifications of a concrete use of the dictionary are provided, by means of the representations of the main data models, such as relational, object-relational or XSD-based. Moreover, we demonstrate how set operators can be redefined with respect to our dictionary and easily applied on it. Finally, we show how such a dictionary can be exploited to automatically produce detailed descriptions of schema and data models, in a textual (i.e. XML) or visual (i.e. UML class diagram) way."],"author":["Atzeni, Paolo","Gianforme, Giorgio","Cappellari, Paolo"],"booktitle":["Transactions on Large-Scale Data- and Knowledge-Centered Systems I"],"date":["2009"],"doi":["10.1007/978-3-642-03722-1_2"],"editor":["Hameurlain, Abdelkader","Küng, Josef","Wagner, Roland"],"isbn":["978-3-642-03721-4 978-3-642-03722-1"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nA universal metamodel aimed at the representation of schemas in a way that is at the same time model-independent and model-aware is discussed, which can be the basis for the definition of a complete model-management system."],"pages":["38–62"],"publisher":["Springer Berlin Heidelberg"],"title":["A Universal Metamodel and Its Dictionary"],"volume":["5740"]},"creators":{"author":[{"lastName":"Atzeni","firstName":"Paolo"},{"lastName":"Gianforme","firstName":"Giorgio"},{"lastName":"Cappellari","firstName":"Paolo"}],"editor":[{"lastName":"Hameurlain","firstName":"Abdelkader"},{"lastName":"Küng","firstName":"Josef"},{"lastName":"Wagner","firstName":"Roland"}]}},{"key":"atzoriInternetThingsSurvey2010","type":"article","fields":{"langid":["english"],"abstract":["This paper addresses the Internet of Things. Main enabling factor of this promising paradigm is the integration of several technologies and communications solutions. Identification and tracking technologies, wired and wireless sensor and actuator networks, enhanced communication protocols (shared with the Next Generation Internet), and distributed intelligence for smart objects are just the most relevant. As one can easily imagine, any serious contribution to the advance of the Internet of Things must necessarily be the result of synergetic activities conducted in different fields of knowledge, such as telecommunications, informatics, electronics and social science. In such a complex scenario, this survey is directed to those who want to approach this complex discipline and contribute to its development. Different visions of this Internet of Things paradigm are reported and enabling technologies reviewed. What emerges is that still major issues shall be faced by the research community. The most relevant among them are addressed in details."],"author":["Atzori, Luigi","Iera, Antonio","Morabito, Giacomo"],"date":["2010-10"],"doi":["10.1016/j.comnet.2010.05.010"],"issn":["13891286"],"journaltitle":["Computer Networks"],"keywords":["relevant"],"note":["TL;DR \n\nThe definitions, architecture, fundamental technologies, and applications of IoT are systematically reviewed and the major challenges which need addressing by the research community and corresponding potential solutions are investigated."],"number":["15"],"pages":["2787–2805"],"shorttitle":["The Internet of Things"],"title":["The Internet of Things: A survey"],"volume":["54"]},"creators":{"author":[{"lastName":"Atzori","firstName":"Luigi"},{"lastName":"Iera","firstName":"Antonio"},{"lastName":"Morabito","firstName":"Giacomo"}]},"sentenceCased":true},{"key":"augusteijnNeuralNetworkClassification2002","type":"article","fields":{"author":["Augusteijn, M. F.","B. A. Folkert"],"date":["2002"],"journaltitle":["Int. J. Remote Sens."],"nodoi":["10.1080/01431160110055804"],"number":["14"],"pages":["2891–2902"],"publisher":["Taylor & Francis"],"title":["Neural network classification and novelty detection"],"volume":["23"]},"creators":{"author":[{"lastName":"Augusteijn","firstName":"M. F."},{"literal":"B. A. Folkert"}]},"sentenceCased":true},{"key":"authorExtensionsScalabilityExperiments2024","type":"article","fields":{"langid":["english"],"abstract":["Until recently, the state-of-the-art of Software Product Line (SPL) configuration and verification automation consisted of a collection of ad-hoc approaches tightly coupling a single input Variability Modeling Language (VML) with a single constraint solver. To remedy this situation, a novel generic Model-Driven Architecture (MDA) was then proposed that enables using a variety of VMLs and solvers. The key ideas of this proposal were (a) the use of a standard logical language (CLIF) as a pivot between VMLs and solvers, and (b) the use of a standard data exchange format (JSON) to explicilty and declaratively specify the abstract syntax and semantics of the VMLs to be used in an SPL engineering project and the automated reasoning task to be performed by the solvers."],"author":["Author, Anonymous"],"date":["2024"],"title":["Extensions and Scalability Experiments of a Generic Model-Driven Architecture for Variability Model Reasoning"]},"creators":{"author":[{"lastName":"Author","firstName":"Anonymous"}]}},{"key":"authorMetricRecommendationService","type":"article","fields":{"langid":["english"],"abstract":["Today’s monitoring and failure management mechanisms for online systems heavily rely on metrics, which are time series data that can describe the real-time state of a system from various perspectives. Though several attempts have been devoted to automatic failure management based on metrics, the primary step, metric selection, remains manual to a large extent. To better understand the prior practice, we conduct an empirical study on the selected metrics in prior work and obtain some findings. Based on the findings, we develop a metric recommendation service for online systems, which can automate the metrics selection practice and greatly ease the burden in managing an online system. Specifically, we analyze the needs of two key failure management tasks, i.e., anomaly detection and fault diagnosis, and design metric recommendation mechanisms for them respectively. Graph learning techniques are employed in the automation of metric recommendation. Our experiments demonstrate that the proposed approach can achieve an F1score of 0.912 in selecting metrics for anomaly detection, and an accuracy of 0.859 in retrieving metrics for faults diagnosis, which significantly outperforms the compared baselines."],"author":["Author, Anonymous"],"pages":["12"],"title":["A Metric Recommendation Service for Online Systems using Graph Learning"]},"creators":{"author":[{"lastName":"Author","firstName":"Anonymous"}]},"sentenceCased":true},{"key":"authorModelNotBuilt2024","type":"article","fields":{"langid":["english"],"abstract":["Conceptual modeling plays a crucial role in model-driven engineering. When the system description is highly complicated or the modelers lack sufficient domain knowledge, the task can become particularly challenging. Large language models (LLMs) can facilitate the task by automatically generating an initial conceptual model from the system description. Nevertheless, model generation is more complex than code generation, and a single prompt to LLMs cannot solve the problem well. This paper proposes an LLMbased conceptual modeling approach via question decomposition. Following conventional modeling guidelines, we divide the model generation task into several sub-problems, i.e., class generation, association and aggregation generation, and inheritance generation. For each sub-problem, we carefully design the prompt by choosing more efficient query words and providing essential modeling knowledge to unlock the modeling potential of LLMs. Finally, we sum up the answers of all the sub-problems and programmatically create a conceptual model to avoid trivial syntactic model errors. We evaluate our approach with 10 systems from different application domains. The preliminary results show that our approach outperforms the singe-prompt-based baseline by improving recall values and F1 scores in most systems."],"author":["Author, Anonymous"],"date":["2024"],"title":["A Model Is Not Built By A Single Prompt: LLM-Based Conceptual Modeling With Question Decomposition"]},"creators":{"author":[{"lastName":"Author","firstName":"Anonymous"}]}},{"key":"authorTopFilterApproachRecommend2020","type":"article","fields":{"langid":["english"],"author":["Author, Anonymous"],"date":["2020"],"note":["TL;DR \n\nThe results confirm that collaborative filtering techniques can successfully be used to provide relevant topics for GitHub repositories, and show that TopFilter can gain a significant boost in prediction performances by employing the outcomes obtained by the MNB network as its initial set of topics."],"pages":["11"],"title":["TopFilter: An Approach to Recommend Relevant GitHub Topics"]},"creators":{"author":[{"lastName":"Author","firstName":"Anonymous"}]}},{"key":"autiliEAGLEEngineeringSoftwAre2011","type":"inproceedings","fields":{"abstract":["\"In the next future we will be surrounded by a virtually infinite number of software applications that provide computational software resources in the open Globe. This will radically change the way software will be produced and used. Users will be keen on producing their own piece of software, by also reusing existing software, to better satisfy their needs, therefore with a goal oriented, opportunistic use in mind. The produced software will need to be able to evolve, react and adapt to a continuously changing environment, while guaranteeing dependability. The strongest adversary to this view is the lack of knowledge on the software's structure, behavior, and execution context. Despite the possibility to extract observational models from existing software, a producer will always operate with software artifacts that exhibit a degree of uncertainty in terms of their functional and non functional characteristics. We believe that uncertainty can only be controlled by making it explicit and by using it to drive the production process itself. In this paper, we introduce a novel paradigm of software production process that explores available software and assesses its degree of uncertainty in relation to the opportunistic goal G, assists the producer in creating the appropriate integration means towards G, and validates the quality of the integrated system with respect to G and the current context.\""],"author":["Autili, M","Cortellessa, V","Di Ruscio, D","Inverardi, P","Pelliccione, P","Tivoli, M"],"booktitle":["SIGSOFTFSE11 19th ACM SIGSOFT Symp. Found. Softw. Eng. FSE-19 ESEC11 13th Eur. Softw. Eng. Conf. ESEC-13 Szeged Hung. Sept. 5-9 2011"],"date":["2011"],"doi":["10.1145/2025113.2025199"],"ids":["autiliEAGLEEngineeringSoftwAre2011a,autiliEAGLEEngineeringSoftwAre2011b,autiliEAGLEEngineeringSoftware2011"],"isbn":["978-1-4503-0443-6"],"location":["NEW YORK, NY, USA"],"note":["cited By 15 \n\ncited By 15 \n\nTL;DR \n\nA novel paradigm of software production process is introduced that explores available software and assesses its degree of uncertainty in relation to the opportunistic goal G, assists the producer in creating the appropriate integration means towards G, and validates the quality of the integrated system with respect to G and the current context."],"pages":["488–491"],"publisher":["Association for Computing Machinery, Inc. (ACM)"],"title":["EAGLE: Engineering softwAre in the ubiquitous Globe by Leveraging uncErtainty"]},"creators":{"author":[{"lastName":"Autili","firstName":"M"},{"lastName":"Cortellessa","firstName":"V"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Inverardi","firstName":"P"},{"lastName":"Pelliccione","firstName":"P"},{"lastName":"Tivoli","firstName":"M"}]},"sentenceCased":true},{"key":"autiliIntegrationArchitectureSynthesis2012","type":"inproceedings","fields":{"abstract":["\"\\\"\\\"The abundance of software that will be more and more available will promote the production of appropriate integration means (architectures, connectors, integration patterns). The produced software will need to be able to evolve, react and adapt quickly to a continuously changing environment, while guaranteeing dependability through (on-the-fly) validation. The strongest adversary to this view is the lack of information about the software, notably about its structure, behavior, and execution context. Despite the possibility to extract observational models from existing software, a producer will always operate with software artifacts that exhibit a degree of uncertainty in terms of their functional and non functional characteristics. Uncertainty can only be controlled by making it explicit and by using it to drive the production process itself. This calls for a production process that explores available software and assesses its degree of uncertainty in relation to the opportunistic goal G, assists the producer in creating the appropriate integration means towards G, and validates the quality of the integrated system with respect to the goal G and the current context. In this paper we discuss how goal-oriented software systems can be opportunistically created by integrating under uncertainty existing pieces of software. © 2012 Springer-Verlag.\\\"\\\"\""],"author":["Autili, Marco","Cortellessa, Vittorio","DI RUSCIO, Davide","Inverardi, Paola","Pelliccione, Patrizio","Tivoli, Massimo"],"booktitle":["Large-Scale Complex IT Syst. Dev. Oper. Manag. - 17th Monterey Workshop 2012 Oxf. UK March 19-21 2012 Revis. Sel. Pap. Lect. Notes Comput. Sci."],"date":["2012"],"doi":["10.1007/978-3-642-34059-8_6"],"ids":["autiliIntegrationArchitectureSynthesis2012a,autiliIntegrationArchitectureSynthesis2012b,autiliIntegrationArchitectureSynthesis2012c,autiliIntegrationArchitectureSynthesis2012d"],"isbn":["978-3-642-34058-1"],"location":["BERLIN HEIDELBERG"],"note":["cited By 10 \n\ncited By 10 \n\nTL;DR \n\nHow goal-oriented software systems can be opportunistically created by integrating under uncertainty existing pieces of software is discussed."],"pages":["118–131"],"publisher":["Springer-Verlag"],"series":["Lecture Notes in Computer Science"],"title":["Integration Architecture Synthesis for Taming Uncertainty in the Digital Space"],"volume":["7539 LNCS"]},"creators":{"author":[{"lastName":"Autili","firstName":"Marco"},{"lastName":"Cortellessa","firstName":"Vittorio"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Inverardi","firstName":"Paola"},{"lastName":"Pelliccione","firstName":"Patrizio"},{"lastName":"Tivoli","firstName":"Massimo"}]}},{"key":"autiliModelbasedSynthesisProcess2013","type":"inproceedings","fields":{"abstract":["\"\"The near future in service-oriented system development envisions a ubiquitous world of available services that collaborate to fit users’ needs. Modern service-oriented applications are often built by reusing and assembling distributed services. This can be done by considering a global specification of the interactions between the participant services, namely the choreography. In this paper, we propose a synthesis approach to automatically synthesize a choreography out of a specification of it and a set of services discovered as suitable participants. The synthesis is model-based in the sense that it works by assuming a finite state model of the services’s protocol and a BPMN model for the choreography specification. The result of the synthesis is a set of distributed components, called coordination delegates, that coordinate the services’ interaction in order to realize the specified choreography. The work advances the state-of-the-art in two directions: (i) we provide a solution to the problem of choreography realizability enforcement, and (ii) we provide a model-based tool chain to support the development of choreography-based systems.\"\""],"author":["Autili, Marco","DI RUSCIO, Davide","DI SALLE, Amleto","Inverardi, Paola","Tivoli, Massimo"],"booktitle":["Fundam. Approaches Softw. Eng. - 16th Int. Conf. FASE 2013 Held Part Eur. Jt. Conf. Theory Pract. Softw. ETAPS 2013 Rome Italy March 16-24 2013 Proc."],"date":["2013"],"doi":["10.1007/978-3-642-37057-1_4"],"ids":["autiliModelBasedSynthesisProcess2013,autiliModelbasedSynthesisProcess2013a,autiliModelbasedSynthesisProcess2013b"],"isbn":["978-3-642-37056-4"],"keywords":["Choreography Realizability Enforcement","Service Choreographies","Service Oriented Architectures"],"note":["cited By 38 \n\ncited By 38 \n\nTL;DR \n\nA synthesis approach to automatically synthesize a choreography out of a specification of it and a set of services discovered as suitable participants and provides a model-based tool chain to support the development of choreography-based systems."],"pages":["37–52"],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture Notes in Computer Science"],"title":["A model-based synthesis process for choreography realizability enforcement"],"volume":["7793 LNCS"]},"creators":{"author":[{"lastName":"Autili","firstName":"Marco"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"DI SALLE","firstName":"Amleto"},{"lastName":"Inverardi","firstName":"Paola"},{"lastName":"Tivoli","firstName":"Massimo"}]},"sentenceCased":true},{"key":"autiliModelLANDWhereModels2014","type":"incollection","fields":{"author":["Autili, Marco","DI RUSCIO, Davide","Inverardi, Paola","Pelliccione, Patrizio","Tivoli, Massimo"],"booktitle":["Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)"],"date":["2014"],"doi":["10.1007/978-3-319-08915-7_6"],"ids":["autiliModelLANDWhereModels2011,autiliModelLANDWhereModels2011a,autiliModelLANDWhereModels2014a,autiliModelLANDWhereModels2014b,autiliModelLANDWhereModels2014c"],"isbn":["978-3-319-08914-0"],"keywords":["Computer Science (all)","Theoretical Computer Science"],"note":["cited By 5 \n\ncited By 5 \n\nTL;DR \n\nThis work states that a flourishing of model-based engineering techniques has been defined for building, managing, verifying, validating and controlling software systems."],"pages":["162–187"],"publisher":["Springer Verlag"],"series":["Lecture Notes in Computer Science"],"title":["ModelLAND: Where do models come from?"],"volume":["LNCS 8378"]},"creators":{"author":[{"lastName":"Autili","firstName":"Marco"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Inverardi","firstName":"Paola"},{"lastName":"Pelliccione","firstName":"Patrizio"},{"lastName":"Tivoli","firstName":"Massimo"}]},"sentenceCased":true},{"key":"AutonomousSemiAutonomousSoftware","type":"online","fields":{"title":["Autonomous and Semi-Autonomous Software Systems"],"url":["http://aosgrp.com/featured-research/autonomy_and_agents/autonomous_systems/autonomous_and_semi-autonom.html"],"urldate":["2016-08-24"]},"creators":{}},{"key":"AutonomousSystems","type":"online","fields":{"title":["Autonomous Systems"],"url":["https://www.cranfield.ac.uk/Academic%20disciplines/Autonomous-Systems"],"urldate":["2016-08-21"]},"creators":{}},{"key":"AutonomousSystemsFormerly","type":"online","fields":{"title":["Autonomous Systems (formerly Unmanned Systems)"],"url":["http://www.northropgrumman.com/Capabilities/AutonomousSystems/Pages/default.aspx"],"urldate":["2016-08-26"]},"creators":{},"sentenceCased":true},{"key":"Autonomy","type":"online","fields":{"title":["Autonomy"],"url":["http://aosgrp.com/featured-research/autonomy_and_agents/autonomous_systems/autonomy.html"],"urldate":["2016-08-24"]},"creators":{}},{"key":"AutoTaskLearningGenerate2021","type":"article","fields":{"langid":["english"],"date":["2021"],"pages":["11"],"title":["AutoTask: Learning to Generate Machine Learning Pipelines"]},"creators":{}},{"key":"avgeriou_et_al:DR:2016:6693","type":"article","fields":{"author":["Avgeriou, Paris","Kruchten, Philippe","Ozkaya, Ipek","Seaman, Carolyn"],"date":["2016"],"doi":["10.4230/DagRep.6.4.110"],"editor":["Avgeriou, Paris","Kruchten, Philippe","Ozkaya, Ipek","Seaman, Carolyn"],"issn":["2192-5283"],"journaltitle":["Dagstuhl Rep."],"location":["Dagstuhl, Germany"],"nopublisher":["Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik"],"note":["Keywords: coding tools and techniques, design tools and techniques, management, metrics, software engineering \n\nTL;DR \n\nThis report documents the program and outcomes of Dagstuhl Seminar 16162, “Managing Technical Debt in Software Engineering,” and summarizes the goals and format, results from the breakout groups, and a definition for technical debt."],"nourl":["http://drops.dagstuhl.de/opus/volltexte/2016/6693"],"number":["4"],"pages":["110–138"],"title":["Managing technical debt in software engineering (dagstuhl seminar 16162)"],"urn":["urn:nbn:de:0030-drops-66938"],"volume":["6"]},"creators":{"author":[{"lastName":"Avgeriou","firstName":"Paris"},{"lastName":"Kruchten","firstName":"Philippe"},{"lastName":"Ozkaya","firstName":"Ipek"},{"lastName":"Seaman","firstName":"Carolyn"}],"editor":[{"lastName":"Avgeriou","firstName":"Paris"},{"lastName":"Kruchten","firstName":"Philippe"},{"lastName":"Ozkaya","firstName":"Ipek"},{"lastName":"Seaman","firstName":"Carolyn"}]},"sentenceCased":true},{"key":"avgeriouOverviewComparisonTechnical2021","type":"article","fields":{"langid":["english"],"abstract":["Different tools adopt different terms, metrics, and ways to identify and measure technical debt. We attempt to clarify the situation by comparing the features and popularity of technical debt measurement tools and analyzing the existing empirical evidence on their validity."],"author":["Avgeriou, Paris C.","Taibi, Davide","Ampatzoglou, Apostolos","Fontana, Francesca Arcelli","Besker, Terese","Chatzigeorgiou, Alexander","Lenarduzzi, Valentina","Martini, Antonio","Moschou, Athanasia","Pigazzini, Ilaria","Saarimaki, Nyyti","Sas, Darius Daniel","family=Toledo, given=Saulo Soares, prefix=de, useprefix=false","Tsintzira, Angeliki Agathi"],"date":["2021-05-01"],"doi":["10.1109/MS.2020.3024958"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nThis work attempts to clarify the situation by comparing the features and popularity of technical debt measurement tools and analyzing the existing empirical evidence on their validity."],"number":["03"],"pages":["61–71"],"publisher":["IEEE Computer Society"],"title":["An Overview and Comparison of Technical Debt Measurement Tools"],"volume":["38"]},"creators":{"author":[{"lastName":"Avgeriou","firstName":"Paris C."},{"lastName":"Taibi","firstName":"Davide"},{"lastName":"Ampatzoglou","firstName":"Apostolos"},{"lastName":"Fontana","firstName":"Francesca Arcelli"},{"lastName":"Besker","firstName":"Terese"},{"lastName":"Chatzigeorgiou","firstName":"Alexander"},{"lastName":"Lenarduzzi","firstName":"Valentina"},{"lastName":"Martini","firstName":"Antonio"},{"lastName":"Moschou","firstName":"Athanasia"},{"lastName":"Pigazzini","firstName":"Ilaria"},{"lastName":"Saarimaki","firstName":"Nyyti"},{"lastName":"Sas","firstName":"Darius Daniel"},{"lastName":"Toledo","firstName":"SauloSoares","prefix":"de","useprefix":false},{"lastName":"Tsintzira","firstName":"Angeliki Agathi"}]}},{"key":"avila2023chatgpt","type":"article","fields":{"author":["Avila-Chauvet, Laurent","Mejía, Diana","Acosta Quiroz, Christian Oswaldo"],"date":["2023"],"journaltitle":["Available SSRN 4329020"],"title":["Chatgpt as a support tool for online behavioral task programming"]},"creators":{"author":[{"lastName":"Avila-Chauvet","firstName":"Laurent"},{"lastName":"Mejía","firstName":"Diana"},{"lastName":"Acosta Quiroz","firstName":"Christian Oswaldo"}]},"sentenceCased":true},{"key":"avitabileDefeatingMassSurveillance","type":"article","fields":{"langid":["english"],"abstract":["Mass surveillance can be more easily achieved leveraging fear and desire of the population to feel protected while affected by devastating events. In such cases governments are more legitimate to adopt exceptional measures that limit civil rights, usually receiving large support from their citizens."],"author":["Avitabile, Gennaro","Botta, Vincenzo","Iovino, Vincenzo","Visconti, Ivan"],"note":["TL;DR \n\nTaking into account the privacy and integrity vulnerabilities of DP-3T systems, the design of a decentralized contact tracing system named Pronto-C2 is shown that has better resilience against various attacks."],"pages":["25"],"title":["Towards Defeating Mass Surveillance and SARS-CoV-2: The Pronto-C2 Fully Decentralized Automatic Contact Tracing System"]},"creators":{"author":[{"lastName":"Avitabile","firstName":"Gennaro"},{"lastName":"Botta","firstName":"Vincenzo"},{"lastName":"Iovino","firstName":"Vincenzo"},{"lastName":"Visconti","firstName":"Ivan"}]}},{"key":"azzaraPyoTMacroprogrammingFramework2014","type":"inproceedings","fields":{"author":["Azzara, Andrea","Alessandrelli, Daniele","Bocchino, Stefano","Petracca, Matteo","Pagano, Paolo"],"booktitle":["Ind. Embed. Syst. SIES 2014 9th IEEE Int. Symp. On"],"date":["2014"],"note":["TL;DR \n\nPyoT is presented, a framework designed to simplify the development of complex applications for the Internet of Things, coordinating the activities of group of nodes, adopting the macroprogramming paradigm."],"pages":["96–103"],"publisher":["IEEE"],"title":["PyoT, a macroprogramming framework for the Internet of Things"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6871193"],"urldate":["2016-05-30"]},"creators":{"author":[{"lastName":"Azzara","firstName":"Andrea"},{"lastName":"Alessandrelli","firstName":"Daniele"},{"lastName":"Bocchino","firstName":"Stefano"},{"lastName":"Petracca","firstName":"Matteo"},{"lastName":"Pagano","firstName":"Paolo"}]},"sentenceCased":true},{"key":"baba-cheikhPreliminaryStudyOpensource2020","type":"article","fields":{"langid":["english"],"abstract":["The Internet of Things (IoT) market is growing fast with an increasing number of connected devices. This led many software companies to shift their focus to develop and provide IoT solutions. IoT development has its own challenges as typical IoT solutions are composed of heterogeneous devices, protocols and software. To cope with these challenges, many frameworks are available to help developers to build IoT applications. Some of these frameworks are open source and might be of great interest for small and mediumsized companies wishing to build IoT solutions at a lower cost. In this paper, we present the results of a preliminary study of four open source IoT development frameworks. In particular, we used these frameworks to implement a sample of three IoT applications and we analyze them against a minimal set of IoT requirements. We focus in our study on the IoT development for Raspberry PI as it is a very low-cost and popular platform."],"author":["Baba-Cheikh, Zeineb","El-Boussaidi, Ghizlane","Gascon-Samson, Julien","Mili, Hafedh","Guéhéneuc, Yann-Gael"],"date":["2020"],"note":["TL;DR \n\nThis paper presents the results of a preliminary study of four open source IoT development frameworks used to implement a sample of three IoT applications and analyzes them against a minimal set of IoT requirements."],"pages":["8"],"title":["A preliminary study of open-source IoT development frameworks"]},"creators":{"author":[{"lastName":"Baba-Cheikh","firstName":"Zeineb"},{"lastName":"El-Boussaidi","firstName":"Ghizlane"},{"lastName":"Gascon-Samson","firstName":"Julien"},{"lastName":"Mili","firstName":"Hafedh"},{"lastName":"Guéhéneuc","firstName":"Yann-Gael"}]},"sentenceCased":true},{"key":"babaeigiglouLLMs4OLLargeLanguage2023","type":"inproceedings","fields":{"langid":["english"],"abstract":["We propose the LLMs4OL approach, which utilizes Large Language Models (LLMs) for Ontology Learning (OL). LLMs have shown significant advancements in natural language processing, demonstrating their ability to capture complex language patterns in different knowledge domains. Our LLMs4OL paradigm investigates the following hypothesis: Can LLMs effectively apply their language pattern capturing capability to OL, which involves automatically extracting and structuring knowledge from natural language text? To test this hypothesis, we conduct a comprehensive evaluation using the zero-shot prompting method. We evaluate nine different LLM model families for three main OL tasks: term typing, taxonomy discovery, and extraction of non-taxonomic relations. Additionally, the evaluations encompass diverse genres of ontological knowledge, including lexicosemantic knowledge in WordNet, geographical knowledge in GeoNames, and medical knowledge in UMLS."],"author":["Babaei Giglou, Hamed","D’Souza, Jennifer","Auer, Sören"],"booktitle":["Semantic Web – ISWC 2023"],"date":["2023"],"doi":["10.1007/978-3-031-47240-4_22"],"editor":["Payne, Terry R.","Presutti, Valentina","Qi, Guilin","Poveda-Villalón, María","Stoilos, Giorgos","Hollink, Laura","Kaoudi, Zoi","Cheng, Gong","Li, Juanzi"],"isbn":["978-3-031-47240-4"],"keywords":["Large Language Models","LLMs","Ontologies","Ontology Learning","Prompt-based Learning","Prompting"],"location":["Cham"],"pages":["408–427"],"publisher":["Springer Nature Switzerland"],"series":["Lecture Notes in Computer Science"],"shorttitle":["LLMs4OL"],"title":["LLMs4OL: Large Language Models for Ontology Learning"]},"creators":{"author":[{"lastName":"Babaei Giglou","firstName":"Hamed"},{"lastName":"D’Souza","firstName":"Jennifer"},{"lastName":"Auer","firstName":"Sören"}],"editor":[{"lastName":"Payne","firstName":"Terry R."},{"lastName":"Presutti","firstName":"Valentina"},{"lastName":"Qi","firstName":"Guilin"},{"lastName":"Poveda-Villalón","firstName":"María"},{"lastName":"Stoilos","firstName":"Giorgos"},{"lastName":"Hollink","firstName":"Laura"},{"lastName":"Kaoudi","firstName":"Zoi"},{"lastName":"Cheng","firstName":"Gong"},{"lastName":"Li","firstName":"Juanzi"}]}},{"key":"babikianAutomatedGenerationConsistent2020","type":"incollection","fields":{"langid":["english"],"author":["Babikian, Aren A.","Semeráth, Oszkár","Varró, Dániel"],"booktitle":["Fundamental Approaches to Software Engineering"],"date":["2020"],"doi":["10.1007/978-3-030-45234-6_22"],"editor":["Wehrheim, Heike","Cabot, Jordi"],"isbn":["978-3-030-45233-9 978-3-030-45234-6"],"keywords":["/unread","⛔ No INSPIRE recid found"],"location":["Cham"],"note":["TL;DR \n\nThis paper proposes a transformation technique to map such graph generation tasks to a problem consisting of first-order logic formulae, which can be solved by state-of-the-art TPTP-compliant theorem provers, producing valid graph models as outputs."],"pages":["441–461"],"publisher":["Springer International Publishing"],"title":["Automated generation of consistent graph models with first-order logic theorem provers"],"volume":["12076"]},"creators":{"author":[{"lastName":"Babikian","firstName":"Aren A."},{"lastName":"Semeráth","firstName":"Oszkár"},{"lastName":"Varró","firstName":"Dániel"}],"editor":[{"lastName":"Wehrheim","firstName":"Heike"},{"lastName":"Cabot","firstName":"Jordi"}]},"sentenceCased":true},{"key":"BabikianSLMV22","type":"article","fields":{"langid":["english"],"author":["Babikian, Aren A.","Semeráth, Oszkár","Li, Anqi","Marussy, Kristóf","Varró, Dániel"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2022"],"doi":["10.1007/S10270-021-00918-6"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["5"],"pages":["1763–1787"],"timestamp":["Tue, 06 Dec 2022 13:15:29 +0100"],"title":["Automated generation of consistent models using qualitative abstractions and exploration strategies"],"volume":["21"]},"creators":{"author":[{"lastName":"Babikian","firstName":"Aren A."},{"lastName":"Semeráth","firstName":"Oszkár"},{"lastName":"Li","firstName":"Anqi"},{"lastName":"Marussy","firstName":"Kristóf"},{"lastName":"Varró","firstName":"Dániel"}]},"sentenceCased":true},{"key":"Babur2016888","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["ASE - Proc. IEEE/ACM Int. Conf. Autom. Softw. Eng."],"affiliation":["Eindhoven University of Technology, Eindhoven, 5600 MB, Netherlands"],"author":["Babur, Ö."],"correspondence_address1":["Babur, Ö.; Eindhoven University of TechnologyNetherlands; email: O.Babur@tue.nl"],"date":["2016"],"document_type":["Conference Paper"],"doi":["10.1145/2970276.2975938"],"editor":["Khurshid S., Lo D., Apel S."],"isbn":["978-1-4503-3845-5"],"keywords":["GOAL_Model-Comparison","notion","TECHNIQUE_K-NEAREST-NEIGHBORS"],"note":["cited By 7 \n\nTL;DR \n\nThis work would like to develop a generic approach for model comparison and analysis for large datasets; using techniques from information retrieval, natural language processing and machine learning."],"pages":["888–891"],"publisher":["Association for Computing Machinery, Inc"],"series":["ASE 2016 - Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering"],"source":["Scopus"],"title":["Statistical analysis of large sets of models"]},"creators":{"author":[{"lastName":"Babur","firstName":"Ö."}],"editor":[{"lastName":"Khurshid S.","suffix":"Lo D.","firstName":"Apel S."}]},"sentenceCased":true},{"key":"Babur2018129","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Eindhoven University of Technology, Eindhoven, Netherlands; Wageningen University & Research, Wageningen, Netherlands; University of Twente, Enschede, Netherlands"],"author":["Babur, Ö.","Cleophas, L.","family=Brand, given=M., prefix=van den, useprefix=true","Tekinerdogan, B.","Aksit, M."],"correspondence_address1":["Babur, Ö.; Eindhoven University of TechnologyNetherlands; email: O.Babur@tue.nl"],"date":["2018"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-319-74730-9_10"],"editor":["Zschaler S., Seidl M."],"isbn":["9783319747293"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 8"],"pages":["129–135"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Models, more models, and then a lot more"],"volume":["10748 LNCS"]},"creators":{"author":[{"lastName":"Babur","firstName":"Ö."},{"lastName":"Cleophas","firstName":"L."},{"lastName":"Brand","firstName":"M.","prefix":"vanden","useprefix":true},{"lastName":"Tekinerdogan","firstName":"B."},{"lastName":"Aksit","firstName":"M."}],"editor":[{"lastName":"Zschaler S.","firstName":"Seidl M."}]},"sentenceCased":true},{"key":"Babur2018778","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["CEUR Workshop Proc."],"abstract":["In this paper (expanded from an invited talk at AISEC 2010), we discuss an emerging field of study: adversarial machine learning—the study of effective machine learning techniques against an adversarial opponent. In this paper, we: give a taxonomy for classifying attacks against online machine learning algorithms; discuss application-specific factors that limit an adversary's capabilities; introduce two models for modeling an adversary's capabilities; explore the limits of an adversary's knowledge about the algorithm, feature space, training, and input data; explore vulnerabilities in machine learning algorithms; discuss countermeasures against attacks; introduce the evasion challenge; and discuss privacy-preserving learning techniques."],"affiliation":["Eindhoven University of Technology, Eindhoven, Netherlands; Chalmers | University of Gothenburg, Gothenburg, Sweden; Eindhoven University of Technology Eindhoven, Netherlands Stellenbosch University, Stellenbosch, South Africa; University of L'Aquila, L'Aquila, Italy; University of York York, United Kingdom"],"author":["Wang, Jianyong","Han, Jiawei"],"booktitle":["Proc. 4th ACM Workshop Secur. Artif. Intell."],"date":["2004"],"document_type":["Conference Paper"],"doi":["10.1145/2046684.2046692"],"isbn":["0-7695-2065-0"],"issn":["16130073"],"keywords":["adversarial learning","computer security","duplicate-citation-key","game theory","intrusion detection","machine learning","security metrics","spam filters","statistical learning"],"location":["Washington, DC, USA"],"note":["TL;DR \n\nBIDE is an efficient algorithm for mining frequent closed sequences without candidate maintenance, which adopts a novel sequence closure checking scheme called bidirectional extension, and prunes the search space more deeply compared to the previous algorithms by using the BackScan pruning method and the Scan-Skip optimization technique."],"pages":["43–58"],"pagetotal":["16"],"publisher":["IEEE Computer Society"],"series":["AISec '11"],"source":["Scopus"],"title":["BIDE: Efficient mining of frequent closed sequences"],"volume":["15"]},"creators":{"author":[{"lastName":"Wang","firstName":"Jianyong"},{"lastName":"Han","firstName":"Jiawei"}]},"sentenceCased":true},{"key":"Babur2018778","type":"incollection","fields":{"abbrev_source_title":["CEUR Workshop Proc."],"abstract":["Model-based approaches promote the use of models and related artifacts (such as metamodels and model transformations) as central elements to tackle the complexity of building systems. Both in academia and in industry there is a growing need to efficiently i) store; ii) analyze; and ii) search & navigate, and iii) curate large collections of models. Such collections include for example large sets of software models such as the Lindholmen UML dataset [1], or of heterogeneous models in large MDE ecosystems and systems-of-systems, including e.g. software, hardware, and business models. The workshop Analytics and Mining of Model Repositories (AMMoRe) aims to gather modelling researchers and practitioners to discuss the emerging problems and propose solutions. The scope ranges from industrial reports and empirical analyses in the problem domain to novel cross-disciplinary approaches for large-scale analytics and management, e.g. exploiting techniques from data analytics, repository mining and machine learning. © 2018 CEUR-WS. All rights reserved."],"affiliation":["Eindhoven University of Technology, Eindhoven, Netherlands; Chalmers | University of Gothenburg, Gothenburg, Sweden; Eindhoven University of Technology Eindhoven, Netherlands Stellenbosch University, Stellenbosch, South Africa; University of L'Aquila, L'Aquila, Italy; University of York York, United Kingdom"],"author":["Babur, O.","Chaudron, M. R. V.","Cleophas, L.","Di Ruscio, D.","Kolovos, D."],"booktitle":["CEUR Workshop Proceedings"],"date":["2018"],"document_type":["Conference Paper"],"ids":["baburAMMoRe2018First2018,baburAMMoRe2018First2018a,baburAMMoRe2018First2018b,baburAMMoRe2018First2018c,baburAMMoRe2018First2018d"],"issn":["16130073"],"keywords":["duplicate-citation-key"],"note":["cited By 2 \n\ncited By 2 \n\ncited By 2 \n\ncited By 3 \n\ncited By 3 \n\nTL;DR \n\nThe workshop Analytics and Mining of Model Repositories (AMMoRe) aims to gather modelling researchers and practitioners to discuss the emerging problems and propose solutions to solve the growing need to efficiently store, analyze, and curate large collections of models."],"pages":["778–779"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"source":["Scopus"],"title":["AMMoRe 2018: First international workshop on analytics and mining of model repositories"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063109105&partnerID=40&md5=9b6af321cedc951abe47939224d38e2b"],"volume":["2245"]},"creators":{"author":[{"lastName":"Babur","firstName":"O."},{"lastName":"Chaudron","firstName":"M. R. V."},{"lastName":"Cleophas","firstName":"L."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Kolovos","firstName":"D."}]},"sentenceCased":true},{"key":"baburLabeledEcoreMetamodel2019","type":"dataset","fields":{"abstract":["Manually labeled 555 metamodels mined from GitHub in April 2017. Domains: (1) bibliography, (2) conference management, (3) bug/issue tracker, (4) build systems, (5) document/office products, (6) requirement/use case, (7) database/sql, (8) state machines, (9) petri nets Procedure for constructing the dataset: fully manual, by searching for certain keywords and regexes (e.g. \"state\" and \"transition\" for state machines) in the metamodels and inspecting the results for inclusion. Format for the file names: ABSINDEX_CLUSTER_ITEMINDEX_name_hash.ecore"],"author":["Babur, Önder"],"date":["2019-03-06"],"doi":["10.5281/ZENODO.2585456"],"ids":["onder_babur_2019_2585456"],"keywords":["clustering","metamodel","model analytics","model-driven engineering"],"publisher":["Zenodo"],"title":["A labeled Ecore metamodel dataset for domain clustering"],"version":["0.1.1"]},"creators":{"author":[{"lastName":"Babur","firstName":"Önder"}]},"sentenceCased":true},{"key":"Bachinger2020263","type":"article","fields":{"abstract":["With the increasing number of created and deployed prediction models and the complexity of machine learning workflows we require so called model management systems to support data scientists in their tasks. In this work we describe our technological concept for such a model management system. This concept includes versioned storage of data, support for different machine learning algorithms, fine tuning of models, subsequent deployment of models and monitoring of model performance after deployment. We describe this concept with a close focus on model lifecycle requirements stemming from our industry application cases, but generalize key features that are relevant for all applications of machine learning. © 2020, Springer Nature Switzerland AG."],"author":["Bachinger, F.","Kronberger, G."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-45093-9_32"],"editor":["Moreno-Diaz R., Quesada-Arencibia A., Pichler F."],"isbn":["9783030450922"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 0 \n\nTL;DR \n\nThis work describes the technological concept for a model management system that includes versioned storage of data, support for different machine learning algorithms, fine tuning of models, subsequent deployment of models and monitoring of model performance after deployment."],"pages":["263–270"],"publisher":["Springer"],"source":["Scopus"],"title":["Concept for a technical infrastructure for management of predictive models in industrial applications"],"volume":["12013 LNCS"]},"creators":{"author":[{"lastName":"Bachinger","firstName":"F."},{"lastName":"Kronberger","firstName":"G."}],"editor":[{"lastName":"Moreno-Diaz R.","suffix":"Quesada-Arencibia A.","firstName":"Pichler F."}]},"sentenceCased":true},{"key":"Bae2015","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Int. J. Distrib. Sens. Netw."],"affiliation":["Department of Management Information Systems, Keimyung University, 1095 Dalgubeoldaero, Daegu, 704-701, South Korea; School of Business, Sogang University, 1 Sinsu-dong, Seoul, 121-742, South Korea"],"art_number":["179060"],"author":["Bae, J.K.","Kim, J."],"correspondence_address1":["Bae, J.K.; Department of Management Information Systems, Keimyung University, 1095 Dalgubeoldaero, South Korea"],"date":["2015"],"document_type":["Article"],"doi":["10.1155/2015/179060"],"issn":["15501329"],"journaltitle":["Int. J. Distrib. Sens. Netw."],"note":["cited By 5"],"publisher":["Hindawi Publishing Corporation"],"source":["Scopus"],"title":["A personal credit rating prediction model using data mining in smart ubiquitous environments"],"volume":["2015"]},"creators":{"author":[{"lastName":"Bae","firstName":"J.K."},{"lastName":"Kim","firstName":"J."}]},"sentenceCased":true},{"key":"Bae2022","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Appl. Soft Comput."],"affiliation":["Department of Nuclear Engineering, Ulsan National Institute of Science and Technology, 50 UNIST-gil, Ulsan, 44919, South Korea"],"art_number":["109007"],"author":["Bae, J.","Park, J.W.","Lee, S.J."],"correspondence_address1":["Lee, S.J.; Department of Nuclear Engineering, 50 UNIST-gil, South Korea; email: sjlee420@unist.ac.kr"],"date":["2022"],"document_type":["Article"],"doi":["10.1016/j.asoc.2022.109007"],"issn":["15684946"],"journaltitle":["Appl. Soft Comput."],"note":["cited By 0"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Limit Surface/States searching algorithm with a deep neural network and Monte Carlo dropout for nuclear power plant safety assessment"],"volume":["124"]},"creators":{"author":[{"lastName":"Bae","firstName":"J."},{"lastName":"Park","firstName":"J.W."},{"lastName":"Lee","firstName":"S.J."}]},"sentenceCased":true},{"key":"bagnatoDeveloperCentricKnowledgeMining2017","type":"inproceedings","fields":{"author":["Bagnato, Alessandra","Barmpis, Konstantinos","Bessis, Nik","Cabrera-Diego, Luis Adrián","Rocco, Juri Di","Ruscio, Davide Di","Gergely, Tamás","Hansen, Scott","Kolovos, Dimitris S.","Krief, Philippe","Korkontzelos, Ioannis","Laurière, Stéphane","family=Fuente, given=Jose Manrique Lopez, prefix=de la, useprefix=false","Maló, Pedro","Paige, Richard F.","Spinellis, Diomidis","Thomas, Cedric","Vinju, Jurgen J."],"booktitle":["Softw. Technol. Appl. Found. - STAF 2017 Collocated Workshop Marburg Ger. July 17-21 2017 Revis. Sel. Pap."],"date":["2017"],"doi":["10.1007/978-3-319-74730-9_33"],"editor":["Seidl, Martina","Zschaler, Steffen"],"ids":["bagnatoDeveloperCentricKnowledgeMining2017a,bagnatoDeveloperCentricKnowledgeMining2018,bagnatoDeveloperCentricKnowledgeMining2018a"],"note":["cited By 9 \n\ncited By 9"],"pages":["375–384"],"publisher":["Springer"],"series":["Lecture Notes in Computer Science"],"title":["Developer-Centric Knowledge Mining from Large Open-Source Software Repositories (CROSSMINER)"],"volume":["10748"]},"creators":{"author":[{"lastName":"Bagnato","firstName":"Alessandra"},{"lastName":"Barmpis","firstName":"Konstantinos"},{"lastName":"Bessis","firstName":"Nik"},{"lastName":"Cabrera-Diego","firstName":"Luis Adrián"},{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Gergely","firstName":"Tamás"},{"lastName":"Hansen","firstName":"Scott"},{"lastName":"Kolovos","firstName":"Dimitris S."},{"lastName":"Krief","firstName":"Philippe"},{"lastName":"Korkontzelos","firstName":"Ioannis"},{"lastName":"Laurière","firstName":"Stéphane"},{"lastName":"Fuente","firstName":"JoseManriqueLopez","prefix":"dela","useprefix":false},{"lastName":"Maló","firstName":"Pedro"},{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Spinellis","firstName":"Diomidis"},{"lastName":"Thomas","firstName":"Cedric"},{"lastName":"Vinju","firstName":"Jurgen J."}],"editor":[{"lastName":"Seidl","firstName":"Martina"},{"lastName":"Zschaler","firstName":"Steffen"}]}},{"key":"Bai2022112","type":"article","fields":{"abstract":["In massive machine-type communications (mMTC), the conflict between millions of potential access devices and limited channel freedom leads to a sharp decrease in spectrum efficiency. The nature of sporadic activity in mMTC provides a solution to enhance spectrum efficiency by employing compressive sensing (CS) to perform multiuser detection (MUD). However, CS-MUD suffers from high computation complexity and fails to meet the strict latency requirement in some critical applications. To address this problem, in this paper, we propose a novel deep learning (DL) based framework for grant-free non-orthogonal multiple access (GF-NOMA), where we utilize the information distilled from the initial data recovery phase to further enhance channel estimation, which in turn improves data recovery performance. Besides, we design an interpretable and structured Model-driven Prior Information Aided Network (M-PIAN) and provide theoretical analysis that demonstrates the proposed M-PIAN can converge faster and support more users. Experiments show that the proposed method outperforms existing CS algorithms and DL methods in both computation complexity and reconstruction accuracy. © 1983-2012 IEEE."],"author":["Bai, Y.","Chen, W.","Ai, B.","Zhong, Z.","Wassell, I.J."],"coden":["ISACE"],"date":["2022"],"document_type":["Article"],"doi":["10.1109/JSAC.2021.3126071"],"issn":["07338716"],"journaltitle":["IEEE J. Sel. Areas Commun."],"note":["cited By 2 \n\nTL;DR \n\nA novel deep learning (DL) based framework for grant-free non-orthogonal multiple access (GF-NOMA) is proposed, where the information distilled from the initial data recovery phase is utilized to further enhance channel estimation, which in turn improves data recovery performance."],"number":["1"],"pages":["112–126"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Prior information aided deep learning method for grant-free NOMA in mMTC"],"volume":["40"]},"creators":{"author":[{"lastName":"Bai","firstName":"Y."},{"lastName":"Chen","firstName":"W."},{"lastName":"Ai","firstName":"B."},{"lastName":"Zhong","firstName":"Z."},{"lastName":"Wassell","firstName":"I.J."}]},"sentenceCased":true},{"key":"bakerSingularValueDecomposition2005","type":"unpublished","fields":{"added-at":["2009-04-17T10:27:21.000+0200"],"author":["Baker, Kirk","Baker, Kirk"],"biburl":["https://www.bibsonomy.org/bibtex/2abdcfb3746e47898ac93929ab88298af/voigtmannc"],"date":["2005"],"interhash":["52abe308f6c46087df51a5876c1ab6e9"],"intrahash":["abdcfb3746e47898ac93929ab88298af"],"keywords":["algorithm datamining decomposition singular svd tutorial"],"timestamp":["2009-04-17T10:27:21.000+0200"],"title":["Singular value decomposition tutorial"]},"creators":{"author":[{"lastName":"Baker","firstName":"Kirk"},{"lastName":"Baker","firstName":"Kirk"}]},"sentenceCased":true},{"key":"baki2016multi","type":"article","fields":{"langid":["english"],"author":["Baki, Islem","Sahraoui, Houari"],"date":["2016"],"journaltitle":["ACM Trans. Softw. Eng. Methodol. (TOSEM)"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis article proposes an MTBE process to learn complex model transformations by considering three common requirements: element context and state dependencies and complex value derivation, and relies on two strategies to reduce the size of the search space and to better explore it, namely, multi-step learning and adaptive search."],"number":["3"],"pages":["1–37"],"title":["Multi-step learning and adaptive search for learning complex model transformations from examples"],"volume":["25"]},"creators":{"author":[{"lastName":"Baki","firstName":"Islem"},{"lastName":"Sahraoui","firstName":"Houari"}]},"sentenceCased":true},{"key":"balabanPatternbasedApproachImproving2015","type":"article","fields":{"langid":["english"],"author":["Balaban, Mira","Maraee, Azzam","Sturm, Arnon","Jelnov, Pavel"],"date":["2015-10"],"doi":["10.1007/s10270-013-0390-0"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"number":["4"],"pages":["1527–1555"],"title":["A pattern-based approach for improving model quality"],"volume":["14"]},"creators":{"author":[{"lastName":"Balaban","firstName":"Mira"},{"lastName":"Maraee","firstName":"Azzam"},{"lastName":"Sturm","firstName":"Arnon"},{"lastName":"Jelnov","firstName":"Pavel"}]},"sentenceCased":true},{"key":"Balasubramanian20153","type":"article","fields":{"abstract":["Complex sensing, processing and control applications running on distributed platforms are difficult to design, develop, analyze, integrate, deploy and operate, especially if resource constraints, fault tolerance and security issues are to be addressed. While technology exists today for engineering distributed, real-time component-based applications, many problems remain unsolved by existing tools. Model-driven development techniques are powerful, but there are very few existing and complete tool chains that offer an end-to-end solution to developers, from design to deployment. There is a need for an integrated model-driven development environment that addresses all phases of application lifecycle including design, development, verification, analysis, integration, deployment, operation and maintenance, with supporting automation in every phase. Arguably, a centerpiece of such a model-driven environment is the modeling language. To that end, this paper presents a wide-spectrum architecture design language called DREMS ML that itself is an integrated collection of individual domain-specific sub-languages. We claim that the language promotes \"correct-by-construction\" software development and integration by supporting each individual phase of the application lifecycle. Using a case study, we demonstrate how the design of DREMS ML impacts the development of embedded systems. © 2015 Elsevier B.V. All rights reserved."],"author":["Balasubramanian, D.","Dubey, A.","Otte, W.","Levendovszky, T.","Gokhale, A.","Kumar, P.","Emfinger, W.","Karsai, G."],"coden":["SCPGD"],"date":["2015"],"document_type":["Article"],"doi":["10.1016/j.scico.2015.04.002"],"issn":["01676423"],"journaltitle":["Sci. Comput. Program."],"note":["cited By 9"],"pages":["3–29"],"publisher":["Elsevier B.V."],"source":["Scopus"],"title":["DREMS ML: A wide spectrum architecture design language for distributed computing platforms"],"volume":["106"]},"creators":{"author":[{"lastName":"Balasubramanian","firstName":"D."},{"lastName":"Dubey","firstName":"A."},{"lastName":"Otte","firstName":"W."},{"lastName":"Levendovszky","firstName":"T."},{"lastName":"Gokhale","firstName":"A."},{"lastName":"Kumar","firstName":"P."},{"lastName":"Emfinger","firstName":"W."},{"lastName":"Karsai","firstName":"G."}]},"sentenceCased":true},{"key":"balogDeepCoderLearningWrite2016","type":"article","fields":{"author":["Balog, Matej","Gaunt, Alexander L.","Brockschmidt, Marc","Nowozin, Sebastian","Tarlow, Daniel"],"date":["2016"],"eprint":["1611.01989"],"eprinttype":["arxiv"],"journaltitle":["ArXiv Prepr. ArXiv161101989"],"shorttitle":["DeepCoder"],"title":["DeepCoder: Learning to Write Programs"],"url":["https://arxiv.org/abs/1611.01989"],"urldate":["2017-02-25"]},"creators":{"author":[{"lastName":"Balog","firstName":"Matej"},{"lastName":"Gaunt","firstName":"Alexander L."},{"lastName":"Brockschmidt","firstName":"Marc"},{"lastName":"Nowozin","firstName":"Sebastian"},{"lastName":"Tarlow","firstName":"Daniel"}]}},{"key":"balouek-thomertComputingContinuumEnabling2019","type":"article","fields":{"langid":["english"],"abstract":["Dramatic changes in the technology landscape marked by increasing scales and pervasiveness of compute and data have resulted in the proliferation of edge applications aimed at effectively processing data in a timely manner. As the levels and fidelity of instrumentation increases and the types and volumes of available data grow, new classes of applications are being explored that seamlessly combine real-time data with complex models and data analytics to monitor and manage systems of interest. However, these applications require a fluid integration of resources at the edge, the core, and along the data path to support dynamic and data-driven application workflows, that is, they need to leverage a computing continuum. In this article, we present our vision for enabling such a computing continuum and specifically focus on enabling edge-to-cloud integration to support data-driven workflows. The research is driven by an online data-driven tsunami warning use case that is supported by the deployment of large-scale national environment observation systems. This article presents our overall approach as well as current status and next steps."],"author":["Balouek-Thomert, Daniel","Renart, Eduard Gibert","Zamani, Ali Reza","Simonet, Anthony","Parashar, Manish"],"date":["2019-11"],"doi":["10.1177/1094342019877383"],"ids":["balouek-thomertComputingContinuumEnabling2019a"],"issn":["1094-3420, 1741-2846"],"journaltitle":["The International Journal of High Performance Computing Applications"],"note":["TL;DR \n\nThis article presents the overall approach as well as current status and next steps for enabling edge-to-cloud integration to support data-driven workflows and is driven by an online data- driven tsunami warning use case that is supported by the deployment of large-scale national environment observation systems."],"number":["6"],"pages":["1159–1174"],"shorttitle":["Towards a computing continuum"],"title":["Towards a computing continuum: Enabling edge-to-cloud integration for data-driven workflows"],"volume":["33"]},"creators":{"author":[{"lastName":"Balouek-Thomert","firstName":"Daniel"},{"lastName":"Renart","firstName":"Eduard Gibert"},{"lastName":"Zamani","firstName":"Ali Reza"},{"lastName":"Simonet","firstName":"Anthony"},{"lastName":"Parashar","firstName":"Manish"}]},"sentenceCased":true},{"key":"baltesSOTorrentReconstructingAnalyzing2018","type":"inproceedings","fields":{"acmid":["3196430"],"author":["Baltes, Sebastian","Dumani, Lorik","Treude, Christoph","Diehl, Stephan"],"booktitle":["Proc. 15th Int. Conf. Min. Softw. Repos."],"date":["2018"],"isbn":["978-1-4503-5716-6"],"keywords":["code snippets","open dataset","software evolution","stack overflow"],"location":["New York, NY, USA"],"nodoi":["10.1145/3196398.3196430"],"numpages":["12"],"pages":["319–330"],"publisher":["ACM"],"series":["MSR '18"],"title":["SOTorrent: Reconstructing and analyzing the evolution of stack overflow posts"],"url":["http://doi.acm.org/10.1145/3196398.3196430"]},"creators":{"author":[{"lastName":"Baltes","firstName":"Sebastian"},{"lastName":"Dumani","firstName":"Lorik"},{"lastName":"Treude","firstName":"Christoph"},{"lastName":"Diehl","firstName":"Stephan"}]},"sentenceCased":true},{"key":"balzeraniSupportingWebApplications2006","type":"article","fields":{"author":["Balzerani, Luca","Angelis, Guglielmo De","Ruscio, Davide Di","Pierantonio, Alfonso"],"date":["2006"],"ids":["balzeraniSupportingWebApplications2006a"],"journaltitle":["J. Web Eng."],"number":["1"],"pages":["25–42"],"title":["Supporting Web Applications development with a PLA"],"url":["http://www.rintonpress.com/xjwe5/jwe-5-1/025-042.pdf"],"volume":["5"]},"creators":{"author":[{"lastName":"Balzerani","firstName":"Luca"},{"lastName":"Angelis","firstName":"Guglielmo De"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"banchsInformationRetrievalTechnology2013","type":"book","fields":{"date":["2013"],"doi":["10.1007/978-3-642-45068-6"],"editor":["Banchs, Rafael E.","Silvestri, Fabrizio","Liu, Tie-Yan","Zhang, Min","Gao, Sheng","Lang, Jun"],"editorb":["Hutchison, David","Kanade, Takeo","Kittler, Josef","Kleinberg, Jon M.","Mattern, Friedemann","Mitchell, John C.","Naor, Moni","Nierstrasz, Oscar","Pandu Rangan, C.","Steffen, Bernhard","Sudan, Madhu","Terzopoulos, Demetri","Tygar, Doug","Vardi, Moshe Y.","Weikum, Gerhard"],"editorbtype":["redactor"],"isbn":["978-3-642-45067-9 978-3-642-45068-6"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nThis work investigates the relationship between relevance likelihood and retrieval rank, seeking to identify plausible methods for estimating document relevance and hence computing an inferred gain."],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture Notes in Computer Science"],"title":["Information Retrieval Technology"],"volume":["8281"]},"creators":{"editor":[{"lastName":"Banchs","firstName":"Rafael E."},{"lastName":"Silvestri","firstName":"Fabrizio"},{"lastName":"Liu","firstName":"Tie-Yan"},{"lastName":"Zhang","firstName":"Min"},{"lastName":"Gao","firstName":"Sheng"},{"lastName":"Lang","firstName":"Jun"}],"editorb":[{"lastName":"Hutchison","firstName":"David"},{"lastName":"Kanade","firstName":"Takeo"},{"lastName":"Kittler","firstName":"Josef"},{"lastName":"Kleinberg","firstName":"Jon M."},{"lastName":"Mattern","firstName":"Friedemann"},{"lastName":"Mitchell","firstName":"John C."},{"lastName":"Naor","firstName":"Moni"},{"lastName":"Nierstrasz","firstName":"Oscar"},{"lastName":"Pandu Rangan","firstName":"C."},{"lastName":"Steffen","firstName":"Bernhard"},{"lastName":"Sudan","firstName":"Madhu"},{"lastName":"Terzopoulos","firstName":"Demetri"},{"lastName":"Tygar","firstName":"Doug"},{"lastName":"Vardi","firstName":"Moshe Y."},{"lastName":"Weikum","firstName":"Gerhard"}]}},{"key":"bansiyaHierarchicalModelObjectoriented2002","type":"article","fields":{"author":["Bansiya, J.","Davis, C.G."],"date":["2002"],"doi":["10.1109/32.979986"],"journaltitle":["IEEE Trans. Softw. Eng."],"keywords":["⛔ No INSPIRE recid found","OO metrics","quality assessment"],"number":["1"],"pages":["4–17"],"title":["A hierarchical model for object-oriented design quality assessment"],"volume":["28"]},"creators":{"author":[{"lastName":"Bansiya","firstName":"J."},{"lastName":"Davis","firstName":"C.G."}]},"sentenceCased":true},{"key":"bao_mining_2018","type":"inproceedings","fields":{"abstract":["The popularity of Android platform on mobile devices has attracted much attention from many developers and researchers, as well as malware writers. Recently, Jamrozik et al. proposed a technique to secure Android applications referred to as mining sandboxes. They used an automated test case generation technique to explore the behavior of the app under test and then extracted a set of sensitive APIs that were called. Based on the extracted sensitive APIs, they built a sandbox that can block access to APIs not used during testing. However, they only evaluated the proposed technique with benign apps but not investigated whether it was effective in detecting malicious behavior of malware that infects benign apps. Furthermore, they only investigated one test case generation tool (i.e., Droidmate) to build the sandbox, while many others have been proposed in the literature. In this work, we complement Jamrozik et al.'s work in two ways: (1) we evaluate the effectiveness of mining sandboxes on detecting malicious behaviors; (2) we investigate the effectiveness of multiple automated test case generation tools to mine sandboxes. To investigate effectiveness of mining sandboxes in detecting malicious behaviors, we make use of pairs of malware and benign app it infects. We build a sandbox based on sensitive APIs called by the benign app and check if it can identify malicious behaviors in the corresponding malware. To generate inputs to apps, we investigate five popular test case generation tools: Monkey, Droidmate, Droidbot, GUIRipper, and PUMA. We conduct two experiments to evaluate the effectiveness and efficiency of these test case generation tools on detecting malicious behavior. In the first experiment, we select 10 apps and allow test case generation tools to run for one hour; while in the second experiment, we select 102 pairs of apps and allow the test case generation tools to run for one minute. Our experiments highlight that 75.5%-77.2% of malware in our dataset can be uncovered by mining sandboxes - showing its power to protect Android apps. We also find that Droidbot performs best in generating test cases for mining sandboxes, and its effectiveness can be further boosted when coupled with other test case generation tools."],"author":["Bao, L.","Le, T. B.","Lo, D."],"booktitle":["2018 IEEE 25th Int. Conf. Softw. Anal. Evol. Reengineering SANER"],"date":["2018-03"],"doi":["10.1109/SANER.2018.8330231"],"keywords":["Android (operating system)","Android apps","Android Malware","Androids","application program interfaces","Automated Test Case Generation","automated test case generation technique","benign apps","data mining","Droidbot","Droidmate","GUIRipper","Humanoid robots","invasive software","Java","malicious behavior","malware","Malware","Mining Sandboxing","mobile computing","Mobile handsets","Monkey","multiple automated test case generation tools","program testing","PUMA","sandboxes mining","sensitive APIs","test case generation tool","Testing","Tools"],"pages":["445–455"],"shorttitle":["Mining sandboxes"],"title":["Mining sandboxes: Are we there yet?"]},"creators":{"author":[{"lastName":"Bao","firstName":"L."},{"lastName":"Le","firstName":"T. B."},{"lastName":"Lo","firstName":"D."}]},"sentenceCased":true},{"key":"Bao2021706","type":"article","fields":{"langid":["chinese"],"abbrev_source_title":["Jisuanji Yanjiu yu Fazhan"],"affiliation":["School of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China; Key Laboratory of Safety-critical Software, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China; Aviation Computing Technology Research Institute, Xi'an, 710065, China"],"author":["Bao, Y.","Yang, Z.","Yang, Y.","Xie, J.","Zhou, Y.","Yue, T.","Huang, Z.","Guo, P."],"coden":["JYYFE"],"correspondence_address1":["Yang, Z.; School of Computer Science and Technology, China; email: yangzhibin168@163.com"],"date":["2021"],"document_type":["Article"],"doi":["10.7544/issn1000-1239.2021.20200757"],"issn":["10001239"],"journaltitle":["Jisuanji Yanjiu Yu FazhanComputer Res. Dev."],"keywords":["GOAL_Model-synthesis","notion","TECHNIQUE_DNN"],"note":["cited By 0 \n\nONLY THE ABSTRACT IS WRITTEN IN ENGLISH!"],"number":["4"],"pages":["706–730"],"publisher":["Science Press"],"source":["Scopus"],"title":["An Automated Approach to Generate SysML Models from Restricted Natural Language Requirements in Chinese [基于限定中文自然语言需求的SysML模型自动生成方法]"],"volume":["58"]},"creators":{"author":[{"lastName":"Bao","firstName":"Y."},{"lastName":"Yang","firstName":"Z."},{"lastName":"Yang","firstName":"Y."},{"lastName":"Xie","firstName":"J."},{"lastName":"Zhou","firstName":"Y."},{"lastName":"Yue","firstName":"T."},{"lastName":"Huang","firstName":"Z."},{"lastName":"Guo","firstName":"P."}]}},{"key":"baresiBuildingSoftwareInternet2015","type":"article","fields":{"langid":["english"],"author":["Baresi, Luciano","Mottola, Luca","Dustdar, Schahram"],"date":["2015-03"],"doi":["10.1109/MIC.2015.31"],"issn":["1089-7801"],"journaltitle":["IEEE Internet Comput."],"note":["TL;DR \n\nThe guest editors present a special issue on building software for the Internet of Things (IoT) with a focus on artificial intelligence (AI) and robotics."],"number":["2"],"pages":["6–8"],"title":["Building Software for the Internet of Things"],"volume":["19"]},"creators":{"author":[{"lastName":"Baresi","firstName":"Luciano"},{"lastName":"Mottola","firstName":"Luca"},{"lastName":"Dustdar","firstName":"Schahram"}]}},{"key":"Barmpis20141","type":"article","fields":{"langid":["english"],"abbrev_source_title":["J. Object Technol."],"affiliation":["Department of Computer Science, University of York, Heslington, York, YO10 5DD, United Kingdom"],"author":["Barmpis, K.","Kolovos, D.S."],"date":["2014"],"document_type":["Article"],"doi":["10.5381/jot.2014.13.3.a3"],"issn":["16601769"],"journaltitle":["J. Object Technol."],"note":["cited By 25"],"number":["3"],"pages":["1–26"],"publisher":["Association Internationale pour les Technologies Objets"],"source":["Scopus"],"title":["Evaluation of contemporary graph databases for ecient persistence of large-scale models"],"volume":["13"]},"creators":{"author":[{"lastName":"Barmpis","firstName":"K."},{"lastName":"Kolovos","firstName":"D.S."}]},"sentenceCased":true},{"key":"Barriga20221135","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Softw. Syst. Model."],"affiliation":["Western Norway University of Applied Sciences, Bergen, Norway"],"author":["Barriga, A.","Rutle, A.","Heldal, R."],"correspondence_address1":["Barriga, A.; Western Norway University of Applied SciencesNorway; email: abar@hvl.no"],"date":["2022"],"document_type":["Article"],"doi":["10.1007/s10270-022-00983-5"],"issn":["16191366"],"journaltitle":["Softw. Syst. Model."],"keywords":["GOAL_Model-Repair","notion","TECHNIQUE_DNN","TECHNIQUE_GENETIC_ALGORITHMS","TECHNIQUE_ILP","TECHNIQUE_MARKOV_DECISION_PROCESS","TECHNIQUE_NN"],"note":["cited By 0 \n\nTL;DR \n\nA number of research opportunities are presented by taking inspiration from other fields which have successfully used artificial intelligence, such as code repair, in the field of AI-powered model repair."],"number":["3"],"pages":["1135–1157"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["AI-powered model repair: An experience Report—Lessons learned, challenges, and opportunities"],"volume":["21"]},"creators":{"author":[{"lastName":"Barriga","firstName":"A."},{"lastName":"Rutle","firstName":"A."},{"lastName":"Heldal","firstName":"R."}]},"sentenceCased":true},{"key":"barriga2022parmorel","type":"article","fields":{"langid":["english"],"author":["Barriga, Angela","Heldal, Rogardt","Rutle, Adrian","Iovino, Ludovico"],"date":["2022"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nA customizable and extensible model repair framework, PARMOREL, that enables users to deal with different issues in different types of models and uses reinforcement learning to automatically find the best sequence of actions for repairing a broken model according to user preferences."],"number":["5"],"pages":["1739–1762"],"title":["PARMOREL: A framework for customizable model repair"],"volume":["21"]},"creators":{"author":[{"lastName":"Barriga","firstName":"Angela"},{"lastName":"Heldal","firstName":"Rogardt"},{"lastName":"Rutle","firstName":"Adrian"},{"lastName":"Iovino","firstName":"Ludovico"}]},"sentenceCased":true},{"key":"barrigaDesigningSimulatingIoT2022","type":"inproceedings","fields":{"author":["Barriga, Jose A.","Clemente, Pedro J."],"booktitle":["2022 17th Iber. Conf. Inf. Syst. Technol. CISTI"],"date":["2022-06-22"],"doi":["10.23919/CISTI54924.2022.9820477"],"eventtitle":["2022 17th Iberian Conference on Information Systems and Technologies (CISTI)"],"isbn":["978-989-33-3436-2"],"location":["Madrid, Spain"],"pages":["1–6"],"publisher":["IEEE"],"title":["Designing and simulating IoT environments by using a model-driven approach <sup>*</sup>"]},"creators":{"author":[{"lastName":"Barriga","firstName":"Jose A."},{"lastName":"Clemente","firstName":"Pedro J."}]},"sentenceCased":true},{"key":"barrigaExtensibleToolchainAnalyzing2020","type":"inproceedings","fields":{"author":["Barriga, Angela","Di Ruscio, D.","Iovino, L.","Nguyen, Thanh Phuong","Pierantonio, A."],"booktitle":["Proc. - 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS-C 2020 - Companion Proc."],"date":["2020"],"doi":["10.1145/3417990.3419626"],"ids":["barrigaExtensibleToolchainAnalyzing2020a,barrigaExtensibleToolchainAnalyzing2020b"],"isbn":["978-1-4503-8135-2"],"keywords":["Analysis","Dataset","Metamodels","Repositories"],"note":["cited By 4 \n\ncited By 4 \n\nTL;DR \n\nA dataset of metamodels has been collected for experimenting with different approaches conceived by the authors and has been automatically curated using a toolchain, which has been re-designed post-ante the definition of the proposed approaches to foster its future reuse."],"pages":["316–323"],"publisher":["Association for Computing Machinery, Inc"],"title":["An extensible tool-chain for analyzing datasets of metamodels"]},"creators":{"author":[{"lastName":"Barriga","firstName":"Angela"},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Iovino","firstName":"L."},{"lastName":"Nguyen","firstName":"Thanh Phuong"},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"Barzdins202076","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - ACM/IEEE Int. Conf. Model Driven Eng. Lang. Syst., MODELS-C - Companion Proc."],"affiliation":["Institute of Mathematics and Computer Science, University of Latvia, Riga, Latvia; Innovation Labs LETA, Riga, Latvia"],"author":["Barzdins, P.","Celms, E.","Barzdins, J.","Kalnins, A.","Sprogis, A.","Grasmanis, M.","Rikacovs, S."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3417990.3420050"],"isbn":["978-1-4503-8135-2"],"note":["cited By 1 \n\nTL;DR \n\nA new Domain Specific Language (DSL) based approach to Deep Learning (DL) lifecycle data management (LDM) is presented and an advanced extension mechanism is presented that converts the Core tool into a DSL tool building framework for DL LDM tasks."],"pages":["76–77"],"publisher":["Association for Computing Machinery, Inc"],"series":["Proceedings - 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2020 - Companion Proceedings"],"source":["Scopus"],"title":["Metamodel specialization based DSL for DL lifecycle data management"]},"creators":{"author":[{"lastName":"Barzdins","firstName":"P."},{"lastName":"Celms","firstName":"E."},{"lastName":"Barzdins","firstName":"J."},{"lastName":"Kalnins","firstName":"A."},{"lastName":"Sprogis","firstName":"A."},{"lastName":"Grasmanis","firstName":"M."},{"lastName":"Rikacovs","firstName":"S."}]},"sentenceCased":true},{"key":"Barzdins202217","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Baltic J. Mod. Comp."],"affiliation":["Institute of Mathematics and Computer Science, University of Latvia, Raiņa bulvaris 29, Riga, LV-1459, Latvia; Innovation Labs LETA, Latvia, Riga, Satekles iela 2b, Riga, LV 1050, Latvia"],"author":["Barzdins, P.","Kalnins, A.","Celms, E.","Barzdins, J.","Sprogis, A.","Grasmanis, M.","Rikacovs, S.","Barzdins, G."],"date":["2022"],"document_type":["Article"],"doi":["10.22364/BJMC.2022.10.1.02"],"issn":["22558942"],"journaltitle":["Balt. J. Mod. Comput."],"keywords":["notion"],"note":["cited By 0"],"number":["1"],"pages":["17–35"],"publisher":["University of Latvia"],"source":["Scopus"],"title":["Metamodel specialisation based tool extension"],"volume":["10"]},"creators":{"author":[{"lastName":"Barzdins","firstName":"P."},{"lastName":"Kalnins","firstName":"A."},{"lastName":"Celms","firstName":"E."},{"lastName":"Barzdins","firstName":"J."},{"lastName":"Sprogis","firstName":"A."},{"lastName":"Grasmanis","firstName":"M."},{"lastName":"Rikacovs","firstName":"S."},{"lastName":"Barzdins","firstName":"G."}]},"sentenceCased":true},{"key":"basciani2015model","type":"inproceedings","fields":{"author":["Basciani, Francesco","Di Rocco, Juri","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"booktitle":["CloudMDE MoDELS"],"date":["2015"],"ids":["bascianiModelRepositoriesWill2015,bascianiModelRepositoriesWill2015a"],"note":["TL;DR \n\nThe opportunities related to the adoption of model repositories are discussed and the research issues that have to be addressed are identified in order to make model repositories a reality in MDE."],"pages":["37–42"],"series":["CEUR Workshop Proceedings"],"title":["Model repositories: Will they become reality?"],"url":["http://ceur-ws.org/Vol-1563/paper7.pdf"],"volume":["1563"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"bascianiAutomatedClusteringMetamodel2016","type":"inproceedings","fields":{"langid":["english"],"abstract":["Over the last years, several model repositories have been proposed in response to the need of the MDE community for advanced systems supporting the reuse of modeling artifacts. Modelers can interact with MDE repositories with different intents ranging from merely repository browsing, to searching specific artifacts satisfying precise requirements. The organization and browsing facilities provided by current repositories is limited since they do not produce structured overviews of the contained artifacts, and the ategorization mechanisms (if any) are based on manual activities. When dealing with large numbers of modeling artifacts, such limitations increase the effort for managing and reusing artifacts stored in model repositories. By focusing on metamodel repositories, in this paper we propose the application of clustering techniques to automatically organize stored metamodels and to provide users with overviews of the application domains covered by the available metamodels. The approach has been implemented in the MDEForge repository."],"author":["Basciani, Francesco","Di Rocco, Juri","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"booktitle":["Adv. Inf. Syst. Eng. - 28th Int. Conf. CAiSE 2016 Ljubl. Slov. June 13-17 2016 Proc."],"date":["2016"],"doi":["10.1007/978-3-319-39696-5_21"],"ids":["10.1007/978-3-319-39696-5_21,bascianiAutomatedClusteringMetamodel2016a,bascianiAutomatedClusteringMetamodel2016c,bascianiAutomatedClusteringMetamodel2016d,bascianiAutomatedClusteringMetamodel2016e,bascianiAutomatedClusteringMetamodel2016f"],"isbn":["978-3-319-39695-8 978-3-319-39696-5"],"keywords":["⛔ No INSPIRE recid found","Computer Science (all)","GOAL_Model-Classification","MDEForge","Metamodel clustering","Model Driven Engineering","Model repositories","notion","TECHNIQUE_K-NEAREST-NEIGHBORS","Theoretical Computer Science"],"location":["Cham"],"note":["cited By 31 \n\ncited By 31 \n\nTL;DR \n\nThis paper proposes the application of clustering techniques to automatically organize stored metamodels and to provide users with overviews of the application domains covered by the available metAModels. \n\nTL;DR \n\nThis paper proposes the application of clustering techniques to automatically organize stored metamodels and to provide users with overviews of the application domains covered by the available metAModels."],"pages":["342–358"],"publisher":["Springer International Publishing"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Automated clustering of metamodel repositories"],"volume":["abs/1006.5761"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"bascianiAutomatedQualityAssessment2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["Over the last decade, several repositories have been proposed by the Model-Driven Engineering (MDE) community to enable the reuse of modeling artifacts and foster empirical studies to analyze specifications and tools made available by MDE researchers and practitioners. In this respect, different approaches have been proposed to measure the quality of, e.g., models, metamodels, and transformations, with respect to characteristics defined by quality models. However, when a modeling ecosystem is available, measuring the constituting artifacts singularly might not be enough. This paper proposes a quality assessment approach, which considers the relationships among the artifacts under analysis as part of the quality measurement process. For instance, to assess the quality of model transformations, further than measuring their structural characteristics, users might be interested in quality aspects like coverage and information loss related to the depending metamodels and the way models are consumed by transformations, respectively. The proposed approach is based on weaving models, which permit to link quality definitions of different kinds of artifacts, and it can generate Epsilon Object Language (EOL) programs by means of a model-to-code transformation to perform the specified quality assessment process. © 2021 IEEE."],"author":["Basciani, F.","Ruscio, D.D.","Iovino, L.","Pierantonio, A."],"booktitle":["47th Euromicro Conf. Softw. Eng. Adv. Appl. SEAA 2021 Palermo Italy Sept. 1-3 2021"],"date":["2021"],"doi":["10.1109/SEAA53835.2021.00037"],"editor":["Baldassarre M.T., Scanniello G., Skavhaug A."],"ids":["bascianiAutomatedQualityAssessment2021a,bascianiAutomatedQualityAssessment2021b,bascianiAutomatedQualityAssessment2021c,bascianiAutomatedQualityAssessment2021d"],"isbn":["978-1-66542-705-0"],"keywords":["Cosine transforms","Ecosystems","Empirical studies","Engineering community","Interrelated models","Meta model","Model ecosystems","Model-driven Engineering","Quality assessment","Quality control","Quality evaluation system","Quality modeling","Reuse"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0 \n\nTL;DR \n\nA quality assessment approach is proposed, which considers the relationships among the artifacts under analysis as part of the quality measurement process and can generate Epsilon Object Language (EOL) programs by means of a model-to-code transformation to perform the specified quality assessment process."],"pages":["234–243"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Automated quality assessment of interrelated modeling artifacts"]},"creators":{"author":[{"lastName":"Basciani","firstName":"F."},{"lastName":"Ruscio","firstName":"D.D."},{"lastName":"Iovino","firstName":"L."},{"lastName":"Pierantonio","firstName":"A."}],"editor":[{"lastName":"Baldassarre M.T.","suffix":"Scanniello G.","firstName":"Skavhaug A."}]},"sentenceCased":true},{"key":"bascianiAutomatedSelectionOptimal2020","type":"article","fields":{"author":["Basciani, F.","Demidio, M.","Ruscio, D.D.","Frigioni, D.","Iovino, L.","Pierantonio, A."],"date":["2020"],"doi":["10.1109/TSE.2018.2846223"],"ids":["bascianiAutomatedSelectionOptimal2020a"],"journaltitle":["IEEE Trans. Softw. Eng."],"note":["cited By 8 \n\nTL;DR \n\nThis paper proposes an approach, based on well-established algorithms, to support modellers when multiple transformation chains are available to bridge a source metamodel with a target one."],"number":["3"],"pages":["251–279"],"title":["Automated Selection of Optimal Model Transformation Chains via Shortest-Path Algorithms"],"volume":["46"]},"creators":{"author":[{"lastName":"Basciani","firstName":"F."},{"lastName":"Demidio","firstName":"M."},{"lastName":"Ruscio","firstName":"D.D."},{"lastName":"Frigioni","firstName":"D."},{"lastName":"Iovino","firstName":"L."},{"lastName":"Pierantonio","firstName":"A."}]}},{"key":"bascianiExploringModelRepositories2018","type":"article","fields":{"langid":["english"],"abstract":["Great strides have been made in the development of tools and techniques for advance model management over the last decade. Despite the use of model repositories is gaining traction in industry, their use is still hampered by the limited understanding of the underlying platform semantics. Consequently, the all-important goal of reusing artefacts has led to an enduring quest for ways to search and retrieve artifacts more efficiently and accurately. Arguably, a contributory factor limiting the use of current search engines is the poor alignment between the query languages and the lattice of relations among the different and heterogeneous artifacts in the repository."],"author":["Basciani, Francesco","Ruscio, Davide Di","Rocco, Juri Di","Iovino, Ludovico","Pierantonio, Alfonso"],"date":["2018"],"ids":["basciani2018exploring,bascianiExploringModelRepositories2018a,bascianiExploringModelRepositories2018b,bascianiExploringModelRepositories2018c,bascianiExploringModelRepositories2018d,bascianiExploringModelRepositories2018e"],"journaltitle":["CEUR Workshop Proc."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["cited By 4 \n\ncited By 4"],"pages":["793–798"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"title":["Exploring model repositories by means of megamodel-aware search operators"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063097668&partnerID=40&md5=3d9cdf61d3885e4147334d00c123786c"],"volume":["2245"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"bascianiIntegratingSemanticReasoning2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["Models transformations are at the heart of model-driven engineering. They are increasingly recognized as crucial entities to achieve superior automation in many software engineering areas, whether it be requirements traceability, consistency restoration, and model management. As with many knowledge-intensive artifacts, model transformations can be challenging to design, develop, and maintain. Thus, defining complex model transformations by chaining existing ones is key to enhanced quality and increased reuse. Identifying the right transformation chains demand dedicated support when multiple paths are available to bridge a source metamodel with a target one. Metamodel coverage and Information Loss are among already established factors that can be adopted for supporting chain selections. In this work, we introduce the notion of Semantic Importance for metamodel elements involved in the transformation chains under analysis. The goal is improving the estimation accuracy of the Information Loss, which is being considered for ranking the possible transformations chains. The approach is supported by CITRIC+ tool, which includes a semantic reasoner able to select chains that induce the lowest Information Loss, with respect to the Semantic Importance specified by modelers, using a dedicated DSL. © 2021 ACM."],"author":["Basciani, F.","Di Pompeo, D.","Di Ruscio, D.","Iovino, L.","Pierantonio, A."],"booktitle":["Proc. ACM Symp. Appl. Comput."],"date":["2021"],"doi":["10.1145/3412841.3442024"],"ids":["bascianiIntegratingSemanticReasoning2021a,bascianiIntegratingSemanticReasoning2021b,bascianiIntegratingSemanticReasoning2021c,bascianiIntegratingSemanticReasoning2021d"],"isbn":["978-1-4503-8104-8"],"keywords":["Model management","Model transformation","Model-driven Engineering","Models transformations","Requirements engineering","Requirements traceability","Semantic importance","Semantic reasoning","Semantics","Software engineering","Transformation chains"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0"],"pages":["1494–1503"],"publisher":["Association for Computing Machinery"],"title":["Integrating semantic reasoning in information loss-based transformation chain rankers"]},"creators":{"author":[{"lastName":"Basciani","firstName":"F."},{"lastName":"Di Pompeo","firstName":"D."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Iovino","firstName":"L."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"bascianiMDEForgeExtensibleWebbased2014","type":"inproceedings","fields":{"langid":["english"],"abstract":["Model-Driven Engineering (MDE) refers to the systematic use of models as first class entities throughout the software development life cycle. Over the last few years, many MDE technologies have been conceived for developing domain specific modeling languages, and for supporting a wide range of model management activities. However, existing modeling platforms neglect a number of important features that if missed reduce the acceptance and the relevance of MDE in industrial contexts, e.g., the possibility to search and reuse already developed modeling artifacts, and to adopt model management tools as a service."],"author":["Basciani, Francesco","Rocco, Juri Di","Ruscio, Davide Di","Salle, Amleto Di","Pierantonio, Alfonso"],"booktitle":["Proc. 2nd Int. Workshop Model-Driven Eng. Cloud Co-Located 17th Int. Conf. Model Driven Eng. Lang. Syst. CloudMDEMoDELS 2014 Valencia Spain Sept. 30 2014"],"date":["2014"],"ids":["bascianiMDEForgeExtensibleWebBased2014,bascianiMDEForgeExtensibleWebbased2014a,bascianiMDEForgeExtensibleWebbased2014b"],"keywords":["Computer Science (all)"],"note":["cited By 68 \n\ncited By 68 \n\nTL;DR \n\nMDEForge is proposed, a novel extensible Web-based modeling platform specifically conceived to foster a community- based modeling repository that enables the adoption of model management tools as software-as-a-service that can be remotely used without overwhelming the users with intricate and error-prone installation and configuration procedures."],"pages":["66–75"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"title":["MDEForge: An extensible Web-based modeling platform"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84911959056&partnerID=40&md5=96d3c4967b26e5806ee9f0f62bb1015f"],"volume":["1242"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Salle","firstName":"Amleto Di"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"bascianiToolsupportedApproachAssessing2019","type":"article","fields":{"langid":["english"],"abstract":["Context: Software quality engineering is increasingly gaining interests also in the Model-Driven Engineering community as testified by a large corpus of research that has been produced over the last few years. Quality models are presented as convenient artifacts to specify and organize quality attributes that are of interest for considered stakeholders. Motivation: Existing approaches enabling the specification of quality models are affected by relevant limitations including limited extensibility, artifact specificity, and manual assessment, which might lead to informal, subjective, and non-reproducible assessment processes. Goal: This paper presents an approach and related tools supporting the definition of quality models underpinning the quality assessment of modeling artifacts. Quality models are defined in terms of sets of high-level quality attributes, which are top-down decomposed into sets of subordinate attributes. An operative environment is also provided to apply the defined quality models on actual modeling artifacts enabling automated quality assessment. A set of dedicated experiments is conducted to validate the approach. The experimental results show that the proposed techniques permit modelers to define quality models taken from the literature, and apply them to assess the quality of metamodels and transformations retrieved from public repositories. The validation permitted also to analyse the performance in terms of various population structures and size."],"author":["Basciani, Francesco","Di Rocco, Juri","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"date":["2019-04-01"],"doi":["10.1016/j.cola.2019.02.003"],"issn":["2590-1184"],"journaltitle":["J. Comput. Lang."],"keywords":["/unread","⛔ No INSPIRE recid found","Assessment of metamodel quality","Assessment of model transformation quality","Automated quality assessment","Model driven engineering"],"pages":["173–192"],"title":["A tool-supported approach for assessing the quality of modeling artifacts"],"volume":["51"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"bascianiTyphonMLModelingEnvironment2020","type":"inproceedings","fields":{"author":["Basciani, F.","Di Rocco, J.","Di Ruscio, D.","Pierantonio, A.","Iovino, L."],"booktitle":["Proc. - 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS-C 2020 - Companion Proc."],"date":["2020"],"doi":["10.1145/3417990.3421999"],"ids":["bascianiTyphonMLModelingEnvironment2020a,bascianiTyphonMLModelingEnvironment2020b"],"isbn":["978-1-4503-8135-2"],"keywords":["Data modelling","Database technologies","Hybrid polystore","Tools"],"note":["cited By 8 \n\ncited By 8 \n\nTL;DR \n\nTyphonML is proposed, a modeling language and supporting environment, which permits modelers to specify data that need to be persisted in hybrid architectures, by abstracting over the specificities of the underlying technologies."],"pages":["6–10"],"publisher":["Association for Computing Machinery, Inc"],"title":["TyphonML: A modeling environment to develop hybrid polystores"]},"creators":{"author":[{"lastName":"Basciani","firstName":"F."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Pierantonio","firstName":"A."},{"lastName":"Iovino","firstName":"L."}]},"sentenceCased":true},{"key":"bascianiUncertaintyManagementExtrafunctional2021","type":"article","fields":{"author":["Basciani, Francesco","Ruscio, Davide Di","Iovino, Ludovico","Pierantonio, Alfonso"],"date":["2021"],"doi":["10.5381/jot.2021.20.3.a2"],"journaltitle":["J. Object Technol."],"number":["3"],"pages":["2:1–15"],"title":["Uncertainty management with extra-functional qualities in multi-artefact co-evolution"],"volume":["20"]},"creators":{"author":[{"lastName":"Basciani","firstName":"Francesco"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"basiliSoftwareEngineeringResearch2018","type":"article","fields":{"abstract":["Software engineering is not only an increasingly challenging endeavor that goes beyond the intellectual capabilities of any single individual engineer but also an intensely human one. Tools and methods to develop software are employed by engineers of varied backgrounds within a large variety of organizations and application domains. As a result, the variation in challenges and practices in system requirements, architecture, and quality assurance is staggering. Human, domain, and organizational factors define the context within which software engineering methodologies and technologies are to be applied and therefore the context that research needs to account for, if it is to be impactful. This article provides an assessment of the current challenges faced by software engineering research in achieving its potential, a description of the root causes of such challenges, and a proposal for the field to move forward and become more impactful through collaborative research and innovation between public research and industry. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Basili, V.","Briand, L.","Bianculli, D.","Nejati, S.","Pastore, F.","Sabetzadeh, M."],"date":["2018-09"],"doi":["10.1109/MS.2018.290110216"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"number":["5"],"pages":["44–49"],"shorttitle":["Software Engineering Research and Industry"],"title":["Software Engineering Research and Industry: A Symbiotic Relationship to Foster Impact"],"volume":["35"]},"creators":{"author":[{"lastName":"Basili","firstName":"V."},{"lastName":"Briand","firstName":"L."},{"lastName":"Bianculli","firstName":"D."},{"lastName":"Nejati","firstName":"S."},{"lastName":"Pastore","firstName":"F."},{"lastName":"Sabetzadeh","firstName":"M."}]}},{"key":"Basmer201986","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - IEEE/ACM Int. Conf. Autom. Softw. Eng. Workshops, ASEW"],"affiliation":["Department of Computer Science, Humboldt-Universität zu Berlin, Germany"],"art_number":["8967417"],"author":["Basmer, M.","Kehrer, T."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/ASEW.2019.00035"],"isbn":["978-1-72814-136-7"],"note":["cited By 0 \n\nTL;DR \n\nThis paper reports on ongoing work encoding the adaptability of SiDiff as an algorithm configuration problem which is amenable to a sequential model-based optimization tool known as SMAC."],"pages":["86–89"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshops, ASEW 2019"],"source":["Scopus"],"title":["Encoding adaptability of software engineering tools as algorithm configuration problem: A case study"]},"creators":{"author":[{"lastName":"Basmer","firstName":"M."},{"lastName":"Kehrer","firstName":"T."}]},"sentenceCased":true},{"key":"Bataleblu20153418","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["IEEE Congr. Evol. Comput., CEC - Proc."],"affiliation":["Department of Aerospace Engineering, K. N. Toosi University of Technology, Tehran, Iran"],"art_number":["7257318"],"author":["Bataleblu, A.A.","Roshanian, J."],"date":["2015"],"document_type":["Conference Paper"],"doi":["10.1109/CEC.2015.7257318"],"isbn":["978-1-4799-7492-4"],"note":["cited By 6"],"pages":["3418–3425"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings"],"source":["Scopus"],"title":["Robust trajectory optimization of space launch vehicle using computational intelligence"]},"creators":{"author":[{"lastName":"Bataleblu","firstName":"A.A."},{"lastName":"Roshanian","firstName":"J."}]},"sentenceCased":true},{"key":"batot2016generic","type":"inproceedings","fields":{"langid":["english"],"author":["Batot, Edouard","Sahraoui, Houari"],"booktitle":["Proc. ACMIEEE 19th Int. Conf. Model Driven Eng. Lang. Syst."],"date":["2016"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nA generic framework for model-set selection for learning or testing Model-Driven Engineering tasks that apply to or manipulate models, such as model definition, model well-formedness checking, and model transformation is proposed."],"pages":["374–384"],"title":["A generic framework for model-set selection for the unification of testing and learning MDE tasks"]},"creators":{"author":[{"lastName":"Batot","firstName":"Edouard"},{"lastName":"Sahraoui","firstName":"Houari"}]},"sentenceCased":true},{"key":"batot2017heuristic","type":"inproceedings","fields":{"langid":["english"],"author":["Batot, Edouard","Kessentini, Wael","Sahraoui, Houari","Famelis, Michalis"],"booktitle":["2017 ACMIEEE 20th Int. Conf. Model Driven Eng. Lang. Syst. MODELS"],"date":["2017"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["210–220"],"publisher":["IEEE"],"title":["Heuristic-based recommendation for Metamodel—Ocl coevolution"]},"creators":{"author":[{"lastName":"Batot","firstName":"Edouard"},{"lastName":"Kessentini","firstName":"Wael"},{"lastName":"Sahraoui","firstName":"Houari"},{"lastName":"Famelis","firstName":"Michalis"}]},"sentenceCased":true},{"key":"batot2022promoting","type":"article","fields":{"langid":["english"],"author":["Batot, Edouard R.","Sahraoui, Houari"],"date":["2022-06"],"doi":["10.1007/s10270-021-00969-9"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"keywords":["/unread","⛔ No INSPIRE recid found","GOAL_Model-Assistance","notion","TECHNIQUE_GENETIC_ALGORITHMS"],"number":["3"],"pages":["1159–1178"],"title":["Promoting social diversity for the automated learning of complex MDE artifacts"],"volume":["21"]},"creators":{"author":[{"lastName":"Batot","firstName":"Edouard R."},{"lastName":"Sahraoui","firstName":"Houari"}]},"sentenceCased":true},{"key":"Bauer:2012:SAA:2473496.2473600","type":"inproceedings","fields":{"acmid":["2473600"],"author":["Bauer, Veronika","Heinemann, Lars","Deissenboeck, Florian"],"booktitle":["Proc. 2012 IEEE Int. Conf. Softw. Maint."],"date":["2012"],"isbn":["978-1-4673-2313-0"],"keywords":["API","Libraries","library","Maintenance engineering","Measurement","Modeling","software maintenance","Software maintenance","software reuse","Software systems"],"location":["Washington, DC, USA"],"nodoi":["10.1109/ICSM.2012.6405311"],"numpages":["10"],"pages":["483–492"],"publisher":["IEEE Computer Society"],"series":["ICSM '12"],"title":["A structured approach to assess third-party library usage"],"url":["http://dx.doi.org/10.1109/ICSM.2012.6405311"]},"creators":{"author":[{"lastName":"Bauer","firstName":"Veronika"},{"lastName":"Heinemann","firstName":"Lars"},{"lastName":"Deissenboeck","firstName":"Florian"}]},"sentenceCased":true},{"key":"bauerIoTReferenceModel2013","type":"incollection","fields":{"langid":["english"],"author":["Bauer, Martin","Bui, Nicola","De Loof, Jourik","Magerkurth, Carsten","Nettsträter, Andreas","Stefa, Julinda","Walewski, Joachim W."],"booktitle":["Enabling Things to Talk"],"date":["2013"],"editor":["Bassi, Alessandro","Bauer, Martin","Fiedler, Martin","Kramp, Thorsten","family=Kranenburg, given=Rob, prefix=van, useprefix=true","Lange, Sebastian","Meissner, Stefan"],"isbn":["978-3-642-40402-3 978-3-642-40403-0"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nThis Chapter introduces the IoT Reference Model as a precondition for working with the Reference Architecture that is introduced in Chap."],"pages":["113–162"],"publisher":["Springer Berlin Heidelberg"],"title":["IoT Reference Model"],"url":["http://link.springer.com/10.1007/978-3-642-40403-0_7"],"urldate":["2016-05-30"]},"creators":{"author":[{"lastName":"Bauer","firstName":"Martin"},{"lastName":"Bui","firstName":"Nicola"},{"lastName":"De Loof","firstName":"Jourik"},{"lastName":"Magerkurth","firstName":"Carsten"},{"lastName":"Nettsträter","firstName":"Andreas"},{"lastName":"Stefa","firstName":"Julinda"},{"lastName":"Walewski","firstName":"Joachim W."}],"editor":[{"lastName":"Bassi","firstName":"Alessandro"},{"lastName":"Bauer","firstName":"Martin"},{"lastName":"Fiedler","firstName":"Martin"},{"lastName":"Kramp","firstName":"Thorsten"},{"lastName":"Kranenburg","firstName":"Rob","prefix":"van","useprefix":true},{"lastName":"Lange","firstName":"Sebastian"},{"lastName":"Meissner","firstName":"Stefan"}]}},{"key":"bauerTestSuiteQuality2011","type":"article","fields":{"author":["Bauer, Eduard","Küster, Jochen M.","Engels, Gregor"],"date":["2011"],"doi":["10.1007/978-3-642-21952-8_3"],"journaltitle":["Objects Models Compon. Patterns"],"note":["TL;DR \n\nThis paper presents a coverage analysis approach for measuring test suite quality for model transformation chains that combines different coverage criteria and yields detailed coverage information that can be used to identify missing and redundant test cases."],"pages":["3–19"],"title":["Test Suite Quality for Model Transformation Chains"],"volume":["6705"]},"creators":{"author":[{"lastName":"Bauer","firstName":"Eduard"},{"lastName":"Küster","firstName":"Jochen M."},{"lastName":"Engels","firstName":"Gregor"}]}},{"key":"Baxter2008QualitativeCS","type":"article","fields":{"author":["Baxter, Pamela","Jack, Susan M."],"date":["2008"],"journaltitle":["Qual. Rep."],"note":["TL;DR \n\nAn overview of the types of case study designs is provided along with general recommendations for writing the research questions, developing propositions, determining the “case” under study, binding the case and a discussion of data sources and triangulation."],"pages":["544–559"],"title":["Qualitative case study methodology: Study design and implementation for novice researchers"],"volume":["13"]},"creators":{"author":[{"lastName":"Baxter","firstName":"Pamela"},{"lastName":"Jack","firstName":"Susan M."}]},"sentenceCased":true},{"key":"Bayraktar2021","type":"article","fields":{"abstract":["We study the problem of prediction with expert advice with adversarial corruption where the adversary can at most corrupt one expert. Using tools from viscosity theory, we characterize the long-time behavior of the value function of the game between the forecaster and the adversary. We provide lower and upper bounds for the growth rate of regret without relying on a comparison result. We show that depending on the description of regret, the limiting behavior of the game can significantly differ. © 2021 Erhan Bayraktar, Ibrahim Ekren and Xin Zhang."],"author":["Bayraktar, E.","Ekren, I.","Zhang, X."],"author_keywords":["Asymptotic expansion; Discontinuous viscosity solutions; Expert advice framework; Machine learning"],"date":["2021"],"document_type":["Article"],"issn":["15324435"],"journaltitle":["J. Mach. Learn. Res."],"keywords":["Artificial intelligence","Comparison result","Limiting behavior","Long time behavior","Lower and upper bounds","Prediction with expert advice","Software engineering","Value functions"],"note":["cited By 0"],"publisher":["Microtome Publishing"],"source":["Scopus"],"title":["Prediction against a limited adversary"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105844594&partnerID=40&md5=24bb99dc7bd439e1c91273ea25c881d6"],"volume":["22"]},"creators":{"author":[{"lastName":"Bayraktar","firstName":"E."},{"lastName":"Ekren","firstName":"I."},{"lastName":"Zhang","firstName":"X."}]},"sentenceCased":true},{"key":"BeautifulMonitoringGrafana","type":"online","fields":{"keywords":["grafana","influxdb"],"title":["Beautiful Monitoring With Grafana and InfluxDB"],"url":["https://www2.slideshare.net/leesjensen/beautiful-monitoring-with-grafana-and-influxdb?qid=2eb80839-115d-421d-afaa-e6dcbd79c280&v=&b=&from_search=4"],"urldate":["2021-01-05"]},"creators":{}},{"key":"beckerSymbolicInvariantVerification2006","type":"inproceedings","fields":{"author":["Becker, Basil","Beyer, Dirk","Giese, Holger","Klein, Florian","Schilling, Daniela"],"booktitle":["Proc. 28th Int. Conf. Softw. Eng."],"date":["2006"],"pages":["72–81"],"publisher":["ACM"],"title":["Symbolic invariant verification for systems with dynamic structural adaptation"],"url":["http://dl.acm.org/citation.cfm?id=1134297"],"urldate":["2015-04-07"]},"creators":{"author":[{"lastName":"Becker","firstName":"Basil"},{"lastName":"Beyer","firstName":"Dirk"},{"lastName":"Giese","firstName":"Holger"},{"lastName":"Klein","firstName":"Florian"},{"lastName":"Schilling","firstName":"Daniela"}]},"sentenceCased":true},{"key":"beechamPreparingTomorrowSoftware2017","type":"article","fields":{"langid":["english"],"abstract":["Global software engineering (GSE) is becoming common. It's thus important to educate university software engineering students in GSE. The authors discuss challenges to and recommendations for implementing such instruction."],"author":["Beecham, Sarah","Clear, Tony","Barr, John","Daniels, Mats","Oudshoorn, Michael","Noll, John","undefined","undefined","undefined","undefined"],"date":["2017-01"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["software engineering"],"note":["TL;DR \n\nThe authors discuss challenges to and recommendations for implementing such instruction in GSE and suggest ways to improve the quality of instruction."],"number":["1"],"pages":["9–12"],"title":["Preparing Tomorrow's Software Engineers for Work in a Global Environment"],"url":["http://ieeexplore.ieee.org/document/7819397/"],"volume":["34"]},"creators":{"author":[{"lastName":"Beecham","firstName":"Sarah"},{"lastName":"Clear","firstName":"Tony"},{"lastName":"Barr","firstName":"John"},{"lastName":"Daniels","firstName":"Mats"},{"lastName":"Oudshoorn","firstName":"Michael"},{"lastName":"Noll","firstName":"John"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"begelAnalyzeThis1452014","type":"inproceedings","fields":{"author":["Begel, Andrew","Zimmermann, Thomas"],"booktitle":["Proc. 36th Int. Conf. Softw. Eng."],"date":["2014"],"pages":["12–23"],"publisher":["ACM"],"title":["Analyze this! 145 questions for data scientists in software engineering"],"url":["http://dl.acm.org/citation.cfm?id=2568233"],"urldate":["2016-01-22"]},"creators":{"author":[{"lastName":"Begel","firstName":"Andrew"},{"lastName":"Zimmermann","firstName":"Thomas"}]},"sentenceCased":true},{"key":"begoliHeterogeneousPolystorelikeData2016","type":"inproceedings","fields":{"langid":["english"],"author":["Begoli, Edmon","Kistler, Derek","Bates, Jack"],"date":["2016-12"],"doi":["10.1109/BigData.2016.7840896"],"isbn":["978-1-4673-9005-7"],"pages":["2550–2554"],"publisher":["IEEE"],"title":["Towards a heterogeneous, polystore-like data architecture for the US Department of Veteran Affairs (VA) enterprise analytics"]},"creators":{"author":[{"lastName":"Begoli","firstName":"Edmon"},{"lastName":"Kistler","firstName":"Derek"},{"lastName":"Bates","firstName":"Jack"}]},"sentenceCased":true},{"key":"Behjat2020","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Des. Eng. Tech. Conf."],"affiliation":["Department of Mechanical and Aerospace Engineering, University at Buffalo, Buffalo, NY 14260, United States"],"art_number":["V11BT11A024"],"author":["Behjat, A.","Oddiraju, M.","Attarzadeh, M.A.","Nouh, M.","Chowdhury, S."],"correspondence_address1":["Chowdhury, S.; Department of Mechanical and Aerospace Engineering, United States; email: soumacho@buffalo.edu"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1115/DETC2020-22747"],"isbn":["978-0-7918-8401-0"],"note":["cited By 2"],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the ASME Design Engineering Technical Conference"],"source":["Scopus"],"title":["Metamodel based forward and inverse design for passive vibration suppression"],"volume":["11B-2020"]},"creators":{"author":[{"lastName":"Behjat","firstName":"A."},{"lastName":"Oddiraju","firstName":"M."},{"lastName":"Attarzadeh","firstName":"M.A."},{"lastName":"Nouh","firstName":"M."},{"lastName":"Chowdhury","firstName":"S."}]},"sentenceCased":true},{"key":"BellogiN:2013:CSH:2397740.2398191","type":"article","fields":{"acmid":["2398191"],"author":["Bellogín, Alejandro","Cantador, IváN","Castells, Pablo"],"date":["2013-02"],"issn":["0020-0255"],"issue_date":["February, 2013"],"journaltitle":["Inf. Sci."],"keywords":["Collaborative tagging","Evaluation","Implicit feedback","Recommender system","Social network","Social Web"],"noaddress":["New York, NY, USA"],"nodoi":["10.1016/j.ins.2012.09.039"],"numpages":["28"],"pages":["142–169"],"publisher":["Elsevier Science Inc."],"title":["A comparative study of heterogeneous item recommendations in social systems"],"url":["http://dx.doi.org/10.1016/j.ins.2012.09.039"],"volume":["221"]},"creators":{"author":[{"lastName":"Bellogín","firstName":"Alejandro"},{"lastName":"Cantador","firstName":"IváN"},{"lastName":"Castells","firstName":"Pablo"}]},"sentenceCased":true},{"key":"Bellogin2011","type":"inproceedings","fields":{"author":["Bellogin, A.","Castells, P.","Cantador, I."],"booktitle":["ACM RecSys 11"],"date":["2011"],"pages":["333–336"],"title":["Precision-oriented evaluation of recommender systems: An algorithmic comparison"]},"creators":{"author":[{"lastName":"Bellogin","firstName":"A."},{"lastName":"Castells","firstName":"P."},{"lastName":"Cantador","firstName":"I."}]},"sentenceCased":true},{"key":"Benaben20191549","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Winter Simul. Conf."],"affiliation":["IMT Mines Albi, Centre Génie Industriel, Albi, 81000, France"],"art_number":["9004828"],"author":["Benaben, F.","Lauras, M.","Fertier, A.","Salatge, N."],"coden":["WSCPD"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/WSC40007.2019.9004828"],"isbn":["978-1-72813-283-9"],"issn":["08917736"],"note":["cited By 2 \n\nTL;DR \n\nThe use of Model-Driven Engineering tools (such as metamodel and model transformation) could benefit to the domain of AI by introducing a way to extend the apprehension of unknown situations."],"pages":["1549–1563"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - Winter Simulation Conference"],"source":["Scopus"],"title":["Integrating model-driven engineering as the next challenge for artificial intelligence - application to risk and crisis management"],"volume":["2019-December"]},"creators":{"author":[{"lastName":"Benaben","firstName":"F."},{"lastName":"Lauras","firstName":"M."},{"lastName":"Fertier","firstName":"A."},{"lastName":"Salatge","firstName":"N."}]},"sentenceCased":true},{"key":"Bencomo20121","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Workshop Models@run.time, MRT - Being Part ACM/IEEE Int. Conf. Model Driven Eng. Lang. Syst., MODELS"],"affiliation":["INRIA Paris-Rocquencourt, France; Lancester University, United Kingdom; Technische Universität, Dresden, Germany; Stiftelsen SINTEF, Norway; RWTH Aachen, Germany"],"author":["Bencomo, N.","Blair, G.","Götz, S.","Morin, B.","Rumpe, B."],"correspondence_address1":["Bencomo, N.; INRIA Paris-RocquencourtFrance; email: nelly@acm.org"],"date":["2012"],"document_type":["Conference Paper"],"doi":["10.1145/2422518.2422519"],"isbn":["978-1-4503-1799-3"],"note":["cited By 0"],"pages":["1–2"],"series":["Proceedings of the 7th Workshop on Models@run.Time, MRT 2012 - Being Part of the ACM/IEEE 15th International Conference on Model Driven Engineering Languages and Systems, MODELS 2012"],"source":["Scopus"],"title":["Summary of the 7th International Workshop on Models@run.Time"]},"creators":{"author":[{"lastName":"Bencomo","firstName":"N."},{"lastName":"Blair","firstName":"G."},{"lastName":"Götz","firstName":"S."},{"lastName":"Morin","firstName":"B."},{"lastName":"Rumpe","firstName":"B."}]}},{"key":"BencomoGS19","type":"article","fields":{"langid":["english"],"author":["Bencomo, Nelly","Götz, Sebastian","Song, Hui"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2019"],"doi":["10.1007/S10270-018-00712-X"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["5"],"pages":["3049–3082"],"timestamp":["Fri, 18 Sep 2020 11:19:25 +0200"],"title":["Models@run.Time: A guided tour of the state of the art and research challenges"],"volume":["18"]},"creators":{"author":[{"lastName":"Bencomo","firstName":"Nelly"},{"lastName":"Götz","firstName":"Sebastian"},{"lastName":"Song","firstName":"Hui"}]},"sentenceCased":true},{"key":"bencomoModelsRunTime2014","type":"book","fields":{"date":["2014"],"editor":["Bencomo, Nelly","France, Robert","Cheng, Betty H. C.","Aßmann, Uwe"],"editorb":["Hutchison, David","Kanade, Takeo","Kittler, Josef","Kleinberg, Jon M.","Kobsa, Alfred","Mattern, Friedemann","Mitchell, John C.","Naor, Moni","Nierstrasz, Oscar","Pandu Rangan, C.","Steffen, Bernhard","Terzopoulos, Demetri","Tygar, Doug","Weikum, Gerhard"],"editorbtype":["redactor"],"isbn":["978-3-319-08914-0 978-3-319-08915-7"],"location":["Cham"],"note":["TL;DR \n\nThis book comprises four research roadmaps, written by the original participants of the Dagstuhl Seminar over the course of two years following the seminar, and seven research papers from experts in the area that provide insights to key features of the use of runtime models."],"publisher":["Springer International Publishing"],"series":["Lecture Notes in Computer Science"],"title":["Models@run.Time"],"url":["http://link.springer.com/10.1007/978-3-319-08915-7"],"urldate":["2016-08-21"],"volume":["8378"]},"creators":{"editor":[{"lastName":"Bencomo","firstName":"Nelly"},{"lastName":"France","firstName":"Robert"},{"lastName":"Cheng","firstName":"Betty H. C."},{"lastName":"Aßmann","firstName":"Uwe"}],"editorb":[{"lastName":"Hutchison","firstName":"David"},{"lastName":"Kanade","firstName":"Takeo"},{"lastName":"Kittler","firstName":"Josef"},{"lastName":"Kleinberg","firstName":"Jon M."},{"lastName":"Kobsa","firstName":"Alfred"},{"lastName":"Mattern","firstName":"Friedemann"},{"lastName":"Mitchell","firstName":"John C."},{"lastName":"Naor","firstName":"Moni"},{"lastName":"Nierstrasz","firstName":"Oscar"},{"lastName":"Pandu Rangan","firstName":"C."},{"lastName":"Steffen","firstName":"Bernhard"},{"lastName":"Terzopoulos","firstName":"Demetri"},{"lastName":"Tygar","firstName":"Doug"},{"lastName":"Weikum","firstName":"Gerhard"}]}},{"key":"bendraouComparisonSixUMLBased2010","type":"article","fields":{"langid":["english"],"abstract":["Describing and managing activities, resources, and constraints of software development processes is a challenging goal for many organizations. A first generation of Software Process Modeling Languages (SPMLs) appeared in the 1990s but failed to gain broad industrial support. Recently, however, a second generation of SPMLs has appeared, leveraging the strong industrial interest for modeling languages such as UML. In this paper, we propose a comparison of these UML-based SPMLs. While not exhaustive, this comparison concentrates on SPMLs most representative of the various alternative approaches, ranging from UML-based framework specializations to full-blown executable metamodeling approaches. To support the comparison of these various approaches, we propose a frame gathering a set of requirements for process modeling, such as semantic richness, modularity, executability, conformity to the UML standard, and formality. Beyond discussing the relative merits of these approaches, we also evaluate the overall suitability of these UML-based SPMLs for software process modeling. Finally, we discuss the impact of these approaches on the current state of the practice, and conclude with lessons we have learned in doing this comparison."],"author":["Bendraou, Reda","Jezequel, Jean-Marc","Gervais, Marie-Pierre","Blanc, Xavier"],"date":["2010-09"],"doi":["10.1109/TSE.2009.85"],"issn":["0098-5589"],"journaltitle":["IIEEE Trans. Software Eng."],"keywords":["comparison analysis","uml"],"note":["TL;DR \n\nThis article proposes a comparison of these UML-based SPMLs most representative of the various alternative approaches, ranging from UML-based framework specializations to full-blown executable meta-modeling approaches, and proposes a frame gathering a set of requirements for process modeling."],"number":["5"],"pages":["662–675"],"title":["A Comparison of Six UML-Based Languages for Software Process Modeling"],"volume":["36"]},"creators":{"author":[{"lastName":"Bendraou","firstName":"Reda"},{"lastName":"Jezequel","firstName":"Jean-Marc"},{"lastName":"Gervais","firstName":"Marie-Pierre"},{"lastName":"Blanc","firstName":"Xavier"}]}},{"key":"benelallamMavenDependencyGraph2019","type":"article","fields":{"author":["Benelallam, Amine","Harrand, Nicolas","Soto-Valero, César","Baudry, Benoit","Barais, Olivier"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/journals/corr/abs-1901-05392"],"date":["2019"],"eprint":["1901.05392"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"timestamp":["Fri, 01 Feb 2019 13:39:59 +0100"],"title":["The maven dependency graph: A temporal graph-based representation of maven central"],"url":["http://arxiv.org/abs/1901.05392"],"volume":["abs/1901.05392"]},"creators":{"author":[{"lastName":"Benelallam","firstName":"Amine"},{"lastName":"Harrand","firstName":"Nicolas"},{"lastName":"Soto-Valero","firstName":"César"},{"lastName":"Baudry","firstName":"Benoit"},{"lastName":"Barais","firstName":"Olivier"}]},"sentenceCased":true},{"key":"bengioPracticalRecommendationsGradientbased2012","type":"incollection","fields":{"abstract":["Learning algorithms related to artificial neural networks and in particular for Deep Learning may seem to involve many bells and whistles, called hyper-parameters. This chapter is meant as a practical guide with recommendations for some of the most commonly used hyperparameters, in particular in the context of learning algorithms based on back-propagated gradient and gradient-based optimization. It also discusses how to deal with the fact that more interesting results can be obtained when allowing one to adjust many hyper-parameters. Overall, it describes elements of the practice used to successfully and efficiently train and debug large-scale and often deep multi-layer neural networks. It closes with open questions about the training difficulties observed with deeper architectures."],"author":["Bengio, Yoshua"],"booktitle":["Neural networks: Tricks of the trade: Second edition"],"date":["2012"],"doi":["10.1007/978-3-642-35289-8₂6"],"editor":["Montavon, Grégoire","Orr, Geneviève B.","Müller, Klaus-Robert"],"isbn":["978-3-642-35289-8"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nOverall, this chapter describes elements of the practice used to successfully and efficiently train and debug large-scale and often deep multi-layer neural networks and closes with open questions about the training difficulties observed with deeper architectures."],"pages":["437–478"],"publisher":["Springer Berlin Heidelberg"],"title":["Practical recommendations for gradient-based training of deep architectures"]},"creators":{"author":[{"lastName":"Bengio","firstName":"Yoshua"}],"editor":[{"lastName":"Montavon","firstName":"Grégoire"},{"lastName":"Orr","firstName":"Geneviève B."},{"lastName":"Müller","firstName":"Klaus-Robert"}]},"sentenceCased":true},{"key":"benoitGlobalizingModelingLanguages","type":"article","fields":{"author":["Benoit, Comemale","Julien, DeAntoni","Benoit, Baudry","Robert B., France","Jean-Marc, Jezequel","Jeff, Gray"],"doi":["10.1109/MC.2014.147"],"note":["TL;DR \n\nA research initiative is described that broadens the DSML research focus beyond independent DSML development to one that supports globalized DSMLs-that is, DS MLs that facilitate coordination of work across different domains of expertise."],"title":["Globalizing Modeling Languages"]},"creators":{"author":[{"lastName":"Benoit","firstName":"Comemale"},{"lastName":"Julien","firstName":"DeAntoni"},{"lastName":"Benoit","firstName":"Baudry"},{"lastName":"Robert B.","firstName":"France"},{"lastName":"Jean-Marc","firstName":"Jezequel"},{"lastName":"Jeff","firstName":"Gray"}]}},{"key":"BenSalem2018719","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Struct. Mutltidiscip. Opt."],"affiliation":["Ecole des mines de St-Etienne, Saint Étienne, France; ANSYS, Inc., Villeurbanne, France"],"author":["Ben Salem, M.","Tomaso, L."],"coden":["SMOTB"],"correspondence_address1":["Ben Salem, M.; ANSYS, France; email: Malek.ben-salem@emse.fr"],"date":["2018"],"document_type":["Article"],"doi":["10.1007/s00158-018-1925-3"],"issn":["1615147X"],"journaltitle":["Struct. Multidiscip. Optim."],"keywords":["GOAL_Model-Search","notion"],"note":["cited By 21 \n\nTL;DR \n\nA universal criterion that can be applied to any type of surrogate models is introduced, composed of three complementary components measuring the quality of general surrogate models: internal accuracy, predictive performance and a roughness penalty. \n\nTO BE EXCLUDED"],"number":["2"],"pages":["719–734"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Automatic selection for general surrogate models"],"volume":["58"]},"creators":{"author":[{"lastName":"Ben Salem","firstName":"M."},{"lastName":"Tomaso","firstName":"L."}]},"sentenceCased":true},{"key":"bergmayrOutplaceTransformationEvolution2014","type":"inproceedings","fields":{"langid":["english"],"author":["Bergmayr, Alexander","Troya, Javier","Wimmer, Manuel"],"date":["2014"],"doi":["10.1145/2642937.2642946"],"isbn":["978-1-4503-3013-8"],"note":["TL;DR \n\nThe idea is to infer from evolved out-place transformations patch transformations that propagate changes to existing models by re-executing solely the affected parts based on an in-place execution strategy, so that existing models are only updated by a patch instead of newly produced."],"pages":["647–652"],"publisher":["ACM Press"],"title":["From out-place transformation evolution to in-Place model patching"]},"creators":{"author":[{"lastName":"Bergmayr","firstName":"Alexander"},{"lastName":"Troya","firstName":"Javier"},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"Berkhin2006","type":"article","fields":{"author":["Berkhin, Pavel","others"],"date":["2006"],"doi":["10.1007/3-540-28349-8_2"],"ids":["B06,berkhin2006survey"],"journaltitle":["Group. Multidimens. Data Recent Adv. Clust."],"pages":["25–71"],"title":["A survey of clustering data mining techniques."],"volume":["25"]},"creators":{"author":[{"lastName":"Berkhin","firstName":"Pavel"},{"lastName":"others"}]},"sentenceCased":true},{"key":"bermejo-alonsoOntologicalFrameworkAutonomous2010","type":"article","fields":{"author":["Bermejo-Alonso, Julita","Sanz, Ricardo","Rodríguez, Manuel","Hernández, Carlos"],"date":["2010"],"journaltitle":["Int. J. Adv. Intell. Syst."],"note":["TL;DR \n\nThis work develops a domain ontology and an ontologybased methodology to support the conceptual modelling of autonomous systems, and exploits the ontology to generate the conceptual models for a generic engineering process."],"number":["3"],"title":["An ontological framework for autonomous systems modelling"],"url":["http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.641.7853&rep=rep1&type=pdf#page=57"],"urldate":["2016-08-21"],"volume":["3"]},"creators":{"author":[{"lastName":"Bermejo-Alonso","firstName":"Julita"},{"lastName":"Sanz","firstName":"Ricardo"},{"lastName":"Rodríguez","firstName":"Manuel"},{"lastName":"Hernández","firstName":"Carlos"}]},"sentenceCased":true},{"key":"bermejoalonsoEngineeringOntologyAutonomous2011","type":"article","fields":{"author":["Bermejo Alonso, Julita","Sanz Bravo, Ricardo","Rodríguez, Manuel","Hernández Corbato, Carlos"],"date":["2011"],"title":["Engineering an Ontology for Autonomous Systems-The OASys Ontology"],"url":["http://oa.upm.es/11957/"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Bermejo Alonso","firstName":"Julita"},{"lastName":"Sanz Bravo","firstName":"Ricardo"},{"lastName":"Rodríguez","firstName":"Manuel"},{"lastName":"Hernández Corbato","firstName":"Carlos"}]}},{"key":"bernardo_object_2012","type":"incollection","fields":{"langid":["english"],"abstract":["The Object Constraint Language (OCL) started as a complement of the UML notation with the goal to overcome the limitations of UML (and in general, any graphical notation) in terms of precisely specifying detailed aspects of a system design. Since then, OCL has become a key component of any model-driven engineering (MDE) technique as the default language for expressing all kinds of (meta)model query, manipulation and specification requirements. Among many other applications, OCL is frequently used to express model transformations (as part of the source and target patterns of transformation rules), well-formedness rules (as part of the definition of new domain-specific languages), or code-generation templates (as a way to express the generation patterns and rules)."],"author":["Cabot, Jordi","Gogolla, Martin"],"booktitle":["Formal Methods for Model-Driven Engineering"],"date":["2012"],"doi":["10.1007/978-3-642-30982-3_3"],"editor":["Bernardo, Marco","Cortellessa, Vittorio","Pierantonio, Alfonso"],"isbn":["978-3-642-30981-6 978-3-642-30982-3"],"location":["Berlin, Heidelberg"],"note":["Series Title: Lecture Notes in Computer Science \n\nTL;DR \n\nThis chapter pretends to provide a comprehensive view of this language, its many applications and available tool support as well as the latest research developments and open challenges around it."],"pages":["58–90"],"publisher":["Springer Berlin Heidelberg"],"shorttitle":["Object Constraint Language (OCL)"],"title":["Object Constraint Language (OCL): A Definitive Guide"],"volume":["7320"]},"creators":{"author":[{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Gogolla","firstName":"Martin"}],"editor":[{"lastName":"Bernardo","firstName":"Marco"},{"lastName":"Cortellessa","firstName":"Vittorio"},{"lastName":"Pierantonio","firstName":"Alfonso"}]}},{"key":"Berry:1997:DMT:560675","type":"book","fields":{"author":["Berry, Michael J.","Linoff, Gordon"],"date":["1997"],"isbn":["0-471-17980-9"],"location":["New York, NY, USA"],"note":["TL;DR \n\nOne of the first practical guides to mining business data, Data Mining Techniques describes techniques for detecting customer behavior patterns useful in formulating marketing, sales, and customer support strategies."],"publisher":["John Wiley & Sons, Inc."],"title":["Data mining techniques: For marketing, sales, and customer support"]},"creators":{"author":[{"lastName":"Berry","firstName":"Michael J."},{"lastName":"Linoff","firstName":"Gordon"}]},"sentenceCased":true},{"key":"bert2018","type":"misc","fields":{"author":["Devlin, Jacob","Chang, Ming-Wei","Lee, Kenton","Toutanova, Kristina"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2018"],"eprint":["1810.04805"],"eprinttype":["arxiv"],"ids":["BERT18"],"keywords":["Computation and Language (cs.CL)","FOS: Computer and information sciences"],"organization":["arXiv"],"timestamp":["Tue, 30 Oct 2018 20:39:56 +0100"],"title":["BERT: Pre-training of deep bidirectional transformers for language understanding"],"url":["https://arxiv.org/abs/1810.04805"]},"creators":{"author":[{"lastName":"Devlin","firstName":"Jacob"},{"lastName":"Chang","firstName":"Ming-Wei"},{"lastName":"Lee","firstName":"Kenton"},{"lastName":"Toutanova","firstName":"Kristina"}]},"sentenceCased":true},{"key":"bertoaQualityAttributesSoftware2010","type":"article","fields":{"author":["Bertoa, Manuel","Vallecillo, Antonio"],"date":["2010"],"ids":["bertoaQualityAttributesSoftware"],"journaltitle":["Málaga Spain"],"note":["TL;DR \n\nA quality model for Metamodels is proposed, that defines a set of quality attributes for evaluating MetAModels."],"title":["Quality attributes for software metamodels"],"url":["http://www.lcc.uma.es/~av/Publicaciones/10/qaoose10.pdf"],"urldate":["2015-09-15"]},"creators":{"author":[{"lastName":"Bertoa","firstName":"Manuel"},{"lastName":"Vallecillo","firstName":"Antonio"}]},"sentenceCased":true},{"key":"BestDataPipeline","type":"online","fields":{"title":["The Best Data Pipeline Tools List for 2021 | Hevo Blog"],"url":["https://hevodata.com/blog/data-pipeline-tools-list/"],"urldate":["2021-03-18"]},"creators":{}},{"key":"bettiniDetectingMetamodelEvolutions2020","type":"article","fields":{"langid":["english"],"abstract":["Model-Driven Engineering [Sch06] (MDE) is a discipline that leverages abstraction and automation in software development. Projects are typically composed of inherently different artifacts, including models, metamodels, model transformations, code generators, and concrete syntax definitions. Despite the increasing availability of reusable projects (e.g., through GitHub), their reuse possibilities depend on the availability of accurate, high-level metadata describing architectural information about the project at hand."],"author":["Bettini, Lorenzo","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"date":["2020"],"doi":["10.5381/jot.2020.19.2.a14"],"ids":["bettiniDetectingMetamodelEvolutions2020a,bettiniDetectingMetamodelEvolutions2020b"],"issn":["1660-1769"],"journaltitle":["JOT"],"keywords":["Evolution","Megamodels","Model-driven engineering","Quality","Reverse engineering"],"note":["cited By 1"],"number":["2"],"pages":["14:1"],"title":["Detecting Metamodel Evolutions in Repositories of Model-Driven Projects."],"volume":["19"]},"creators":{"author":[{"lastName":"Bettini","firstName":"Lorenzo"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]}},{"key":"bettiniEdeltaApproachDefining2017","type":"inproceedings","fields":{"author":["Bettini, Lorenzo","DI RUSCIO, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"booktitle":["CEUR Workshop Proc."],"date":["2017"],"ids":["bettini2017edelta,bettiniEdeltaApproachDefining2017a,bettiniEdeltaApproachDefining2017b,bettiniEdeltaApproachDefining2017c,bettiniEdeltaApproachDefining2017d"],"note":["cited By 13 \n\ncited By 13 \n\nTL;DR \n\nEdelta is proposed, a domain specific language for specifying reusable libraries of metamodel refactorings that allows both atomic and complex changes and it is supported by an Eclipse-based IDE."],"pages":["71–80"],"publisher":["CEUR-WS.org"],"series":["CEUR Workshop Proceedings"],"title":["Edelta: An approach for defining and applying reusable metamodel refactorings"],"url":["http://ceur-ws.org/Vol-2019/me_4.pdf"],"volume":["2019"]},"creators":{"author":[{"lastName":"Bettini","firstName":"Lorenzo"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"bettiniEdeltaSupportingLive2020","type":"inproceedings","fields":{"author":["Bettini, Lorenzo","Di Ruscio, D.","Iovino, L.","Pierantonio, A."],"booktitle":["Proc. - 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS-C 2020 - Companion Proc."],"date":["2020"],"doi":["10.1145/3417990.3419501"],"ids":["bettiniEdeltaSupportingLive2020a,bettiniEdeltaSupportingLive2020b,bettiniEdeltaSupportingLive2020c"],"isbn":["978-1-4503-8135-2"],"keywords":["Edelta","Evolution","Metamodels","Refactoring"],"note":["cited By 1 \n\ncited By 1 \n\nTL;DR \n\nThe new version of Edelta is presented, which provides EMF modelers with linguistic constructs for specifying both basic and complex refactorings and allows the users to easily introduce additional validation checks in their own Edelta programs, which are taken into consideration by the Edelta compiler and the IDE."],"pages":["324–333"],"publisher":["Association for Computing Machinery, Inc"],"title":["Edelta 2.0: Supporting live metamodel evolutions"]},"creators":{"author":[{"lastName":"Bettini","firstName":"Lorenzo"},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Iovino","firstName":"L."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"bettiniExecutableMetamodelRefactoring2022","type":"article","fields":{"abstract":["Like any software artifacts, metamodels are evolving entities that constantly change over time for different reasons. Changing metamodels by keeping them consistent with other existing artifacts is an error-prone and tedious activity without the availability of automated support. In this paper, we foster the adoption of metamodel refactorings collected in a curated catalog. The Edelta framework is proposed as an operative environment to provide modelers with constructs for specifying basic refactorings and evolution operators, to define a complete metamodel refactoring catalog. The proposed environment has been used to implement the metamodel refactorings available in the literature and make them executable. A detailed discussion on how modelers can use and contribute to the definition of the catalog is also given. © 2022, The Author(s)."],"author":["Bettini, L.","Di Ruscio, D.","Iovino, L.","Pierantonio, A."],"date":["2022"],"doi":["10.1007/s10270-022-01034-9"],"ids":["bettiniExecutableMetamodelRefactoring2022b"],"issn":["16191366"],"journaltitle":["Softw. Syst. Model."],"keywords":["Automated support","Catalog","Change-over time","Error prones","Evolution","Evolution operator","Executables","Meta model","Metamodels","Refactoring","Refactorings","Software artefacts","Software engineering"],"note":["cited By 0 \n\nTL;DR \n\nThe Edelta framework is proposed as an operative environment to provide modelers with constructs for specifying basic refactorings and evolution operators, to define a complete metamodel refactoring catalog."],"number":["5"],"pages":["1689–1709"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"title":["An executable metamodel refactoring catalog"],"volume":["21"]},"creators":{"author":[{"lastName":"Bettini","firstName":"L."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Iovino","firstName":"L."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"bettiniSupportingSafeMetamodel2022","type":"article","fields":{"author":["Bettini, L","Di Ruscio, D","Iovino, L","Pierantonio, A"],"date":["2022"],"doi":["10.1007/s10009-022-00646-2"],"ids":["bettiniSupportingSafeMetamodel2022a,bettiniSupportingSafeMetamodel2022b,bettiniSupportingSafeMetamodel2022c,bettiniSupportingSafeMetamodel2022d,bettiniSupportingSafeMetamodel2022e"],"journaltitle":["Int. J. Softw. TOOLS Technol. Transf."],"keywords":["Management operation","Meta model","Meta-model evolutions","Metamodel evolution","Model management","Model transformation","Model-based OPC","Model-driven engineering","Model-driven Engineering","Modeling analyzes","Parallel evolution","Safe evolution"],"note":["cited By 1 \n\ncited By 1 \n\ncited By 2 \n\nTL;DR \n\nThis paper presents a tool-supported approach that can automatically analyze the available metamodels and alert modelers in case of change operations that can give place to invalid situations like dangling references."],"publisher":["Springer Science and Business Media Deutschland GmbH"],"title":["Supporting safe metamodel evolution with edelta"]},"creators":{"author":[{"lastName":"Bettini","firstName":"L"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Iovino","firstName":"L"},{"lastName":"Pierantonio","firstName":"A"}]},"sentenceCased":true},{"key":"Beyer:2018:ACP:3196321.3196333","type":"inproceedings","fields":{"acmid":["3196333"],"author":["Beyer, Stefanie","Macho, Christian","Pinzger, Martin","Di Penta, Massimiliano"],"booktitle":["Proc. 26th Conf. Program Comprehension"],"date":["2018"],"isbn":["978-1-4503-5714-2"],"location":["New York, NY, USA"],"nodoi":["10.1145/3196321.3196333"],"numpages":["11"],"pages":["211–221"],"publisher":["ACM"],"series":["ICPC '18"],"title":["Automatically classifying posts into question categories on stack overflow"],"url":["http://doi.acm.org/10.1145/3196321.3196333"]},"creators":{"author":[{"lastName":"Beyer","firstName":"Stefanie"},{"lastName":"Macho","firstName":"Christian"},{"lastName":"Pinzger","firstName":"Martin"},{"lastName":"Di Penta","firstName":"Massimiliano"}]},"sentenceCased":true},{"key":"beyer2020kind","type":"article","fields":{"author":["Beyer, Stefanie","Macho, Christian","Di Penta, Massimiliano","Pinzger, Martin"],"date":["2020"],"journaltitle":["Empir. Softw. Eng."],"number":["3"],"pages":["2258–2301"],"publisher":["Springer"],"title":["What kind of questions do developers ask on Stack Overflow? A comparison of automated approaches to classify posts into question categories"],"volume":["25"]},"creators":{"author":[{"lastName":"Beyer","firstName":"Stefanie"},{"lastName":"Macho","firstName":"Christian"},{"lastName":"Di Penta","firstName":"Massimiliano"},{"lastName":"Pinzger","firstName":"Martin"}]},"sentenceCased":true},{"key":"beyhlSmartModelSearch","type":"article","fields":{"author":["Beyhl, Thomas","Giese, Holger"],"title":["Smart Model Search in Model Repositories by Modular Search Index Generation and Querying (Submitted to SLE2014 - confidential)"]},"creators":{"author":[{"lastName":"Beyhl","firstName":"Thomas"},{"lastName":"Giese","firstName":"Holger"}]},"sentenceCased":true},{"key":"beyhlSmartModelSearcha","type":"article","fields":{"langid":["english"],"abstract":["Model search engines (MSEs) retrieve knowledge embodied by model repositories. Existing MSEs perform text-based search and exploit meta-models to enable queries that require meta-information. However, model repositories embody relevant hidden knowledge as well. Existing MSEs do not retrieve such hidden knowledge, because their general-purpose search index does not support to derive hidden knowledge effectively. In this paper, we present a smart model search approach, which exploits low-level knowledge to derive high-level knowledge by supporting modules that allow the integration of existing querying and mining techniques. Our approach permits the pre-computation of results for time-consuming modules in terms of a search index to guarantee reasonable response times, while less time-consuming modules are computed on demand. Our approach guides the systematic integration of modules by means of well-formedness checks to guarantee reasonable search results. We evaluate our approach by a case study using multiple data sets derived from an open source project."],"author":["Beyhl, Thomas","Giese, Holger"],"pages":["20"],"title":["Smart Model Search in Model Repositories by Modular Search Index Generation and Querying"]},"creators":{"author":[{"lastName":"Beyhl","firstName":"Thomas"},{"lastName":"Giese","firstName":"Holger"}]}},{"key":"BezivinJRV05","type":"inproceedings","fields":{"author":["Bézivin, Jean","Jouault, Frédéric","Rosenthal, Peter","Valduriez, Patrick"],"booktitle":["Eur. MDA Workshop MDAFA 2003 MDAFA 2004 Revis. Sel. Pap."],"date":["2005"],"pages":["33–46"],"publisher":["Springer"],"series":["LNCS"],"title":["Modeling in the Large and Modeling in the Small"],"volume":["3599"]},"creators":{"author":[{"lastName":"Bézivin","firstName":"Jean"},{"lastName":"Jouault","firstName":"Frédéric"},{"lastName":"Rosenthal","firstName":"Peter"},{"lastName":"Valduriez","firstName":"Patrick"}]}},{"key":"BezivinJV04","type":"inproceedings","fields":{"author":["Bézivin, J.","Jouault, F.","Valduriez, P."],"booktitle":["Proc OOPSLAGPCE Best Pract. Model-Driven Softw. Dev. Workshop"],"date":["2004"],"ids":["bezivin2004need"],"note":["TL;DR \n\nBesides argumenting for the need to use mega-models in a variety of situations, the paper argues on the importance of this concept as an essential part of any model-driven software development platform."],"title":["On the need for Megamodels"]},"creators":{"author":[{"lastName":"Bézivin","firstName":"J."},{"lastName":"Jouault","firstName":"F."},{"lastName":"Valduriez","firstName":"P."}]},"sentenceCased":true},{"key":"bezivinUnificationPowerModels2005","type":"article","fields":{"langid":["english"],"author":["Bézivin, Jean"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2005-05"],"doi":["10.1007/s10270-005-0079-0"],"ids":["Bezivin05"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["2"],"pages":["171–188"],"timestamp":["Fri, 18 Sep 2020 11:19:18 +0200"],"title":["On the unification power of models"],"volume":["4"]},"creators":{"author":[{"lastName":"Bézivin","firstName":"Jean"}]},"sentenceCased":true},{"key":"bhandariSerendipitousRecommendationMobile2013","type":"inproceedings","fields":{"added-at":["2013-12-14T00:00:00.000+0100"],"author":["Bhandari, Upasna","Sugiyama, Kazunari","Datta, Anindya","Jindal, Rajni"],"biburl":["https://www.bibsonomy.org/bibtex/202e78647742172b1076224a8af342fea/dblp"],"booktitle":["AIRS"],"date":["2013"],"editor":["Banchs, Rafael E.","Silvestri, Fabrizio","Liu, Tie-Yan","Zhang, Min","Gao, Sheng","Lang, Jun"],"ee":["http://dx.doi.org/10.1007/978-3-642-45068-6₃8"],"interhash":["9b6654f3f311708df5e2faf14c15d05a"],"intrahash":["02e78647742172b1076224a8af342fea"],"isbn":["978-3-642-45067-9"],"keywords":["dblp"],"pages":["440–451"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["2015-04-28T17:38:09.000+0200"],"title":["Serendipitous recommendation for mobile apps using item-item similarity graph."],"url":["http://dblp.uni-trier.de/db/conf/airs/airs2013.html#BhandariSDJ13"],"volume":["8281"]},"creators":{"author":[{"lastName":"Bhandari","firstName":"Upasna"},{"lastName":"Sugiyama","firstName":"Kazunari"},{"lastName":"Datta","firstName":"Anindya"},{"lastName":"Jindal","firstName":"Rajni"}],"editor":[{"lastName":"Banchs","firstName":"Rafael E."},{"lastName":"Silvestri","firstName":"Fabrizio"},{"lastName":"Liu","firstName":"Tie-Yan"},{"lastName":"Zhang","firstName":"Min"},{"lastName":"Gao","firstName":"Sheng"},{"lastName":"Lang","firstName":"Jun"}]},"sentenceCased":true},{"key":"Bhattacharjee20191607","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - IEEE Int. Conf. Big Data, Big Data"],"affiliation":["Vanderbilt University, EECS Dept, Nashville, TN, United States; Lockheed Martin Advanced Technology Labs, Cherry Hill, NJ, United States"],"art_number":["9006518"],"author":["Bhattacharjee, A.","Barve, Y.","Khare, S.","Bao, S.","Kang, Z.","Gokhale, A.","Damiano, T."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/BigData47090.2019.9006518"],"editor":["Baru C., Huan J., Hu X.T., Ak R., Tian Y., Barga R., Zaniolo C., Lee K., Ye Y.F., Khan L."],"isbn":["978-1-72810-858-2"],"note":["cited By 6 \n\nTL;DR \n\nThis paper presents Stratum, which is an event-driven Big Data-as-a-Service offering for IoT analytics lifecycle management, which provides users with an intuitive, declarative mechanism based on the principles of model-driven engineering to specify the application and infrastructure requirements."],"pages":["1607–1612"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019"],"source":["Scopus"],"title":["STRATUM: A BigData-as-a-Service for lifecycle management of IoT analytics applications"]},"creators":{"author":[{"lastName":"Bhattacharjee","firstName":"A."},{"lastName":"Barve","firstName":"Y."},{"lastName":"Khare","firstName":"S."},{"lastName":"Bao","firstName":"S."},{"lastName":"Kang","firstName":"Z."},{"lastName":"Gokhale","firstName":"A."},{"lastName":"Damiano","firstName":"T."}],"editor":[{"lastName":"Baru C.","suffix":"Huan J.","firstName":"Hu X.T., Ak R., Tian Y., Barga R., Zaniolo C., Lee K., Ye Y.F., Khan L."}]},"sentenceCased":true},{"key":"BiasInRSSErepo","type":"software","fields":{"author":["Anonymous"],"date":["2023-01"],"organization":["Zenodo"],"title":["Artifacts: Popularity bias in RSSE"],"url":["https://github.com/MSR23-BiasInRSSE/BiasInRSSE"]},"creators":{"author":[{"literal":"Anonymous"}]},"sentenceCased":true},{"key":"BickfordBBP20","type":"article","fields":{"langid":["english"],"author":["Bickford, Jason","Bossuyt, Douglas L. Van","Beery, Paul T.","Pollman, Anthony G."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2020"],"doi":["10.1002/SYS.21559"],"journaltitle":["Syst. Eng."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nHow objectives in DT development align with those of model-based systems engineering (MBSE), and how the MBSE process can answer questions necessary to define the digital twin (DT) is explored."],"number":["6"],"pages":["724–750"],"timestamp":["Wed, 13 Jul 2022 12:40:35 +0200"],"title":["Operationalizing digital twins through model-based systems engineering methods"],"volume":["23"]},"creators":{"author":[{"lastName":"Bickford","firstName":"Jason"},{"lastName":"Bossuyt","firstName":"Douglas L. Van"},{"lastName":"Beery","firstName":"Paul T."},{"lastName":"Pollman","firstName":"Anthony G."}]},"sentenceCased":true},{"key":"bielik_adversarial_2020","type":"inproceedings","fields":{"langid":["english"],"abstract":["Machine learning and deep learning in particular has been recently used to successfully address many tasks in the domain of code such as finding and fixing bugs, code completion, decompilation, typ..."],"author":["Bielik, Pavol","Vechev, Martin"],"booktitle":["Int. Conf. Mach. Learn."],"date":["2020-11"],"ids":["pmlr-v119-bielik20a"],"note":["ISSN: 2640-3498 \n\nTL;DR \n\nThis work instantiating adversarial attacks for code, and showing that, similar to other domains, neural models for code are vulnerable to adversarial attack, and combining existing and novel techniques to improve robustness while preserving high accuracy are explored."],"pages":["896–907"],"publisher":["PMLR"],"title":["Adversarial Robustness for Code"],"url":["http://proceedings.mlr.press/v119/bielik20a.html"],"urldate":["2021-04-15"]},"creators":{"author":[{"lastName":"Bielik","firstName":"Pavol"},{"lastName":"Vechev","firstName":"Martin"}]}},{"key":"BiermannEKKTW06","type":"article","fields":{"langid":["english"],"author":["Biermann, Enrico","Ehrig, Karsten","Köhler, Christian","Kuhns, Günter","Taentzer, Gabriele","Weiss, Eduard"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2006"],"doi":["10.14279/TUJ.ECEASST.3.34"],"journaltitle":["Electron. Commun. Eur. Assoc. Softw. Sci. Technol."],"keywords":["/unread","⛔ No INSPIRE recid found"],"timestamp":["Tue, 25 Aug 2020 16:49:29 +0200"],"title":["EMF model refactoring based on graph transformation concepts"],"volume":["3"]},"creators":{"author":[{"lastName":"Biermann","firstName":"Enrico"},{"lastName":"Ehrig","firstName":"Karsten"},{"lastName":"Köhler","firstName":"Christian"},{"lastName":"Kuhns","firstName":"Günter"},{"lastName":"Taentzer","firstName":"Gabriele"},{"lastName":"Weiss","firstName":"Eduard"}]},"sentenceCased":true},{"key":"BiermannEKKTW06","type":"inproceedings","fields":{"langid":["english"],"author":["Biermann, Enrico","Ehrig, Karsten","Köhler, Christian","Kuhns, Günter","Taentzer, Gabriele","Weiss, Eduard"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Model Driven Eng. Lang. Syst. 9th Int. Conf. MoDELS 2006 Genova Italy Oct. 1-6 2006 Proc."],"date":["2006"],"doi":["10.1007/11880240\\_30"],"editor":["Nierstrasz, Oscar","Whittle, Jon","Harel, David","Reggio, Gianna"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nA framework for in-place EMF model transformation based on graph transformation is presented, which can be compiled to Java code building up on generated EMF classes."],"pages":["425–439"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Tue, 24 May 2022 15:28:49 +0200"],"title":["Graphical definition of in-place transformations in the eclipse modeling framework"],"volume":["4199"]},"creators":{"author":[{"lastName":"Biermann","firstName":"Enrico"},{"lastName":"Ehrig","firstName":"Karsten"},{"lastName":"Köhler","firstName":"Christian"},{"lastName":"Kuhns","firstName":"Günter"},{"lastName":"Taentzer","firstName":"Gabriele"},{"lastName":"Weiss","firstName":"Eduard"}],"editor":[{"lastName":"Nierstrasz","firstName":"Oscar"},{"lastName":"Whittle","firstName":"Jon"},{"lastName":"Harel","firstName":"David"},{"lastName":"Reggio","firstName":"Gianna"}]},"sentenceCased":true},{"key":"BigDAWGPolystoreSystem","type":"online","fields":{"title":["The BigDAWG polystore system and architecture — Northwestern Scholars"],"url":["https://www.scholars.northwestern.edu/en/publications/the-bigdawg-polystore-system-and-architecture"],"urldate":["2018-04-16"]},"creators":{},"sentenceCased":true},{"key":"BIGGIO2018317","type":"article","fields":{"abstract":["Learning-based pattern classifiers, including deep networks, have shown impressive performance in several application domains, ranging from computer vision to cybersecurity. However, it has also been shown that adversarial input perturbations carefully crafted either at training or at test time can easily subvert their predictions. The vulnerability of machine learning to such wild patterns (also referred to as adversarial examples), along with the design of suitable countermeasures, have been investigated in the research field of adversarial machine learning. In this work, we provide a thorough overview of the evolution of this research area over the last ten years and beyond, starting from pioneering, earlier work on the security of non-deep learning algorithms up to more recent work aimed to understand the security properties of deep learning algorithms, in the context of computer vision and cybersecurity tasks. We report interesting connections between these apparently-different lines of work, highlighting common misconceptions related to the security evaluation of machine-learning algorithms. We review the main threat models and attacks defined to this end, and discuss the main limitations of current work, along with the corresponding future challenges towards the design of more secure learning algorithms."],"author":["Biggio, Battista","Roli, Fabio"],"date":["2018"],"doi":["10.1016/j.patcog.2018.07.023"],"issn":["0031-3203"],"journaltitle":["Pattern Recognit."],"keywords":["Adversarial examples","Adversarial machine learning","Deep learning","Evasion attacks","Poisoning attacks","Secure learning"],"pages":["317–331"],"title":["Wild patterns: Ten years after the rise of adversarial machine learning"],"volume":["84"]},"creators":{"author":[{"lastName":"Biggio","firstName":"Battista"},{"lastName":"Roli","firstName":"Fabio"}]},"sentenceCased":true},{"key":"BillFTMW19","type":"article","fields":{"langid":["english"],"author":["Bill, Robert","Fleck, Martin","Troya, Javier","Mayerhofer, Tanja","Wimmer, Manuel"],"date":["2019"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["2"],"pages":["1017–1046"],"title":["A local and global tour on MOMoT"],"volume":["18"]},"creators":{"author":[{"lastName":"Bill","firstName":"Robert"},{"lastName":"Fleck","firstName":"Martin"},{"lastName":"Troya","firstName":"Javier"},{"lastName":"Mayerhofer","firstName":"Tanja"},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"BinTang2007","type":"inproceedings","fields":{"author":["Tang, B.","Spiteri, R.","Milios, E.","Zhang, R.","Wang, S.","Tougas, J.","Shafiei, M."],"booktitle":["2013 IEEE 29th Int Conf Data Eng. Workshop ICDEW"],"date":["2007-04"],"location":["Los Alamitos, CA, USA"],"nodoi":["10.1109/ICDEW.2007.4401066"],"note":["TL;DR \n\nA systematic study in which three different document representation methods for text are used, together with three Dimension Reduction Techniques (DRT), in the context of the text clustering problem, and it is demonstrated that a profile length of 2000 is sufficient to capture the information."],"pages":["770–779"],"publisher":["IEEE Computer Society"],"title":["Document representation and dimension reduction for text clustering"]},"creators":{"author":[{"lastName":"Tang","firstName":"B."},{"lastName":"Spiteri","firstName":"R."},{"lastName":"Milios","firstName":"E."},{"lastName":"Zhang","firstName":"R."},{"lastName":"Wang","firstName":"S."},{"lastName":"Tougas","firstName":"J."},{"lastName":"Shafiei","firstName":"M."}]},"sentenceCased":true},{"key":"Bishop:1995:NNP:525960","type":"book","fields":{"author":["Bishop, Christopher M."],"date":["1995"],"isbn":["0-19-853864-2"],"location":["New York, NY, USA"],"publisher":["Oxford University Press, Inc."],"title":["Neural networks for pattern recognition"]},"creators":{"author":[{"lastName":"Bishop","firstName":"Christopher M."}]},"sentenceCased":true},{"key":"bizer_linked_2009","type":"article","fields":{"added-at":["2011-11-02T15:40:20.000+0100"],"author":["Bizer, C.","Heath, T.","Berners-Lee, T."],"biburl":["https://www.bibsonomy.org/bibtex/25e13b99f0fe4d28c1261158410041c70/mgraube"],"date":["2009"],"interhash":["599c4dfb0c1625c0c4368a1ab8346646"],"intrahash":["5e13b99f0fe4d28c1261158410041c70"],"journaltitle":["Int. J. Semantic Web Inf. Syst."],"number":["3"],"pages":["1–22"],"timestamp":["2011-11-02T15:40:20.000+0100"],"title":["Linked data - the story so far"],"volume":["5"]},"creators":{"author":[{"lastName":"Bizer","firstName":"C."},{"lastName":"Heath","firstName":"T."},{"lastName":"Berners-Lee","firstName":"T."}]},"sentenceCased":true},{"key":"bjarnasonAligningRequirementsTesting2017","type":"article","fields":{"abstract":["The proper alignment of requirements engineering and testing (RET) can be key to software's success. Three practices can provide effective RET alignment: using test cases as requirements, harvesting trace links, and reducing distances between requirements engineers and testers. The Web extra https://youtu.be/M65ZKxfxqME is an audio podcast of author Elizabeth Bjarnason reading the the Requirements column she cowrote with Markus Borg."],"author":["Bjarnason, Elizabeth","Borg, Markus","undefined","undefined","undefined","undefined"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["software engineering"],"number":["1"],"pages":["20–23"],"shorttitle":["Aligning Requirements and Testing"],"title":["Aligning Requirements and Testing: Working Together toward the Same Goal"],"volume":["34"]},"creators":{"author":[{"lastName":"Bjarnason","firstName":"Elizabeth"},{"lastName":"Borg","firstName":"Markus"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"bjarnasonChallengesPracticesAligning2014","type":"article","fields":{"langid":["english"],"author":["Bjarnason, Elizabeth","Runeson, Per","Borg, Markus","Unterkalmsteiner, Michael","Engström, Emelie","Regnell, Björn","Sabaliauskaite, Giedre","Loconsole, Annabella","Gorschek, Tony","Feldt, Robert"],"date":["2014-12"],"doi":["10.1007/s10664-013-9263-y"],"issn":["1382-3256, 1573-7616"],"journaltitle":["Empir Software Eng"],"note":["TL;DR \n\nA multi-unit case study is performed to gain insight into issues around aligning RE and VV by interviewing 30 practitioners from 6 software developing companies, involving 10 researchers in a flexible research process for case studies and provides a strategic roadmap for practitioners improvement work to address alignment challenges."],"number":["6"],"pages":["1809–1855"],"shorttitle":["Challenges and practices in aligning requirements with verification and validation"],"title":["Challenges and practices in aligning requirements with verification and validation: A case study of six companies"],"volume":["19"]},"creators":{"author":[{"lastName":"Bjarnason","firstName":"Elizabeth"},{"lastName":"Runeson","firstName":"Per"},{"lastName":"Borg","firstName":"Markus"},{"lastName":"Unterkalmsteiner","firstName":"Michael"},{"lastName":"Engström","firstName":"Emelie"},{"lastName":"Regnell","firstName":"Björn"},{"lastName":"Sabaliauskaite","firstName":"Giedre"},{"lastName":"Loconsole","firstName":"Annabella"},{"lastName":"Gorschek","firstName":"Tony"},{"lastName":"Feldt","firstName":"Robert"}]},"sentenceCased":true},{"key":"Blondel:2004:MSG:1035533.1035557","type":"article","fields":{"acmid":["1035557"],"address":["Philadelphia, PA, USA"],"author":["Blondel, Vincent D.","Gajardo, Anahí","Heymans, Maureen","Senellart, Pierre","Dooren, Paul Van"],"date":["2004-04"],"issn":["0036-1445"],"issue_date":["2004"],"journaltitle":["SIAM Rev."],"keywords":["algorithms","eigenvalues of graphs","graph algorithms","graph theory"],"nodoi":["10.1137/S0036144502415960"],"number":["4"],"numpages":["20"],"pages":["647–666"],"publisher":["Society for Industrial and Applied Mathematics"],"title":["A measure of similarity between graph vertices: Applications to synonym extraction and web searching"],"url":["http://dx.doi.org/10.1137/S0036144502415960"],"volume":["46"]},"creators":{"author":[{"lastName":"Blondel","firstName":"Vincent D."},{"lastName":"Gajardo","firstName":"Anahí"},{"lastName":"Heymans","firstName":"Maureen"},{"lastName":"Senellart","firstName":"Pierre"},{"lastName":"Dooren","firstName":"Paul Van"}]},"sentenceCased":true},{"key":"blouinFirstInternationalWorkshop","type":"article","fields":{"langid":["english"],"abstract":["Model-Based Systems Engineering (MBSE) is a popular way to specify, design, implement, deploy and maintain complex systems with high quality and lower costs. These systems combine multiple areas of engineering, including mechanical, electrical, hydraulic, biochemical, control, signal processing, and more. To represent all these aspects, a large number of heterogeneous models are required. However, managing these models correctly can be challenging, especially when different teams work on them simultaneously, which is common in collaborative and concurrent engineering. This activity is called Model Management (MoM) and includes activities beyond maintaining model consistency, such as managing model views, model validity, model versions, and development workflows."],"author":["Blouin, Dominique","Guerin, Sylvain","Amaral, Vasco","Bhobe, Anish","Almeida, Joao"],"title":["First International Workshop on Model Management (MoM)"]},"creators":{"author":[{"lastName":"Blouin","firstName":"Dominique"},{"lastName":"Guerin","firstName":"Sylvain"},{"lastName":"Amaral","firstName":"Vasco"},{"lastName":"Bhobe","firstName":"Anish"},{"lastName":"Almeida","firstName":"Joao"}]}},{"key":"blouinKomprenModelingGenerating2012","type":"article","fields":{"author":["Blouin, Arnaud","Combemale, Benoît","Baudry, Benoit","Beaudoux, Olivier"],"date":["2012"],"doi":["10.1007/s10270-012-0300-x"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nThis paper proposes the Kompren language to model and generate model slicers for any DSL (e.g. modeling for software development or for civil engineering) and for different purposes and provides a set of expected properties about the slices that are extracted by the different forms of the slicer."],"title":["Kompren: Modeling and generating model slicers"]},"creators":{"author":[{"lastName":"Blouin","firstName":"Arnaud"},{"lastName":"Combemale","firstName":"Benoît"},{"lastName":"Baudry","firstName":"Benoit"},{"lastName":"Beaudoux","firstName":"Olivier"}]},"sentenceCased":true},{"key":"blouinSlicingbasedTechniquesVisualizing","type":"article","fields":{"abstract":["In model-driven engineering, a model describes an aspect of a system. A model conforms to a metamodel that defines the concepts and relationships of a given domain. Metamodels are thus corner-stones of various meta-modeling activities that require a good understanding of the metamodels or parts of them. Current metamodel editing tools are based on standard visualization and navigation features, such as physical zooms. However, as soon as metamodels become larger, navigating through large metamodels becomes a tedious task that hinders their understanding. In this work, we promote the use of model slicing techniques to build visualization techniques dedicated to metamodels. We propose an approach based on model slicing, inspired from program slicing, to build interactive visualization techniques dedicated to metamodels. These techniques permit users to focus on metamodel elements of interest, which aims at improving the understandability. This approach is implemented in a metamodel visualizer, called Explen."],"author":["Blouin, Arnaud","Moha, Naouel","Baudry, Benoit","Saharaoui, Houaru"],"note":["TL;DR \n\nThis work proposes an approach based on model slicing, inspired from program slicing, to build interactive visualization techniques dedicated to metamodels, which permits users to focus on meetamodel elements of interest, which aims at improving the understand ability."],"title":["Slicing-based Techniques for Visualizing Large Metamodels"]},"creators":{"author":[{"lastName":"Blouin","firstName":"Arnaud"},{"lastName":"Moha","firstName":"Naouel"},{"lastName":"Baudry","firstName":"Benoit"},{"lastName":"Saharaoui","firstName":"Houaru"}]},"sentenceCased":true},{"key":"Blum:1992:NNC:129269","type":"book","fields":{"author":["Blum, Adam"],"date":["1992"],"isbn":["0-471-53847-7"],"location":["New York, NY, USA"],"note":["TL;DR \n\nBesides providing a wealth of examples in C++, full coverage of three major application areas of neural network programming is included along with a complete C++ class library especially designed for neural network usage."],"publisher":["John Wiley & Sons, Inc."],"title":["Neural networks in C++: An object-oriented framework for building connectionist systems"]},"creators":{"author":[{"lastName":"Blum","firstName":"Adam"}]},"sentenceCased":true},{"key":"boardmanSystemSystemstheMeaning2006","type":"inproceedings","fields":{"author":["Boardman, John","Sauser, Brian"],"booktitle":["2006 IEEESMC Int. Conf. Syst. Syst. Eng."],"date":["2006"],"note":["TL;DR \n\nThe difference in these terms in a fundamental sense is one that impacts their structure, behavior and realization, and the distinction comes from the manner in which parts and relationships are gathered together and therefore in the nature of the emergent whole."],"pages":["6–pp"],"publisher":["IEEE"],"title":["System of Systems-the meaning of of"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1652284"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Boardman","firstName":"John"},{"lastName":"Sauser","firstName":"Brian"}]},"sentenceCased":true},{"key":"bobadillaRecommenderSystemsSurvey2013a","type":"article","fields":{"author":["Bobadilla, J.","Ortega, F.","Hernando, A.","Gutiérrez, A."],"date":["2013-07"],"doi":["10.1016/j.knosys.2013.03.012"],"issn":["09507051"],"journaltitle":["Knowl.-Based Syst."],"pages":["109–132"],"title":["Recommender systems survey"],"volume":["46"]},"creators":{"author":[{"lastName":"Bobadilla","firstName":"J."},{"lastName":"Ortega","firstName":"F."},{"lastName":"Hernando","firstName":"A."},{"lastName":"Gutiérrez","firstName":"A."}]},"sentenceCased":true},{"key":"bockLowCodePlatform2021","type":"article","fields":{"langid":["english"],"author":["Bock, Alexander C.","Frank, Ulrich"],"date":["2021-12"],"doi":["10.1007/s12599-021-00726-8"],"issn":["2363-7005, 1867-0202"],"journaltitle":["Bus Inf Syst Eng"],"keywords":["LOGSEQ"],"note":["TL;DR \n\nUnder the heading of ‘low-code’, a new class of software development environments has emerged in recent years which is not only said to afford the prospect of a substantial increase in software development productivity, but also to yield new ways of promoting business IT alignment and user empowerment."],"number":["6"],"pages":["733–740"],"title":["Low-Code Platform"],"volume":["63"]},"creators":{"author":[{"lastName":"Bock","firstName":"Alexander C."},{"lastName":"Frank","firstName":"Ulrich"}]}},{"key":"bockSearchEssenceLowCode2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["Rapidly growing attention has been directed in recent years toward a type of software development and execution environment now passing under the name of ‘low-code development platforms.’ The fundamental claim is that limiting traditional coding mechanisms in favor of a variety of alternative means of design and specification yields substantial efficiency gains in professional and private software development. But although much stir at present surrounds low-code development platforms, it is by no means clear what, if any, features are distinctive of these systems, and whether any of these features mark out a technology which can be considered original. This paper presents an exploratory study of seven low-code development platforms, with the aim of discovering their essence and assessing them critically in the light of research in information systems development. An analysis framework covering a number of criteria regarding professional information systems development is used to characterize the selected platforms, and to point out features commonly, occasionally, and rarely possessed by them. The study reveals that hardly any features of low-code development are innovative in and of themselves, with novelty primarily consisting in their combination and integration. Still, we argue in conclusion, a number of research opportunities can be made out with an eye on the leitmotif of low-code development."],"author":["Bock, Alexander C.","Frank, Ulrich"],"booktitle":["2021 ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion MODELS-C"],"date":["2021-10"],"doi":["10.1109/MODELS-C53483.2021.00016"],"eventtitle":["2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)"],"isbn":["978-1-66542-484-4"],"keywords":["LOGSEQ"],"location":["Fukuoka, Japan"],"note":["TL;DR \n\nAn exploratory study of seven low-code development platforms is presented, with the aim of discovering their essence and assessing them critically in the light of research in information systems development, revealing that hardly any features of low- code development are innovative in and of themselves."],"pages":["57–66"],"publisher":["IEEE"],"shorttitle":["In Search of the Essence of Low-Code"],"title":["In Search of the Essence of Low-Code: An Exploratory Study of Seven Development Platforms"]},"creators":{"author":[{"lastName":"Bock","firstName":"Alexander C."},{"lastName":"Frank","firstName":"Ulrich"}]}},{"key":"Bogoclu20163344","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["ECCOMAS Congress - Proc. Euro. Congr. Comput. Methods Appl. Sci. Eng."],"affiliation":["Institute of Modeling and High-Performance Computing, Niederrhein University of Applied Sciences, Germany"],"author":["Bogoclu, C.","Roos, D."],"date":["2016"],"document_type":["Conference Paper"],"doi":["10.7712/100016.2039.7645"],"editor":["Stefanou G., Papadrakakis M., Plevris V., Papadopoulos V."],"isbn":["978-618-82844-0-1"],"keywords":["notion"],"note":["cited By 4"],"pages":["3344–3360"],"publisher":["National Technical University of Athens"],"series":["ECCOMAS Congress 2016 - Proceedings of the 7th European Congress on Computational Methods in Applied Sciences and Engineering"],"source":["Scopus"],"title":["A benchmark of contemporary metamodeling algorithms"],"volume":["2"]},"creators":{"author":[{"lastName":"Bogoclu","firstName":"C."},{"lastName":"Roos","firstName":"D."}],"editor":[{"lastName":"Stefanou G.","suffix":"Papadrakakis M.","firstName":"Plevris V., Papadopoulos V."}]},"sentenceCased":true},{"key":"bononiIoTSensorData","type":"article","fields":{"langid":["english"],"author":["Bononi, L","Felice, M Di"],"keywords":["data processing","DONE","GOOD_SOURCE","internet of things","slides"],"pages":["28"],"title":["IoT Sensor Data Management"]},"creators":{"author":[{"lastName":"Bononi","firstName":"L"},{"lastName":"Felice","firstName":"M Di"}]}},{"key":"bononiIoTSensorDataa","type":"article","fields":{"langid":["english"],"author":["Bononi, L","Felice, M Di"],"keywords":["data processing","DONE","internet of things","slides"],"pages":["43"],"title":["IoT Sensor Data Processing"]},"creators":{"author":[{"lastName":"Bononi","firstName":"L"},{"lastName":"Felice","firstName":"M Di"}]}},{"key":"boochHistorySoftwareEngineering2018","type":"article","fields":{"abstract":["Grady Booch, one of UML’s original authors, offers his perspective on the history of software engineering. This article is part of a theme issue on software engineering’s 50th anniversary. The Web Extra, a version of the article with an expanded bibliography, is at https://extras.computer.org/extra/mso2018050108s1.pdf."],"author":["Booch, G."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571234"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"number":["5"],"pages":["108–114"],"title":["The History of Software Engineering"],"volume":["35"]},"creators":{"author":[{"lastName":"Booch","firstName":"G."}]}},{"key":"books/sp/mining2012/AggarwalZ12a","type":"incollection","fields":{"added-at":["2012-02-18T00:00:00.000+0100"],"author":["Aggarwal, Charu C.","Zhai, ChengXiang"],"biburl":["http://www.bibsonomy.org/bibtex/28cfea77bb8aecd46ab2ba9db26c4338b/dblp"],"booktitle":["Mining text data"],"date":["2012"],"editor":["Aggarwal, Charu C.","Zhai, ChengXiang"],"ee":["http://dx.doi.org/10.1007/978-1-4614-3223-4₄"],"interhash":["a8614bc450f82d917149afd58fabf02a"],"intrahash":["8cfea77bb8aecd46ab2ba9db26c4338b"],"isbn":["978-1-4419-8462-3"],"keywords":["dblp"],"pages":["77–128"],"publisher":["Springer"],"timestamp":["2012-02-21T11:35:00.000+0100"],"title":["A survey of text clustering algorithms."],"url":["http://dblp.uni-trier.de/db/books/collections/Mining2012.html#AggarwalZ12a"]},"creators":{"author":[{"lastName":"Aggarwal","firstName":"Charu C."},{"lastName":"Zhai","firstName":"ChengXiang"}],"editor":[{"lastName":"Aggarwal","firstName":"Charu C."},{"lastName":"Zhai","firstName":"ChengXiang"}]},"sentenceCased":true},{"key":"Borg:2014:RSD:2652524.2652556","type":"inproceedings","fields":{"acmid":["2652556"],"articleno":["8"],"author":["Borg, Markus","Runeson, Per","Johansson, Jens","Mäntylä, Mika V."],"booktitle":["Proc. 8th ACMIEEE Int. Symp. Empir. Softw. Eng. Meas."],"date":["2014"],"isbn":["978-1-4503-2774-9"],"keywords":["information retrieval","issue management","replication","software evolution"],"location":["New York, NY, USA"],"nodoi":["10.1145/2652524.2652556"],"numpages":["4"],"pages":["8:1-8:4"],"publisher":["ACM"],"series":["ESEM '14"],"title":["A replicated study on duplicate detection: Using apache lucene to search among android defects"],"url":["http://doi.acm.org/10.1145/2652524.2652556"]},"creators":{"author":[{"lastName":"Borg","firstName":"Markus"},{"lastName":"Runeson","firstName":"Per"},{"lastName":"Johansson","firstName":"Jens"},{"lastName":"Mäntylä","firstName":"Mika V."}]},"sentenceCased":true},{"key":"borgPipelineInfrastructureRequired2023","type":"article","fields":{"langid":["english"],"author":["Borg, Markus"],"date":["2023-01"],"doi":["10.1109/MS.2022.3211687"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"number":["1"],"pages":["18–22"],"title":["Pipeline Infrastructure Required to Meet the Requirements on AI"],"volume":["40"]},"creators":{"author":[{"lastName":"Borg","firstName":"Markus"}]}},{"key":"borgSupportingChangeImpact2016","type":"article","fields":{"author":["Borg, Markus","Wnuk, Krzysztof","Regnell, Bjorn","Runeson, Per"],"date":["2016"],"doi":["10.1109/TSE.2016.2620458"],"issn":["0098-5589, 1939-3520"],"journaltitle":["IEEE Trans. Softw. Eng."],"note":["TL;DR \n\nA case study on ImpRec, a recommendation System for Software Engineering (RSSE), tailored for CIA at a process automation company, shows the potential of reusing traceability associated with developers’ past activities in an RSSE."],"pages":["1–1"],"shorttitle":["Supporting Change Impact Analysis Using a Recommendation System"],"title":["Supporting Change Impact Analysis Using a Recommendation System: An Industrial Case Study in a Safety-Critical Context"]},"creators":{"author":[{"lastName":"Borg","firstName":"Markus"},{"lastName":"Wnuk","firstName":"Krzysztof"},{"lastName":"Regnell","firstName":"Bjorn"},{"lastName":"Runeson","firstName":"Per"}]}},{"key":"Borji201941","type":"article","fields":{"abstract":["Generative models, in particular generative adversarial networks (GANs), have gained significant attention in recent years. A number of GAN variants have been proposed and have been utilized in many applications. Despite large strides in terms of theoretical progress, evaluating and comparing GANs remains a daunting task. While several measures have been introduced, as of yet, there is no consensus as to which measure best captures strengths and limitations of models and should be used for fair model comparison. As in other areas of computer vision and machine learning, it is critical to settle on one or few good measures to steer the progress in this field. In this paper, I review and critically discuss more than 24 quantitative and 5 qualitative measures for evaluating generative models with a particular emphasis on GAN-derived models. I also provide a set of 7 desiderata followed by an evaluation of whether a given measure or a family of measures is compatible with them. © 2018 Elsevier Inc."],"author":["Borji, A."],"author_keywords":["Deep learning; Evaluation; Generative adversarial nets; Generative models; Neural networks"],"coden":["CVIUF"],"date":["2019"],"document_type":["Article"],"doi":["10.1016/j.cviu.2018.10.009"],"issn":["10773142"],"journaltitle":["Comput. Vis. Image Underst."],"keywords":["Adversarial networks","Deep learning","Evaluation","Evaluation measures","Generative adversarial nets","Generative model","Image understanding","Model comparison","Neural networks","Software engineering"],"note":["cited By 340"],"pages":["41–65"],"publisher":["Academic Press Inc."],"source":["Scopus"],"title":["Pros and cons of GAN evaluation measures"],"volume":["179"]},"creators":{"author":[{"lastName":"Borji","firstName":"A."}]},"sentenceCased":true},{"key":"borjiBattleWordsmithsComparing2023","type":"article","fields":{"langid":["english"],"abstract":["Although informal evaluations of modern LLMs can be found on social media, blogs, and news outlets, a formal and comprehensive comparison among them has yet to be conducted. In response to this gap, we have undertaken an extensive benchmark evaluation of LLMs and conversational bots. Our evaluation involved the collection of 1002 questions encompassing 27 categories, which we refer to as the “Wordsmiths dataset.” These categories include reasoning, logic, facts, coding, bias, language, humor, and more. Each question in the dataset is accompanied by an accurate and verified answer. We meticulously assessed four leading chatbots: ChatGPT, GPT-4, Bard, and Claude, using this dataset. The results of our evaluation revealed the following key findings: a) GPT-4 emerged as the top-performing chatbot across almost all categories, achieving a success rate of 84.1%. On the other hand, Bard faced challenges and achieved a success rate of 62.4%. b) Among the four models evaluated, one of them responded correctly approximately 93% of the time. However, all models were correct only about 44%. c) Bard is less correlated with other models while ChatGPT and GPT-4 are highly correlated in terms of their responses. d) Chatbots demonstrated proficiency in language understanding, facts, and self-awareness. However, they encountered difficulties in areas such as math, coding, IQ, and reasoning. e) In terms of bias, discrimination, and ethics categories, models generally performed well, suggesting they are relatively safe to utilize. To make future model evaluations on our dataset easier, we also provide a multiple-choice version of it (called Wordsmiths-MCQ). Dataset link: [MASKED]."],"author":["Borji, Ali","Mohammadian, Mehrdad"],"date":["2023"],"doi":["10.2139/ssrn.4476855"],"issn":["1556-5068"],"journaltitle":["SSRN Journal"],"keywords":["LOGSEQ"],"shorttitle":["Battle of the Wordsmiths"],"title":["Battle of the Wordsmiths: Comparing ChatGPT, GPT-4, Claude, and Bard"]},"creators":{"author":[{"lastName":"Borji","firstName":"Ali"},{"lastName":"Mohammadian","firstName":"Mehrdad"}]}},{"key":"bosu2015characteristics","type":"inproceedings","fields":{"abstract":["Over the past decade, both open source and commercial software projects have adopted contemporary peer code review practices as a quality control mechanism. Prior research has shown that developers spend a large amount of time and effort performing code reviews. Therefore, identifying factors that lead to useful code reviews can benefit projects by increasing code review effectiveness and quality. In a three-stage mixed research study, we qualitatively investigated what aspects of code reviews make them useful to developers, used our findings to build and verify a classification model that can distinguish between useful and not useful code review feedback, and finally we used this classifier to classify review comments enabling us to empirically investigate factors that lead to more effective code review feedback. In total, we analyzed 1.5 millions review comments from five Microsoft projects and uncovered many factors that affect the usefulness of review feedback. For example, we found that the proportion of useful comments made by a reviewer increases dramatically in the first year that he or she is at Microsoft but tends to plateau afterwards. In contrast, we found that the more files that are in a change, the lower the proportion of comments in the code review that will be of value to the author of the change. Based on our findings, we provide recommendations for practitioners to improve effectiveness of code reviews."],"author":["Bosu, Amiangshu","Greiler, Michaela","Bird, Christian"],"booktitle":["Proc. Int. Conf. Min. Softw. Repos."],"date":["2015-05"],"edition":["Proceedings of the International Conference on Mining Software Repositories"],"note":["TL;DR \n\nThe proportion of useful comments made by a reviewer increases dramatically in the first year that he or she is at Microsoft but tends to plateau afterwards, and it is found that the more files that are in a change, the lower the proportion of comments in the code review that will be of value to the author of the change."],"publisher":["IEEE - Institute of Electrical and Electronics Engineers"],"title":["Characteristics of useful code reviews: An empirical study at microsoft"],"url":["https://www.microsoft.com/en-us/research/publication/characteristics-of-useful-code-reviews-an-empirical-study-at-microsoft/"]},"creators":{"author":[{"lastName":"Bosu","firstName":"Amiangshu"},{"lastName":"Greiler","firstName":"Michaela"},{"lastName":"Bird","firstName":"Christian"}]},"sentenceCased":true},{"key":"Böttcher2021","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Adv Eng Software"],"affiliation":["Institute for Structural Analysis, Technische Universität Dresden, Dresden, 01062, Germany"],"art_number":["102974"],"author":["Böttcher, M.","Fuchs, A.","Leichsenring, F.","Graf, W.","Kaliske, M."],"coden":["AESOD"],"correspondence_address1":["Kaliske, M.; Institute for Structural Analysis, Germany; email: michael.kaliske@tu-dresden.de"],"date":["2021"],"document_type":["Article"],"doi":["10.1016/j.advengsoft.2021.102974"],"issn":["09659978"],"journaltitle":["Adv. Eng. Softw."],"note":["cited By 1"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["ELSA: An efficient, adaptive ensemble learning-based sampling approach"],"volume":["154"]},"creators":{"author":[{"lastName":"Böttcher","firstName":"M."},{"lastName":"Fuchs","firstName":"A."},{"lastName":"Leichsenring","firstName":"F."},{"lastName":"Graf","firstName":"W."},{"lastName":"Kaliske","firstName":"M."}]},"sentenceCased":true},{"key":"Bottou91stochasticgradient","type":"inproceedings","fields":{"author":["Bottou, Léon"],"booktitle":["Proc. Neuro-Nîmes EC2"],"date":["1991"],"note":["TL;DR \n\nThis chapter discusses connectionist learning algorithms, which consists of minimizing a cost of the form C(w) = E(J(z,w)dP(z) where dP is an unknown probability distribution that characterizes the problem to learn, and J, the loss function, defines the learning system itself."],"title":["Stochastic gradient learning in neural networks"]},"creators":{"author":[{"lastName":"Bottou","firstName":"Léon"}]},"sentenceCased":true},{"key":"Boubekeur202084","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - ACM/IEEE Int. Conf. Model Driven Eng. Lang. Syst., MODELS-C - Companion Proc."],"affiliation":["McGill University, Montreál, Canada; University of Waterloo, Waterloo, Canada"],"author":["Boubekeur, Y.","Mussbacher, G.","McIntosh, S."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3417990.3418741"],"isbn":["978-1-4503-8135-2"],"keywords":["GOAL_Automatic_Model_Assessment","notion","TECHNIQUE_DECISION-TREE","TECHNIQUE_K-NEAREST-NEIGHBORS","TECHNIQUE_LOGIC-REGRESSION","TECHNIQUE_NAIVE-BAYES","TECHNIQUE_RandomForests"],"note":["cited By 5 \n\n“Logistic regression (LR), Naïve Bayes (NB), Decision Tree (DT), Random Forest (RF), and k-Nearest Neighbors (KNN)” (Boubekeur et al., 2020, p. 5) \n\nTL;DR \n\nThis paper investigates how a tool that combines a simple heuristic with machine learning techniques can be used to help assess student submissions in model-driven engineering courses and results are comparable to human grading and a complex rule-based technique."],"pages":["84–93"],"publisher":["Association for Computing Machinery, Inc"],"series":["Proceedings - 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2020 - Companion Proceedings"],"source":["Scopus"],"title":["Automatic assessment of students' software models using a simple heuristic and machine learning"]},"creators":{"author":[{"lastName":"Boubekeur","firstName":"Y."},{"lastName":"Mussbacher","firstName":"G."},{"lastName":"McIntosh","firstName":"S."}]},"sentenceCased":true},{"key":"Boubekeur202094","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - ACM/IEEE Int. Conf. Model Driven Eng. Lang. Syst., MODELS-C - Companion Proc."],"affiliation":["McGill University, Montreál, Canada"],"author":["Boubekeur, Y.","Mussbacher, G."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3417990.3418742"],"isbn":["978-1-4503-8135-2"],"keywords":["GOAL_Model-Assistance","notion"],"note":["cited By 1 \n\nHIGH LEVEL. NO SPECIFIC TECHNIQUES ARE MENTIONED. \n\nTL;DR \n\nThe interactions between a student modeler and an interactive domain modeling assistant are explored with the aim of better understanding the required interaction and forming a corpus of learning material that supports the assistant interactions."],"pages":["94–103"],"publisher":["Association for Computing Machinery, Inc"],"series":["Proceedings - 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2020 - Companion Proceedings"],"source":["Scopus"],"title":["Towards a better understanding of interactions with a domain modeling assistant"]},"creators":{"author":[{"lastName":"Boubekeur","firstName":"Y."},{"lastName":"Mussbacher","firstName":"G."}]},"sentenceCased":true},{"key":"boudeffaIntegratingDeployingHeterogeneous2019","type":"inproceedings","fields":{"author":["Boudeffa, A.","Abherve, A.","Bagnato, A.","Di Ruscio, D.","Mateus, M.","Almeida, B."],"booktitle":["CEUR Workshop Proc."],"date":["2019"],"ids":["boudeffaIntegratingDeployingHeterogeneous2019a,boudeffaIntegratingDeployingHeterogeneous2019b,boudeffaIntegratingDeployingHeterogeneous2019c"],"keywords":["Deployment","Heterogeneous Legacy Components","Integration","Microservice","Open Source Software"],"note":["cited By 1 \n\ncited By 1 \n\nTL;DR \n\nThis paper presents a microservice architecture, which is implemented by relying on Docker to support the integration and deployment of the CROSSMINER components."],"pages":["67–72"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"title":["Integrating and deploying heterogeneous components by means of a microservices architecture in the CROSSMINER project"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069635650&partnerID=40&md5=f9b4225ecaf8d1f86eb0cb23b241178c"],"volume":["2405"]},"creators":{"author":[{"lastName":"Boudeffa","firstName":"A."},{"lastName":"Abherve","firstName":"A."},{"lastName":"Bagnato","firstName":"A."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Mateus","firstName":"M."},{"lastName":"Almeida","firstName":"B."}]},"sentenceCased":true},{"key":"bourqueGuideSoftwareEngineering2014","type":"book","fields":{"langid":["english"],"author":["Bourque, Pierre","Fairley, R. E","IEEE Computer Society"],"date":["2014"],"isbn":["978-0-7695-5166-1"],"note":["TL;DR \n\nData types Sorting and searching parallel and distributed algorithms 3.0 and 4.0 are presented, covering sorting, searching, and distributing in the context of distributed systems."],"title":["Guide to the software engineering body of knowledge"]},"creators":{"author":[{"lastName":"Bourque","firstName":"Pierre"},{"lastName":"Fairley","firstName":"R. E"},{"literal":"IEEE Computer Society"}]},"sentenceCased":true},{"key":"boussaid2017survey","type":"article","fields":{"langid":["english"],"author":["Boussaïd, Ilhem","Siarry, Patrick","Ahmed-Nacer, Mohamed"],"date":["2017"],"journaltitle":["Autom. Software Eng."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThe purpose of this paper is to survey the relatively recent research activity lying at the interface between these two fields, an area that has come to be known as search-based model-driven engineering."],"pages":["233–294"],"publisher":["Springer"],"title":["A survey on search-based model-driven engineering"],"volume":["24"]},"creators":{"author":[{"lastName":"Boussaïd","firstName":"Ilhem"},{"lastName":"Siarry","firstName":"Patrick"},{"lastName":"Ahmed-Nacer","firstName":"Mohamed"}]},"sentenceCased":true},{"key":"bousseGenerativeApproachDefine2015","type":"inproceedings","fields":{"author":["Bousse, Erwan","Mayerhofer, Tanja","Combemale, Benoit","Baudry, Benoit"],"booktitle":["11th Eur. Conf. Model. Found. Appl. ECMFA"],"date":["2015"],"keywords":["⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis work evaluates a generative approach that defines a rich and domain-specific trace metamodel enabling the construction of execution traces for models conforming to a given xDSML and shows a significant performance improvement and simplification of the semantic differencing rules as compared to the usage of a generic trace metAModel."],"title":["A Generative Approach to Define Rich Domain-Specific Trace Metamodels"],"url":["https://hal.inria.fr/hal-01154225/document"],"urldate":["2015-06-24"]},"creators":{"author":[{"lastName":"Bousse","firstName":"Erwan"},{"lastName":"Mayerhofer","firstName":"Tanja"},{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Baudry","firstName":"Benoit"}]}},{"key":"boutotIoTMoFRequirementsDrivenModelling","type":"article","fields":{"langid":["english"],"author":["Boutot, Paul","Mustafiz, Sadaf"],"keywords":["LOGSEQ"],"note":["<h1>Annotazioni\n (14/1/2024, 22:55:13)</h1> \n\n“he engineering of IoT systems brings about various challenges due to the inherent complexities associated with such adaptive systems.” (Boutot e Mustafiz, p. 1) This is a test to check how notes are managed by LogSeq"],"title":["IoTMoF: A Requirements-Driven Modelling Framework for Adaptive IoT Systems"]},"creators":{"author":[{"lastName":"Boutot","firstName":"Paul"},{"lastName":"Mustafiz","firstName":"Sadaf"}]}},{"key":"Bouzeraib2020","type":"inproceedings","fields":{"abstract":["The rapid development of information and communication technologies makes the Internet of Things (IoT) devices much more complex and heterogeneous. In this context, the massive end devices (IoTs) and the large volume of data raise security and privacy challenges. To tackle these issues, the joint use of the Bockchain (BC) and Machine Learning (ML) seems attractive to achieve decentralized, secure, intelligent and efficient management of networks. On the one hand, the BC can greatly facilitate the sharing of training data and ML models, the decentralization of intelligence, security, privacy and reliable ML decision-making. On the other hand, ML may have significant impacts on the development of BC in communications and networking systems, including energy and resource efficiency, scalability, security, privacy and smart contracting. An important aspect of security intends to detect unusual and potentially inappropriate activities according to traffic patterns. This paper focuses on the problem of imbalance data where the number of abnormal samples is significantly lower than that of the normal (secure) ones. In particular, this paper presents a new equilibrium model based on an exciting recent innovation in ML namely Generator Adverse Networks (GANs) to address the problem of class imbalance and data noise to Intrusion Detection System (IDS) performance. The proposed approach use is illustrated by a case study: a smart house system-based scenario. © 2020 IEEE."],"art_number":["9380110"],"author":["Bouzeraib, W.","Ghenai, A.","Zeghib, N."],"author_keywords":["Blockchain; Generative Adversarial Network (GAN); Internet of Things (IoT); Intrusion Detection System IDS; Machine Learning; Security"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/ICAASE51408.2020.9380110"],"isbn":["978-1-66542-231-4"],"keywords":["Blockchain","Communications and networkings","Data Sharing","Decision making","Efficient managements","Equilibrium modeling","Information and Communication Technologies","Internet of thing (IOT)","Internet of things","Intrusion detection","Intrusion Detection Systems","Network security","Privacy by design","Resource efficiencies","Security and privacy","Software engineering"],"note":["cited By 0"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["ICAASE 2020 - Proceedings, 4th International Conference on Advanced Aspects of Software Engineering"],"source":["Scopus"],"title":["A blockchain data balance using a generative adversarial network approach: Application to smart house IDS"]},"creators":{"author":[{"lastName":"Bouzeraib","firstName":"W."},{"lastName":"Ghenai","firstName":"A."},{"lastName":"Zeghib","firstName":"N."}]},"sentenceCased":true},{"key":"bozhinoskiFLYAQEnablingNonexpert2015","type":"inproceedings","fields":{"author":["Bozhinoski, Darko","DI RUSCIO, Davide","Malavolta, Ivano","Pelliccione, Patrizio","Tivoli, Massimo"],"booktitle":["Proc. - 2015 30th IEEEACM Int. Conf. Autom. Softw. Eng. ASE 2015"],"date":["2015"],"doi":["10.1109/ASE.2015.104"],"ids":["bozhinoskiFLYAQEnablingNonexpert2015a,bozhinoskiFLYAQEnablingNonexpert2015b,bozhinoskiFLYAQEnablingNonexpert2016,bozhinoskiFLYAQEnablingNonexpert2016a"],"isbn":["978-1-5090-0024-1"],"keywords":["Domain-specific Languages","Model-Driven Engineering","Multicopter","Software"],"note":["cited By 31 \n\ncited By 31"],"pages":["801–806"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["FLYAQ: Enabling non-expert users to specify and generate missions of autonomous multicopters"]},"creators":{"author":[{"lastName":"Bozhinoski","firstName":"Darko"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Pelliccione","firstName":"Patrizio"},{"lastName":"Tivoli","firstName":"Massimo"}]},"sentenceCased":true},{"key":"bozhinoskiSafetyMobileRobotic2019","type":"article","fields":{"langid":["english"],"author":["Bozhinoski, Darko","Di Ruscio, Davide","Malavolta, Ivano","Pelliccione, Patrizio","Crnkovic, Ivica"],"date":["2019-05"],"doi":["10.1016/j.jss.2019.02.021"],"ids":["bozhinoskiSafetyMobileRobotic2019a,bozhinoskiSafetyMobileRobotic2019b"],"issn":["01641212"],"journaltitle":["Journal of Systems and Software"],"note":["cited By 23"],"pages":["150–179"],"shorttitle":["Safety for mobile robotic systems"],"title":["Safety for mobile robotic systems: A systematic mapping study from a software engineering perspective"],"volume":["151"]},"creators":{"author":[{"lastName":"Bozhinoski","firstName":"Darko"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Pelliccione","firstName":"Patrizio"},{"lastName":"Crnkovic","firstName":"Ivica"}]},"sentenceCased":true},{"key":"brandLaunchNewJournal2023","type":"article","fields":{"langid":["english"],"author":["family=Brand, given=Mark, prefix=van den, useprefix=false","Dajsuren, Yanja","Saberi, Arash"],"date":["2023-01-23"],"doi":["10.55060/j.jseas.230123.001"],"issn":["2949-9372"],"journaltitle":["J. Softw. Eng. Auton. Syst."],"keywords":["LOGSEQ"],"publisher":["Athena Publishing"],"title":["Launch of New Journal JSEAS"]},"creators":{"author":[{"lastName":"Brand","firstName":"Mark","prefix":"vanden","useprefix":false},{"lastName":"Dajsuren","firstName":"Yanja"},{"lastName":"Saberi","firstName":"Arash"}]}},{"key":"breuTenPrinciplesLiving2010","type":"inproceedings","fields":{"langid":["english"],"abstract":["The new generation of open networked IT systems poses particular challenges to software engineering due to their evolving nature and their high quality requirements. In particular, the management of service oriented systems requires the integration of perspectives from IT management, software engineering and systems operation and a systematic way to handle changes. In this paper we will present the core ideas of Living Models – a novel paradigm of model–based development, management and operation of evolving service oriented systems. A core concern of Living Models is to support the cooperation of stakeholders from IT management, software engineering and systems operation by providing appropriate model-based abstractions and the fostering of interdependencies. Based on this idea the running services together with their modelling environments constitute the basic unit of quality management and evolution. Living Models provides a coherent view of the quality status of the system (integrating the perspectives of all stakeholders) which evolves together with the running systems. This comes along with a software engineering process in which change is a first–class citizen."],"author":["Breu, Ruth"],"booktitle":["2010 Int. Conf. Complex Intell. Softw. Intensive Syst."],"date":["2010-02"],"doi":["10.1109/CISIS.2010.73"],"eventtitle":["2010 International Conference on Complex, Intelligent and Software Intensive Systems (CISIS)"],"isbn":["978-1-4244-5917-9"],"location":["Krakow, TBD, Poland"],"note":["TL;DR \n\nThe core ideas of Living Models are presented - a novel paradigm of model-based development, management and operation of evolving service oriented systems and a coherent view of the quality status of the system which evolves together with the running systems."],"pages":["1–8"],"publisher":["IEEE"],"title":["Ten Principles for Living Models - A Manifesto of Change-Driven Software Engineering"]},"creators":{"author":[{"lastName":"Breu","firstName":"Ruth"}]}},{"key":"BRIGUEZ20146467","type":"article","fields":{"author":["Briguez, Cristian E.","Budán, Maximiliano C.D.","Deagustini, Cristhian A.D.","Maguitman, Ana G.","Capobianco, Marcela","Simari, Guillermo R."],"date":["2014"],"issn":["0957-4174"],"journaltitle":["Expert Syst. Appl."],"keywords":["Defeasible argumentation","Qualitative vs quantitative recommendations"],"nodoi":["https://doi.org/10.1016/j.eswa.2014.03.046"],"number":["14"],"pages":["6467–6482"],"title":["Argument-based mixed recommenders and their application to movie suggestion"],"url":["http://www.sciencedirect.com/science/article/pii/S0957417414001845"],"volume":["41"]},"creators":{"author":[{"lastName":"Briguez","firstName":"Cristian E."},{"lastName":"Budán","firstName":"Maximiliano C.D."},{"lastName":"Deagustini","firstName":"Cristhian A.D."},{"lastName":"Maguitman","firstName":"Ana G."},{"lastName":"Capobianco","firstName":"Marcela"},{"lastName":"Simari","firstName":"Guillermo R."}]},"sentenceCased":true},{"key":"brockman2016openai","type":"article","fields":{"author":["Brockman, Greg","Cheung, Vicki","Pettersson, Ludwig","Schneider, Jonas","Schulman, John","Tang, Jie","Zaremba, Wojciech"],"date":["2016"],"eprint":["1606.01540"],"eprinttype":["arxiv"],"journaltitle":["ArXiv Prepr. ArXiv160601540"],"title":["Openai gym"]},"creators":{"author":[{"lastName":"Brockman","firstName":"Greg"},{"lastName":"Cheung","firstName":"Vicki"},{"lastName":"Pettersson","firstName":"Ludwig"},{"lastName":"Schneider","firstName":"Jonas"},{"lastName":"Schulman","firstName":"John"},{"lastName":"Tang","firstName":"Jie"},{"lastName":"Zaremba","firstName":"Wojciech"}]},"sentenceCased":true},{"key":"broringEnablingIoTEcosystems2017","type":"article","fields":{"abstract":["Today, the Internet of Things (IoT) comprises vertically oriented platforms for things. Developers who want to use them need to negotiate access individually and adapt to the platform-specific API and information models. Having to perform these actions for each platform often outweighs the possible gains from adapting applications to multiple platforms. This fragmentation of the IoT and the missing interoperability result in high entry barriers for developers and prevent the emergence of broadly accepted IoT ecosystems. The BIG IoT (Bridging the Interoperability Gap of the IoT) project aims to ignite an IoT ecosystem as part of the European Platforms Initiative. As part of the project, researchers have devised an IoT ecosystem architecture. It employs five interoperability patterns that enable cross-platform interoperability and can help establish successful IoT ecosystems."],"author":["Broring, Arne","Schmid, Stefan","Schindhelm, Corina-Kim","Khelil, Abdelmajid","Kabisch, Sebastian","Kramer, Denis","Phuoc, Danh Le","Mitic, Jelena","Anicic, Darko","Teniente, Ernest"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["internet of things","software engineering"],"note":["TL;DR \n\nThe BIG IoT (Bridging the Interoperability Gap of the IoT) project aims to ignite an IoT ecosystem as part of the European Platforms Initiative and employs five interoperability patterns that enable cross-platform interoperability and can help establish successful IoT ecosystems."],"number":["1"],"pages":["54–61"],"title":["Enabling IoT Ecosystems through Platform Interoperability"],"volume":["34"]},"creators":{"author":[{"lastName":"Broring","firstName":"Arne"},{"lastName":"Schmid","firstName":"Stefan"},{"lastName":"Schindhelm","firstName":"Corina-Kim"},{"lastName":"Khelil","firstName":"Abdelmajid"},{"lastName":"Kabisch","firstName":"Sebastian"},{"lastName":"Kramer","firstName":"Denis"},{"lastName":"Phuoc","firstName":"Danh Le"},{"lastName":"Mitic","firstName":"Jelena"},{"lastName":"Anicic","firstName":"Darko"},{"lastName":"Teniente","firstName":"Ernest"}]}},{"key":"broyYesterdayTodayTomorrow2018","type":"article","fields":{"abstract":["In 2018, we’re now 50 years after the famous groundbreaking conference on software engineering in Garmisch, organized by its chairman F.L. Bauer and his cochairs L. Bolliet and H.J. Helms. This conference introduced the notion and discipline of software engineering. This is a moment to look back at what we’ve achieved, what we haven’t achieved, where we are today, and what challenges lie ahead. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Broy, M."],"date":["2018"],"doi":["10.1109/MS.2018.290111138"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"number":["5"],"pages":["38–43"],"shorttitle":["Yesterday, Today, and Tomorrow"],"title":["Yesterday, Today, and Tomorrow: 50 Years of Software Engineering"],"volume":["35"]},"creators":{"author":[{"lastName":"Broy","firstName":"M."}]}},{"key":"bruchEvaluatingRecommenderSystems2008","type":"inproceedings","fields":{"acmid":["1454254"],"author":["Bruch, Marcel","Schäfer, Thorsten","Mezini, Mira"],"booktitle":["Proc. 2008 Int. Workshop Recomm. Syst. Softw. Eng."],"date":["2008"],"isbn":["978-1-60558-228-3"],"location":["New York, NY, USA"],"nodoi":["10.1145/1454247.1454254"],"note":["TL;DR \n\nAn automated evaluation process is presented which enables the validation of recommendation systems with large test beds in an objective manner by means of precision and recall measures and demonstrates the applicability of this approach by evaluating an improvement of an existing API recommender tool that takes into account the framework-method context for recommendations."],"numpages":["5"],"pages":["16–20"],"publisher":["ACM"],"series":["RSSE '08"],"title":["On evaluating recommender systems for API usages"],"url":["http://doi.acm.org/10.1145/1454247.1454254"]},"creators":{"author":[{"lastName":"Bruch","firstName":"Marcel"},{"lastName":"Schäfer","firstName":"Thorsten"},{"lastName":"Mezini","firstName":"Mira"}]},"sentenceCased":true},{"key":"bruelModelTransformationReuse","type":"article","fields":{"langid":["english"],"abstract":["Model transformations (MTs) are essential elements of model-driven engineering (MDE) solutions. MDE promotes the creation of domain-specific metamodels, but without proper reuse mechanisms, MTs need to be developed from scratch for each new metamodel. In this paper, we classify reuse approaches for MTs across different metamodels and compare a sample of specific approaches – model types, concepts, a-posteriori typing, multilevel modeling, and design patterns for MTs – with the help of a feature model developed for this purpose, as well as a common example. We discuss strengths and weaknesses of each approach, provide a reading grid used to compare their features, and identify gaps in current reuse approaches."],"author":["Bruel, Jean-Michel","Combemale, Benoit","Guerra, Esther","Jézéquel, Jean-Marc"],"pages":["15"],"title":["Model Transformation Reuse across Metamodels"]},"creators":{"author":[{"lastName":"Bruel","firstName":"Jean-Michel"},{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Jézéquel","firstName":"Jean-Marc"}]}},{"key":"brun2007emf","type":"article","fields":{"author":["Brun, Cedric","Musset, Jonathan","Toulme, Antoine"],"date":["2007"],"title":["EMF compare"]},"creators":{"author":[{"lastName":"Brun","firstName":"Cedric"},{"lastName":"Musset","firstName":"Jonathan"},{"lastName":"Toulme","firstName":"Antoine"}]},"sentenceCased":true},{"key":"Brun2008MODELDI","type":"inproceedings","fields":{"langid":["english"],"author":["Brun, Cédric","Obeo","Pierantonio, Alfonso"],"date":["2008"],"keywords":["/unread","⛔ No INSPIRE recid found"],"title":["Model differences in the eclipse modeling framework"],"url":["https://api.semanticscholar.org/CorpusID:16702546"]},"creators":{"author":[{"lastName":"Brun","firstName":"Cédric"},{"literal":"Obeo"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"bruneliere2014modisco","type":"article","fields":{"author":["Bruneliere, Hugo","Cabot, Jordi","Dupé, Grégoire","Madiot, Frédéric"],"date":["2014"],"journaltitle":["Inf. Softw. Technol."],"number":["8"],"pages":["1012–1032"],"publisher":["Elsevier"],"title":["Modisco: A model driven reverse engineering framework"],"volume":["56"]},"creators":{"author":[{"lastName":"Bruneliere","firstName":"Hugo"},{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Dupé","firstName":"Grégoire"},{"lastName":"Madiot","firstName":"Frédéric"}]},"sentenceCased":true},{"key":"BruneliereCJM10","type":"inproceedings","fields":{"langid":["english"],"author":["Bruneliere, Hugo","Cabot, Jordi","Jouault, Frédéric","Madiot, Frédéric"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["ASE 2010 25th IEEEACM Int. Conf. Autom. Softw. Eng. Antwerp Belg. Sept. 20-24 2010"],"date":["2010"],"doi":["10.1145/1858996.1859032"],"editor":["Pecheur, Charles","Andrews, Jamie","Nitto, Elisabetta Di"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nMoDisco intensively uses MDE principles and techniques to improve existing approaches for reverse engineering, and is introduced as a generic and extensible open source reverse engineering solution."],"pages":["173–174"],"publisher":["ACM"],"timestamp":["Sun, 20 Nov 2022 22:43:32 +0100"],"title":["MoDisco: A generic and extensible framework for model driven reverse engineering"]},"creators":{"author":[{"lastName":"Bruneliere","firstName":"Hugo"},{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Jouault","firstName":"Frédéric"},{"lastName":"Madiot","firstName":"Frédéric"}],"editor":[{"lastName":"Pecheur","firstName":"Charles"},{"lastName":"Andrews","firstName":"Jamie"},{"lastName":"Nitto","firstName":"Elisabetta Di"}]},"sentenceCased":true},{"key":"bruneliereIndustrializationResearchTools2010","type":"inproceedings","fields":{"author":["Bruneliere, Hugo","Cabot, Jordi","Jouault, Frédéric","Tisi, Massimo","Bézivin, Jean"],"booktitle":["Third Int. Workshop Acad. Softw. Dev. Tools Tech.-WASDeTT-3 Co-Located 25th IEEEACM Int. Conf. Autom. Softw. Eng.-ASE2010"],"date":["2010"],"note":["TL;DR \n\nIt is argued in this paper that the best solution for research teams aiming to create high-quality and widely-used tools is to industrialize their research prototypes through a partnership with a technology provider."],"shorttitle":["Industrialization of research tools"],"title":["Industrialization of research tools: The ATL case"],"url":["https://hal.inria.fr/hal-00539173/"],"urldate":["2016-10-10"]},"creators":{"author":[{"lastName":"Bruneliere","firstName":"Hugo"},{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Jouault","firstName":"Frédéric"},{"lastName":"Tisi","firstName":"Massimo"},{"lastName":"Bézivin","firstName":"Jean"}]},"sentenceCased":true},{"key":"bruneliereLightweightMetamodelExtension","type":"inproceedings","fields":{"author":["Bruneliere, Hugo","Garcia, Jokin","Desfray, Philippe","Khelladi, Djamel Eddine","Hebig, Regina","Bendraou, Reda","Cabot, Jordi"],"booktitle":["11th Eur. Conf. Model. Found. Appl. ECMFA 2015a STAF 2015 Conf."],"note":["TL;DR \n\nFollowing the ongoing OMG MOF Extension Facility (MEF) RFP, this paper proposes a generic lightweight metamodel extension mechanism developed as part of the MoNoGe collaborative project, with two different implementations of this extension mechanism based on Eclipse/EMF and the Modelio modeling environment."],"title":["On Lightweight Metamodel Extension to Support Modeling Tools Agility"],"url":["https://hal.inria.fr/hal-01146802/"],"urldate":["2015-06-24"]},"creators":{"author":[{"lastName":"Bruneliere","firstName":"Hugo"},{"lastName":"Garcia","firstName":"Jokin"},{"lastName":"Desfray","firstName":"Philippe"},{"lastName":"Khelladi","firstName":"Djamel Eddine"},{"lastName":"Hebig","firstName":"Regina"},{"lastName":"Bendraou","firstName":"Reda"},{"lastName":"Cabot","firstName":"Jordi"}]}},{"key":"brunEngineeringSelfadaptiveSystems2009","type":"incollection","fields":{"author":["Brun, Yuriy","Serugendo, Giovanna Di Marzo","Gacek, Cristina","Giese, Holger","Kienle, Holger","Litoiu, Marin","Müller, Hausi","Pezzè, Mauro","Shaw, Mary"],"booktitle":["Software engineering for self-adaptive systems"],"date":["2009"],"note":["TL;DR \n\nThe state-of-the-art in engineering self-adaptive systems is explored and the critical challenges the community must address to enable systematic and well-organized engineering of self- Adaptive and self-managing software systems are identified."],"pages":["48–70"],"publisher":["Springer"],"title":["Engineering self-adaptive systems through feedback loops"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-02161-9_3"],"urldate":["2016-11-03"]},"creators":{"author":[{"lastName":"Brun","firstName":"Yuriy"},{"lastName":"Serugendo","firstName":"Giovanna Di Marzo"},{"lastName":"Gacek","firstName":"Cristina"},{"lastName":"Giese","firstName":"Holger"},{"lastName":"Kienle","firstName":"Holger"},{"lastName":"Litoiu","firstName":"Marin"},{"lastName":"Müller","firstName":"Hausi"},{"lastName":"Pezzè","firstName":"Mauro"},{"lastName":"Shaw","firstName":"Mary"}]},"sentenceCased":true},{"key":"brunschwigModellingMobileDevices","type":"article","fields":{"langid":["english"],"abstract":["Modelling is central to many disciplines in engineering and the natural and social sciences. A wide variety of modelling languages and tools have been proposed along the years, traditionally for static environments such as desktops and laptops. However, the availability of increasingly powerful mobile devices makes it possible to profit from their embedded sensors and components (e.g., camera, microphone, GPS, accelerometer, gyroscope) for modelling. This has promoted a new range of modelling tools specially designed for their use in mobility. Such tools open the door to modelling in dynamic scenarios that go beyond the capabilities of traditional desktop tools. For example, modelling in mobility can be useful to design smart factories on-site, or to create models of hiking routes while walking along the routes, among many other scenarios."],"author":["Brunschwig, Lea","Guerra, Esther","family=Lara, given=Juan, prefix=de, useprefix=true"],"note":["TL;DR \n\nA systematic mapping study is reported on to identify the state of the art and trends in modelling on mobile devices, and derive a classification for mobile modelling tools along three orthogonal dimensions, discuss current gaps, and propose avenues for further research."],"pages":["27"],"title":["Modelling on mobile devices"]},"creators":{"author":[{"lastName":"Brunschwig","firstName":"Lea"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true}]},"sentenceCased":true},{"key":"brynjulfsenXAITextDomainSpecificLanguage","type":"article","fields":{"langid":["english"],"author":["Brynjulfsen, Håvard","Rabbi, Fazle"],"keywords":["GOAL_MDE4AI"],"pages":["105"],"title":["XAIText: A Domain-Specific Language for Developing an AI Pipeline"]},"creators":{"author":[{"lastName":"Brynjulfsen","firstName":"Håvard"},{"lastName":"Rabbi","firstName":"Fazle"}]}},{"key":"bucchiaroneAutonomousShuttleasaServiceASaaS2020","type":"article","fields":{"langid":["english"],"abstract":["Providing mobility services effectively to residents and visitors is a complex socio-technical system task to city public managers. Smart mobility systems aim to support the efficient exploitation of city transport facilities and sustainable mobility within the urban environment. People need to travel quickly and conveniently between locations at different scales, ranging from a few blocks within a city to a journey across cities. At the same time, goods need to be timely delivered, considering both the users and the businesses’ needs. Several cities indicated an interest in using Autonomous Vehicles (AV) for the “last-mile” mobility services in the last few years. With them, it seems to be easier to get people and goods around using fewer vehicles. In this context, Autonomous Shuttles (AS) are beginning to be thought of as a new mobility/delivery service into the city center where narrow streets are not easily served by traditional buses. They allow them to perform critical areas with minimal new infrastructure and reduce noise and pollution. The article analyses the state-of-art on autonomous shuttles by proposing four application scenarios targeting the last-mile delivery of goods, the tourist experiences, and the shared and integrated mobility. Furthermore, we contribute with the proposition of the Autonomous Shuttles-as-a service (ASaaS) concept as the key pillar for the realization of innovative and sustainable proximity mobility. Our research proposed new research challenges for ASaaS, and we discuss social implications and governance challenges that consider user engagement and sustainability. It also recommended extending new research to focus on simulation and machine learning techniques for last-mile mobility planning and explore the journeys tracking certification via artificial intelligence and blockchain-based techniques."],"author":["Bucchiarone, Antonio","Battisti, Sandro","Marconi, Annapaola","Maldacea, Roberto","Ponce, Diego Cardona"],"date":["2020"],"doi":["10.1109/TITS.2020.3025670"],"issn":["1524-9050, 1558-0016"],"journaltitle":["IEEE Trans. Intell. Transport. Syst."],"pages":["1–10"],"shorttitle":["Autonomous Shuttle-as-a-Service (ASaaS)"],"title":["Autonomous Shuttle-as-a-Service (ASaaS): Challenges, Opportunities, and Social Implications"]},"creators":{"author":[{"lastName":"Bucchiarone","firstName":"Antonio"},{"lastName":"Battisti","firstName":"Sandro"},{"lastName":"Marconi","firstName":"Annapaola"},{"lastName":"Maldacea","firstName":"Roberto"},{"lastName":"Ponce","firstName":"Diego Cardona"}]}},{"key":"BucchiaroneCPP20","type":"article","fields":{"langid":["english"],"author":["Bucchiarone, Antonio","Cabot, Jordi","Paige, Richard F.","Pierantonio, Alfonso"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2020"],"doi":["10.1007/S10270-019-00773-6"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThe events brought together experts from industry, academia, and the open-source community to assess what has changed in research in MDE over the last 10 years, what challenges remain, and what new challenges have arisen."],"number":["1"],"pages":["5–13"],"timestamp":["Sun, 25 Jul 2021 11:40:23 +0200"],"title":["Grand challenges in model-driven engineering: An analysis of the state of the research"],"volume":["19"]},"creators":{"author":[{"lastName":"Bucchiarone","firstName":"Antonio"},{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"bucchiaroneRequirementsCodeArchitecturecentric2009","type":"article","fields":{"author":["Bucchiarone, Antonio","Ruscio, Davide Di","Muccini, Henry","Pelliccione, Patrizio"],"date":["2009"],"eprint":["0910.0493"],"eprinttype":["arxiv"],"ids":["bucchiaroneRequirementsCodeArchitecturecentric2009a"],"journaltitle":["CoRR"],"title":["From Requirements to code: An Architecture-centric Approach for producing Quality Systems"],"url":["http://arxiv.org/abs/0910.0493"],"volume":["abs/0910.0493"]},"creators":{"author":[{"lastName":"Bucchiarone","firstName":"Antonio"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Muccini","firstName":"Henry"},{"lastName":"Pelliccione","firstName":"Patrizio"}]},"sentenceCased":true},{"key":"bucchiaroneWhatFutureModeling2021","type":"article","fields":{"langid":["english"],"author":["Bucchiarone, Antonio","Ciccozzi, Federico","Lambers, Leen","Pierantonio, Alfonso","Tichy, Matthias","Tisi, Massimo","Wortmann, Andreas","Zaytsev, Vadim"],"date":["2021-03"],"doi":["10.1109/MS.2020.3041522"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nIt is the right time to define what should be the future of modeling technologies, especially the requirements for the next generation of modeling frameworks and languages."],"number":["2"],"pages":["119–127"],"title":["What Is the Future of Modeling?"],"volume":["38"]},"creators":{"author":[{"lastName":"Bucchiarone","firstName":"Antonio"},{"lastName":"Ciccozzi","firstName":"Federico"},{"lastName":"Lambers","firstName":"Leen"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Tichy","firstName":"Matthias"},{"lastName":"Tisi","firstName":"Massimo"},{"lastName":"Wortmann","firstName":"Andreas"},{"lastName":"Zaytsev","firstName":"Vadim"}]}},{"key":"buczakSurveyDataMining2016","type":"article","fields":{"author":["Buczak, Anna L.","Guven, Erhan"],"date":["2016-22"],"doi":["10.1109/COMST.2015.2494502"],"issn":["1553-877X, 2373-745X"],"journaltitle":["IEEE Commun. Surv. Tutorials"],"note":["TL;DR \n\nA targeted literature survey of machine learning (ML) and data processing (DM) strategies for cyber analytics in support of intrusion detection as it applies to wired networks."],"number":["2"],"pages":["1153–1176"],"title":["A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection"],"volume":["18"]},"creators":{"author":[{"lastName":"Buczak","firstName":"Anna L."},{"lastName":"Guven","firstName":"Erhan"}]}},{"key":"budinskyEclipseModelingFramework2003","type":"book","fields":{"author":["Budinsky, F.","Steinberg, D.","Merks, E.","Ellersick, R.","T.J. Grose"],"date":["2003"],"note":["TL;DR \n\nThe authoritative guide to the Eclipse Modeling Framework (EMF)–written by the lead EMF designers! shows how EMF unifies three important technologies: Java, XML, and UML."],"publisher":["Addison Wesley"],"title":["Eclipse Modeling Framework"]},"creators":{"author":[{"lastName":"Budinsky","firstName":"F."},{"lastName":"Steinberg","firstName":"D."},{"lastName":"Merks","firstName":"E."},{"lastName":"Ellersick","firstName":"R."},{"literal":"T.J. Grose"}]}},{"key":"bugiottiComparisonDataModels","type":"article","fields":{"langid":["english"],"abstract":["NoSQL datastore systems are a new generation of non-relational databases. More than fifty NoSQL systems have been already implemented, each with different characteristics — especially, with different data models and different APIs to access the data. In this paper we describe and compare the data models and operations offered by a number of representative NoSQL datastores, which we have directly used while developing the SOS (Save Our Systems) and ONDM (Object-NoSQL Datastore Mapper) frameworks. We discuss how these NoSQL systems can be used to manage a database consisting of collections of objects. Furthermore, we report on some experimental results concerning the use of the various systems and the implementation of the data representations described in this paper."],"author":["Bugiotti, Francesca","Cabibbo, Luca"],"pages":["12"],"title":["A Comparison of Data Models and APIs of NoSQL Datastores"]},"creators":{"author":[{"lastName":"Bugiotti","firstName":"Francesca"},{"lastName":"Cabibbo","firstName":"Luca"}]}},{"key":"bugiottiDatabaseDesignNoSQL2014","type":"incollection","fields":{"langid":["english"],"abstract":["We propose a database design methodology for NoSQL systems. The approach is based on NoAM (NoSQL Abstract Model), a novel abstract data model for NoSQL databases, which exploits the commonalities of various NoSQL systems and is used to specify a system-independent representation of the application data. This intermediate representation can be then implemented in target NoSQL databases, taking into account their specific features. Overall, the methodology aims at supporting scalability, performance, and consistency, as needed by next-generation web applications."],"author":["Bugiotti, Francesca","Cabibbo, Luca","Atzeni, Paolo","Torlone, Riccardo"],"booktitle":["Conceptual Modeling"],"date":["2014"],"doi":["10.1007/978-3-319-12206-9_18"],"editor":["Yu, Eric","Dobbie, Gillian","Jarke, Matthias","Purao, Sandeep"],"ids":["bugiottiDatabaseDesignNoSQL2014a"],"isbn":["978-3-319-12205-2 978-3-319-12206-9"],"location":["Cham"],"note":["TL;DR \n\nThe approach is based on NoAM (NoSQL Abstract Model), a novel abstract data model for NoSQL databases, which exploits the commonalities of various NoSQL systems and is used to specify a system-independent representation of the application data."],"pages":["223–231"],"publisher":["Springer International Publishing"],"title":["Database Design for NoSQL Systems"],"volume":["8824"]},"creators":{"author":[{"lastName":"Bugiotti","firstName":"Francesca"},{"lastName":"Cabibbo","firstName":"Luca"},{"lastName":"Atzeni","firstName":"Paolo"},{"lastName":"Torlone","firstName":"Riccardo"}],"editor":[{"lastName":"Yu","firstName":"Eric"},{"lastName":"Dobbie","firstName":"Gillian"},{"lastName":"Jarke","firstName":"Matthias"},{"lastName":"Purao","firstName":"Sandeep"}]}},{"key":"BuildingAutomatedMachine","type":"online","fields":{"title":["Building an Automated Machine Learning Pipeline: Part One | by Ceren Iyim | Towards Data Science"],"url":["https://towardsdatascience.com/building-an-automated-machine-learning-pipeline-part-one-5c70ae682f35"],"urldate":["2021-04-21"]},"creators":{}},{"key":"BuildingIoTOntologies","type":"online","fields":{"title":["Building IoT ontologies and integrating them with Eclipse projects | EclipseCon Europe 2016"],"url":["https://www.eclipsecon.org/europe2016/session/building-iot-ontologies-and-integrating-them-eclipse-projects"],"urldate":["2016-09-27"]},"creators":{},"sentenceCased":true},{"key":"BuildingRaspberryPi","type":"online","fields":{"title":["Building A Raspberry Pi VPN Part One: How And Why To Build A Server - ReadWrite"],"url":["http://readwrite.com/2014/04/10/raspberry-pi-vpn-tutorial-server-secure-web-browsing"],"urldate":["2015-04-17"]},"creators":{}},{"key":"BuildingSmarterEclipse","type":"online","fields":{"title":["Building a Smarter Eclipse IoT Greenhouse with Eclipse Vorto, Kura, Californium and Paho | EclipseCon Europe 2016"],"url":["https://www.eclipsecon.org/europe2016/session/building-smarter-eclipse-iot-greenhouse-eclipse-vorto-kura-californium-and-paho"],"urldate":["2016-09-27"]},"creators":{}},{"key":"Bunne20191374","type":"inproceedings","fields":{"abstract":["Generative Adversarial Networks have shown remarkable success in learning a distribution that faithfully recovers a reference distribution in its entirety. However, in some cases, we may want to only learn some aspects (e.g., cluster or manifold structure), while modifying others (e.g., style, orientation or dimension). In this work, we propose an approach to learn generative models across such incomparable spaces, and demonstrate how to steer the learned distribution towards target properties. A key component of our model is the Gromov-Wasserstein distance, a notion of discrepancy that compares distributions relationally rather than absolutely. While this framework subsumes current generative models in identically reproducing distributions, its inherent flexibility allows application to tasks in manifold learning, relational learning and cross-domain learning. © 36th International Conference on Machine Learning, ICML 2019. All rights reserved."],"author":["Bunne, C.","Alvarez-Melis, D.","Krause, A.","Jegelka, S."],"date":["2019"],"document_type":["Conference Paper"],"isbn":["978-1-5108-8698-8"],"keywords":["Adversarial networks","Artificial intelligence","Cross-domain learning","Generative model","Inherent flexibility","Machine learning","Manifold learning","Manifold structures","Relational learning","Software engineering","Wasserstein distance"],"note":["cited By 20"],"pages":["1374–1389"],"publisher":["International Machine Learning Society (IMLS)"],"series":["36th International Conference on Machine Learning, ICML 2019"],"source":["Scopus"],"title":["Learning generative models across incomparable spaces"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077966344&partnerID=40&md5=28c6da710bb574e41803cd5cf2d19ea2"],"volume":["2019-June"]},"creators":{"author":[{"lastName":"Bunne","firstName":"C."},{"lastName":"Alvarez-Melis","firstName":"D."},{"lastName":"Krause","firstName":"A."},{"lastName":"Jegelka","firstName":"S."}]},"sentenceCased":true},{"key":"Burattin2018322","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Technical University of Denmark, Kgs. Lyngby, Denmark; University of Haifa, Haifa, Israel; Eindhoven University of Technology, Eindhoven, Netherlands; Vienna University of Economics and Business, Vienna, Austria; Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Humboldt-University, Berlin, Germany; University of Innsbruck, Innsbruck, Austria"],"author":["Burattin, A.","Soffer, P.","Fahland, D.","Mendling, J.","Reijers, H.A.","Vanderfeesten, I.","Weidlich, M.","Weber, B."],"correspondence_address1":["Burattin, A.; Technical University of DenmarkDenmark; email: andbur@dtu.dk"],"date":["2018"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-319-98648-7_19"],"editor":["Montali M., Weber I., vom Brocke J., Weske M."],"isbn":["9783319986470"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"keywords":["GOAL_Model-Classification","notion","TECHNIQUE_FFNN"],"note":["cited By 2"],"pages":["322–338"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Who is behind the model? Classifying modelers based on pragmatic model features"],"volume":["11080 LNCS"]},"creators":{"author":[{"lastName":"Burattin","firstName":"A."},{"lastName":"Soffer","firstName":"P."},{"lastName":"Fahland","firstName":"D."},{"lastName":"Mendling","firstName":"J."},{"lastName":"Reijers","firstName":"H.A."},{"lastName":"Vanderfeesten","firstName":"I."},{"lastName":"Weidlich","firstName":"M."},{"lastName":"Weber","firstName":"B."}],"editor":[{"lastName":"Montali M.","suffix":"Weber I.","firstName":"vom Brocke J., Weske M."}]},"sentenceCased":true},{"key":"BurduselZ018","type":"inproceedings","fields":{"langid":["english"],"author":["Burdusel, Alexandru","Zschaler, Steffen","Strüber, Daniel"],"booktitle":["Proc. 21st ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion Proc. MODELS"],"date":["2018"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis tool demostration presents MDEOptimiser (MDEO), a tool for specifying and solving optimisation problems using MDE, and shows that with MDEO, specifying Optimisation problems becomes a less complex task compared to custom implementations."],"pages":["12–16"],"publisher":["ACM"],"title":["MDEoptimiser: A search based model engineering tool"]},"creators":{"author":[{"lastName":"Burdusel","firstName":"Alexandru"},{"lastName":"Zschaler","firstName":"Steffen"},{"lastName":"Strüber","firstName":"Daniel"}]},"sentenceCased":true},{"key":"buresSoftwareEngineeringSmart2015","type":"article","fields":{"langid":["english"],"author":["Bures, Tomas","Krikava, Filip","Mordinyi, Richard","Pronios, Nikos","Weyns, Danny","Berger, Christian","Biffl, Stefan","Daun, Marian","Gabor, Thomas","Garlan, David","Gerostathopoulos, Ilias","Julien, Christine"],"date":["2015-11-11"],"doi":["10.1145/2830719.2830736"],"issn":["01635948"],"journaltitle":["ACM SIGSOFT Softw. Eng. Notes"],"note":["TL;DR \n\nThis paper reports on the results of the First International Workshop on Software Engineering of Smart Cyber-Physical Systems (SEsCPS 2015), where participants discussed characteristics, challenges and opportunities of SE for smart CPS, with the aim to outline an agenda for future research in this important area."],"number":["6"],"pages":["28–32"],"shorttitle":["Software Engineering for Smart Cyber-Physical Systems – Towards a Research Agenda"],"title":["Software Engineering for Smart Cyber-Physical Systems – Towards a Research Agenda: Report on the First International Workshop on Software Engineering for Smart CPS"],"volume":["40"]},"creators":{"author":[{"lastName":"Bures","firstName":"Tomas"},{"lastName":"Krikava","firstName":"Filip"},{"lastName":"Mordinyi","firstName":"Richard"},{"lastName":"Pronios","firstName":"Nikos"},{"lastName":"Weyns","firstName":"Danny"},{"lastName":"Berger","firstName":"Christian"},{"lastName":"Biffl","firstName":"Stefan"},{"lastName":"Daun","firstName":"Marian"},{"lastName":"Gabor","firstName":"Thomas"},{"lastName":"Garlan","firstName":"David"},{"lastName":"Gerostathopoulos","firstName":"Ilias"},{"lastName":"Julien","firstName":"Christine"}]}},{"key":"Burgueño20191","type":"article","fields":{"langid":["english"],"abbrev_source_title":["J. Object Technol."],"affiliation":["IN3, Open University of Catalonia, Spain; Institut LIST, CEA, Université Paris-Saclay, France; ICREA, Spain"],"art_number":["A7"],"author":["Burgueño, L.","Cabot, J.","Gérard, S."],"date":["2019"],"document_type":["Article"],"doi":["10.5381/JOT.2019.18.3.A7"],"issn":["16601769"],"journaltitle":["J. Object Technol."],"keywords":["GOAL_Model-Transformation-Development","notion"],"note":["cited By 19"],"number":["3"],"pages":["1–11"],"publisher":["Association Internationale pour les Technologies Objets"],"source":["Scopus"],"title":["The future of model transformation languages: An open community discussion"],"volume":["18"]},"creators":{"author":[{"lastName":"Burgueño","firstName":"L."},{"lastName":"Cabot","firstName":"J."},{"lastName":"Gérard","firstName":"S."}]},"sentenceCased":true},{"key":"Burgueno2019168","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - ACM/IEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion, MODELS-C"],"affiliation":["IN3, Open University of Catalonia, Spain; Institut LIST, CEA, Université Paris-Saclay, France; King's College London, United Kingdom; CDL-MINT, Johannes Kepler Universit t Linz, Austria"],"art_number":["8904820"],"author":["Burgueno, L.","Burdusel, A.","Gerard, S.","Wimmer, M."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/MODELS-C.2019.00028"],"editor":["Burgueno L., Burgueno L., Voss S., Chaudron M., Kienzle J., Volter M., Gerard S., Zahedi M., Bousse E., Rensink A., Polack F., Engels G., Kappel G., Pretschner A."],"isbn":["978-1-72815-125-0"],"note":["cited By 2 \n\nTL;DR \n\nThe 1st edition of the Workshop on Artificial Intelligence and Model-driven Engineering (MDE Intelligence) was held on September 16, 2019 in Munich, Germany, as part of the satellite events of the IEEE/ACM 22th International Conference on Model-Driven Engineering Languages and Systems (MODELS 2019)."],"pages":["168–169"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2019"],"source":["Scopus"],"title":["Preface to MDE intelligence 2019: 1st workshop on artificial intelligence and model-driven engineering"]},"creators":{"author":[{"lastName":"Burgueno","firstName":"L."},{"lastName":"Burdusel","firstName":"A."},{"lastName":"Gerard","firstName":"S."},{"lastName":"Wimmer","firstName":"M."}],"editor":[{"lastName":"Burgueno L.","suffix":"Burgueno L.","firstName":"Voss S., Chaudron M., Kienzle J., Volter M., Gerard S., Zahedi M., Bousse E., Rensink A., Polack F., Engels G., Kappel G., Pretschner A."}]},"sentenceCased":true},{"key":"Burgueño2019294","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - ACM/IEEE Int. Conf. Model Driven Eng. Lang. Syst., MODELS"],"affiliation":["IN3, Open University of Catalonia, Institut LIST, CEA, Université Paris-Saclay, France; ICREA, IN3, Open University of Catalonia, Spain"],"art_number":["8906971"],"author":["Burgueño, L.","Cabot, J.","Gérard, S."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/MODELS.2019.00013"],"editor":["Kessentini M., Yue T., Pretschner A., Voss S., Burgueno L., Burgueno L., Yue T."],"isbn":["978-1-72812-535-0"],"keywords":["GOAL_Model-Transformation-Development","notion","TECHNIQUE_LSTM"],"note":["cited By 22"],"pages":["294–299"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems, MODELS 2019"],"source":["Scopus"],"title":["An LSTM-Based neural network architecture for model transformations"]},"creators":{"author":[{"lastName":"Burgueño","firstName":"L."},{"lastName":"Cabot","firstName":"J."},{"lastName":"Gérard","firstName":"S."}],"editor":[{"lastName":"Kessentini M.","suffix":"Yue T.","firstName":"Pretschner A., Voss S., Burgueno L., Burgueno L., Yue T."}]},"sentenceCased":true},{"key":"Burgueno2021148","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Companion Proc. - Int. Conf. Model-Driven Eng. Lang. Syst., MODELS-C"],"affiliation":["IN3, Open University of Catalonia, Spain; University of Michigan, Dearborn, United States; CDL-MINT, Johannes Kepler Universität Linz, Austria; King's College, London, United Kingdom"],"author":["Burgueno, L.","Kessentini, M.","Wimmer, M.","Zschaler, S."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/MODELS-C53483.2021.00026"],"isbn":["978-1-66542-484-4"],"note":["cited By 0"],"pages":["148–149"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Companion Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021"],"source":["Scopus"],"title":["MDE intelligence 2021: 3rdWorkshop on artificial intelligence and model-driven engineering"]},"creators":{"author":[{"lastName":"Burgueno","firstName":"L."},{"lastName":"Kessentini","firstName":"M."},{"lastName":"Wimmer","firstName":"M."},{"lastName":"Zschaler","firstName":"S."}]},"sentenceCased":true},{"key":"BurguenoCLG22","type":"article","fields":{"langid":["english"],"author":["Burgueño, Loli","Cabot, Jordi","Li, Shuai","Gérard, Sébastien"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2022"],"doi":["10.1007/S10270-021-00893-Y"],"ids":["burgueno2022generic"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["1"],"pages":["139–156"],"timestamp":["Sun, 02 Oct 2022 15:49:27 +0200"],"title":["A generic LSTM neural network architecture to infer heterogeneous model transformations"],"volume":["21"]},"creators":{"author":[{"lastName":"Burgueño","firstName":"Loli"},{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Li","firstName":"Shuai"},{"lastName":"Gérard","firstName":"Sébastien"}]},"sentenceCased":true},{"key":"burguenoContentsModelBasedSoftware2019","type":"article","fields":{"langid":["english"],"abstract":["Although Model-Based Software Engineering (MBE) is a widely accepted Software Engineering (SE) discipline, no agreedupon core set of concepts and practices (i.e., a Body of Knowledge) has been defined for it yet. With the goals of characterizing the contents of the MBE discipline, promoting a global consistent view of it, clarifying its scope with regard to other SE disciplines, and defining a foundation for the development of educational curricula on MBE, this paper proposes the contents for a Body of Knowledge for MBE. We also describe the methodology that we have used to come up with the proposed list of contents, as well as the results of a survey study that we conducted to sound out the opinion of the community on the importance of the proposed topics and their level of coverage in the existing SE curricula."],"author":["Burgueño, Loli","Ciccozzi, Federico","Famelis, Michalis","Kappel, Gerti","Lambers, Leen","Mosser, Sebastien","Paige, Richard F.","Pierantonio, Alfonso","Rensink, Arend","Salay, Rick","Taentzer, Gabriele","Vallecillo, Antonio","Wimmer, Manuel"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2019-12"],"doi":["10.1007/s10270-019-00746-9"],"ids":["BurguenoCFKLMPP19"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper proposes the contents for a Body of Knowledge for MBE, and describes the methodology that was used to come up with the proposed list of contents, as well as the results of a survey study conducted to sound out the opinion of the community."],"number":["6"],"pages":["3193–3205"],"timestamp":["Sat, 09 Apr 2022 12:28:53 +0200"],"title":["Contents for a Model-Based Software Engineering Body of Knowledge"],"volume":["18"]},"creators":{"author":[{"lastName":"Burgueño","firstName":"Loli"},{"lastName":"Ciccozzi","firstName":"Federico"},{"lastName":"Famelis","firstName":"Michalis"},{"lastName":"Kappel","firstName":"Gerti"},{"lastName":"Lambers","firstName":"Leen"},{"lastName":"Mosser","firstName":"Sebastien"},{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Rensink","firstName":"Arend"},{"lastName":"Salay","firstName":"Rick"},{"lastName":"Taentzer","firstName":"Gabriele"},{"lastName":"Vallecillo","firstName":"Antonio"},{"lastName":"Wimmer","firstName":"Manuel"}]}},{"key":"burguenoGuestEditorialTheme2022","type":"article","fields":{"langid":["english"],"abstract":["This theme section brings together the latest research at the intersection of artificial intelligence (AI) and model-driven engineering (MDE). Over the past years, we have witnessed a substantial rise of AI successfully applied to different domains, including software development and MDE. Dedicated events at the intersection of AI and MDE have been created, too, such as the MDE Intelligence workshop series co-located with the MODELS conference. This theme section covers research contributions integrating AI components into MDE approaches—increasing the current benefits of MDE processes and tools and pushing the limits of “classic” MDE with the goal to provide software and systems engineers with the right techniques to develop the next generation of highly complex model-based systems—and applications of MDE to the development of AI components. In total, nine submissions were accepted in the theme section after a thorough peer-reviewing process."],"author":["Burgueño, Lola","Cabot, Jordi","Wimmer, Manuel","Zschaler, Steffen"],"date":["2022-06"],"doi":["10.1007/s10270-022-00988-0"],"ids":["burguenoGuestEditorialTheme2022a"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"number":["3"],"pages":["963–965"],"title":["Guest editorial to the theme section on AI-enhanced model-driven engineering"],"volume":["21"]},"creators":{"author":[{"lastName":"Burgueño","firstName":"Lola"},{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Zschaler","firstName":"Steffen"}]},"sentenceCased":true},{"key":"burguenoMDEIntelligence6th","type":"article","fields":{"langid":["english"],"abstract":["Artificial Intelligence (AI) has become part of everyone’s life. More recently, AI has started to impact all aspects of the system and software development lifecycle, from specification to design, testing, deployment, and maintenance, with the main goal of helping engineers produce higher-quality systems and software more efficiently while being able to handle ever more complex systems. We believe there is a clear need for AI-empowered MDE, which will push the limits of “classic” MDE and provide the proper techniques to develop the next generation of highly complex software systems engineers will have to design tomorrow."],"author":["Burgueno, Lola","Bork, Dominik","Cabot, Jordi","Gerard, Sebastien","Ramırez, Aurora"],"title":["MDE Intelligence: 6th Workshop on Artificial Intelligence and Model-driven Engineering"]},"creators":{"author":[{"lastName":"Burgueno","firstName":"Lola"},{"lastName":"Bork","firstName":"Dominik"},{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Gerard","firstName":"Sebastien"},{"lastName":"Ramırez","firstName":"Aurora"}]}},{"key":"burguenoNLPbasedArchitectureAutocompletion","type":"article","fields":{"langid":["english"],"abstract":["Domain models capture the key concepts and relationships of a business domain. Typically, domain models are manually defined by software designers in the initial phases of a software development cycle, based on their interactions with the client and their own domain expertise. Given the key role of domain models in the quality of the final system, it is important that they properly reflect the reality of the business. To facilitate the definition of domain models and improve their quality, we propose to move towards a more assisted domain modeling building process where an NLP-based assistant will provide autocomplete suggestions for the partial model under construction based on the automatic analysis of the textual information available for the project (contextual knowledge) and/or its related business domain (general knowledge). The process will also take into account the feedback collected from the designer’s interaction with the assistant. We have developed a proof-of-concept tool and have performed a preliminary evaluation that shows promising results."],"author":["Burgueño, Loli","Clarisó, Robert","Li, Shuai","Gérard, Sébastien","Cabot, Jordi"],"note":["TL;DR \n\nThis work proposes to move towards a more assisted domain modeling building process where an NLP-based assistant will provide autocomplete suggestions for the partial model under construction based on the automatic analysis of the textual information available for the project and/or its related business domain."],"pages":["16"],"title":["A NLP-based architecture for the autocompletion of partial domain models"]},"creators":{"author":[{"lastName":"Burgueño","firstName":"Loli"},{"lastName":"Clarisó","firstName":"Robert"},{"lastName":"Li","firstName":"Shuai"},{"lastName":"Gérard","firstName":"Sébastien"},{"lastName":"Cabot","firstName":"Jordi"}]},"sentenceCased":true},{"key":"burguenoProceedingsMODELS20172017","type":"book","fields":{"date":["2017"],"editor":["Burgueño, Loli","Corley, Jonathan","Bencomo, Nelly","Clarke, Peter J.","Collet, Philippe","Famelis, Michalis","Ghosh, Sudipto","Gogolla, Martin","Greenyer, Joel","Guerra, Esther","Kokaly, Sahar","Pierantonio, Alfonso","Rubin, Julia","Ruscio, Davide Di"],"ids":["burguenoProceedingsMODELS20172017a"],"publisher":["CEUR-WS.org"],"series":["CEUR Workshop Proceedings"],"title":["Proceedings of MODELS 2017 Satellite Event: Workshops (ModComp, ME, EXE, COMMitMDE, MRT, MULTI, GEMOC, MoDeVVa, MDETools, FlexMDE, MDEbug), Posters, Doctoral Symposium, Educator Symposium, ACM Student Research Competition, and Tools and Demonstrations co-located with ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems (MODELS 2017), Austin, TX, USA, September, 17, 2017"],"url":["http://ceur-ws.org/Vol-2019"],"volume":["2019"]},"creators":{"editor":[{"lastName":"Burgueño","firstName":"Loli"},{"lastName":"Corley","firstName":"Jonathan"},{"lastName":"Bencomo","firstName":"Nelly"},{"lastName":"Clarke","firstName":"Peter J."},{"lastName":"Collet","firstName":"Philippe"},{"lastName":"Famelis","firstName":"Michalis"},{"lastName":"Ghosh","firstName":"Sudipto"},{"lastName":"Gogolla","firstName":"Martin"},{"lastName":"Greenyer","firstName":"Joel"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Kokaly","firstName":"Sahar"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Rubin","firstName":"Julia"},{"lastName":"Ruscio","firstName":"Davide Di"}]},"sentenceCased":true},{"key":"burguenoStaticFaultLocalization2015","type":"article","fields":{"author":["Burgueno, Loli","Troya, Javier","Wimmer, Manuel","Vallecillo, Antonio"],"date":["2015-05-01"],"doi":["10.1109/TSE.2014.2375201"],"issn":["0098-5589, 1939-3520"],"journaltitle":["IEEE Trans. Softw. Eng."],"note":["TL;DR \n\nThis paper presents a light-weight and static approach for locating the faulty rules in model transformations, based on matching functions that automatically establish these alignments using the metamodel footprints, i.e., the metAModel elements used."],"number":["5"],"pages":["490–506"],"title":["Static Fault Localization in Model Transformations"],"volume":["41"]},"creators":{"author":[{"lastName":"Burgueno","firstName":"Loli"},{"lastName":"Troya","firstName":"Javier"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Vallecillo","firstName":"Antonio"}]}},{"key":"BurguenoWV16","type":"article","fields":{"langid":["english"],"author":["Burgueño, Loli","Wimmer, Manuel","Vallecillo, Antonio"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2016"],"doi":["10.1016/J.INFSOF.2016.06.001"],"journaltitle":["Inf. Softw. Technol."],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["17–35"],"timestamp":["Tue, 16 Aug 2022 23:05:33 +0200"],"title":["A linda-based platform for the parallel execution of out-Place model transformations"],"volume":["79"]},"creators":{"author":[{"lastName":"Burgueño","firstName":"Loli"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Vallecillo","firstName":"Antonio"}]},"sentenceCased":true},{"key":"buttingModelingReusablePlatformIndependent2016","type":"article","fields":{"author":["Butting, Arvid","Rumpe, Bernhard","Schulze, Christoph","Thomas, Ulrike","Wortmann, Andreas"],"date":["2016"],"eprint":["1601.02452"],"eprinttype":["arxiv"],"journaltitle":["ArXiv Prepr. ArXiv160102452"],"note":["TL;DR \n\nA new domain-specific language and toolchain for robot assembly tasks for compliant manipulators with the LightRocks toolchain, allowing a separation of concerns between domain experts and robotics experts."],"title":["Modeling Reusable, Platform-Independent Robot Assembly Processes"],"url":["http://arxiv.org/abs/1601.02452"],"urldate":["2016-01-18"]},"creators":{"author":[{"lastName":"Butting","firstName":"Arvid"},{"lastName":"Rumpe","firstName":"Bernhard"},{"lastName":"Schulze","firstName":"Christoph"},{"lastName":"Thomas","firstName":"Ulrike"},{"lastName":"Wortmann","firstName":"Andreas"}]}},{"key":"buyyaInternetThingsPrinciples2016","type":"book","fields":{"langid":["english"],"author":["Buyya, Rajkumar","Dastjerdi, Amir Vahid"],"date":["2016"],"isbn":["978-0-12-805395-9"],"location":["Amsterdam Boston Heidelberg"],"note":["TL;DR \n\nInternet of Things: Principles and Paradigms captures the state-of-the-art research in Internet of Things, its applications, architectures, and technologies and identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications."],"pagetotal":["354"],"publisher":["Morgan Kaufmann"],"shorttitle":["Internet of Things"],"title":["Internet of Things: Principles and paradigms"]},"creators":{"author":[{"lastName":"Buyya","firstName":"Rajkumar"},{"lastName":"Dastjerdi","firstName":"Amir Vahid"}]},"sentenceCased":true},{"key":"BWMB06","type":"inproceedings","fields":{"author":["Bhaumik, Runa","Williams, Chad","Mobasher, Bamshad","Burke, Robin"],"booktitle":["Proc. ITWP06"],"date":["2006-07"],"location":["Held at AAAI 2006, Boston, Massachusetts"],"note":["TL;DR \n\nThis paper examines approaches for detecting suspicious rating trends based on statistical anomaly detection and empirically shows these techniques can be highly successful at detecting items under attack and time intervals when an attack occurred."],"title":["Securing collaborative filtering against malicious attacks through anomaly detection"],"url":["http://www.aaai.org/Press/Reports/Workshops/ws-06-10.php"]},"creators":{"author":[{"lastName":"Bhaumik","firstName":"Runa"},{"lastName":"Williams","firstName":"Chad"},{"lastName":"Mobasher","firstName":"Bamshad"},{"lastName":"Burke","firstName":"Robin"}]},"sentenceCased":true},{"key":"CA7F13858DC9A0A2F2B68A7CEA562E672","type":"article","fields":{"title":["CA7F13858DC9A0A2F2B68A7CEA562E67-2"]},"creators":{}},{"key":"CabotCR07","type":"inproceedings","fields":{"langid":["english"],"author":["Cabot, Jordi","Clarisó, Robert","Riera, Daniel"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["22nd IEEEACM Int. Conf. Autom. Softw. Eng. ASE 2007 Novemb. 5-9 2007 Atlanta Ga. USA"],"date":["2007"],"doi":["10.1145/1321631.1321737"],"editor":["Stirewalt, R. E. Kurt","Egyed, Alexander","Fischer, Bernd"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nUMLtoCSP is a tool for the formal verification of UML/OCL models that is able to automatically check several correctness properties, such as the strong and weak satisfiability of the model or the lack of redundant constraints."],"pages":["547–548"],"publisher":["ACM"],"timestamp":["Wed, 14 Nov 2018 10:58:39 +0100"],"title":["UMLtoCSP: A tool for the formal verification of UML/OCL models using constraint programming"]},"creators":{"author":[{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Clarisó","firstName":"Robert"},{"lastName":"Riera","firstName":"Daniel"}],"editor":[{"lastName":"Stirewalt","firstName":"R. E. Kurt"},{"lastName":"Egyed","firstName":"Alexander"},{"lastName":"Fischer","firstName":"Bernd"}]},"sentenceCased":true},{"key":"Cacheda:2011:CCF:1921591.1921593","type":"article","fields":{"acmid":["1921593"],"address":["New York, NY, USA"],"articleno":["2"],"author":["Cacheda, Fidel","Carneiro, Víctor","Fernández, Diego","Formoso, Vreixo"],"date":["2011-02"],"issn":["1559-1131"],"issue_date":["February 2011"],"journaltitle":["ACM Trans. Web"],"keywords":["Collaborative filtering","recommender systems"],"nodoi":["10.1145/1921591.1921593"],"number":["1"],"numpages":["33"],"pages":["2:1-2:33"],"publisher":["ACM"],"title":["Comparison of collaborative filtering algorithms: Limitations of current techniques and proposals for scalable, high-performance recommender systems"],"url":["http://doi.acm.org/10.1145/1921591.1921593"],"volume":["5"]},"creators":{"author":[{"lastName":"Cacheda","firstName":"Fidel"},{"lastName":"Carneiro","firstName":"Víctor"},{"lastName":"Fernández","firstName":"Diego"},{"lastName":"Formoso","firstName":"Vreixo"}]},"sentenceCased":true},{"key":"cadavidAnalysisMetamodelingPractices2015","type":"article","fields":{"langid":["english"],"author":["Cadavid, Juan José","Combemale, Benoit","Baudry, Benoit"],"date":["2015-03"],"doi":["10.1016/j.cl.2015.02.002"],"issn":["14778424"],"journaltitle":["Comput. Lang. Syst. Struct."],"title":["An analysis of metamodeling practices for MOF and OCL"]},"creators":{"author":[{"lastName":"Cadavid","firstName":"Juan José"},{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Baudry","firstName":"Benoit"}]},"sentenceCased":true},{"key":"calegariVerificationModelTransformations2013","type":"article","fields":{"abstract":["Within the Model-Driven Engineering paradigm, software development is based on the definition of models providing different views of the system to be constructed and model transformations supporting a (semi)automatic development process. The verification of models and model transformations is crucial in order to improve the quality and the reliability of the products developed using this paradigm. In this context, the verification of a model transformation has three main components: the transformation itself, the properties of interest addressed, and the verification techniques used to establish the properties. In this paper we present an exhaustive review of the literature on the verification of model transformations analyzing these three components. We also take a problem-based approach exemplifying those aspects of interest that could be verified on a model transformation and show how this can be done. Finally, we conclude the need of an integrated environment for addressing the heterogeneous verification of model transformations."],"author":["Calegari, Daniel","Szasz, Nora"],"date":["2013-03-05"],"doi":["10.1016/j.entcs.2013.02.002"],"issn":["1571-0661"],"journaltitle":["Electronic Notes in Theoretical Computer Science"],"pages":["5–25"],"series":["Proceedings of the XXXVIII Latin American Conference in Informatics (CLEI)"],"shorttitle":["Verification of Model Transformations"],"title":["Verification of Model Transformations: A Survey of the State-of-the-Art"],"volume":["292"]},"creators":{"author":[{"lastName":"Calegari","firstName":"Daniel"},{"lastName":"Szasz","firstName":"Nora"}]}},{"key":"callowAddressingSystemsVerification2011","type":"inproceedings","fields":{"author":["Callow, Glenn","Kalawsky, Roy","Watson, Graham","Okuda, Yuki"],"booktitle":["Syst. Syst. Eng. SoSE 2011 6th Int. Conf. On"],"date":["2011"],"note":["TL;DR \n\nA domain modeling approach that employs novel bi-directional model transformations to enable the verification of an autonomous system's functions and performance and can be applied to other types of complex system."],"pages":["311–316"],"publisher":["IEEE"],"shorttitle":["Addressing systems verification of autonomous systems through Bi-directional model transformations"],"title":["Addressing systems verification of autonomous systems through Bi-directional model transformations: A systems model driven architecture approach"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5966616"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Callow","firstName":"Glenn"},{"lastName":"Kalawsky","firstName":"Roy"},{"lastName":"Watson","firstName":"Graham"},{"lastName":"Okuda","firstName":"Yuki"}]},"sentenceCased":true},{"key":"Çam2018372","type":"inproceedings","fields":{"abstract":["Recent developments in computational science and engineering allow a great deal of experimental work to be conducted through computer simulation. In a simulation experiment, a model of the phenomena to be studied is run in a computing environment under varying model and environment settings. As models are adjusted to experimental procedures and execution environments, variations arise. Models also evolve in time. Thus, models must be managed. We propose to bring Global Model Management (GMM) to bear on simulation experiment management by using techniques and tools from megamodeling. The proposed approach will facilitate model management tasks by providing an interface to query the model repository, relate models with each other, and apply model transformations from/to simulation models. Our proposed Megamodel for Simulation Experiments is based on SED-ML (Simulation Experiment Description Markup Language). Copyright © 2018 by SCITEPRESS-Science and Technology Publications, Lda. All rights reserved."],"author":["Çam, S.","Dayibaş, O.","Görür, B.K.","Oǧuztüzün, H.","Yilmaz, L.","Chakladar, S.","Doud, K.","Smith, A.E.","Teran-Somohano, A."],"date":["2018"],"document_type":["Conference Paper"],"doi":["10.5220/0006586703720378"],"editor":["Hammoudi S., Pires L.F., Selic B."],"isbn":["978-989-758-283-7"],"note":["cited By 1 \n\nTL;DR \n\nThe proposed Megamodel for Simulation Experiments is based on SED-ML (Simulation Experiment Description Markup Language) and will facilitate model management tasks by providing an interface to query the model repository, relate models with each other, and apply model transformations from/to simulation models."],"pages":["372–378"],"publisher":["SciTePress"],"series":["MODELSWARD 2018 - Proceedings of the 6th International Conference on Model-Driven Engineering and Software Development"],"source":["Scopus"],"title":["Supporting simulation experiments with megamodeling"],"volume":["2018-January"]},"creators":{"author":[{"lastName":"Çam","firstName":"S."},{"lastName":"Dayibaş","firstName":"O."},{"lastName":"Görür","firstName":"B.K."},{"lastName":"Oǧuztüzün","firstName":"H."},{"lastName":"Yilmaz","firstName":"L."},{"lastName":"Chakladar","firstName":"S."},{"lastName":"Doud","firstName":"K."},{"lastName":"Smith","firstName":"A.E."},{"lastName":"Teran-Somohano","firstName":"A."}],"editor":[{"lastName":"Hammoudi S.","suffix":"Pires L.F.","firstName":"Selic B."}]},"sentenceCased":true},{"key":"camara2023assessment","type":"article","fields":{"langid":["english"],"author":["Cámara, Javier","Troya, Javier","Burgueño, Lola","Vallecillo, Antonio"],"date":["2023"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThe findings show that, in contrast to code generation, the performance of the current version of ChatGPT for software modeling is limited, with various syntactic and semantic deficiencies, lack of consistency in responses and scalability issues."],"number":["3"],"pages":["781–793"],"title":["On the assessment of generative AI in modeling tasks: An experience report with ChatGPT and UML"],"volume":["22"]},"creators":{"author":[{"lastName":"Cámara","firstName":"Javier"},{"lastName":"Troya","firstName":"Javier"},{"lastName":"Burgueño","firstName":"Lola"},{"lastName":"Vallecillo","firstName":"Antonio"}]},"sentenceCased":true},{"key":"camaraBridgingGapControl2020","type":"article","fields":{"abstract":["Two of the main paradigms used to build adaptive software employ different types of properties to capture relevant aspects of the system's run-time behavior. On the one hand, control systems consider properties that concern static aspects like stability, as well as dynamic properties that capture the transient evolution of variables such as settling time. On the other hand, self-adaptive systems consider mostly non-functional properties that capture concerns such as performance, reliability, and cost. In general, it is not easy to reconcile these two types of properties or identify under which conditions they constitute a good fit to provide run-time guarantees. There is a need of identifying the key properties in the areas of control and self-adaptation, as well as of characterizing and mapping them to better understand how they relate and possibly complement each other. In this paper, we take a first step to tackle this problem by: (1) identifying a set of key properties in control theory, (2) illustrating the formalization of some of these properties employing temporal logic languages commonly used to engineer self-adaptive software systems, and (3) illustrating how to map key properties that characterize self-adaptive software systems into control properties, leveraging their formalization in temporal logics. We illustrate the different steps of the mapping on an exemplar case in the cloud computing domain and conclude with identifying open challenges in the area."],"author":["Cámara, Javier","Papadopoulos, Alessandro V.","Vogel, Thomas","Weyns, Danny","Garlan, David","Huang, Shihong","Tei, Kenji"],"date":["2020-06-29"],"doi":["10.1145/3387939.3391568"],"eprint":["2004.11846"],"eprinttype":["arxiv"],"journaltitle":["Proc. IEEEACM 15th Int. Symp. Softw. Eng. Adapt. Self-Manag. Syst."],"note":["TL;DR \n\nThis paper identifies a set of key properties in control theory and illustrates the formalization of some of these properties employing temporal logic languages commonly used to engineer self-adaptive software systems, and illustrates how to map key properties that characterize self- Adaptive software Systems into control properties, leveraging their formalization in temporal logics."],"pages":["78–84"],"title":["Towards Bridging the Gap between Control and Self-Adaptive System Properties"]},"creators":{"author":[{"lastName":"Cámara","firstName":"Javier"},{"lastName":"Papadopoulos","firstName":"Alessandro V."},{"lastName":"Vogel","firstName":"Thomas"},{"lastName":"Weyns","firstName":"Danny"},{"lastName":"Garlan","firstName":"David"},{"lastName":"Huang","firstName":"Shihong"},{"lastName":"Tei","firstName":"Kenji"}]}},{"key":"camaraUncertaintyInteractionProblem2022","type":"article","fields":{"langid":["english"],"abstract":["The problem of mitigating uncertainty in self-adaptation has driven much of the research proposed in the area of software engineering for self-adaptive systems in the last decade. Although many solutions have already been proposed, most of them tend to tackle specific types, sources, and dimensions of uncertainty (e.g., in goals, resources, adaptation functions) in isolation. A special concern are the aspects associated with uncertainty modeling in an integrated fashion. Different uncertainties are rarely independent and often compound, affecting the satisfaction of goals and other system properties in subtle and often unpredictable ways. Hence, there is still limited understanding about the specific ways in which uncertainties from various sources interact and ultimately affect the properties of self-adaptive, software-intensive systems. In this SoSym expert voice, we introduce the Uncertainty Interaction Problem as a way to better qualify the scope of the challenges with respect to representing different types of uncertainty while capturing their interaction in models employed to reason about self-adaptation. We contribute a characterization of the problem and discuss its relevance in the context of case studies taken from two representative application domains. We posit that the Uncertainty Interaction Problem should drive future research in software engineering for autonomous and self-adaptive systems, and therefore, contribute to evolving uncertainty modeling towards holistic approaches that would enable the construction of more resilient self-adaptive systems."],"author":["Cámara, Javier","Troya, Javier","Vallecillo, Antonio","Bencomo, Nelly","Calinescu, Radu","Cheng, Betty H. C.","Garlan, David","Schmerl, Bradley"],"date":["2022-08"],"doi":["10.1007/s10270-022-01037-6"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"note":["TL;DR \n\nIt is proposed that the Uncertainty Interaction Problem should drive future research in software engineering for autonomous and self- Adaptive systems, and therefore, contribute to evolving uncertainty modeling towards holistic approaches that would enable the construction of more resilient self-adaptive systems."],"number":["4"],"pages":["1277–1294"],"title":["The uncertainty interaction problem in self-adaptive systems"],"volume":["21"]},"creators":{"author":[{"lastName":"Cámara","firstName":"Javier"},{"lastName":"Troya","firstName":"Javier"},{"lastName":"Vallecillo","firstName":"Antonio"},{"lastName":"Bencomo","firstName":"Nelly"},{"lastName":"Calinescu","firstName":"Radu"},{"lastName":"Cheng","firstName":"Betty H. C."},{"lastName":"Garlan","firstName":"David"},{"lastName":"Schmerl","firstName":"Bradley"}]},"sentenceCased":true},{"key":"Can2012424","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Comp. Oper. Res."],"abstract":["Genetic programming (GP) and artificial neural networks (ANNs) can be used in the development of surrogate models of complex systems. The purpose of this paper is to provide a comparative analysis of GP and ANNs for metamodeling of discrete-event simulation (DES) models. Three stochastic industrial systems are empirically studied: an automated material handling system (AMHS) in semiconductor manufacturing, an (s,S) inventory model and a serial production line. The results of the study show that GP provides greater accuracy in validation tests, demonstrating a better generalization capability than ANN. However, GP when compared to ANN requires more computation in metamodel development. Even given this increased computational requirement, the results presented indicate that GP is very competitive in metamodeling of DES models. © 2011 Elsevier Ltd."],"affiliation":["Enterprise Research Centre, ERB, University of Limerick, Limerick, Ireland"],"author":["Can, B.","Heavey, C."],"coden":["CMORA"],"correspondence_address1":["Can, B.; Enterprise Research Centre, , Limerick, Ireland; email: birkan.can@ul.ie"],"date":["2012"],"document_type":["Article"],"doi":["10.1016/j.cor.2011.05.004"],"issn":["03050548"],"journaltitle":["Comput. Oper. Res."],"keywords":["Automated material handling systems","Comparative analysis","Computational requirements","Computer simulation","Decision support systems","Decision support tools","Design of experiments","Discrete events","Discrete-event simulation model","Generalization capability","Genetic programming","Industrial systems","Inventory models","Manufacture","Materials handling","Materials handling equipment","Meta model","Metamodel development","Metamodeling","Neural networks","notion","Semiconductor device manufacture","Semiconductor manufacturing","Serial production line","Stochastic models","Surrogate model","Symbolic regression","Validation test"],"note":["cited By 79 \n\ncited By 81"],"number":["2"],"pages":["424–436"],"source":["Scopus"],"title":["A comparison of genetic programming and artificial neural networks in metamodeling of discrete-event simulation models"],"volume":["39"]},"creators":{"author":[{"lastName":"Can","firstName":"B."},{"lastName":"Heavey","firstName":"C."}]},"sentenceCased":true},{"key":"candelUnifiedMetamodelNoSQL2021","type":"article","fields":{"abstract":["The Database field is undergoing significant changes. Although relational systems are still predominant, the interest in NoSQL systems is continuously increasing. In this scenario, polyglot persistence is envisioned as the database architecture to be prevalent in the future. Multi-model database tools normally use a generic or unified metamodel to represent schemas of the data model that they support. Such metamodels facilitate developing utilities, as they can be built on a common representation. Also, the number of mappings required to migrate databases from a data model to another is reduced, and integrability is favored. In this paper, we present the U-Schema unified metamodel able to represent logical schemas for the four most popular NoSQL paradigms (columnar, document, key-value, and graph) as well as relational schemas. We will formally define the mappings between U-Schema and the data model defined for each paradigm. How these mappings have been implemented and validated will be discussed, and some applications of U-Schema will be shown. To achieve flexibility to respond to data changes, most of NoSQL systems are \"schema-on-write,\" and the declaration of schemas is not required. Such an absence of schema declaration makes structural variability possible, i.e., stored data of the same entity type can have different structure. Moreover, data relationships supported by each data model are different. We will show how all these issues have been tackled in our approach. Our metamodel goes beyond the existing proposals by distinguishing entity types and relationship types, representing aggregation and reference relationships, and including the notion of structural variability. Our contributions also include developing schema extraction strategies for schemaless systems of each NoSQL data model, and tackling performance and scalability in the implementation for each store."],"author":["Candel, Carlos J. Fernández","Ruiz, Diego Sevilla","García-Molina, Jesús J."],"date":["2021-05-17"],"eprint":["2105.06494"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv210506494 Cs"],"keywords":["Computer Science - Databases"],"note":["Comment: 31 pages, 18 figures"],"title":["A Unified Metamodel for NoSQL and Relational Databases"],"url":["http://arxiv.org/abs/2105.06494"],"urldate":["2021-06-27"]},"creators":{"author":[{"lastName":"Candel","firstName":"Carlos J. Fernández"},{"lastName":"Ruiz","firstName":"Diego Sevilla"},{"lastName":"García-Molina","firstName":"Jesús J."}]}},{"key":"canoHybridRecommenderSystems2017","type":"article","fields":{"langid":["english"],"abstract":["Recommender systems are software tools used to generate and provide suggestions for items and other entities to the users by exploiting various strategies. Hybrid recommender systems combine two or more recommendation strategies in different ways to benefit from their complementary advantages. This systematic literature review presents the state of the art in hybrid recommender systems of the last decade. It is the first quantitative review work completely focused in hybrid recommenders. We address the most relevant problems considered and present the associated data mining and recommendation techniques used to overcome them. We also explore the hybridization classes each hybrid recommender belongs to, the application domains, the evaluation process and proposed future research directions. Based on our findings, most of the studies combine collaborative filtering with another technique often in a weighted way. Also cold-start and data sparsity are the two traditional and top problems being addressed in 23 and 22 studies each, while movies and movie datasets are still widely used by most of the authors. As most of the studies are evaluated by comparisons with similar methods using accuracy metrics, providing more credible and user oriented evaluations remains a typical challenge. Besides this, newer challenges were also identified such as responding to the variation of user context, evolving user tastes or providing cross-domain recommendations. Being a hot topic, hybrid recommenders represent a good basis with which to respond accordingly by exploring newer opportunities such as contextualizing recommendations, involving parallel hybrid algorithms, processing larger datasets, etc."],"author":["Çano, Erion","Morisio, Maurizio"],"date":["2017-11-15"],"doi":["10.3233/IDA-163209"],"issn":["1088467X, 15714128"],"journaltitle":["Intell. Data Anal."],"number":["6"],"pages":["1487–1524"],"shorttitle":["Hybrid recommender systems"],"title":["Hybrid recommender systems: A systematic literature review"],"volume":["21"]},"creators":{"author":[{"lastName":"Çano","firstName":"Erion"},{"lastName":"Morisio","firstName":"Maurizio"}]},"sentenceCased":true},{"key":"cao_adversarial_2020","type":"inproceedings","fields":{"langid":["english"],"abstract":["Adversarial attacks pose significant challenges for detecting adversarial attacks at an early stage. We propose attack-agnostic detection on reinforcement learning-based interactive recommendation systems. We first craft adversarial examples to show their diverse distributions and then augment recommendation systems by detecting potential attacks with a deep learning-based classifier based on the crafted data. Finally, we study the attack strength and frequency of adversarial examples and evaluate our model on standard datasets with multiple crafting methods. Our extensive experiments show that most adversarial attacks are effective, and both attack strength and attack frequency impact the attack performance. The strategically-timed attack achieves comparative attack performance with only 1/3 to 1/2 attack frequency. Besides, our black-box detector trained with one crafting method has the generalization ability over several crafting methods."],"author":["Cao, Yuanjiang","Chen, Xiaocong","Yao, Lina","Wang, Xianzhi","Zhang, Wei Emma"],"booktitle":["Proc. 43rd ACM SIGIR"],"date":["2020-07"],"doi":["10.1145/3397271.3401196"],"isbn":["978-1-4503-8016-4"],"location":["Virtual Event China"],"pages":["1669–1672"],"publisher":["ACM"],"title":["Adversarial Attacks and Detection on Reinforcement Learning-Based Interactive Recommender Systems"]},"creators":{"author":[{"lastName":"Cao","firstName":"Yuanjiang"},{"lastName":"Chen","firstName":"Xiaocong"},{"lastName":"Yao","firstName":"Lina"},{"lastName":"Wang","firstName":"Xianzhi"},{"lastName":"Zhang","firstName":"Wei Emma"}]}},{"key":"Cao2020","type":"inproceedings","fields":{"abstract":["How to predict the wireless network level performance such as the network capacity, the average user data rate, and the 5-tile user data rate is a million-dollar question. In the literature, some pioneering works have been proposed by exploiting either the information theoretic techniques on the physical layer (PHY) information or the Markov chain techniques on the multiple access control (MAC) layer information. However, since these mathematical model-driven approaches usually focus on a small part of the network structure, they cannot characterize the whole network performance. In this paper, we propose to utilize a data-driven machine learning approach to tackle this problem. More specifically, both PHY and MAC information is fed into a deep neural network (DNN) specifically designed for network-level performance prediction. Simulation results show that the network level performance can be accurately predicted at the cost of higher computational complexity. © 2020 IEEE."],"art_number":["9149189"],"author":["Cao, Q.","Zeng, S.","Pun, M.-O.","Chen, Y."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/ICC40277.2020.9149189"],"isbn":["978-1-72815-089-5"],"issn":["15503607"],"note":["cited By 0 \n\nTL;DR \n\nThis paper proposes to utilize a data-driven machine learning approach to tackle the wireless network level performance prediction by fed into a deep neural network specifically designed for network-level performance prediction."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["IEEE International Conference on Communications"],"source":["Scopus"],"title":["Network-level system performance prediction using deep neural networks with cross-layer information"],"volume":["2020-June"]},"creators":{"author":[{"lastName":"Cao","firstName":"Q."},{"lastName":"Zeng","firstName":"S."},{"lastName":"Pun","firstName":"M.-O."},{"lastName":"Chen","firstName":"Y."}]},"sentenceCased":true},{"key":"Cao2021","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Winter Simul. Conf."],"affiliation":["Centre for Operational Research, Management Science and Information Systems, University of Southampton, Southampton, SO17 1BJ, United Kingdom; PowerTrain Manufacturing Engineering, Ford Motor Company, Dunton Research Centre, Basildon, SS15 6EE, United Kingdom"],"author":["Cao, Y.","Currie, C.","Onggo, B.S.","Higgins, M."],"coden":["WSCPD"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/WSC52266.2021.9715498"],"isbn":["978-1-66543-311-2"],"issn":["08917736"],"keywords":["notion"],"note":["cited By 1"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - Winter Simulation Conference"],"source":["Scopus"],"title":["Simulation optimization for a digital twin using a multi-fidelity framework"],"volume":["2021-December"]},"creators":{"author":[{"lastName":"Cao","firstName":"Y."},{"lastName":"Currie","firstName":"C."},{"lastName":"Onggo","firstName":"B.S."},{"lastName":"Higgins","firstName":"M."}]},"sentenceCased":true},{"key":"cao2023study","type":"misc","fields":{"author":["Cao, Jialun","Li, Meiziniu","Wen, Ming","Cheung, Shing-chi"],"date":["2023"],"eprint":["2304.08191"],"eprintclass":["cs.SE"],"eprinttype":["arxiv"],"title":["A study on prompt design, advantages and limitations of ChatGPT for deep learning program repair"]},"creators":{"author":[{"lastName":"Cao","firstName":"Jialun"},{"lastName":"Li","firstName":"Meiziniu"},{"lastName":"Wen","firstName":"Ming"},{"lastName":"Cheung","firstName":"Shing-chi"}]},"sentenceCased":true},{"key":"Capiluppi:2019:JSS:Clustering","type":"article","fields":{"author":["Capiluppi, Andrea","Di Ruscio, Davide","Di Rocco, Juri","Nguyen, Phuong T.","Ajienka, Nemitari"],"date":["2019"],"journaltitle":["J. Syst. Softw."],"title":["The Effects of Clustering on the Characteristics of Java Software - manuscript under revision"]},"creators":{"author":[{"lastName":"Capiluppi","firstName":"Andrea"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Ajienka","firstName":"Nemitari"}]},"sentenceCased":true},{"key":"capiluppiDetectingJavaSoftware2019","type":"article","fields":{"langid":["english"],"abstract":["Research on empirical software engineering has increasingly been conducted by analysing and measuring vast amounts of software systems. Hundreds, thousands and even millions of systems have been (and are) considered by researchers, and often within the same study, in order to test theories, demonstrate approaches or run prediction models. A much less investigated aspect is whether the collected metrics might be context-specific, or whether systems should be better analysed in clusters."],"author":["Capiluppi, Andrea","Di Ruscio, Davide","Di Rocco, Juri","Nguyen, Phuong T","Ajienka, Nemitari"],"date":["2019"],"journaltitle":["Elsevier Inf. Softw. Technol. IST J."],"pages":["40"],"title":["Detecting Java Software Similarities by using Different Clustering Techniques"]},"creators":{"author":[{"lastName":"Capiluppi","firstName":"Andrea"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Nguyen","firstName":"Phuong T"},{"lastName":"Ajienka","firstName":"Nemitari"}]},"sentenceCased":true},{"key":"capiluppiDetectingJavaSoftware2020","type":"article","fields":{"author":["Capiluppi, Andrea","Di Ruscio, Davide","Di Rocco, Juri","Nguyen, Phuong T.","Ajienka, Nemitari"],"date":["2020"],"doi":["10.1016/j.infsof.2020.106279"],"ids":["capiluppiDetectingJavaSoftware2020a,capiluppiDetectingJavaSoftware2020b"],"journaltitle":["Inf. Softw. Technol."],"note":["cited By 6"],"title":["Detecting Java Software Similarities by using Different Clustering Techniques"]},"creators":{"author":[{"lastName":"Capiluppi","firstName":"Andrea"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Ajienka","firstName":"Nemitari"}]},"sentenceCased":true},{"key":"cardaioliItMatterStyle2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["Social bots are computer algorithms able to produce content and interact with other users on social media autonomously, trying to emulate and possibly influence humans’ behavior. Indeed, bots are largely employed for malicious purposes, like spreading disinformation and conditioning electoral campaigns. Nowadays, bots’ capability of emulating human behaviors has become increasingly sophisticated, making their detection harder. In this paper, we aim at recognizing bot-driven accounts by evaluating the consistency of users’ writing style over time. In particular, we leverage the intuition that while bots compose posts according to fairly deterministic processes, humans are influenced by subjective factors (e.g., emotions) that can alter their writing style. To verify this assumption, by using stylistic consistency indicators, we characterize the writing style of more than 12,000 among bot-driven and human-operated Twitter accounts and find that statistically significant differences can be observed between the different types of users. Thus, we evaluate the effectiveness of different machine learning (ML) algorithms based on stylistic consistency features in discerning between human-operated and bot-driven Twitter accounts and show that the experimented ML algorithms can achieve high performance (i.e., F-measure values up to 98%) in social bot detection tasks."],"author":["Cardaioli, Matteo","Conti, Mauro","Sorbo, Andrea Di","Fabrizio, Enrico","Laudanna, Sonia","Visaggio, Corrado A."],"booktitle":["2021 Int. Conf. Comput. Commun. Netw. 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ICMLA"],"date":["2020-12"],"doi":["10.1109/ICMLA51294.2020.00104"],"eventtitle":["2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA)"],"isbn":["978-1-72818-470-8"],"keywords":["LOGSEQ"],"location":["Miami, FL, USA"],"note":["TL;DR \n\nThis paper presents an approach, based on a simple API and set of tools, to monitor ML solutions, and indicates that the approach can deliver useful information to help in decision making, proper resource provision and operation of ML systems."],"pages":["626–633"],"publisher":["IEEE"],"title":["Benchmarking Machine Learning Solutions in Production"]},"creators":{"author":[{"lastName":"Cardoso Silva","firstName":"Lucas"},{"lastName":"Rezende Zagatti","firstName":"Fernando"},{"lastName":"Silva Sette","firstName":"Bruno"},{"lastName":"Nildaimon Dos Santos Silva","firstName":"Lucas"},{"lastName":"Lucredio","firstName":"Daniel"},{"lastName":"Furtado Silva","firstName":"Diego"},{"lastName":"De Medeiros Caseli","firstName":"Helena"}]}},{"key":"carletonAIEffectWorking2020","type":"article","fields":{"langid":["english"],"author":["Carleton, Anita D.","Harper, Erin","Menzies, Tim","Xie, Tao","Eldh, Sigrid","Lyu, Michael R."],"date":["2020-07"],"doi":["10.1109/MS.2020.2987666"],"ids":["carletonAIEffectWorking"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"number":["4"],"pages":["26–35"],"shorttitle":["The AI Effect"],"title":["The AI Effect: Working at the Intersection of AI and SE"],"volume":["37"]},"creators":{"author":[{"lastName":"Carleton","firstName":"Anita D."},{"lastName":"Harper","firstName":"Erin"},{"lastName":"Menzies","firstName":"Tim"},{"lastName":"Xie","firstName":"Tao"},{"lastName":"Eldh","firstName":"Sigrid"},{"lastName":"Lyu","firstName":"Michael R."}]}},{"key":"carpenterHandbookBrainTheory1998","type":"incollection","fields":{"acmid":["303586"],"author":["Carpenter, Gail A.","Grossberg, Stephen"],"chapter":["Adaptive Resonance Theory (ART)"],"date":["1998"],"editor":["Arbib, Michael A."],"isbn":["0-262-51102-9"],"location":["Cambridge, MA, USA"],"note":["TL;DR \n\nThe second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language and contains 287 articles, compared to the 266 in the first edition."],"numpages":["4"],"pages":["79–82"],"publisher":["MIT Press"],"title":["The handbook of brain theory and neural networks"],"url":["http://dl.acm.org/citation.cfm?id=303568.303586"]},"creators":{"author":[{"lastName":"Carpenter","firstName":"Gail A."},{"lastName":"Grossberg","firstName":"Stephen"}],"editor":[{"lastName":"Arbib","firstName":"Michael A."}]},"sentenceCased":true},{"key":"caruanaEmpiricalComparisonSupervised2006","type":"inproceedings","fields":{"langid":["english"],"abstract":["A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog Project in the early 90’s. We present a large-scale empirical comparison between ten supervised learning methods: SVMs, neural nets, logistic regression, naive bayes, memory-based learning, random forests, decision trees, bagged trees, boosted trees, and boosted stumps. We also examine the effect that calibrating the models via Platt Scaling and Isotonic Regression has on their performance. An important aspect of our study is the use of a variety of performance criteria to evaluate the learning methods."],"author":["Caruana, Rich","Niculescu-Mizil, Alexandru"],"booktitle":["Proc. 23rd Int. Conf. Mach. Learn. - ICML 06"],"date":["2006"],"doi":["10.1145/1143844.1143865"],"eventtitle":["The 23rd international conference"],"isbn":["978-1-59593-383-6"],"location":["Pittsburgh, Pennsylvania"],"note":["TL;DR \n\nA large-scale empirical comparison between ten supervised learning methods: SVMs, neural nets, logistic regression, naive bayes, memory-based learning, random forests, decision trees, bagged trees, boosted trees, and boosted stumps is presented."],"pages":["161–168"],"publisher":["ACM Press"],"title":["An empirical comparison of supervised learning algorithms"]},"creators":{"author":[{"lastName":"Caruana","firstName":"Rich"},{"lastName":"Niculescu-Mizil","firstName":"Alexandru"}]},"sentenceCased":true},{"key":"carverExtractingRequirementsModeling2021","type":"article","fields":{"langid":["english"],"abstract":["Presents papers from the 2020 IEEE Conference on Requirements Engineering and the ACM/ IEEE 23rd International Conference on Model Driven Engineering Languages and Systems (MODELS 2020)."],"author":["Carver, Jeffrey C.","Abrahao, Silvia","Penzenstadler, Birgit"],"date":["2021-05-01"],"doi":["10.1109/MS.2021.3056989"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"number":["03"],"pages":["121–124"],"publisher":["IEEE Computer Society"],"title":["Extracting Requirements and Modeling Information and Controlling Risk"],"volume":["38"]},"creators":{"author":[{"lastName":"Carver","firstName":"Jeffrey C."},{"lastName":"Abrahao","firstName":"Silvia"},{"lastName":"Penzenstadler","firstName":"Birgit"}]}},{"key":"carverIndustryAcademiaCollaboration2018","type":"article","fields":{"abstract":["This article aims to encourage more industry–academia collaborations by highlighting examples of successful collaborations. Through these examples, the authors hope to help practitioners and researchers understand the breadth of options available for such interactions. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Carver, J. C.","Prikladnicki, R."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571250"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"note":["TL;DR \n\nThis article aims to encourage more industry–academia collaborations by highlighting examples of successful collaborations and to help practitioners and researchers understand the breadth of options available for such interactions."],"number":["5"],"pages":["120–124"],"title":["Industry–Academia Collaboration in Software Engineering"],"volume":["35"]},"creators":{"author":[{"lastName":"Carver","firstName":"J. C."},{"lastName":"Prikladnicki","firstName":"R."}]}},{"key":"Casalaro202219","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Softw. Syst. Model."],"affiliation":["Department of Information Engineering, Computer Science and Mathematics, University of L’Aquila, L’Aquila, Italy; School of Innovation, Design and Engineering, Mälardalen University, Västerås, Sweden; Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Chair of Software Engineering, RWTH Aachen University, Aachen, Germany; Chalmers | University of Gothenburg, Gothenburg, Sweden; University of L’Aquila, L’Aquila, Italy"],"author":["Casalaro, G.L.","Cattivera, G.","Ciccozzi, F.","Malavolta, I.","Wortmann, A.","Pelliccione, P."],"correspondence_address1":["Ciccozzi, F.; School of Innovation, Sweden; email: federico.ciccozzi@mdh.se"],"date":["2022"],"document_type":["Article"],"doi":["10.1007/s10270-021-00908-8"],"issn":["16191366"],"journaltitle":["Softw. Syst. Model."],"note":["cited By 0"],"number":["1"],"pages":["19–49"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Model-driven engineering for mobile robotic systems: A systematic mapping study"],"volume":["21"]},"creators":{"author":[{"lastName":"Casalaro","firstName":"G.L."},{"lastName":"Cattivera","firstName":"G."},{"lastName":"Ciccozzi","firstName":"F."},{"lastName":"Malavolta","firstName":"I."},{"lastName":"Wortmann","firstName":"A."},{"lastName":"Pelliccione","firstName":"P."}]},"sentenceCased":true},{"key":"cassell_essential_2022","type":"book","fields":{"author":["Cassell, Catherine","Symon, Gillian"],"date":["2022-11"],"doi":["10.4135/9781446280119"],"location":["London"],"title":["Essential Guide to Qualitative Methods in Organizational Research"]},"creators":{"author":[{"lastName":"Cassell","firstName":"Catherine"},{"lastName":"Symon","firstName":"Gillian"}]}},{"key":"castanoExploringCarbonFootprint2023","type":"inproceedings","fields":{"abstract":["The rise of machine learning (ML) systems has exacerbated their carbon footprint due to increased capabilities and model sizes. However, there is scarce knowledge on how the carbon footprint of ML models is actually measured, reported, and evaluated. In light of this, the paper aims to analyze the measurement of the carbon footprint of 1,417 ML models and associated datasets on Hugging Face, which is the most popular repository for pretrained ML models. The goal is to provide insights and recommendations on how to report and optimize the carbon efficiency of ML models. The study includes the first repository mining study on the Hugging Face Hub API on carbon emissions. This study seeks to answer two research questions: (1) how do ML model creators measure and report carbon emissions on Hugging Face Hub?, and (2) what aspects impact the carbon emissions of training ML models? The study yielded several key findings. These include a stalled proportion of carbon emissions-reporting models, a slight decrease in reported carbon footprint on Hugging Face over the past 2 years, and a continued dominance of NLP as the main application domain. Furthermore, the study uncovers correlations between carbon emissions and various attributes such as model size, dataset size, and ML application domains. These results highlight the need for software measurements to improve energy reporting practices and promote carbon-efficient model development within the Hugging Face community. In response to this issue, two classifications are proposed: one for categorizing models based on their carbon emission reporting practices and another for their carbon efficiency. The aim of these classification proposals is to foster transparency and sustainable model development within the ML community."],"author":["Castaño, Joel","Martínez-Fernández, Silverio","Franch, Xavier","Bogner, Justus"],"booktitle":["2023 ACMIEEE Int. Symp. Empir. Softw. Eng. Meas. ESEM"],"date":["2023-10-26"],"doi":["10.1109/ESEM56168.2023.10304801"],"eprint":["2305.11164"],"eprintclass":["cs, stat"],"eprinttype":["arxiv"],"keywords":["Computer Science - Computers and Society","Computer Science - Information Retrieval","Computer Science - Machine Learning","Statistics - Machine Learning"],"note":["Comment: Accepted at the 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) \n\nTL;DR \n\nThis paper analyzes the measurement of the carbon footprint of 1,417 ML models and associated datasets on Hugging Face and proposes two classifications: one for categorizing models based on their carbon emission reporting practices and another for their carbon efficiency."],"pages":["1–12"],"shorttitle":["Exploring the Carbon Footprint of Hugging Face's ML Models"],"title":["Exploring the Carbon Footprint of Hugging Face's ML Models: A Repository Mining Study"]},"creators":{"author":[{"lastName":"Castaño","firstName":"Joel"},{"lastName":"Martínez-Fernández","firstName":"Silverio"},{"lastName":"Franch","firstName":"Xavier"},{"lastName":"Bogner","firstName":"Justus"}]}},{"key":"Castells_noveltyand","type":"inproceedings","fields":{"author":["Castells, Pablo","Vargas, Saúl"],"booktitle":["Proc. Int. Workshop Divers. Doc. Retr. DDR"],"citeulike-article-id":["9136077"],"ids":["Castells_novelty"],"keywords":["diversity","novelty","project-mavir","recommender","uam"],"pages":["29–37"],"posted-at":["2011-04-11 15:46:44"],"priority":["2"],"title":["Novelty and diversity metrics for recommender systems: Choice, discovery and relevance"]},"creators":{"author":[{"lastName":"Castells","firstName":"Pablo"},{"lastName":"Vargas","firstName":"Saúl"}]},"sentenceCased":true},{"key":"castelnovoResponsibleAIBanking","type":"article","fields":{"langid":["english"],"author":["Castelnovo, Alessandro"],"note":["TL;DR \n\nThis thesis embarks on a comprehensive exploration of bias and fairness, with a particular emphasis on their ramifications within the banking sector, where AI-driven decisions bear substantial societal consequences."],"title":["Towards Responsible AI in Banking: Addressing Bias for Fair Decision-Making"]},"creators":{"author":[{"lastName":"Castelnovo","firstName":"Alessandro"}]}},{"key":"castroRiseServerlessComputing2019","type":"article","fields":{"langid":["english"],"abstract":["The server is dead, long live the server."],"author":["Castro, Paul","Ishakian, Vatche","Muthusamy, Vinod","Slominski, Aleksander"],"date":["2019-11-21"],"doi":["10.1145/3368454"],"issn":["0001-0782, 1557-7317"],"journaltitle":["Commun. ACM"],"keywords":["LOGSEQ"],"number":["12"],"pages":["44–54"],"title":["The rise of serverless computing"],"volume":["62"]},"creators":{"author":[{"lastName":"Castro","firstName":"Paul"},{"lastName":"Ishakian","firstName":"Vatche"},{"lastName":"Muthusamy","firstName":"Vinod"},{"lastName":"Slominski","firstName":"Aleksander"}]},"sentenceCased":true},{"key":"CatedrasaesumuNoSQLDataEngineeringNoSQL","type":"online","fields":{"title":["Catedrasaes-umu/NoSQLDataEngineering: NoSQL Data Engineering"],"url":["https://github.com/catedrasaes-umu/NoSQLDataEngineering#schema-models"],"urldate":["2018-05-07"]},"creators":{},"sentenceCased":true},{"key":"cedeno-mielesDataAnalysisModeling2020","type":"article","fields":{"langid":["english"],"abstract":["There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments."],"author":["Cedeno-Mieles, Vanessa","Hu, Zhihao","Ren, Yihui","Deng, Xinwei","Contractor, Noshir","Ekanayake, Saliya","Epstein, Joshua M.","Goode, Brian J.","Korkmaz, Gizem","Kuhlman, Chris J.","Machi, Dustin","Macy, Michael","Marathe, Madhav V.","Ramakrishnan, Naren","Saraf, Parang","Self, Nathan"],"date":["2020-11-24"],"doi":["10.1371/journal.pone.0242453"],"editor":["Cai, Ning"],"issn":["1932-6203"],"journaltitle":["PLoS ONE"],"note":["TL;DR \n\nThis work describes the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses."],"number":["11"],"pages":["e0242453"],"title":["Data analysis and modeling pipelines for controlled networked social science experiments"],"volume":["15"]},"creators":{"author":[{"lastName":"Cedeno-Mieles","firstName":"Vanessa"},{"lastName":"Hu","firstName":"Zhihao"},{"lastName":"Ren","firstName":"Yihui"},{"lastName":"Deng","firstName":"Xinwei"},{"lastName":"Contractor","firstName":"Noshir"},{"lastName":"Ekanayake","firstName":"Saliya"},{"lastName":"Epstein","firstName":"Joshua M."},{"lastName":"Goode","firstName":"Brian J."},{"lastName":"Korkmaz","firstName":"Gizem"},{"lastName":"Kuhlman","firstName":"Chris J."},{"lastName":"Machi","firstName":"Dustin"},{"lastName":"Macy","firstName":"Michael"},{"lastName":"Marathe","firstName":"Madhav V."},{"lastName":"Ramakrishnan","firstName":"Naren"},{"lastName":"Saraf","firstName":"Parang"},{"lastName":"Self","firstName":"Nathan"}],"editor":[{"lastName":"Cai","firstName":"Ning"}]},"sentenceCased":true},{"key":"celebiFAIRProtocolsWorkflows2020","type":"article","fields":{"langid":["english"],"abstract":["It is essential for the advancement of science that researchers share, reuse and reproduce each other’s workflows and protocols. The FAIR principles are a set of guidelines that aim to maximize the value and usefulness of research data, and emphasize the importance of making digital objects findable and reusable by others. The question of how to apply these principles not just to data but also to the workflows and protocols that consume and produce them is still under debate and poses a number of challenges. In this paper we describe a two-fold approach of simultaneously applying the FAIR principles to scientific workflows as well as the involved data. We apply and evaluate our approach on the case of the PREDICT workflow, a highly cited drug repurposing workflow. This includes FAIRification of the involved datasets, as well as applying semantic technologies to represent and store data about the detailed versions of the general protocol, of the concrete workflow instructions, and of their execution traces. We propose a semantic model to address these specific requirements and was evaluated by answering competency questions. This semantic model consists of classes and relations from a number of existing ontologies, including Workflow4ever, PROV, EDAM, and BPMN. This allowed us then to formulate and answer new kinds of competency questions. Our evaluation shows the high degree to which our FAIRified OpenPREDICT workflow now adheres to the FAIR principles and the practicality and usefulness of being able to answer our new competency questions."],"author":["Celebi, Remzi","Rebelo Moreira, Joao","Hassan, Ahmed A.","Ayyar, Sandeep","Ridder, Lars","Kuhn, Tobias","Dumontier, Michel"],"date":["2020-09-21"],"doi":["10.7717/peerj-cs.281"],"issn":["2376-5992"],"journaltitle":["PeerJ Comput. Sci."],"note":["TL;DR \n\nThis paper describes a two-fold approach of simultaneously applying the FAIR principles to scientific workflows as well as the involved data, and proposes a semantic model to address these specific requirements."],"pages":["e281"],"shorttitle":["Towards FAIR protocols and workflows"],"title":["Towards FAIR protocols and workflows: The OpenPREDICT use case"],"volume":["6"]},"creators":{"author":[{"lastName":"Celebi","firstName":"Remzi"},{"lastName":"Rebelo Moreira","firstName":"Joao"},{"lastName":"Hassan","firstName":"Ahmed A."},{"lastName":"Ayyar","firstName":"Sandeep"},{"lastName":"Ridder","firstName":"Lars"},{"lastName":"Kuhn","firstName":"Tobias"},{"lastName":"Dumontier","firstName":"Michel"}]},"sentenceCased":true},{"key":"celisseOptimalCrossvalidationDensity2014","type":"article","fields":{"author":["Celisse, Alain"],"date":["2014-10-01"],"doi":["10.1214/14-AOS1240"],"issn":["0090-5364"],"journaltitle":["Ann. Statist."],"number":["5"],"title":["Optimal cross-validation in density estimation with the $L ̂{2}$-Loss"],"volume":["42"]},"creators":{"author":[{"lastName":"Celisse","firstName":"Alain"}]},"sentenceCased":true},{"key":"Celms2020205","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Commun. Comput. Info. Sci."],"affiliation":["Institute of Mathematics and Computer Science, University of Latvia, Riga, Latvia; Innovation Labs LETA, Riga, Latvia"],"author":["Celms, E.","Barzdins, J.","Kalnins, A.","Sprogis, A.","Grasmanis, M.","Rikacovs, S.","Barzdins, P."],"correspondence_address1":["Celms, E.; Institute of Mathematics and Computer Science, Latvia; email: edgars.celms@lumii.lv"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-57672-1_16"],"editor":["Robal T., Haav H.-M., Matulevicius R., Penjam J."],"isbn":["9783030576714"],"issn":["18650929"],"journaltitle":["Commun. Comput. Inf. Sci."],"note":["cited By 2"],"pages":["205–218"],"publisher":["Springer"],"source":["Scopus"],"title":["Towards dsl for dl lifecycle data management"],"volume":["1243 CCIS"]},"creators":{"author":[{"lastName":"Celms","firstName":"E."},{"lastName":"Barzdins","firstName":"J."},{"lastName":"Kalnins","firstName":"A."},{"lastName":"Sprogis","firstName":"A."},{"lastName":"Grasmanis","firstName":"M."},{"lastName":"Rikacovs","firstName":"S."},{"lastName":"Barzdins","firstName":"P."}],"editor":[{"lastName":"Robal T.","suffix":"Haav H.-M.","firstName":"Matulevicius R., Penjam J."}]},"sentenceCased":true},{"key":"Celms2021597","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Baltic J. Mod. Comp."],"affiliation":["Institute of Mathematics and Computer Science, University of Latvia, Raiņa bulvaris 29, Riga, LV-1459, Latvia; Innovation Labs LETA, Latvia, Riga, Marijas iela 2, Riga, LV 1050, Latvia"],"author":["Celms, E.","Barzdins, J.","Kalnins, A.","Barzdins, P.","Sprogis, A.","Grasmanis, M.","Rikacovs, S."],"date":["2021"],"document_type":["Article"],"doi":["10.22364/BJMC.2020.8.4.09"],"issn":["22558942"],"journaltitle":["Balt. J. Mod. Comput."],"note":["cited By 1"],"number":["4"],"pages":["597–617"],"publisher":["University of Latvia"],"source":["Scopus"],"title":["DSL approach to deep learning lifecycle data management"],"volume":["8"]},"creators":{"author":[{"lastName":"Celms","firstName":"E."},{"lastName":"Barzdins","firstName":"J."},{"lastName":"Kalnins","firstName":"A."},{"lastName":"Barzdins","firstName":"P."},{"lastName":"Sprogis","firstName":"A."},{"lastName":"Grasmanis","firstName":"M."},{"lastName":"Rikacovs","firstName":"S."}]},"sentenceCased":true},{"key":"CEURWorkshopProceedings2015","type":"book","fields":{"date":["2015"],"publisher":["CEUR-WS"],"title":["CEUR Workshop Proceedings"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992533486&partnerID=40&md5=bd42da7c52ba8ecd02ca81bcc01132c9"],"volume":["1406"]},"creators":{}},{"key":"chaaben2023towards","type":"inproceedings","fields":{"langid":["english"],"author":["Chaaben, Meriem Ben","Burgueño, Lola","Sahraoui, Houari"],"booktitle":["2023 IEEEACM 45th Int. Conf. Softw. Eng. New Ideas Emerg. Results ICSE-NIER"],"date":["2023"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["7–12"],"title":["Towards using few-shot prompt learning for automating model completion"]},"creators":{"author":[{"lastName":"Chaaben","firstName":"Meriem Ben"},{"lastName":"Burgueño","firstName":"Lola"},{"lastName":"Sahraoui","firstName":"Houari"}]},"sentenceCased":true},{"key":"Chabanet2021","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Comput Ind"],"affiliation":["Université de Lorraine, CNRS, CRAN, Epinal, F-88000, France"],"art_number":["103529"],"author":["Chabanet, S.","Bril El-Haouzi, H.","Thomas, P."],"coden":["CINUD"],"correspondence_address1":["Chabanet, S.; Université de Lorraine, France; email: sylvain.chabanet@univ-lorraine.fr"],"date":["2021"],"document_type":["Article"],"doi":["10.1016/j.compind.2021.103529"],"issn":["01663615"],"journaltitle":["Comput. Ind."],"keywords":["notion"],"note":["cited By 3"],"publisher":["Elsevier B.V."],"source":["Scopus"],"title":["Coupling digital simulation and machine learning metamodel through an active learning approach in Industry 4.0 context"],"volume":["133"]},"creators":{"author":[{"lastName":"Chabanet","firstName":"S."},{"lastName":"Bril El-Haouzi","firstName":"H."},{"lastName":"Thomas","firstName":"P."}]},"sentenceCased":true},{"key":"Chabanet2021573","type":"article","fields":{"langid":["english"],"abbrev_source_title":["IFIP Advances in Information and Communication Technology"],"affiliation":["Université de Lorraine, CNRS, CRAN, Epinal, 88000, France"],"author":["Chabanet, S.","Chazelle, V.","Thomas, P.","El-Haouzi, H.B."],"correspondence_address1":["Chabanet, S.; Université de Lorraine, France; email: sylvain.chabanet@univ-lorraine.fr"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-85906-0_62"],"editor":["Dolgui A., Bernard A., von Cieminski G., Romero D., Lemoine D."],"isbn":["9783030859053"],"issn":["18684238"],"journaltitle":["IFIP Adv. Inf. Commun. Technol."],"note":["cited By 0"],"pages":["573–581"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Dissimilarity to class medoids as features for 3D point cloud classification"],"volume":["632 IFIP"]},"creators":{"author":[{"lastName":"Chabanet","firstName":"S."},{"lastName":"Chazelle","firstName":"V."},{"lastName":"Thomas","firstName":"P."},{"lastName":"El-Haouzi","firstName":"H.B."}],"editor":[{"lastName":"Dolgui A.","suffix":"Bernard A.","firstName":"von Cieminski G., Romero D., Lemoine D."}]},"sentenceCased":true},{"key":"Chai2022","type":"article","fields":{"abstract":["Machine learning(ML) has widespread applications and has revolutionized many industries, but suffers from several challenges. First, sufficient high-quality training data is inevitable for producing a well-performed model, but the data is always human expensive to acquire.Second, a large amount of training data and complicated model structures lead to the inefficiency of training and inference. Third, given an ML task, one always needs to train lots of models, which are hard to manage in real applications. Fortunately, database techniques can benefit ML by addressing the above three challenges. In this paper, we review existing studies from the following three aspects along with the pipeline highly related to ML. (1) Data preparation(Pre-ML): it focuses on preparing high-quality training data that can improve the performance of the ML model, where we review data discovery, data cleaning and data labeling. (2) Model training &amp; inference(In-ML): researchers in ML community focus on improving the model performance during training, while in this survey we mainly study how to accelerate the entire training process, also including feature selection and model selection. (3) Model management(Post-ML): in this part, we survey how to store, query, deploy and debug the models after training. Finally, we provide research challenges and future directions. IEEE"],"author":["Chai, C.","Wang, J.","Luo, Y.","Niu, Z.","Li, G."],"coden":["ITKEE"],"date":["2022"],"document_type":["Article"],"doi":["10.1109/TKDE.2022.3148237"],"issn":["10414347"],"journaltitle":["IEEE Trans. Knowl. Data Eng."],"keywords":["GOAL_MDE4AI"],"note":["cited By 0 \n\nTL;DR \n\nThis paper reviews existing studies from the following three aspects along with the pipeline highly related to ML, and surveys how to store, query, deploy and debug the models after training."],"publisher":["IEEE Computer Society"],"source":["Scopus"],"title":["Data management for machine learning: A survey"]},"creators":{"author":[{"lastName":"Chai","firstName":"C."},{"lastName":"Wang","firstName":"J."},{"lastName":"Luo","firstName":"Y."},{"lastName":"Niu","firstName":"Z."},{"lastName":"Li","firstName":"G."}]},"sentenceCased":true},{"key":"ChakrabortyM0M20","type":"inproceedings","fields":{"author":["Chakraborty, Joymallya","Majumder, Suvodeep","Yu, Zhe","Menzies, Tim"],"booktitle":["ESECFSE 20 28th ACM Jt. Eur. Softw. Eng. Conf. Symp. Found. Softw. Eng. Virtual Event USA Novemb. 8-13 2020"],"date":["2020"],"note":["TL;DR \n\nThis work explains how ground-truth bias in training data affects machine learning model fairness and how to find that bias in AI software, and proposes a method Fairway which combines pre-processing and in-processing approach to remove ethical bias from training data and trained model."],"pages":["654–665"],"publisher":["ACM"],"title":["Fairway: A way to build fair ML software"]},"creators":{"author":[{"lastName":"Chakraborty","firstName":"Joymallya"},{"lastName":"Majumder","firstName":"Suvodeep"},{"lastName":"Yu","firstName":"Zhe"},{"lastName":"Menzies","firstName":"Tim"}]},"sentenceCased":true},{"key":"ChakrabortyMM21","type":"inproceedings","fields":{"author":["Chakraborty, Joymallya","Majumder, Suvodeep","Menzies, Tim"],"booktitle":["ESECFSE 21 29th ACM Jt. Eur. Softw. Eng. Conf. Symp. Found. Softw. Eng. Athens Greece August 23-28 2021"],"date":["2021"],"pages":["429–440"],"publisher":["ACM"],"title":["Bias in machine learning software: Why? How? What to do?"]},"creators":{"author":[{"lastName":"Chakraborty","firstName":"Joymallya"},{"lastName":"Majumder","firstName":"Suvodeep"},{"lastName":"Menzies","firstName":"Tim"}]},"sentenceCased":true},{"key":"ChakrabortyPM20","type":"inproceedings","fields":{"author":["Chakraborty, Joymallya","Peng, Kewen","Menzies, Tim"],"booktitle":["35th IEEEACM Int. Conf. Autom. Softw. Eng. ASE 2020 Melb. Aust. Sept. 21-25 2020"],"date":["2020"],"note":["TL;DR \n\nThis work shows how the proposed method based on K nearest neighbors can overcome shortcomings and find the underlying bias of black box models and describes the future framework combining explanation and planning to build fair software."],"pages":["1229–1233"],"publisher":["IEEE"],"title":["Making fair ML software using trustworthy explanation"]},"creators":{"author":[{"lastName":"Chakraborty","firstName":"Joymallya"},{"lastName":"Peng","firstName":"Kewen"},{"lastName":"Menzies","firstName":"Tim"}]},"sentenceCased":true},{"key":"chatgpt","type":"misc","fields":{"title":["ChatGPT <span class=\"nocase\">https://openai.com/blog/chatgpt</span>"]},"creators":{}},{"key":"Chatzimparmpas20211","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - Int. Conf. Control Syst. Comput. Sci. Technol., CSCS"],"affiliation":["Linnaeus University, Department of Computer Science and Media Technology, Växjö, Sweden; Department of Computer Science and Media Technology, Linnaeus University, Växjö, Sweden; Department of Science and Technology, Linköping University, Norrköping, Sweden"],"art_number":["9481023"],"author":["Chatzimparmpas, A.","Martins, R.M.","Kucher, K.","Kerren, A."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/CSCS52396.2021.00008"],"isbn":["978-1-66543-939-8"],"note":["cited By 4"],"pages":["1–8"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2021 23rd International Conference on Control Systems and Computer Science Technologies, CSCS 2021"],"source":["Scopus"],"title":["Empirical study: Visual analytics for comparing stacking to blending ensemble learning"]},"creators":{"author":[{"lastName":"Chatzimparmpas","firstName":"A."},{"lastName":"Martins","firstName":"R.M."},{"lastName":"Kucher","firstName":"K."},{"lastName":"Kerren","firstName":"A."}]},"sentenceCased":true},{"key":"Chatzimparmpas20211547","type":"article","fields":{"langid":["english"],"abbrev_source_title":["IEEE Trans Visual Comput Graphics"],"affiliation":["Linnaeus University, Växjö, Sweden"],"art_number":["9222343"],"author":["Chatzimparmpas, A.","Martins, R.M.","Kucher, K.","Kerren, A."],"coden":["ITVGE"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/TVCG.2020.3030352"],"issn":["10772626"],"journaltitle":["IEEE Trans. Vis. Comput. Graph."],"note":["cited By 13 \n\nTL;DR \n\nA knowledge generation model, which supports ensemble learning with the use of visualization, and a visual analytics system for stacked generalization, which helps users to decide between distinct models and to reduce the complexity of the resulting stack by removing overpromising and underperforming models."],"number":["2"],"pages":["1547–1557"],"publisher":["IEEE Computer Society"],"pubmed_id":["33048687"],"source":["Scopus"],"title":["StackGenVis: Alignment of data, algorithms, and models for stacking ensemble learning using performance metrics"],"volume":["27"]},"creators":{"author":[{"lastName":"Chatzimparmpas","firstName":"A."},{"lastName":"Martins","firstName":"R.M."},{"lastName":"Kucher","firstName":"K."},{"lastName":"Kerren","firstName":"A."}]},"sentenceCased":true},{"key":"Chatzimparmpas2022161","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["IEEE Pacific Visual. Symp."],"affiliation":["Linnaeus University, Linköping University, Sweden"],"author":["Chatzimparmpas, A.","Park, V.","Kerren, A."],"correspondence_address1":["Chatzimparmpas, A.; Linnaeus University, Sweden; email: angelos.chatzimparmpas@lnu.se"],"date":["2022"],"document_type":["Conference Paper"],"doi":["10.1109/PacificVis53943.2022.00025"],"isbn":["978-1-66542-335-9"],"issn":["21658765"],"note":["cited By 0 \n\nTL;DR \n\nThe results indicate that StackGen Vis is significantly more powerful than OVS based on the qualitative feedback provided by the participants, and the average completion time for all tasks was comparable between both tools."],"pages":["161–165"],"publisher":["IEEE Computer Society"],"series":["IEEE Pacific Visualization Symposium"],"source":["Scopus"],"title":["Evaluating StackGenVis with a comparative user study"],"volume":["2022-April"]},"creators":{"author":[{"lastName":"Chatzimparmpas","firstName":"A."},{"lastName":"Park","firstName":"V."},{"lastName":"Kerren","firstName":"A."}]},"sentenceCased":true},{"key":"chaudronProceedings40thInternational2018","type":"book","fields":{"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/conf/icse/2018"],"date":["2018"],"doi":["10.1145/3180155"],"editor":["Chaudron, Michel","Crnkovic, Ivica","Chechik, Marsha","Harman, Mark"],"isbn":["978-1-4503-5638-1"],"publisher":["ACM"],"timestamp":["Wed, 21 Nov 2018 12:43:58 +0100"],"title":["Proceedings of the 40th international conference on software engineering, ICSE 2018, gothenburg, sweden, may 27 - june 03, 2018"]},"creators":{"editor":[{"lastName":"Chaudron","firstName":"Michel"},{"lastName":"Crnkovic","firstName":"Ivica"},{"lastName":"Chechik","firstName":"Marsha"},{"lastName":"Harman","firstName":"Mark"}]},"sentenceCased":true},{"key":"chen_adversarial_2017","type":"inproceedings","fields":{"abstract":["Since malware has caused serious damages and evolving threats to computer and Internet users, its detection is of great interest to both anti-malware industry and researchers. In recent years, machine learning-based systems have been successfully deployed in malware detection, in which different kinds of classifiers are built based on the training samples using different feature representations. Unfortunately, as classifiers become more widely deployed, the incentive for defeating them increases. In this paper, we explore the adversarial machine learning in malware detection. In particular, on the basis of a learning-based classifier with the input of Windows Application Programming Interface (API) calls extracted from the Portable Executable (PE) files, we present an effective evasion attack model (named EvnAttack) by considering different contributions of the features to the classification problem. To be resilient against the evasion attack, we further propose a secure-learning paradigm for malware detection (named SecDefender), which not only adopts classifier retraining technique but also introduces the security regularization term which considers the evasion cost of feature manipulations by attackers to enhance the system security. Comprehensive experimental results on the real sample collections from Comodo Cloud Security Center demonstrate the effectiveness of our proposed methods."],"author":["Chen, L.","Ye, Y.","Bourlai, T."],"booktitle":["2017 Eur. Intell. Secur. Inform. Conf. EISIC"],"date":["2017-09"],"doi":["10.1109/EISIC.2017.21"],"keywords":["Adversarial Machine Learning","Computer security","Data mining","Data models","Evasion Attack and Defense","Feature extraction","Malware","Malware Detection"],"note":["00048"],"pages":["99–106"],"shorttitle":["Adversarial Machine Learning in Malware Detection"],"title":["Adversarial Machine Learning in Malware Detection: Arms Race between Evasion Attack and Defense"]},"creators":{"author":[{"lastName":"Chen","firstName":"L."},{"lastName":"Ye","firstName":"Y."},{"lastName":"Bourlai","firstName":"T."}]}},{"key":"Chen:2005:CCF:2154509.2154540","type":"inproceedings","fields":{"acmid":["2154540"],"author":["Chen, Annie"],"booktitle":["Proc. First Int. Conf. Locat. Context-Aware."],"date":["2005"],"isbn":["3-540-25896-5 978-3-540-25896-4"],"location":["Berlin, Heidelberg"],"nodoi":["10.1007/11426646₂3"],"note":["TL;DR \n\nA context-aware collaborative filtering system that predicts a user's preference in different context situations based on past experiences and can help predict the user's behavior in different situations without the user actively defining it is presented."],"numpages":["10"],"pages":["244–253"],"publisher":["Springer-Verlag"],"series":["LoCA'05"],"title":["Context-aware collaborative filtering system: Predicting the user's preference in the ubiquitous computing environment"],"url":["http://dx.doi.org/10.1007/11426646_23"]},"creators":{"author":[{"lastName":"Chen","firstName":"Annie"}]},"sentenceCased":true},{"key":"Chen20191901","type":"inproceedings","fields":{"abstract":["A broad range of cross-m-domain generation researches boil down to matching a joint distribution by deep generative models (DGMs). Hitherto algorithms excel in pairwise domains while as m increases, remain struggling to scale themselves to fit a joint distribution. In this paper, we propose a domain-scalable DGM, i.e., MMI-ALI for m-domain joint distribution matching. As an m-domain ensemble model of ALIs (Dumoulin et al., 2016), MMI-ALI is adversarially trained with maximizing Multivariate Mutual Information (MMI) w.r.t. joint variables of each pair of domains and their shared feature. The negative MMIs are upper bounded by a series of feasible losses that provably lead to matching m-domain joint distributions. MMI-ALI linearly scales as m increases and thus, strikes a right balance between efficacy and scalability. We evaluate MMI-ALI in diverse challenging m-domain scenarios and verify its superiority. © 2019 by the Author(S)."],"author":["Chen, Z.","Yang, Z.","Wang, X.","Liang, X.","Yan, X.","Li, G.","Lin, L."],"date":["2019"],"document_type":["Conference Paper"],"isbn":["978-1-5108-8698-8"],"keywords":["Artificial intelligence","Ensemble modeling","Generative model","Joint distributions","Machine learning","Multivariate mutual information","Software engineering"],"note":["cited By 0 \n\nTL;DR \n\nA domain-scalable DGM, i.e., MMI-ALI for $m-domain joint distribution matching, which linearly scales as $m$ increases and thus, strikes a right balance between efficacy and scalability."],"pages":["1901–1910"],"publisher":["International Machine Learning Society (IMLS)"],"series":["36th International Conference on Machine Learning, ICML 2019"],"source":["Scopus"],"title":["Multivariate-information adversarial ensemble for scalable joint distribution matching"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078043028&partnerID=40&md5=0e04ea8110817d757bfa4fdda4d16605"],"volume":["2019-June"]},"creators":{"author":[{"lastName":"Chen","firstName":"Z."},{"lastName":"Yang","firstName":"Z."},{"lastName":"Wang","firstName":"X."},{"lastName":"Liang","firstName":"X."},{"lastName":"Yan","firstName":"X."},{"lastName":"Li","firstName":"G."},{"lastName":"Lin","firstName":"L."}]},"sentenceCased":true},{"key":"Chen201978","type":"inproceedings","fields":{"abstract":["Software systems assisted with deep neural networks (DNNs) are gaining increasing popularities. However, one outstanding problem is to judge whether a given application scenario suits a DNN model, whose answer highly affects its concerned system's performance. Existing work indirectly addressed this problem by seeking for higher test coverage or generating adversarial inputs. One pioneering work is SynEva, which exactly addressed this problem by synthesizing mirror programs for scenario suitableness evaluation of general machine learning programs, but fell short in supporting DNN models. In this paper, we propose VISION to eValuatIng Scenario suItableness fOr DNN models, specially catered for DNN characteristics. We conducted experiments on a real-world self-driving dataset Udacity, and the results show that VISION was effective in evaluating scenario suitableness for DNN models with an accuracy of 75.6-89.0% as compared to that of SynEva, 50.0-81.8%. We also explored different meta-models in VISION, and found out that the decision tree logic learner meta-model could be the best one for balancing VISION's effectiveness and efficiency. © 2019 IEEE."],"art_number":["8945698"],"author":["Chen, Z.","Wang, H.","Xu, C.","Ma, X.","Cao, C."],"author_keywords":["DNN model; mirror synthesis; scenario suitableness evaluation"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/APSEC48747.2019.00020"],"isbn":["978-1-72814-648-5"],"issn":["15301362"],"keywords":["Application scenario","Balancing","Decision tree logic","Decision trees","Deep neural networks","Effectiveness and efficiencies","Mirror synthesis","Mirrors","scenario suitableness evaluation","Software engineering","Software systems","System's performance","Test coverage"],"note":["cited By 1"],"pages":["78–85"],"publisher":["IEEE Computer Society"],"series":["Proceedings - Asia-Pacific Software Engineering Conference, APSEC"],"source":["Scopus"],"title":["VISION: Evaluating scenario suitableness for DNN models by mirror synthesis"],"volume":["2019-December"]},"creators":{"author":[{"lastName":"Chen","firstName":"Z."},{"lastName":"Wang","firstName":"H."},{"lastName":"Xu","firstName":"C."},{"lastName":"Ma","firstName":"X."},{"lastName":"Cao","firstName":"C."}]},"sentenceCased":true},{"key":"chen2023automated","type":"inproceedings","fields":{"langid":["english"],"author":["Chen, Kua","Yang, Yujing","Chen, Boqi","López, José Antonio Hernández","Mussbacher, Gunter","Varró, Dániel"],"booktitle":["2023 ACMIEEE 26th Int. Conf. Model Driven Eng. Lang. Syst. MODELS"],"date":["2023"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["162–172"],"publisher":["IEEE"],"title":["Automated domain modeling with large language models: A comparative study"]},"creators":{"author":[{"lastName":"Chen","firstName":"Kua"},{"lastName":"Yang","firstName":"Yujing"},{"lastName":"Chen","firstName":"Boqi"},{"lastName":"López","firstName":"José Antonio Hernández"},{"lastName":"Mussbacher","firstName":"Gunter"},{"lastName":"Varró","firstName":"Dániel"}]},"sentenceCased":true},{"key":"chen2023ontheuse","type":"inproceedings","fields":{"langid":["english"],"author":["Chen, Boqi","Chen, Kua","Hassani, Shabnam","Yang, Yujing","Amyot, Daniel","Lessard, Lysanne","Mussbacher, Gunter","Sabetzadeh, Mehrdad","Varró, Dániel"],"booktitle":["2023 IEEE 31st Int. Requir. Eng. Conf. Workshop REW"],"date":["2023"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["262–271"],"title":["On the use of GPT-4 for creating goal models: An exploratory study"]},"creators":{"author":[{"lastName":"Chen","firstName":"Boqi"},{"lastName":"Chen","firstName":"Kua"},{"lastName":"Hassani","firstName":"Shabnam"},{"lastName":"Yang","firstName":"Yujing"},{"lastName":"Amyot","firstName":"Daniel"},{"lastName":"Lessard","firstName":"Lysanne"},{"lastName":"Mussbacher","firstName":"Gunter"},{"lastName":"Sabetzadeh","firstName":"Mehrdad"},{"lastName":"Varró","firstName":"Dániel"}]},"sentenceCased":true},{"key":"chenFairnessTestingComprehensive2022","type":"online","fields":{"abstract":["Software systems are vulnerable to fairness bugs and frequently exhibit unfair behaviors, making software fairness an increasingly important concern for software engineers. Research has focused on helping software engineers to detect fairness bugs automatically. This paper provides a comprehensive survey of existing research on fairness testing. We collect 122 papers and organise them based on the testing workflow (i.e., the testing activities) and the testing components (i.e., where to find fairness bugs) for conducting fairness testing. We also analyze the research focus, trends, promising directions, as well as widely-adopted datasets and open source tools for fairness testing."],"author":["Chen, Zhenpeng","Zhang, Jie M.","Hort, Max","Sarro, Federica","Harman, Mark"],"date":["2022-08-05"],"eprint":["2207.10223"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Software Engineering","LOGSEQ"],"note":["TL;DR \n\nA comprehensive survey of existing studies in fairness testing of ML software is offered, and the research focus, trends, and promising directions in the realm of fairness testing are analyzed."],"pubstate":["preprint"],"shorttitle":["Fairness Testing"],"title":["Fairness Testing: A Comprehensive Survey and Analysis of Trends"],"url":["http://arxiv.org/abs/2207.10223"],"urldate":["2023-03-09"]},"creators":{"author":[{"lastName":"Chen","firstName":"Zhenpeng"},{"lastName":"Zhang","firstName":"Jie M."},{"lastName":"Hort","firstName":"Max"},{"lastName":"Sarro","firstName":"Federica"},{"lastName":"Harman","firstName":"Mark"}]}},{"key":"Cheng2019472","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Xi’an Shiyou University, Shaanxi, China; Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, China; Deakin University, Geelong, Australia; University of Connecticut, Storrs, CT, United States"],"author":["Cheng, X.","Luo, W.","Gan, G.","Li, G."],"correspondence_address1":["Luo, W.; Deakin UniversityAustralia; email: wei.luo@deakin.edu.au"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-29551-6_42"],"editor":["Douligeris C., Apostolou D., Karagiannis D."],"isbn":["9783030295509"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 3 \n\nTL;DR \n\nA novel and highly effective method for selecting representative contracts using a deep neighbor embedding that supports robust clustering of the contracts in a portfolio and achieves significant improvement in valuation accuracy."],"pages":["472–480"],"publisher":["Springer"],"source":["Scopus"],"title":["Deep neighbor embedding for evaluation of large portfolios of variable annuities"],"volume":["11775 LNAI"]},"creators":{"author":[{"lastName":"Cheng","firstName":"X."},{"lastName":"Luo","firstName":"W."},{"lastName":"Gan","firstName":"G."},{"lastName":"Li","firstName":"G."}],"editor":[{"lastName":"Douligeris C.","suffix":"Apostolou D.","firstName":"Karagiannis D."}]},"sentenceCased":true},{"key":"chengSoftwareEngineeringSelfadaptive2009","type":"book","fields":{"date":["2009"],"editor":["Cheng, Betty H. C."],"isbn":["978-3-642-02160-2"],"location":["Berlin ; New York"],"number":["5525"],"pagetotal":["260"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"title":["Software engineering for self-adaptive systems"]},"creators":{"editor":[{"lastName":"Cheng","firstName":"Betty H. C."}]},"sentenceCased":true},{"key":"chenouardAutomaticallyDiscoveringHidden2009","type":"article","fields":{"author":["Chenouard, Raphaël","Jouault, Frédéric"],"date":["2009"],"doi":["10.1007/978-3-642-04425-0_8"],"journaltitle":["Model Driven Eng. Lang. Syst."],"pages":["92–106"],"title":["Automatically Discovering Hidden Transformation Chaining Constraints"],"volume":["5795"]},"creators":{"author":[{"lastName":"Chenouard","firstName":"Raphaël"},{"lastName":"Jouault","firstName":"Frédéric"}]}},{"key":"chenSimAppFrameworkDetecting2015","type":"inproceedings","fields":{"langid":["english"],"acmid":["2685305"],"author":["Chen, Ning","Hoi, Steven C.H.","Li, Shaohua","Xiao, Xiaokui"],"date":["2015"],"doi":["10.1145/2684822.2685305"],"ids":["Chen:2015:SFD:2684822.2685305"],"isbn":["978-1-4503-3317-7"],"keywords":["mobile applications","multi-modal data","multiple kernels","online kernel learning","similarity function"],"location":["Shanghai, China"],"nodoi":["10.1145/2684822.2685305"],"note":["TL;DR \n\nThis paper explores multi-modal heterogeneous data in app markets (e.g., description text, images, user reviews, etc.), and presents \"SimApp\" – a novel framework for detecting similar apps using machine learning."],"numpages":["10"],"pages":["305–314"],"publisher":["ACM Press"],"shorttitle":["SimApp"],"title":["SimApp: A Framework for Detecting Similar Mobile Applications by Online Kernel Learning"]},"creators":{"author":[{"lastName":"Chen","firstName":"Ning"},{"lastName":"Hoi","firstName":"Steven C.H."},{"lastName":"Li","firstName":"Shaohua"},{"lastName":"Xiao","firstName":"Xiaokui"}]}},{"key":"ChenSN05","type":"inproceedings","fields":{"langid":["english"],"author":["Chen, Kai","Sztipanovits, Janos","Neema, Sandeep"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["EMSOFT 2005 Sept. 18-22 2005 Jersey City NJ USA 5th ACM Int. Conf. Embed. Softw. Proc."],"date":["2005"],"doi":["10.1145/1086228.1086236"],"editor":["Wolf, Wayne H."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper uses a mathematical model, Abstract State Machines, a common semantic framework to define the semantic domains of DSML-s, and proposes a formal well founded methodology with supporting tools to anchor the semantics of DS ML to precisely defined and validated \"semantic units\"."],"pages":["35–43"],"publisher":["ACM"],"timestamp":["Mon, 05 Feb 2024 20:35:04 +0100"],"title":["Toward a semantic anchoring infrastructure for domain-specific modeling languages"]},"creators":{"author":[{"lastName":"Chen","firstName":"Kai"},{"lastName":"Sztipanovits","firstName":"Janos"},{"lastName":"Neema","firstName":"Sandeep"}],"editor":[{"lastName":"Wolf","firstName":"Wayne H."}]},"sentenceCased":true},{"key":"Chowdhury2017","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Des. Eng. Tech. Conf."],"affiliation":["University at Buffalo, Buffalo, NY 14260, United States; Columbia University, New York, NY 10027, United States; Department of Mechanical and Aerospace Engineering, ASME, United States"],"author":["Chowdhury, S.","Mehmani, A."],"correspondence_address1":["Chowdhury, S.; Department of Mechanical and Aerospace Engineering, United States; email: soumacho@buffalo.edu"],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.1115/DETC2017-68385"],"isbn":["978-0-7918-5815-8"],"note":["cited By 2"],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the ASME Design Engineering Technical Conference"],"source":["Scopus"],"title":["Optimal metamodeling to interpret activity-based health sensor data"],"volume":["3"]},"creators":{"author":[{"lastName":"Chowdhury","firstName":"S."},{"lastName":"Mehmani","firstName":"A."}]},"sentenceCased":true},{"key":"Christen20194124","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Conf. Proc. IEEE Int. Conf. Syst. Man Cybern."],"affiliation":["Institute for Information Systems, FHNW, Olten, Switzerland; ETH Zurich, Zurich, Switzerland"],"art_number":["8913839"],"author":["Christen, P.","Fabbro, O.D."],"coden":["PICYE"],"correspondence_address1":["Christen, P.; Institute for Information Systems, Switzerland; email: patrik.christen@fhnw.ch"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/SMC.2019.8913839"],"isbn":["978-1-72814-569-3"],"issn":["1062922X"],"note":["cited By 2 \n\nTL;DR \n\nThis paper emphasises this allagmatic theory by showing how Simondon’s philosophical concepts can be used to formulate a generic computer model or metamodel for complex systems modelling and its implementation in program code, according to generic programming."],"pages":["4124–4130"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics"],"source":["Scopus"],"title":["Cybernetical concepts for cellular automaton and artificial neural network modelling and implementation"],"volume":["2019-October"]},"creators":{"author":[{"lastName":"Christen","firstName":"P."},{"lastName":"Fabbro","firstName":"O.D."}]},"sentenceCased":true},{"key":"chughSurveyHandlingComputationally2019","type":"article","fields":{"abstract":["Evolutionary algorithms are widely used for solving multiobjective optimization problems but are often criticized because of a large number of function evaluations needed. Approximations, especially function approximations, also referred to as surrogates or metamodels are commonly used in the literature to reduce the computation time. This paper presents a survey of 45 different recent algorithms proposed in the literature between 2008 and 2016 to handle computationally expensive multiobjective optimization problems. Several algorithms are discussed based on what kind of an approximation such as problem, function or fitness approximation they use. Most emphasis is given to function approximation-based algorithms. We also compare these algorithms based on different criteria such as metamodeling technique and evolutionary algorithm used, type and dimensions of the problem solved, handling constraints, training time and the type of evolution control. Furthermore, we identify and discuss some promising elements and major issues among algorithms in the literature related to using an approximation and numerical settings used. In addition, we discuss selecting an algorithm to solve a given computationally expensive multiobjective optimization problem based on the dimensions in both objective and decision spaces and the computation budget available. © 2017, Springer-Verlag GmbH Germany, part of Springer Nature."],"author":["Chugh, T.","Sindhya, K.","Hakanen, J.","Miettinen, K."],"date":["2019"],"doi":["10.1007/s00500-017-2965-0"],"issn":["14327643"],"journaltitle":["Soft Comput."],"keywords":["Approximation algorithms","Budget control","Computational costs","Evolutionary algorithms","Learning systems","Meta model","Multicriteria optimization","Multiobjective optimization","Pareto principle","Pareto-optimality","Problem solving","Response surface approximation","Surrogate","Surveys"],"note":["cited By 93 \n\nTL;DR \n\nA survey of 45 different recent algorithms proposed in the literature between 2008 and 2016 to handle computationally expensive multiobjective optimization problems and identifies and discusses some promising elements and major issues among algorithms in the Literature related to using an approximation and numerical settings used."],"number":["9"],"pages":["3137–3166"],"publisher":["Springer Verlag"],"title":["A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms"],"volume":["23"]},"creators":{"author":[{"lastName":"Chugh","firstName":"T."},{"lastName":"Sindhya","firstName":"K."},{"lastName":"Hakanen","firstName":"J."},{"lastName":"Miettinen","firstName":"K."}]},"sentenceCased":true},{"key":"chuiInternetThings2010","type":"article","fields":{"author":["Chui, Michael","Löffler, Markus","Roberts, Roger"],"date":["2010"],"journaltitle":["McKinsey Q."],"number":["2010"],"pages":["1–9"],"title":["The internet of things"],"url":["https://realyze.in/downloads/TheInternetofThings.pdf"],"urldate":["2016-08-21"],"volume":["2"]},"creators":{"author":[{"lastName":"Chui","firstName":"Michael"},{"lastName":"Löffler","firstName":"Markus"},{"lastName":"Roberts","firstName":"Roger"}]},"sentenceCased":true},{"key":"cicchettiAutomatingCoevolutionModelDriven2008","type":"inproceedings","fields":{"author":["Cicchetti, A","DI RUSCIO, Davide","Eramo, R","Pierantonio, Alfonso"],"booktitle":["12th Int. IEEE Enterp. Distrib. Object Comput. Conf. ECOC 2008 15-19 Sept. 2008 Munich Ger."],"date":["2008"],"doi":["10.1109/EDOC.2008.44"],"ids":["cicchettiAutomatingCoevolutionModelDriven2008a,cicchettiAutomatingCoevolutionModeldriven2008,cicchettiAutomatingCoevolutionModeldriven2008a"],"note":["cited By 218 \n\ncited By 218"],"pages":["222–231"],"publisher":["IEEE Computer Society"],"title":["Automating Co-evolution in Model-Driven Engineering"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"A"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Eramo","firstName":"R"},{"lastName":"Pierantonio","firstName":"Alfonso"}]}},{"key":"cicchettiMetamodelIndependentApproach2007","type":"article","fields":{"langid":["english"],"author":["Cicchetti, Antonio","Di Ruscio, Davide","Pierantonio, Alfonso"],"date":["2007"],"doi":["10.5381/jot.2007.6.9.a9"],"issn":["1660-1769"],"journaltitle":["JOT"],"number":["9"],"pages":["165"],"title":["A Metamodel Independent Approach to Difference Representation."],"volume":["6"]},"creators":{"author":[{"lastName":"Cicchetti","firstName":"Antonio"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Pierantonio","firstName":"Alfonso"}]}},{"key":"ciccozziAutomaticSynthesisHeterogeneous2013","type":"inproceedings","fields":{"abstract":["Modern embedded systems present an ever increasing complexity and model-driven engineering has been shown to be helpful in mitigating it. In our previous works we exploited the power of model-driven engineering to develop a round-trip approach for aiding the evaluation and assessment of extra-functional properties preservation from models to code. In addition, we showed how the round-trip approach could be employed to evaluate different deployment strategies, and the focus was on homogeneous CPUbased platforms. Due to the fact that the assortment of target-platforms in the embedded domain is inevitably shifting to heterogeneous solutions, our goal is to broaden the scope of the round-trip approach towards mixed CPU-GPU configurations. In this work we focus on the modelling of heterogeneous deployment and the enhancement of the current automatic code generator to synthesize code targeting such heterogeneous configurations."],"author":["Ciccozzi, F."],"booktitle":["CEUR Workshop Proc."],"date":["2013"],"editor":["Graf S., Ober I., Noyrit F., Karsai G."],"issn":["16130073"],"keywords":["ALF","CHESS-ML","Code synthesis","Codes (symbols)","Computational linguistics","Embedded systems","Heterogeneous systems","MARTE","Model-driven Engineering","UML"],"note":["cited By 0"],"publisher":["CEUR-WS"],"title":["Automatic synthesis of heterogeneous CPU-GPU embedded applications from a UML profile"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84924051199&partnerID=40&md5=70ef85d012e33a637026195a4787b475"],"volume":["1084"]},"creators":{"author":[{"lastName":"Ciccozzi","firstName":"F."}],"editor":[{"lastName":"Graf S.","suffix":"Ober I.","firstName":"Noyrit F., Karsai G."}]},"sentenceCased":true},{"key":"ciccozziBodyKnowledgeModelbased2018","type":"inproceedings","fields":{"langid":["english"],"abstract":["Model-based Software Engineering (MBSE) is now accepted as a Software Engineering (SE) discipline and is being taught as part of more general SE curricula. However, an agreed core of concepts, mechanisms and practices — which constitutes the Body of Knowledge of a discipline — has not been captured anywhere, and is only partially covered by the SE Body of Knowledge (SWEBOK). With the goals of characterizing the contents of the MBSE discipline, promoting a consistent view of it worldwide, clarifying its scope with regard to other SE disciplines, and defining a foundation for a curriculum development on MBSE, this paper provides a proposal for an extension of the contents of SWEBOK with the set of fundamental concepts, terms and mechanisms that should constitute the MBSE Body of Knowledge."],"author":["Ciccozzi, Federico","Famelis, Michalis","Kappel, Gerti","Lambers, Leen","Mosser, Sebastien","Paige, Richard F.","Pierantonio, Alfonso","Rensink, Arend","Salay, Rick","Taentzer, Gabi","Vallecillo, Antonio","Wimmer, Manuel"],"booktitle":["Proc. 21st ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion Proc."],"date":["2018-10-14"],"doi":["10.1145/3270112.3270121"],"eventtitle":["MODELS '18: ACM/IEEE 21th International Conference on Model Driven Engineering Languages and Systems"],"isbn":["978-1-4503-5965-8"],"location":["Copenhagen Denmark"],"note":["TL;DR \n\nThis paper provides a proposal for an extension of the contents of SWEBOK with the set of fundamental concepts, terms and mechanisms that should constitute the MBSE Body of Knowledge."],"pages":["82–89"],"publisher":["ACM"],"title":["Towards a body of knowledge for model-based software engineering"]},"creators":{"author":[{"lastName":"Ciccozzi","firstName":"Federico"},{"lastName":"Famelis","firstName":"Michalis"},{"lastName":"Kappel","firstName":"Gerti"},{"lastName":"Lambers","firstName":"Leen"},{"lastName":"Mosser","firstName":"Sebastien"},{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Rensink","firstName":"Arend"},{"lastName":"Salay","firstName":"Rick"},{"lastName":"Taentzer","firstName":"Gabi"},{"lastName":"Vallecillo","firstName":"Antonio"},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"ciccozziMessageRoSE20182018","type":"article","fields":{"author":["Ciccozzi, F.","Di Ruscio, D.","Malavolta, I.","Pelliccione, P.","Wortmann, A."],"date":["2018"],"ids":["ciccozziMessageRoSE20182018a"],"journaltitle":["Proc. - Int. Conf. Softw. Eng."],"note":["cited By 0 \n\ncited By 0"],"pages":["x"],"title":["Message from the RoSE 2018 Co-Organizers"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051185469&partnerID=40&md5=58d98116887df216a6a4dfdf5660ffdd"],"volume":["Part F137815"]},"creators":{"author":[{"lastName":"Ciccozzi","firstName":"F."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Malavolta","firstName":"I."},{"lastName":"Pelliccione","firstName":"P."},{"lastName":"Wortmann","firstName":"A."}]}},{"key":"ciccozziProceedings1stInternational2018","type":"book","fields":{"date":["2018"],"editor":["Ciccozzi, Federico","Ruscio, Davide Di","Malavolta, Ivano","Pelliccione, Patrizio","Wortmann, Andreas"],"ids":["ciccozziProceedings1stInternational2018a"],"isbn":["978-1-4503-5760-9"],"publisher":["ACM"],"title":["Proceedings of the 1st International Workshop on Robotics Software Engineering, RoSE@ICSE 2018, Gothenburg, Sweden, May 28, 2018"],"url":["http://dl.acm.org/citation.cfm?id=3196558"]},"creators":{"editor":[{"lastName":"Ciccozzi","firstName":"Federico"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Pelliccione","firstName":"Patrizio"},{"lastName":"Wortmann","firstName":"Andreas"}]}},{"key":"ciniselli2021empirical","type":"misc","fields":{"author":["Ciniselli, Matteo","Cooper, Nathan","Pascarella, Luca","Poshyvanyk, Denys","Penta, Massimiliano Di","Bavota, Gabriele"],"date":["2021"],"eprint":["2103.07115"],"eprintclass":["cs.SE"],"eprinttype":["arxiv"],"note":["TL;DR \n\nA large-scale empirical study aimed at exploring the capabilities of state-of-the-art deep learning (DL) models in supporting code completion at different granularity levels, including single tokens, one or multiple entire statements, up to entire code blocks."],"title":["An empirical study on the usage of BERT models for code completion"]},"creators":{"author":[{"lastName":"Ciniselli","firstName":"Matteo"},{"lastName":"Cooper","firstName":"Nathan"},{"lastName":"Pascarella","firstName":"Luca"},{"lastName":"Poshyvanyk","firstName":"Denys"},{"lastName":"Penta","firstName":"Massimiliano Di"},{"lastName":"Bavota","firstName":"Gabriele"}]},"sentenceCased":true},{"key":"CiniselliCPMAPP22","type":"article","fields":{"author":["Ciniselli, Matteo","Cooper, Nathan","Pascarella, Luca","Mastropaolo, Antonio","Aghajani, Emad","Poshyvanyk, Denys","Di Penta, Massimiliano","Bavota, Gabriele"],"date":["2022"],"journaltitle":["IEEE Trans Softw. Eng"],"note":["TL;DR \n\nA large-scale study exploring the capabilities of state-of-the-art Transformer-based models in supporting code completion at different granularity levels, including single tokens, one or multiple entire statements, up to entire code blocks (e.g., the iterated block of a <i>for</i>."],"number":["12"],"pages":["4818–4837"],"title":["An empirical study on the usage of transformer models for code completion"],"volume":["48"]},"creators":{"author":[{"lastName":"Ciniselli","firstName":"Matteo"},{"lastName":"Cooper","firstName":"Nathan"},{"lastName":"Pascarella","firstName":"Luca"},{"lastName":"Mastropaolo","firstName":"Antonio"},{"lastName":"Aghajani","firstName":"Emad"},{"lastName":"Poshyvanyk","firstName":"Denys"},{"lastName":"Di Penta","firstName":"Massimiliano"},{"lastName":"Bavota","firstName":"Gabriele"}]},"sentenceCased":true},{"key":"cioffiArtificialIntelligenceMachine2020","type":"article","fields":{"langid":["english"],"abstract":["Adaptation and innovation are extremely important to the manufacturing industry. This development should lead to sustainable manufacturing using new technologies. To promote sustainability, smart production requires global perspectives of smart production application technology. In this regard, thanks to intensive research efforts in the field of artificial intelligence (AI), a number of AI-based techniques, such as machine learning, have already been established in the industry to achieve sustainable manufacturing. Thus, the aim of the present research was to analyze, systematically, the scientific literature relating to the application of artificial intelligence and machine learning (ML) in industry. In fact, with the introduction of the Industry 4.0, artificial intelligence and machine learning are considered the driving force of smart factory revolution. The purpose of this review was to classify the literature, including publication year, authors, scientific sector, country, institution, and keywords. The analysis was done using the Web of Science and SCOPUS database. Furthermore, UCINET and NVivo 12 software were used to complete them. A literature review on ML and AI empirical studies published in the last century was carried out to highlight the evolution of the topic before and after Industry 4.0 introduction, from 1999 to now. Eighty-two articles were reviewed and classified. A first interesting result is the greater number of works published by the USA and the increasing interest after the birth of Industry 4.0."],"author":["Cioffi, Raffaele","Travaglioni, Marta","Piscitelli, Giuseppina","Petrillo, Antonella","De Felice, Fabio"],"date":["2020-01-08"],"doi":["10.3390/su12020492"],"issn":["2071-1050"],"journaltitle":["Sustainability"],"keywords":["artificial intelligence","DONE","machine learning","smart manufacturing"],"note":["<b>Green Annotations (18/12/2020, 16:35:02)</b> \n\n\"Table 5. Main areas in sustainable manufacturing.\" (<a href=\"zotero://open-pdf/library/items/YUS586FA?page=16\">Cioffi et al 2020:507</a>) \n\n<i>MAYBE USEFUL FOR THE OBJECTIVES (<a href=\"zotero://open-pdf/library/items/YUS586FA?page=16\">note on p.507</a>)</i>"],"number":["2"],"pages":["492"],"shorttitle":["Artificial Intelligence and Machine Learning Applications in Smart Production"],"title":["Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions"],"volume":["12"]},"creators":{"author":[{"lastName":"Cioffi","firstName":"Raffaele"},{"lastName":"Travaglioni","firstName":"Marta"},{"lastName":"Piscitelli","firstName":"Giuseppina"},{"lastName":"Petrillo","firstName":"Antonella"},{"lastName":"De Felice","firstName":"Fabio"}]}},{"key":"citoInteractiveProductionPerformance2019","type":"inproceedings","fields":{"author":["Cito, Jurgen","Leitner, Philipp","Rinard, Martin","Gall, Harald C."],"booktitle":["2019 IEEEACM 41st Int. Conf. Softw. Eng. ICSE"],"date":["2019-05"],"doi":["10.1109/ICSE.2019.00102"],"eventtitle":["2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)"],"isbn":["978-1-72810-869-8"],"location":["Montreal, QC, Canada"],"note":["TL;DR \n\nPerformanceHat, a new system that uses profiling information from production executions to develop a global performance model suitable for integration into interactive development environments, is presented and results indicate that developers using PerformanceHat were significantly faster in detecting the performance problem, and finding the root-cause of the problem."],"pages":["971–981"],"publisher":["IEEE"],"title":["Interactive Production Performance Feedback in the IDE"]},"creators":{"author":[{"lastName":"Cito","firstName":"Jurgen"},{"lastName":"Leitner","firstName":"Philipp"},{"lastName":"Rinard","firstName":"Martin"},{"lastName":"Gall","firstName":"Harald C."}]}},{"key":"clarisoApplyingGraphKernels2018","type":"inproceedings","fields":{"abbrev_source_title":["MASES - Proc. Int. Workshop Mach. Learn. Soft. Eng. Symbiosis, co-located ASE"],"abstract":["Machine Learning (ML) can be used to analyze and classify large collections of graph-based information, e.g. images, location information, the structure of molecules and proteins, . . . Graph kernels is one of the ML techniques typically used for such tasks. In a software engineering context, models of a system such as structural or architectural diagrams can be viewed as labeled graphs. Thus, in this paper we propose to employ graph kernels for clustering software modeling artifacts. Among other benefits, this would improve the efficiency and usability of a variety of software modeling activities, e.g., design space exploration, testing or verification and validation. © 2018 Association for Computing Machinery."],"affiliation":["Multimedia and Telecommunication Dept. Barcelona, Universitat Oberta de Catalunya (UOC) IT, Spain; SOM Research Lab, ICREA, Barcelona, Spain"],"author":["Clarisó, R.","Cabot, J."],"booktitle":["MASES 2018 - Proc. 1st Int. Workshop Mach. Learn. Softw. Eng. Symbiosis Co-Located ASE 2018"],"date":["2018"],"document_type":["Conference Paper"],"doi":["10.1145/3243127.3243128"],"editor":["Perrouin G., Acher M., Devroey X., Cordy M., Cordy M."],"ids":["Clarisó20181"],"isbn":["978-1-4503-5972-6"],"keywords":["Artificial intelligence","Classification (of information)","Clustering","Design space exploration","GOAL_Model-Classification","Graph kernels","Graphic methods","Labeled graphs","Learning systems","Location information","Model-driven Engineering","notion","Software testing","Structure of molecules","Systems analysis","TECHNIQUE_GRAPH-KERNELS","Verification","Verification-and-validation"],"note":["cited By 10 \n\ncited By 10 \n\nTL;DR \n\nThis paper proposes to employ graph kernels for clustering software modeling artifacts to improve the efficiency and usability of a variety of software modeling activities, e.g., design space exploration, testing or verification and validation."],"pages":["1–5"],"publisher":["Association for Computing Machinery, Inc"],"source":["Scopus"],"title":["Applying graph kernels to model-driven engineering problems"]},"creators":{"author":[{"lastName":"Clarisó","firstName":"R."},{"lastName":"Cabot","firstName":"J."}],"editor":[{"lastName":"Perrouin G.","suffix":"Acher M.","firstName":"Devroey X., Cordy M., Cordy M."}]},"sentenceCased":true},{"key":"clarisoBackwardsReasoningModel2015","type":"article","fields":{"langid":["english"],"author":["Clarisó, Robert","Cabot, Jordi","Guerra, Esther","family=Lara, given=Juan, prefix=de, useprefix=true"],"date":["2015-08"],"doi":["10.1016/j.jss.2015.08.017"],"issn":["01641212"],"journaltitle":["J. Syst. Softw."],"shorttitle":["Backwards reasoning for model transformations"],"title":["Backwards reasoning for model transformations: Method and applications"]},"creators":{"author":[{"lastName":"Clarisó","firstName":"Robert"},{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true}]},"sentenceCased":true},{"key":"clarisoModelDrivenPromptEngineering2023","type":"inproceedings","fields":{"abstract":["Generative artificial intelligence (AI) systems are capable of synthesizing complex content such as text, source code or images according to the instructions described in a natural language prompt. The quality of the output depends on crafting a suitable prompt. This has given rise to prompt engineering, the process of designing natural language prompts to best take advantage of the capabilities of generative AI systems.Through experimentation, the creative and research communities have created guidelines and strategies for creating good prompts. However, even for the same task, these best practices vary depending on the particular system receiving the prompt. Moreover, some systems offer additional features using a custom platform-specific syntax, e.g., assigning a degree of relevance to specific concepts within the prompt.In this paper, we propose applying model-driven engineering to support the prompt engineering process. Using a domain-specific language (DSL), we define platform-independent prompts that can later be adapted to provide good quality outputs in a target AI system. The DSL also facilitates managing prompts by providing mechanisms for prompt versioning and prompt chaining. Tool support is available thanks to a Langium-based Visual Studio Code plugin."],"author":["Clarisó, Robert","Cabot, Jordi"],"booktitle":["2023 ACMIEEE 26th Int. Conf. Model Driven Eng. Lang. Syst. MODELS"],"date":["2023-10"],"doi":["10.1109/MODELS58315.2023.00020"],"eventtitle":["2023 ACM/IEEE 26th International Conference on Model Driven Engineering Languages and Systems (MODELS)"],"keywords":["Artificial intelligence","domain-specific language","DSL","generative AI","large language models","Model driven engineering","model-driven engineering","Natural languages","prompt engineering","Source coding","Syntactics","Visualization"],"pages":["47–54"],"title":["Model-Driven Prompt Engineering"]},"creators":{"author":[{"lastName":"Clarisó","firstName":"Robert"},{"lastName":"Cabot","firstName":"Jordi"}]}},{"key":"ClosedloopSystemClosedloop","type":"online","fields":{"title":["Closed-loop System and Closed-loop Control Systems"],"url":["http://www.electronics-tutorials.ws/systems/closed-loop-system.html"],"urldate":["2016-11-01"]},"creators":{},"sentenceCased":true},{"key":"ClusteringIntroduction","type":"online","fields":{"title":["Clustering - Introduction"],"url":["http://home.deib.polimi.it/matteucc/Clustering/tutorial_html/"],"urldate":["2015-04-23"]},"creators":{}},{"key":"ClusteringValidationTechniques","type":"online","fields":{"title":["On Clustering Validation Techniques - Springer"],"url":["http://link.springer.com/article/10.1023/A:1012801612483"],"urldate":["2015-05-07"]},"creators":{}},{"key":"ClusterSummarizationDense","type":"online","fields":{"title":["Cluster Summarization with Dense Region Detection - Springer"],"url":["http://link.springer.com/chapter/10.1007/978-3-319-25840-9_5?wt_mc=alerts.TOCseries"],"urldate":["2015-11-02"]},"creators":{}},{"key":"Cohen:1995:FER:3091622.3091637","type":"inproceedings","fields":{"acmid":["3091637"],"author":["Cohen, William W."],"booktitle":["Proc. Twelfth Int. Conf. Int. Conf. Mach. Learn."],"date":["1995"],"isbn":["1-55860-377-8"],"location":["San Francisco, CA, USA"],"numpages":["9"],"pages":["115–123"],"publisher":["Morgan Kaufmann Publishers Inc."],"series":["ICML'95"],"title":["Fast effective rule induction"],"url":["http://dl.acm.org/citation.cfm?id=3091622.3091637"]},"creators":{"author":[{"lastName":"Cohen","firstName":"William W."}]},"sentenceCased":true},{"key":"cohenFourPillarsResearch2021","type":"article","fields":{"author":["Cohen, Jeremy","Katz, Daniel S.","Barker, Michelle","Chue Hong, Neil","Haines, Robert","Jay, Caroline"],"date":["2021-01"],"doi":["10.1109/MS.2020.2973362"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nFour elements are presented that are key to providing a comprehensive and sustainable support for research software engineering: software development, community, training, and policy."],"number":["1"],"pages":["97–105"],"title":["The Four Pillars of Research Software Engineering"],"volume":["38"]},"creators":{"author":[{"lastName":"Cohen","firstName":"Jeremy"},{"lastName":"Katz","firstName":"Daniel S."},{"lastName":"Barker","firstName":"Michelle"},{"lastName":"Chue Hong","firstName":"Neil"},{"lastName":"Haines","firstName":"Robert"},{"lastName":"Jay","firstName":"Caroline"}]}},{"key":"colantoniDevOpsMLModelingDevOps2020","type":"inproceedings","fields":{"langid":["english"],"abstract":["DevOps and Model Driven Engineering (MDE) provide differently skilled IT stakeholders with methodologies and tools for organizing and automating continuous software engineering activities–from development to operations, and using models as key engineering artifacts, respectively. Both DevOps and MDE aim at shortening the development life-cycle, dealing with complexity, and improve software process and product quality."],"author":["Colantoni, Alessandro","Berardinelli, Luca","Wimmer, Manuel"],"booktitle":["Proc. 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion Proc."],"date":["2020-10-16"],"doi":["10.1145/3417990.3420203"],"eventtitle":["MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems"],"isbn":["978-1-4503-8135-2"],"keywords":["LOGSEQ"],"location":["Virtual Event Canada"],"pages":["1–10"],"publisher":["ACM"],"shorttitle":["DevOpsML"],"title":["DevOpsML: Towards modeling DevOps processes and platforms"]},"creators":{"author":[{"lastName":"Colantoni","firstName":"Alessandro"},{"lastName":"Berardinelli","firstName":"Luca"},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"colinaInternetThingsIoT","type":"article","fields":{"author":["Colina, Antonio Liñán","Vives, Alvaro","Bagula, Antoine","Zennaro, Marco","Pietrosemoli, Ermanno"],"pages":["227"],"title":["Internet of Things (IoT) in 5 days"]},"creators":{"author":[{"lastName":"Colina","firstName":"Antonio Liñán"},{"lastName":"Vives","firstName":"Alvaro"},{"lastName":"Bagula","firstName":"Antoine"},{"lastName":"Zennaro","firstName":"Marco"},{"lastName":"Pietrosemoli","firstName":"Ermanno"}]},"sentenceCased":true},{"key":"collobertNaturalLanguageProcessing2011","type":"article","fields":{"acmid":["2078186"],"author":["Collobert, Ronan","Weston, Jason","Bottou, Léon","Karlen, Michael","Kavukcuoglu, Koray","Kuksa, Pavel"],"date":["2011-11"],"issn":["1532-4435"],"issue_date":["2/1/2011"],"journaltitle":["J. Mach. Learn. Res."],"note":["TL;DR \n\nA unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including part-of-speech tagging, chunking, named entity recognition, and semantic role labeling is proposed."],"numpages":["45"],"pages":["2493–2537"],"publisher":["JMLR.org"],"title":["Natural language processing (almost) from scratch"],"url":["http://dl.acm.org/citation.cfm?id=1953048.2078186"],"volume":["12"]},"creators":{"author":[{"lastName":"Collobert","firstName":"Ronan"},{"lastName":"Weston","firstName":"Jason"},{"lastName":"Bottou","firstName":"Léon"},{"lastName":"Karlen","firstName":"Michael"},{"lastName":"Kavukcuoglu","firstName":"Koray"},{"lastName":"Kuksa","firstName":"Pavel"}]},"sentenceCased":true},{"key":"colnagoInformingDesignPersonalized2020","type":"inproceedings","fields":{"langid":["english"],"author":["Colnago, Jessica","Feng, Yuanyuan","Palanivel, Tharangini","Pearman, Sarah","Ung, Megan","Acquisti, Alessandro","Cranor, Lorrie Faith","Sadeh, Norman"],"booktitle":["Proc. 2020 CHI Conf. Hum. Factors Comput. Syst."],"date":["2020-04-21"],"doi":["10.1145/3313831.3376389"],"eventtitle":["CHI '20: CHI Conference on Human Factors in Computing Systems"],"isbn":["978-1-4503-6708-0"],"location":["Honolulu HI USA"],"pages":["1–13"],"publisher":["ACM"],"title":["Informing the Design of a Personalized Privacy Assistant for the Internet of Things"]},"creators":{"author":[{"lastName":"Colnago","firstName":"Jessica"},{"lastName":"Feng","firstName":"Yuanyuan"},{"lastName":"Palanivel","firstName":"Tharangini"},{"lastName":"Pearman","firstName":"Sarah"},{"lastName":"Ung","firstName":"Megan"},{"lastName":"Acquisti","firstName":"Alessandro"},{"lastName":"Cranor","firstName":"Lorrie Faith"},{"lastName":"Sadeh","firstName":"Norman"}]}},{"key":"Combemale202171","type":"article","fields":{"langid":["english"],"abbrev_source_title":["IEEE Software"],"affiliation":["University of Toulouse, Toulouse, F-35042, France; McGill University, Montréal, QC H3A 0E9, Canada; University of Ottawa, Ottawa, ON K1N 5N5, Canada; Open University of Catalonia, Barcelona, H3C 3J7, Spain; Aston University, Birmingham, B4 7ET, United Kingdom; Concordia University, Montréal, QC F-06103, Canada; Department of Business Informatics-Software Engineering, Johannes Kepler University Linz, Linz, Austria; Michigan State University, East Lansing, MI 48824, United States; University Côte d'Azur, Biot, F-06103, France; Paderborn University, Paderborn, D-33100, Germany; Karlsruhe Institute of Technology, Karlsruhe, D-76128, Germany; University of Rennes, Rennes, F-35042, France; University of Québec Montréal, Montréal, QC H3C 3P8, Canada; Montréal University, Montréal, QC H3C 3J7, Canada; United Nations University Institute, Macau, 150-8925, Macau"],"art_number":["9094197"],"author":["Combemale, B.","Kienzle, J.","Mussbacher, G.","Ali, H.","Amyot, D.","Bagherzadeh, M.","Batot, E.","Bencomo, N.","Benni, B.","Bruel, J.-M.","Cabot, J.","Cheng, B.H.C.","Collet, P.","Engels, G.","Heinrich, R.","Jezequel, J.-M.","Koziolek, A.","Mosser, S.","Reussner, R.","Sahraoui, H.","Saini, R.","Sallou, J.","Stinckwich, S.","Syriani, E.","Wimmer, M."],"coden":["IESOE"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/MS.2020.2995125"],"issn":["07407459"],"journaltitle":["IEEE Softw."],"note":["cited By 8"],"number":["4"],"pages":["71–84"],"publisher":["IEEE Computer Society"],"source":["Scopus"],"title":["A hitchhiker's guide to model-driven engineering for data-centric systems"],"volume":["38"]},"creators":{"author":[{"lastName":"Combemale","firstName":"B."},{"lastName":"Kienzle","firstName":"J."},{"lastName":"Mussbacher","firstName":"G."},{"lastName":"Ali","firstName":"H."},{"lastName":"Amyot","firstName":"D."},{"lastName":"Bagherzadeh","firstName":"M."},{"lastName":"Batot","firstName":"E."},{"lastName":"Bencomo","firstName":"N."},{"lastName":"Benni","firstName":"B."},{"lastName":"Bruel","firstName":"J.-M."},{"lastName":"Cabot","firstName":"J."},{"lastName":"Cheng","firstName":"B.H.C."},{"lastName":"Collet","firstName":"P."},{"lastName":"Engels","firstName":"G."},{"lastName":"Heinrich","firstName":"R."},{"lastName":"Jezequel","firstName":"J.-M."},{"lastName":"Koziolek","firstName":"A."},{"lastName":"Mosser","firstName":"S."},{"lastName":"Reussner","firstName":"R."},{"lastName":"Sahraoui","firstName":"H."},{"lastName":"Saini","firstName":"R."},{"lastName":"Sallou","firstName":"J."},{"lastName":"Stinckwich","firstName":"S."},{"lastName":"Syriani","firstName":"E."},{"lastName":"Wimmer","firstName":"M."}]},"sentenceCased":true},{"key":"CombemaleBW17","type":"inproceedings","fields":{"langid":["english"],"author":["Combemale, Benoît","Barais, Olivier","Wortmann, Andreas"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["2017 IEEE Int. Conf. Softw. Archit. Workshop ICSA Workshop 2017 Gothenbg. Swed. April 5-7 2017"],"date":["2017"],"doi":["10.1109/ICSAW.2017.61"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nFrom such a specification, the ability of the GEMOC studio to automatically support model execution, graphical animation, omniscient debugging, concurrency analysis and concurrent execution of heterogeneous models is demonstrated."],"pages":["189–191"],"publisher":["IEEE Computer Society"],"timestamp":["Fri, 24 Mar 2023 00:02:32 +0100"],"title":["Language engineering with the GEMOC studio"]},"creators":{"author":[{"lastName":"Combemale","firstName":"Benoît"},{"lastName":"Barais","firstName":"Olivier"},{"lastName":"Wortmann","firstName":"Andreas"}]},"sentenceCased":true},{"key":"combemaleChatGPTSoftwareModeling2023","type":"article","fields":{"langid":["english"],"author":["Combemale, Benoit","Gray, Jeff","Rumpe, Bernhard"],"date":["2023-05-11"],"doi":["10.1007/s10270-023-01106-4"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"keywords":["LOGSEQ"],"note":["TL;DR \n\nThis editorial focuses more positively and asks the main question: How will ChatGPT be able to help in a development process, especially in the tasks of developing or using models for analysis, production or understanding of software and systems."],"pages":["s10270-023-01106-4"],"title":["ChatGPT in software modeling"]},"creators":{"author":[{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Gray","firstName":"Jeff"},{"lastName":"Rumpe","firstName":"Bernhard"}]},"sentenceCased":true},{"key":"combemaleFormallyDefiningIterating2012","type":"incollection","fields":{"langid":["english"],"author":["Combemale, Benoit","Thirioux, Xavier","Baudry, Benoit"],"booktitle":["Model Driven Engineering Languages and Systems"],"date":["2012"],"doi":["10.1007/978-3-642-33666-9_9"],"editor":["France, Robert B.","Kazmeier, Jürgen","Breu, Ruth","Atkinson, Colin"],"editorb":["Hutchison, David","Kanade, Takeo","Kittler, Josef","Kleinberg, Jon M.","Mattern, Friedemann","Mitchell, John C.","Naor, Moni","Nierstrasz, Oscar","Pandu Rangan, C.","Steffen, Bernhard","Sudan, Madhu","Terzopoulos, Demetri","Tygar, Doug","Vardi, Moshe Y.","Weikum, Gerhard"],"editorbtype":["redactor"],"isbn":["978-3-642-33665-2 978-3-642-33666-9"],"location":["Berlin, Heidelberg"],"pages":["119–133"],"publisher":["Springer Berlin Heidelberg"],"title":["Formally Defining and Iterating Infinite Models"],"volume":["7590"]},"creators":{"author":[{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Thirioux","firstName":"Xavier"},{"lastName":"Baudry","firstName":"Benoit"}],"editor":[{"lastName":"France","firstName":"Robert B."},{"lastName":"Kazmeier","firstName":"Jürgen"},{"lastName":"Breu","firstName":"Ruth"},{"lastName":"Atkinson","firstName":"Colin"}],"editorb":[{"lastName":"Hutchison","firstName":"David"},{"lastName":"Kanade","firstName":"Takeo"},{"lastName":"Kittler","firstName":"Josef"},{"lastName":"Kleinberg","firstName":"Jon M."},{"lastName":"Mattern","firstName":"Friedemann"},{"lastName":"Mitchell","firstName":"John C."},{"lastName":"Naor","firstName":"Moni"},{"lastName":"Nierstrasz","firstName":"Oscar"},{"lastName":"Pandu Rangan","firstName":"C."},{"lastName":"Steffen","firstName":"Bernhard"},{"lastName":"Sudan","firstName":"Madhu"},{"lastName":"Terzopoulos","firstName":"Demetri"},{"lastName":"Tygar","firstName":"Doug"},{"lastName":"Vardi","firstName":"Moshe Y."},{"lastName":"Weikum","firstName":"Gerhard"}]}},{"key":"combemaleGlobalizingDomainSpecificLanguages2015","type":"book","fields":{"date":["2015"],"editor":["Combemale, Benoit","Cheng, Betty H.C.","France, Robert B.","Jézéquel, Jean-Marc","Rumpe, Bernhard"],"isbn":["978-3-319-26171-3 978-3-319-26172-0"],"location":["Cham"],"publisher":["Springer International Publishing"],"series":["Lecture Notes in Computer Science"],"title":["Globalizing Domain-Specific Languages"],"url":["http://link.springer.com/10.1007/978-3-319-26172-0"],"urldate":["2016-01-26"],"volume":["9400"]},"creators":{"editor":[{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Cheng","firstName":"Betty H.C."},{"lastName":"France","firstName":"Robert B."},{"lastName":"Jézéquel","firstName":"Jean-Marc"},{"lastName":"Rumpe","firstName":"Bernhard"}]}},{"key":"combemaleGlobalizingModelingLanguages2014","type":"article","fields":{"author":["Combemale, Benoit","Deantoni, Julien","Baudry, Benoit","France, Robert B.","Jézéquel, Jean-Marc","Gray, Jordan"],"date":["2014"],"journaltitle":["Computer"],"note":["TL;DR \n\nA research initiative is described that broadens the DSML research focus beyond independent DSML development to one that supports globalized DSMLs-that is, DS MLs that facilitate coordination of work across different domains of expertise."],"number":["6"],"pages":["68–71"],"title":["Globalizing modeling languages"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6839148"],"urldate":["2015-09-23"],"volume":["47"]},"creators":{"author":[{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Deantoni","firstName":"Julien"},{"lastName":"Baudry","firstName":"Benoit"},{"lastName":"France","firstName":"Robert B."},{"lastName":"Jézéquel","firstName":"Jean-Marc"},{"lastName":"Gray","firstName":"Jordan"}]},"sentenceCased":true},{"key":"combemaleLanguageOrientedModeling2015","type":"thesis","fields":{"author":["Combemale, Benoit"],"date":["2015"],"institution":["Université de Rennes 1"],"note":["TL;DR \n\nA decade of research work in the fields of Model-Driven Engineering (MDE) and Software Language Engineering (SLE) is reviewed, and contributions to support a language-oriented modeling are proposed, with the particular focus on enabling early validation &amp; verification of software-intensive systems."],"title":["Towards Language-Oriented Modeling"],"url":["https://hal.inria.fr/tel-01238817/"],"urldate":["2016-01-26"]},"creators":{"author":[{"lastName":"Combemale","firstName":"Benoit"}]}},{"key":"combemaleSLEBOKSoftwareLanguage2018","type":"article","fields":{"langid":["english"],"abstract":["This report documents the program and the outcomes of Dagstuhl Seminar 17342 \"SLEBOK: The Software Language Engineering Body of Knowledge\". Software Language Engineering (SLE) has emerged as a scientific field, with a strong motivation to connect and integrate different research disciplines such as compiler construction, reverse engineering, software transformation, model-driven engineering, and ontologies. This seminar supported further integration of said communities with the clear objective of assembling a Body of Knowledge on SLE (SLEBoK). The BoK features artifacts, definitions, methods, techniques, best practices, open challenges, case studies, teaching material, and other components that will afterwards help students, researchers, teachers, and practitioners to learn from, to better leverage, to better contribute to, and to better disseminate the intellectual contributions and practical tools and techniques coming from the SLE field."],"author":["Combemale, Benoît","Lämmel, Ralf","Van Wyk, Eric"],"date":["2018"],"doi":["10.4230/DAGREP.7.8.45"],"editora":["Herbstritt, Marc"],"editoratype":["collaborator"],"keywords":["000 Computer science, knowledge, general works","Computer Science"],"note":["<h2>Other</h2> \n\nThis report documents the program and the outcomes of Dagstuhl Seminar 17342 \"SLEBOK: The Software Language Engineering Body of Knowledge\". Software Language Engineering (SLE) has emerged as a scientific field, with a strong motivation to connect and integrate different research disciplines such as compiler construction, reverse engineering, software transformation, model-driven engineering, and ontologies. This seminar supported further integration of said communities with the clear objective of assembling a Body of Knowledge on SLE (SLEBoK). The BoK features artifacts, definitions, methods, techniques, best practices, open challenges, case studies, teaching material, and other components that will afterwards help students, researchers, teachers, and practitioners to learn from, to better leverage, to better contribute to, and to better disseminate the intellectual contributions and practical tools and techniques coming from the SLE field."],"pages":["10 pages"],"publisher":["Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany"],"shorttitle":["SLEBOK"],"title":["SLEBOK: The Software Language Engineering Body of Knowledge (Dagstuhl Seminar 17342)"]},"creators":{"author":[{"lastName":"Combemale","firstName":"Benoît"},{"lastName":"Lämmel","firstName":"Ralf"},{"lastName":"Van Wyk","firstName":"Eric"}],"editora":[{"lastName":"Herbstritt","firstName":"Marc"}]}},{"key":"CommunicationsACMFebruary","type":"article","fields":{"langid":["english"],"pages":["124"],"title":["Communications of the ACM - February 2022"]},"creators":{}},{"key":"CommunicationsACMJuly","type":"article","fields":{"langid":["english"],"pages":["116"],"title":["Communications of the ACM - July 2020"]},"creators":{}},{"key":"CommunicationsACMJulya","type":"article","fields":{"langid":["english"],"pages":["116"],"title":["Communications of the ACM - July 2021"]},"creators":{}},{"key":"CommunicationsACMJune","type":"article","fields":{"langid":["english"],"pages":["100"],"title":["Communications of the ACM - June 2020"]},"creators":{}},{"key":"CommunicationsACMJunea","type":"article","fields":{"langid":["english"],"pages":["124"],"title":["Communications of the ACM - June 2021"]},"creators":{}},{"key":"CommunicationsACMMay","type":"article","fields":{"langid":["english"],"pages":["116"],"title":["Communications of the ACM - May 2020"]},"creators":{}},{"key":"CommunicationsACMOctober","type":"article","fields":{"langid":["english"],"pages":["112"],"title":["Communications of the ACM - October 2020"]},"creators":{}},{"key":"ComparisonModelMigration","type":"online","fields":{"title":["A Comparison of Model Migration Tools - Springer"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-16145-2_5"],"urldate":["2015-03-24"]},"creators":{}},{"key":"ComplexNatureMDE","type":"online","fields":{"title":["On the complex nature of MDE evolution and its impact on changeability - Online First - Springer"],"url":["http://link.springer.com/article/10.1007%2Fs10270-015-0464-2"],"urldate":["2015-12-08"]},"creators":{},"sentenceCased":true},{"key":"Compton2020243","type":"inproceedings","fields":{"abstract":["Automatic source code analysis in key areas of software engineering, such as code security, can benefit from Machine Learning (ML). However, many standard ML approaches require a numeric representation of data and cannot be applied directly to source code. Thus, to enable ML, we need to embed source code into numeric feature vectors while maintaining the semantics of the code as much as possible. code2vec is a recently released embedding approach that uses the proxy task of method name prediction to map Java methods to feature vectors. However, experimentation with code2vec shows that it learns to rely on variable names for prediction, causing it to be easily fooled by typos or adversarial attacks. Moreover, it is only able to embed individual Java methods and cannot embed an entire collection of methods such as those present in a typical Java class, making it difficult to perform predictions at the class level (e.g., for the identification of malicious Java classes). Both shortcomings are addressed in the research presented in this paper. We investigate the effect of obfuscating variable names during training of a code2vec model to force it to rely on the structure of the code rather than specific names and consider a simple approach to creating class-level embeddings by aggregating sets of method embeddings. Our results, obtained on a challenging new collection of source-code classification problems, indicate that obfuscating variable names produces an embedding model that is both impervious to variable naming and more accurately reflects code semantics. The datasets, models, and code are shared1 for further ML research on source code. © 2020 ACM."],"author":["Compton, Rhys","Frank, Eibe","Patros, Panos","Koay, Abigail"],"author_keywords":["code obfuscation; code2vec; machine learning; neural networks; source code"],"booktitle":["Proc. 17th Int. Conf. Min. Softw. Repos."],"date":["2020-06"],"document_type":["Conference Paper"],"doi":["10.1145/3379597.3387445"],"isbn":["978-1-4503-7517-7"],"keywords":["Class level","code obfuscation","Code security","Code semantics","code2vec","Embeddings","Feature vectors","Forecasting","Java methods","Java programming language","machine learning","neural networks","Semantics","Simple approach","Software engineering","source code","Source code analysis","Source codes"],"location":["New York, NY, USA"],"note":["cited By 19 \n\nTL;DR \n\nThe effect of obfuscating variable names during training of a code2vec model is investigated to force it to rely on the structure of the code rather than specific names and a simple approach to creating class-level embeddings by aggregating sets of method embeddeddings is considered."],"pages":["243–253"],"publisher":["Association for Computing Machinery, Inc"],"series":["Proceedings - 2020 IEEE/ACM 17th International Conference on Mining Software Repositories, MSR 2020"],"shorttitle":["Embedding Java Classes with code2vec"],"source":["Scopus"],"title":["Embedding Java Classes with code2vec: Improvements from Variable Obfuscation"]},"creators":{"author":[{"lastName":"Compton","firstName":"Rhys"},{"lastName":"Frank","firstName":"Eibe"},{"lastName":"Patros","firstName":"Panos"},{"lastName":"Koay","firstName":"Abigail"}]},"sentenceCased":true},{"key":"conf:iscis:MadylovaO09","type":"inproceedings","fields":{"added-at":["2009-12-30T00:00:00.000+0100"],"author":["Madylova, Ainura","Ögüducü, Sule Gündüz"],"biburl":["https://www.bibsonomy.org/bibtex/2b6f37cbf44daa243cf2b91e00181806f/dblp"],"booktitle":["ISCIS"],"description":["dblp"],"ee":["http://dx.doi.org/10.1109/ISCIS.2009.5291865"],"interhash":["17227ba19186316517f52ffa39fa8568"],"intrahash":["b6f37cbf44daa243cf2b91e00181806f"],"keywords":["dblp"],"note":["TL;DR \n\nA new method based on cosine similarity calculation between concept vectors of documents obtained from a taxonomy of words that captures IS-A relations which results in faster computational time."],"pages":["129–134"],"publisher":["IEEE"],"timestamp":["2009-12-31T11:34:52.000+0100"],"title":["A taxonomy based semantic similarity of documents using the cosine measure."],"url":["http://dblp.uni-trier.de/db/conf/iscis/iscis2009.html#MadylovaO09"],"year":["2009-12-30, 2009"]},"creators":{"author":[{"lastName":"Madylova","firstName":"Ainura"},{"lastName":"Ögüducü","firstName":"Sule Gündüz"}]},"sentenceCased":true},{"key":"conf/cvpr/NguyenYC15","type":"inproceedings","fields":{"added-at":["2016-04-28T00:00:00.000+0200"],"author":["Nguyen, Anh Mai","Yosinski, Jason","Clune, Jeff"],"biburl":["https://www.bibsonomy.org/bibtex/26672da9a292a16afa346ca2d8e3c181a/dblp"],"booktitle":["CVPR"],"date":["2015"],"ee":["http://doi.ieeecomputersociety.org/10.1109/CVPR.2015.7298640"],"interhash":["c8af26890ac9aa947cf1485879db901f"],"intrahash":["6672da9a292a16afa346ca2d8e3c181a"],"isbn":["978-1-4673-6964-0"],"keywords":["dblp"],"pages":["427–436"],"publisher":["IEEE Computer Society"],"timestamp":["2016-04-29T11:54:14.000+0200"],"title":["Deep neural networks are easily fooled: High confidence predictions for unrecognizable images."],"url":["http://dblp.uni-trier.de/db/conf/cvpr/cvpr2015.html#NguyenYC15"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Anh Mai"},{"lastName":"Yosinski","firstName":"Jason"},{"lastName":"Clune","firstName":"Jeff"}]},"sentenceCased":true},{"key":"conf/stids/OlssonPSP11","type":"inproceedings","fields":{"added-at":["2013-07-22T00:00:00.000+0200"],"author":["Olsson, Catherine","Petrov, Plamen","Sherman, Jeff","Perez-Lopez, Andrew"],"biburl":["http://www.bibsonomy.org/bibtex/29536bc182f305da5dad27f51b28a779e/dblp"],"booktitle":["STIDS"],"date":["2011"],"editor":["family=Costa, given=Paulo Cesar G., prefix=da, useprefix=true","Laskey, Kathryn B."],"ee":["http://ceur-ws.org/Vol-808/STIDS2011<sub>C</sub>R<sub>T</sub>7<sub>O</sub>lssonEtAl.pdf"],"interhash":["a078f5c01f90adea0e5067f8a3d88106"],"intrahash":["9536bc182f305da5dad27f51b28a779e"],"keywords":["dblp"],"note":["TL;DR \n\nA definition of an “explanation” of similarity is formulated, a system that can produce such explanations efficiently is described, and a methodology is presented to allow the user to tailor how “obvious” or ”obscure” the provided explanations are."],"pages":["52–59"],"publisher":["CEUR-WS.org"],"series":["CEUR workshop proceedings"],"timestamp":["2013-07-22T00:00:00.000+0200"],"title":["Finding and explaining similarities in linked data."],"url":["http://dblp.uni-trier.de/db/conf/stids/stids2011.html#OlssonPSP11"],"volume":["808"]},"creators":{"author":[{"lastName":"Olsson","firstName":"Catherine"},{"lastName":"Petrov","firstName":"Plamen"},{"lastName":"Sherman","firstName":"Jeff"},{"lastName":"Perez-Lopez","firstName":"Andrew"}],"editor":[{"lastName":"Costa","firstName":"PauloCesarG.","prefix":"da","useprefix":true},{"lastName":"Laskey","firstName":"Kathryn B."}]},"sentenceCased":true},{"key":"connollyWhyComputingBelongs2020","type":"article","fields":{"langid":["english"],"abstract":["Fully appreciating the overarching scope of CS requires weaving more than ethics into the reigning curricula."],"author":["Connolly, Randy"],"date":["2020-07-22"],"doi":["10.1145/3383444"],"issn":["0001-0782, 1557-7317"],"journaltitle":["Commun. ACM"],"note":["TL;DR \n\nFully appreciating the overarching scope of CS requires weaving more than ethics into the reigning curricula."],"number":["8"],"pages":["54–59"],"title":["Why computing belongs within the social sciences"],"volume":["63"]},"creators":{"author":[{"lastName":"Connolly","firstName":"Randy"}]},"sentenceCased":true},{"key":"conselInternetThingsChallenge","type":"article","fields":{"langid":["english"],"author":["Consel, Charles","Kabáč, Milan"],"note":["TL;DR \n\nThe Internet of Things (IoT) has become a reality with the emergence of Smart Cities, populated with large amounts of smart objects which are used to deliver a range of citizen services."],"pages":["3"],"title":["Internet of Things: A Challenge for Software Engineering"]},"creators":{"author":[{"lastName":"Consel","firstName":"Charles"},{"lastName":"Kabáč","firstName":"Milan"}]}},{"key":"ConstructingAutonomousSystems","type":"online","fields":{"title":["Constructing Autonomous Systems"],"url":["http://aosgrp.com/featured-research/autonomy_and_agents/autonomous_systems/constructing_autonomous_sys.html"],"urldate":["2016-08-24"]},"creators":{}},{"key":"ContinuousDeliveryMap","type":"online","fields":{"title":["Continuous Delivery Map | Continuous Delivery Map"],"url":["https://assessment-tools.ca.com/tools/continuous-delivery-tools/en?embed"],"urldate":["2018-04-30"]},"creators":{}},{"key":"ControlSystemsFeedback","type":"online","fields":{"title":["Control Systems/Feedback Loops - Wikibooks, open books for an open world"],"url":["https://en.wikibooks.org/wiki/Control_Systems/Feedback_Loops"],"urldate":["2016-11-01"]},"creators":{},"sentenceCased":true},{"key":"ControlTheory101","type":"online","fields":{"title":["Control Theory 101 for Beginners | Nuvation"],"url":["http://www.nuvation.com/blog/electronic-design-services/control-theory-101-beginners"],"urldate":["2016-09-20"]},"creators":{}},{"key":"ControlTheory1012013","type":"online","fields":{"abstract":["While not as ubiquitous as electric power or microelectronics, control theory is applied everywhere in our daily lives but it is rarely noticed."],"date":["2013-09-24T22:02:15+00:00"],"organization":["Nuvation"],"title":["Control Theory 101 for Beginners"],"url":["http://www.nuvation.com/blog/electronic-design-services/control-theory-101-beginners"],"urldate":["2016-09-20"]},"creators":{}},{"key":"COPEWorkbenchCoupled2011","type":"book","fields":{"langid":["english"],"date":["2011"],"doi":["10.1007/978-3-642-19440-5_18"],"isbn":["978-3-642-19439-9"],"keywords":["linter/error"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nThis paper presents COPE, a tool to automate the coupled evolution of metamodels and models and provides advanced tool support to inspect, refactor and recover the coupling evolution."],"publisher":["Springer Berlin Heidelberg"],"title":["COPE – A Workbench for the Coupled Evolution of Metamodels and Models"],"volume":["6563"]},"creators":{}},{"key":"corbelliniPersistingBigdataNoSQL2017","type":"article","fields":{"langid":["english"],"abstract":["The growing popularity of massively accessed Web applications that store and analyze large amounts of data, being Facebook, Twitter and Google Search some prominent examples of such applications, have posed new requirements that greatly challenge traditional RDBMS. In response to this reality, a new way of creating and manipulating data stores, known as NoSQL databases, has arisen. This paper reviews implementations of NoSQL databases in order to provide an understanding of current tools and their uses. First, NoSQL databases are compared with traditional RDBMS and important concepts are explained. Only databases allowing to persist data and distribute them along different computing nodes are within the scope of this review. Moreover, NoSQL databases are divided into different types: Key-Value, Wide-Column, Document-oriented and Graphoriented. In each case, a comparison of available databases is carried out based on their most important features."],"author":["Corbellini, Alejandro","Mateos, Cristian","Zunino, Alejandro","Godoy, Daniela","Schiaffino, Silvia"],"date":["2017-01"],"doi":["10.1016/j.is.2016.07.009"],"issn":["03064379"],"journaltitle":["Inf. Syst."],"pages":["1–23"],"shorttitle":["Persisting big-data"],"title":["Persisting big-data: The NoSQL landscape"],"volume":["63"]},"creators":{"author":[{"lastName":"Corbellini","firstName":"Alejandro"},{"lastName":"Mateos","firstName":"Cristian"},{"lastName":"Zunino","firstName":"Alejandro"},{"lastName":"Godoy","firstName":"Daniela"},{"lastName":"Schiaffino","firstName":"Silvia"}]},"sentenceCased":true},{"key":"corradiniFloWareModeldrivenApproach2023","type":"article","fields":{"langid":["english"],"abstract":["The relevance of IoT-based solutions in everyday life is continuously increasing. The capability to sense the world, activate computation based on data gathered by sensors, and possibly produce reactions on the world itself results in an almost neverending identification of novel IoT solutions and application scenarios. Nonetheless, IoT’s intrinsic nature, which includes a high degree of variability in used devices, data formats, resources, and communication protocols, complicates the design, development, reuse and customisation of IoT-based software systems. In addition, customers require personalised solutions strongly based on their specific requirements. Reducing the complexity of building customised solutions and increasing the reusability of developed artefacts are among the topmost challenges for enterprises and IoT application developers. Upon these challenges, we propose a model-driven approach organising the modelling and development of IoT applications in different steps, handling the complexity in representing the IoT domain variability, and empowering the reusability of design decisions and artefacts to simplify the derivation of customised IoT applications. Our proposal is named FloWare. It follows the typical path of an MDE solution, providing modelling support through feature models to fully represent and handle the possible variability of devices in a specific IoT application domain. Once a specific configuration has been selected, this will be complemented with specific information about the deployment context to automatically derive fragments of the IoT applications, that will be successively combined by the developer within a low-code development environment. The approach is fully supported by a toolchain that has been released for public use."],"author":["Corradini, Flavio","Fedeli, Arianna","Fornari, Fabrizio","Polini, Andrea","Re, Barbara"],"date":["2023-02"],"doi":["10.1007/s10270-022-01026-9"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"keywords":["LOGSEQ"],"number":["1"],"pages":["131–158"],"shorttitle":["FloWare"],"title":["FloWare: A model-driven approach fostering reuse and customisation in IoT applications modelling and development"],"volume":["22"]},"creators":{"author":[{"lastName":"Corradini","firstName":"Flavio"},{"lastName":"Fedeli","firstName":"Arianna"},{"lastName":"Fornari","firstName":"Fabrizio"},{"lastName":"Polini","firstName":"Andrea"},{"lastName":"Re","firstName":"Barbara"}]},"sentenceCased":true},{"key":"correaCoupledEvolutionMetamodels2013","type":"article","fields":{"author":["Correa, Chessman","Toacy, Oliveira","Claudia, Werner"],"date":["2013"],"title":["Towards Coupled Evolution of Metamodels, Models, Graph-Based Transformations and Traceability Links"]},"creators":{"author":[{"lastName":"Correa","firstName":"Chessman"},{"lastName":"Toacy","firstName":"Oliveira"},{"lastName":"Claudia","firstName":"Werner"}]}},{"key":"cosentinoSystematicMappingStudy2017","type":"article","fields":{"author":["Cosentino, Valerio","Canovas Izquierdo, Javier L.","Cabot, Jordi"],"date":["2017"],"doi":["10.1109/ACCESS.2017.2682323"],"issn":["2169-3536"],"journaltitle":["IEEE Access"],"note":["TL;DR \n\nThe high activity of research work around the field of Open Source collaboration, especially in the software domain, revealed a set of shortcomings and proposed some actions to mitigate them."],"pages":["7173–7192"],"title":["A Systematic Mapping Study of Software Development With GitHub"],"volume":["5"]},"creators":{"author":[{"lastName":"Cosentino","firstName":"Valerio"},{"lastName":"Canovas Izquierdo","firstName":"Javier L."},{"lastName":"Cabot","firstName":"Jordi"}]}},{"key":"cosmoSoftwareHeritageWhy","type":"article","fields":{"langid":["english"],"abstract":["Software is now a key component present in all aspects of our society. Its preservation has attracted growing attention over the past years within the digital preservation community. We claim that source code—the only representation of software that contains human readable knowledge—is a precious digital object that needs special handling: it must be a first class citizen in the preservation landscape and we need to take action immediately, given the increasingly more frequent incidents that result in permanent losses of source code collections. In this paper we present Software Heritage, an ambitious initiative to collect, preserve, and share the entire corpus of publicly accessible software source code. We discuss the archival goals of the project, its use cases and role as a participant in the broader digital preservation ecosystem, and detail its key design decisions. We also report on the project road map and the current status of the Software Heritage archive that, as of early 2017, has collected more than 3 billion unique source code files and 700 million commits coming from more than 50 million software development projects. ACM Reference Format: Roberto Di Cosmo and Stefano Zacchiroli. 2017. Software Heritage: Why and How to Preserve Software Source Code. In Proceedings of 14th International Conference on Digital Preservation (iPRES2017). ACM, New York, NY, USA, 10 pages."],"author":["Cosmo, Roberto Di","Zacchiroli, Stefano"],"note":["TL;DR \n\nThis paper presents Software Heritage, an ambitious initiative to collect, preserve, and share the entire corpus of publicly accessible software source code, and discusses the archival goals, use cases and role as a participant in the broader digital preservation ecosystem, and detail its key design decisions."],"pages":["10"],"title":["Software Heritage: Why and How to Preserve Software Source Code"]},"creators":{"author":[{"lastName":"Cosmo","firstName":"Roberto Di"},{"lastName":"Zacchiroli","firstName":"Stefano"}]}},{"key":"cossette_seeking_2012","type":"inproceedings","fields":{"langid":["english"],"abstract":["Application programming interfaces (APIs) are a common and industrially-relevant means for third-party software developers to reuse external functionality. Several techniques have been proposed to help migrate client code between library versions with incompatible APIs, but it is not clear how well these perform in an absolute sense. We present a retroactive study into the presence and nature of API incompatibilities between several versions of a set of Java-based software libraries; for each, we perform a detailed, manual analysis to determine what the correct adaptations are to migrate from the older to the newer version. In addition, we investigate whether any of a set of adaptation recommender techniques is capable of identifying the correct adaptations for library migration. We find that a given API incompatibility can typically be addressed by only one or two recommender techniques, but sometimes none serve. Furthermore, those techniques give correct recommendations, on average, in only about 20% of cases."],"author":["Cossette, Bradley E.","Walker, Robert J."],"booktitle":["Procs ACM SIGSOFT 20th Int Symp. Found. Softw. Eng. - FSE 12"],"date":["2012"],"doi":["10.1145/2393596.2393661"],"isbn":["978-1-4503-1614-9"],"location":["Cary, North Carolina"],"nopublisher":["ACM Press"],"nourl":["http://dl.acm.org/citation.cfm?doid=2393596.2393661"],"pages":["1"],"shorttitle":["Seeking the ground truth"],"title":["Seeking the ground truth: A retroactive study on the evolution and migration of software libraries"]},"creators":{"author":[{"lastName":"Cossette","firstName":"Bradley E."},{"lastName":"Walker","firstName":"Robert J."}]},"sentenceCased":true},{"key":"costaModelingIoTApplications2016","type":"inproceedings","fields":{"author":["Costa, Bruno","Pires, Paulo F.","Delicato, Flavia C."],"booktitle":["2016 42th Euromicro Conf. Softw. Eng. Adv. Appl. SEAA"],"date":["2016-08"],"doi":["10.1109/SEAA.2016.19"],"eventtitle":["2016 42th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)"],"isbn":["978-1-5090-2820-7"],"location":["Limassol, Cyprus"],"note":["TL;DR \n\nA Model-Based Systems Engineering methodology for IoT application development, focusing on the design phase, is introduced, which aims at helping organizations to develop IoT applications to fully achieve the benefits of this new paradigm."],"pages":["157–164"],"publisher":["IEEE"],"title":["Modeling IoT Applications with SysML4IoT"]},"creators":{"author":[{"lastName":"Costa","firstName":"Bruno"},{"lastName":"Pires","firstName":"Paulo F."},{"lastName":"Delicato","firstName":"Flavia C."}]}},{"key":"CoupledEvolutionModelDriven","type":"online","fields":{"note":["TL;DR \n\nThe authors provide an overview of coupled evolution methods and tools to handle dependencies of model-driven engineering metamodels and how to deal with invalid artifacts."],"title":["Coupled Evolution in Model-Driven Engineering"],"url":["https://ieeexplore-ieee-org.univaq.idm.oclc.org/stamp/stamp.jsp?tp=&arnumber=6336727"],"urldate":["2023-10-03"]},"creators":{}},{"key":"Coutinho2014AnalysisOD","type":"article","fields":{"author":["Coutinho, Ana Emília Victor Barbosa","Cartaxo, Emanuela Gadelha","family=Lima Machado, given=Patrícia Duarte, prefix=de, useprefix=true"],"date":["2014"],"journaltitle":["Softw. Qual. J."],"note":["TL;DR \n\nThe effectiveness of distance functions in the scope of a MBT reduction strategy based on the similarity degree of test cases is investigated and it is shown that the choice of a distance function has little influence on the size of the reduced test suite."],"pages":["407–445"],"title":["Analysis of distance functions for similarity-based test suite reduction in the context of model-based testing"],"volume":["24"]},"creators":{"author":[{"lastName":"Coutinho","firstName":"Ana Emília Victor Barbosa"},{"lastName":"Cartaxo","firstName":"Emanuela Gadelha"},{"lastName":"LimaMachado","firstName":"PatríciaDuarte","prefix":"de","useprefix":true}]},"sentenceCased":true},{"key":"Covington:2016:DNN:2959100.2959190","type":"inproceedings","fields":{"acmid":["2959190"],"author":["Covington, Paul","Adams, Jay","Sargin, Emre"],"booktitle":["Proc. 10th ACM Conf. Recomm. Syst."],"date":["2016"],"isbn":["978-1-4503-4035-9"],"keywords":["deep learning","recommender system","scalability"],"location":["New York, NY, USA"],"nodoi":["10.1145/2959100.2959190"],"note":["TL;DR \n\nThis paper details a deep candidate generation model and then describes a separate deep ranking model and provides practical lessons and insights derived from designing, iterating and maintaining a massive recommendation system with enormous user-facing impact."],"numpages":["8"],"pages":["191–198"],"publisher":["ACM"],"series":["RecSys '16"],"title":["Deep neural networks for YouTube recommendations"],"url":["http://doi.acm.org/10.1145/2959100.2959190"]},"creators":{"author":[{"lastName":"Covington","firstName":"Paul"},{"lastName":"Adams","firstName":"Jay"},{"lastName":"Sargin","firstName":"Emre"}]},"sentenceCased":true},{"key":"coyleEthicalConcernsUnmanned","type":"article","fields":{"author":["Coyle, Eric Joe"],"journaltitle":["age"],"note":["TL;DR \n\nThis paper provides an overview of a new graduate program in unmanned and autonomous systems engineering, and addresses three major ethical issues to be addressed for such a program."],"pages":["1"],"title":["Ethical Concerns of Unmanned and Autonomous Systems in Engineering Programs"],"url":["https://www.asee.org/file_server/papers/attachment/file/0004/3811/ASEE-2014-UNMANNED-ETHICS-final.pdf"],"urldate":["2016-08-21"],"volume":["24"]},"creators":{"author":[{"lastName":"Coyle","firstName":"Eric Joe"}]}},{"key":"Cremonesi:2008:EMC:1468165.1468327","type":"inproceedings","fields":{"acmid":["1468327"],"author":["Cremonesi, Paolo","Turrin, Roberto","Lentini, Eugenio","Matteucci, Matteo"],"booktitle":["Proc. 2008 Int. Conf. Autom. Solut. Cross Media Content Multi-Channel Distrib."],"date":["2008"],"isbn":["978-0-7695-3406-0"],"keywords":["Collaborative","evaluation","knowledge discovery","methodology","naive bayesian networks","recommender systems","svd"],"location":["Washington, DC, USA"],"nodoi":["10.1109/AXMEDIS.2008.13"],"numpages":["8"],"pages":["224–231"],"publisher":["IEEE Computer Society"],"series":["AXMEDIS '08"],"title":["An evaluation methodology for collaborative recommender systems"],"url":["https://doi.org/10.1109/AXMEDIS.2008.13"]},"creators":{"author":[{"lastName":"Cremonesi","firstName":"Paolo"},{"lastName":"Turrin","firstName":"Roberto"},{"lastName":"Lentini","firstName":"Eugenio"},{"lastName":"Matteucci","firstName":"Matteo"}]},"sentenceCased":true},{"key":"cremonesiPerformanceRecommenderAlgorithms2010","type":"inproceedings","fields":{"acmid":["1864721"],"author":["Cremonesi, Paolo","Koren, Yehuda","Turrin, Roberto"],"booktitle":["Proc. Fourth ACM Conf. Recomm. Syst."],"date":["2010"],"isbn":["978-1-60558-906-0"],"keywords":["evaluation","precision","recall","top-n recommendations"],"location":["New York, NY, USA"],"nodoi":["10.1145/1864708.1864721"],"note":["TL;DR \n\nAn extensive evaluation of several state-of-the art recommender algorithms suggests that algorithms optimized for minimizing RMSE do not necessarily perform as expected in terms of top-N recommendation task, and new variants of two collaborative filtering algorithms are offered."],"numpages":["8"],"pages":["39–46"],"publisher":["ACM"],"series":["RecSys '10"],"title":["Performance of recommender algorithms on top-n recommendation tasks"],"url":["http://doi.acm.org/10.1145/1864708.1864721"]},"creators":{"author":[{"lastName":"Cremonesi","firstName":"Paolo"},{"lastName":"Koren","firstName":"Yehuda"},{"lastName":"Turrin","firstName":"Roberto"}]},"sentenceCased":true},{"key":"criadoEnablingReuseStored","type":"article","fields":{"author":["Criado, Javier","Martınez, Salvador","Iribarne, Luis","Cabot, Jordi"],"title":["Enabling the reuse of stored model transformations through annotations"],"url":["http://modeling-languages.com/wp-content/uploads/2015/04/icmt2015.pdf"],"urldate":["2015-05-26"]},"creators":{"author":[{"lastName":"Criado","firstName":"Javier"},{"lastName":"Martınez","firstName":"Salvador"},{"lastName":"Iribarne","firstName":"Luis"},{"lastName":"Cabot","firstName":"Jordi"}]},"sentenceCased":true},{"key":"CROSSMETERQuestionsBegel","type":"online","fields":{"title":["CROSSMETER - Questions from Begel/Zimmermann's ICSE 2014 paper - Google Docs"],"url":["https://docs.google.com/document/d/1jyZJE4xIUsRLHqMqsGjpZDGt9RBGmZAZLh5S_ueTsQQ/edit"],"urldate":["2016-01-22"]},"creators":{},"sentenceCased":true},{"key":"CROSSREC-DATA","type":"article","fields":{"author":["Di Rocco, Juri","Nguyen, Phuong T.","Di Ruscio, Davide"],"date":["2018"],"note":["https://doi.org/10.5281/zenodo.1252848 \n\nhttps://doi.org/10.5281/zenodo.1252848 \n\nhttps://doi.org/10.5281/zenodo.1252848 \n\nhttps://doi.org/10.5281/zenodo.1252848 \n\nhttps://doi.org/10.5281/zenodo.1252848"],"title":["CrossRec tool and evaluation data"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Di Ruscio","firstName":"Davide"}]},"sentenceCased":true},{"key":"Crussell2015AnDarwinSD","type":"article","fields":{"author":["Crussell, Jonathan","Gibler, Clint","Chen, Hao"],"date":["2015"],"journaltitle":["IEEE Trans. Mob. Comput."],"pages":["2007–2019"],"title":["AnDarwin: Scalable detection of android application clones based on semantics"],"volume":["14"]},"creators":{"author":[{"lastName":"Crussell","firstName":"Jonathan"},{"lastName":"Gibler","firstName":"Clint"},{"lastName":"Chen","firstName":"Hao"}]},"sentenceCased":true},{"key":"crussellAndarwinScalableDetection2013","type":"inproceedings","fields":{"author":["Crussell, Jonathan","Gibler, Clint","Chen, Hao"],"booktitle":["Eur. Symp. Res. Comput. Secur."],"date":["2013"],"ids":["Crussell2013"],"pages":["182–199"],"publisher":["Springer"],"shorttitle":["Andarwin"],"title":["Andarwin: Scalable detection of semantically similar android applications"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-40203-6_11"],"urldate":["2017-09-25"]},"creators":{"author":[{"lastName":"Crussell","firstName":"Jonathan"},{"lastName":"Gibler","firstName":"Clint"},{"lastName":"Chen","firstName":"Hao"}]},"sentenceCased":true},{"key":"CSGSSISEAI","type":"online","fields":{"ids":["CSGSSISEAIa,CSGSSISEAIb"],"title":["CS@GSSI - SE-AI Course 2021"],"url":["https://sites.google.com/gssi.it/csgssi/ph-d-program/se-ai-course-2021"],"urldate":["2021-05-07"]},"creators":{}},{"key":"CuadradoBWV22","type":"article","fields":{"langid":["english"],"author":["Cuadrado, Jesús Sánchez","Burgueño, Loli","Wimmer, Manuel","Vallecillo, Antonio"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2022"],"doi":["10.1109/TSE.2020.3011388"],"journaltitle":["IEEE Trans, Softw. Eng,"],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["4"],"pages":["1097–1114"],"timestamp":["Thu, 23 Jun 2022 20:04:59 +0200"],"title":["Efficient execution of ATL model transformations using static analysis and parallelism"],"volume":["48"]},"creators":{"author":[{"lastName":"Cuadrado","firstName":"Jesús Sánchez"},{"lastName":"Burgueño","firstName":"Loli"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Vallecillo","firstName":"Antonio"}]},"sentenceCased":true},{"key":"cuadradoModelFindingEMF2020","type":"article","fields":{"langid":["english"],"abstract":["The EMF framework is the main meta-modelling framework used nowadays. It has a rich ecosystem of plug-ins and tools built with and for it, including the option of enriching meta-models with OCL constraints. However, the EMF ecosystem lacks usable model finding approaches. Given a meta-model, a model finder automatically searches for models that satisfy a given set of formulas (e.g., OCL constraints). This feature can be used for a number of purposes, including model verification and model synthesis. In this paper, we present an approach to support model finding in the EMF ecosystem that is designed to realize several scenarios including model consistency, example generation, partial solution completion and scrolling. Moreover, it allows several OCL variants to be plugged-in via an intermediate representation. This approach has been realized in a tool called EFinder. We have assessed the usability of the approach by implementing three advanced application scenarios and evaluated its verification capabilities by analyzing OCL constraints from an external OCL dataset containing about 300 valid EMF/OCL specifications. Our model finder is able to process about 65% of these EMF/OCL models."],"author":["Cuadrado, Jesús Sánchez","Gogolla, Martin"],"date":["2020"],"doi":["10.5381/jot.2020.19.2.a10"],"issn":["1660-1769"],"journaltitle":["JOT"],"number":["2"],"pages":["10:1"],"title":["Model Finding in the EMF Ecosystem."],"volume":["19"]},"creators":{"author":[{"lastName":"Cuadrado","firstName":"Jesús Sánchez"},{"lastName":"Gogolla","firstName":"Martin"}]}},{"key":"cuadradoVerifiedCatalogueOCL2019","type":"article","fields":{"langid":["english"],"abstract":["OCL is widely used by model-driven engineering tools with different purposes like writing integrity constraints for meta-models, as a navigation language in model transformation languages or to define transformation specifications. Another scenario is the automatic generation of OCL code by a repair system. These generated expressions tend to be complex and unreadable due to the nature of the generative process. However, to be useful this code should be simple and resemble manually written code as much as possible when a developer must manually maintain it. There exists refactorings approaches for manually written OCL code, but there is no tool targeted to the optimisation of OCL expressions which have been automatically synthesised. Moreover, there is no available catalogue of OCL refactorings which can be integrated seamlessly into a tool. In this work, we contribute a set of refactorings intended to optimise OCL expressions, notably covering cases likely to arise in generated OCL code. We also contribute the implementation of these refactorings, built as a generic transformation catalogue using bentō, a transformation reuse tool for ATL. This makes it possible to specialise the catalogue for any OCL variant based on Ecore. Moreover, we propose a method to verify the correctness of the implemented catalogue based on translation validation and model finding. We describe the design and implementation of the catalogue and evaluate it by optimising a large amount of OCL expressions and proving the correctness of each optimisation execution. We also derive working implementations of the catalogue for ATL, EMF/OCL and SimpleOCL made available in a tool called BeautyOCL."],"author":["Cuadrado, Jesús Sánchez"],"date":["2019-07-02"],"doi":["10.1007/s10270-019-00740-1"],"issn":["1619-1374"],"journaltitle":["Softw Syst Model"],"note":["TL;DR \n\nA set of refactorings intended to optimise OCL expressions, notably covering cases likely to arise in generated OCL code, are contributed and a method to verify the correctness of the implemented catalogue based on translation validation and model finding is proposed."],"title":["A verified catalogue of OCL optimisations"]},"creators":{"author":[{"lastName":"Cuadrado","firstName":"Jesús Sánchez"}]},"sentenceCased":true},{"key":"Cui20211223","type":"article","fields":{"langid":["chinese"],"abbrev_source_title":["Kongzhi yu Juece Control Decis"],"affiliation":["Dolinks School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China"],"author":["Cui, J.-S.","Lyu, Y.","Xu, Z.-H."],"coden":["KYJUE"],"correspondence_address1":["Cui, J.-S.; Dolinks School of Economics and Management, China; email: cuijs@manage.ustb.edu.cn"],"date":["2021"],"document_type":["Article"],"doi":["10.13195/j.kzyjc.2019.0993"],"issn":["10010920"],"journaltitle":["Kongzhi Yu JueceControl Decis."],"note":["cited By 1"],"number":["5"],"pages":["1223–1231"],"publisher":["Northeast University"],"source":["Scopus"],"title":["Recommending best suitable metaheuristic based on landmarking feature and meta-learning approach [基于地标特征和元学习方法推荐最适用优化算法]"],"volume":["36"]},"creators":{"author":[{"lastName":"Cui","firstName":"J.-S."},{"lastName":"Lyu","firstName":"Y."},{"lastName":"Xu","firstName":"Z.-H."}]}},{"key":"Cui2021788","type":"article","fields":{"abstract":["In this article, we investigate jointly sparse signal recovery and jointly sparse support recovery in Multiple Measurement Vector (MMV) models for complex signals, which arise in many applications in communications and signal processing. Recent key applications include channel estimation and device activity detection in MIMO-based grant-free random access which is proposed to support massive machine-type communications (mMTC) for Internet of Things (IoT). Utilizing techniques in compressive sensing, optimization and deep learning, we propose two model-driven approaches, based on the standard auto-encoder structure for real numbers. One is to jointly design the common measurement matrix and jointly sparse signal recovery method, and the other aims to jointly design the common measurement matrix and jointly sparse support recovery method. The proposed model-driven approaches can effectively utilize features of sparsity patterns in designing common measurement matrices and adjusting model-driven decoders, and can greatly benefit from the underlying state-of-the-art recovery methods with theoretical guarantee. Hence, the obtained common measurement matrices and recovery methods can significantly outperform the underlying advanced recovery methods. We conduct extensive numerical results on channel estimation and device activity detection in MIMO-based grant-free random access. The numerical results show that the proposed approaches provide pilot sequences and channel estimation or device activity detection methods which can achieve higher estimation or detection accuracy with shorter computation time than existing ones. Furthermore, the numerical results explain how such gains are achieved via the proposed approaches. © 1983-2012 IEEE."],"art_number":["9174792"],"author":["Cui, Y.","Li, S.","Zhang, W."],"coden":["ISACE"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/JSAC.2020.3018802"],"issn":["07338716"],"journaltitle":["IEEE J. Sel. Areas Commun."],"note":["cited By 8 \n\nTL;DR \n\nThe numerical results show that the proposed approaches provide pilot sequences and channel estimation or device activity detection methods which can achieve higher estimation or detection accuracy with shorter computation time than existing ones."],"number":["3"],"pages":["788–803"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Jointly sparse signal recovery and support recovery via deep learning with applications in MIMO-Based grant-free random access"],"volume":["39"]},"creators":{"author":[{"lastName":"Cui","firstName":"Y."},{"lastName":"Li","firstName":"S."},{"lastName":"Zhang","firstName":"W."}]},"sentenceCased":true},{"key":"Cunningham2018","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Des. Eng. Tech. Conf."],"affiliation":["Department of Computer Science and Engineering, Penn State University University, Park, PA 16802, United States; Department of Engineering Design and Industrial and Manufacturing Engineering, Penn State University University, Park, PA 16802, United States"],"author":["Cunningham, J.","Tucker, C.S."],"date":["2018"],"document_type":["Conference Paper"],"doi":["10.1115/DETC201886299"],"isbn":["978-0-7918-5176-0"],"keywords":["notion"],"note":["cited By 3 \n\nTL;DR \n\nThis work presents a deep neural network method for approximating the performance of generated design concepts by discovering the visual features of a design that correlated to good and bad performance by simply observing the pixels of images of many candidate designs and their corresponding performance in a simulation environment."],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the ASME Design Engineering Technical Conference"],"source":["Scopus"],"title":["A validation neural network (VNN) metamodel for predicting the performance of deep generative designs"],"volume":["2B-2018"]},"creators":{"author":[{"lastName":"Cunningham","firstName":"J."},{"lastName":"Tucker","firstName":"C.S."}]},"sentenceCased":true},{"key":"cusumanoSelfdrivingVehicleTechnology2020","type":"article","fields":{"langid":["english"],"author":["Cusumano, Michael A."],"date":["2020-09-23"],"doi":["10.1145/3417074"],"issn":["0001-0782, 1557-7317"],"journaltitle":["Commun. ACM"],"number":["10"],"pages":["20–22"],"shorttitle":["Self-driving vehicle technology"],"title":["Self-driving vehicle technology: Progress and promises"],"volume":["63"]},"creators":{"author":[{"lastName":"Cusumano","firstName":"Michael A."}]},"sentenceCased":true},{"key":"CyberPhysicalSystemsConcept","type":"online","fields":{"title":["Cyber-Physical Systems - a Concept Map"],"url":["http://cyberphysicalsystems.org/"],"urldate":["2015-10-09"]},"creators":{}},{"key":"D'Aloisio2022291","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc Int Conf Software Eng"],"affiliation":["University of l'Aquila, Italy"],"author":["D'Aloisio, G."],"coden":["PCSED"],"correspondence_address1":["D'aloisio, G.; University of l'AquilaItaly; email: giordano.daloisio@graduate.univaq.it"],"date":["2022"],"document_type":["Conference Paper"],"doi":["10.1109/ICSE-Companion55297.2022.9793779"],"isbn":["978-1-66549-598-1"],"issn":["02705257"],"note":["cited By 0 \n\nTL;DR \n\nThis research project will define a new software engineering approach for data-science systems development that assures compliance with quality requirements and implement tools that guide IT professionals and researchers in the realization of ML-based data science pipelines since the requirement engineering."],"pages":["291–293"],"publisher":["IEEE Computer Society"],"series":["Proceedings - International Conference on Software Engineering"],"source":["Scopus"],"title":["Quality-driven machine learning-based data science pipeline realization: A software engineering approach"]},"creators":{"author":[{"lastName":"D'Aloisio","firstName":"G."}]},"sentenceCased":true},{"key":"daFonseca2017950","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Build. Simul. Conf. Proc."],"affiliation":["Environmental Comfort Laboratory, Federal University of Santa Catarina, Brazil; California Lighting Technology Center, UC Davis, United States"],"author":["family=Fonseca, given=R.W., prefix=da, useprefix=true","Pereira, F.O.R.","Papamichael, K."],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.26868/25222708.2017.570"],"editor":["Barnaby C.S., Wetter M."],"isbn":["978-1-5108-7067-3"],"issn":["25222708"],"note":["cited By 0"],"pages":["950–959"],"publisher":["International Building Performance Simulation Association"],"series":["Building Simulation Conference Proceedings"],"source":["Scopus"],"title":["The potential of artificial neural networks to model daylight harvesting in buildings located in different climate zones"],"volume":["2"]},"creators":{"author":[{"lastName":"Fonseca","firstName":"R.W.","prefix":"da","useprefix":true},{"lastName":"Pereira","firstName":"F.O.R."},{"lastName":"Papamichael","firstName":"K."}],"editor":[{"lastName":"Barnaby C.S.","firstName":"Wetter M."}]},"sentenceCased":true},{"key":"dagenaisMovingNewSoftware2010","type":"inproceedings","fields":{"acmid":["1806842"],"author":["Dagenais, Barthélémy","Ossher, Harold","Bellamy, Rachel K. E.","Robillard, Martin P.","family=Vries, given=Jacqueline P., prefix=de, useprefix=true"],"booktitle":["Proc. 32Nd ACMIEEE Int. Conf. Softw. Eng. - Vol. 1"],"date":["2010"],"ids":["Dagenais:2010:MNS:1806799.1806842"],"isbn":["978-1-60558-719-6"],"location":["New York, NY, USA"],"nodoi":["10.1145/1806799.1806842"],"note":["TL;DR \n\nIt is theorized that there are three primary factors that impact the integration experience of newcomers: early experimentation, internalizing structures and cultures, and progress validation."],"numpages":["10"],"pages":["275–284"],"pagetotal":["10"],"publisher":["ACM"],"series":["ICSE '10"],"title":["Moving into a new software project landscape"],"url":["http://doi.acm.org/10.1145/1806799.1806842"]},"creators":{"author":[{"lastName":"Dagenais","firstName":"Barthélémy"},{"lastName":"Ossher","firstName":"Harold"},{"lastName":"Bellamy","firstName":"Rachel K. E."},{"lastName":"Robillard","firstName":"Martin P."},{"lastName":"Vries","firstName":"JacquelineP.","prefix":"de","useprefix":true}]},"sentenceCased":true},{"key":"Dai2017344","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Comput.-Aided Civ. Infrastruct. Eng."],"affiliation":["School of Civil Engineering, Harbin Institute of Technology, Harbin, China and, Key Lab of Structures Dynamic Behavior and Control (Harbin Institute of Technology), Ministry of Education, Harbin, 150090, China"],"author":["Dai, H.","Cao, Z."],"coden":["CCIEF"],"correspondence_address1":["Dai, H.; School of Civil Engineering, China; email: hzdai@hit.edu.cn"],"date":["2017"],"document_type":["Article"],"doi":["10.1111/mice.12257"],"issn":["10939687"],"journaltitle":["Comput.-Aided Civ. Infrastruct. Eng."],"note":["cited By 95"],"number":["4"],"pages":["344–357"],"publisher":["Blackwell Publishing Inc."],"source":["Scopus"],"title":["A wavelet support vector machine-based neural network metamodel for structural reliability assessment"],"volume":["32"]},"creators":{"author":[{"lastName":"Dai","firstName":"H."},{"lastName":"Cao","firstName":"Z."}]},"sentenceCased":true},{"key":"Dalianis2018","type":"incollection","fields":{"abstract":["This chapter describes the metrics for the evaluation of information retrieval and natural language processing systems, the annotation techniques and evaluation metrics and the concepts of training, development and evaluations sets for information retrieval systems."],"author":["Dalianis, Hercules"],"booktitle":["Clinical text mining: Secondary use of electronic patient records"],"date":["2018"],"doi":["10.1007/978-3-319-78503-5_6"],"isbn":["978-3-319-78503-5"],"location":["Cham"],"note":["TL;DR \n\nThis chapter describes the metrics for the evaluation of information retrieval and natural language processing systems, the annotation techniques and evaluation metrics and the concepts of training, development and evaluations sets for information retrieval systems."],"pages":["45–53"],"publisher":["Springer International Publishing"],"title":["Evaluation metrics and evaluation"]},"creators":{"author":[{"lastName":"Dalianis","firstName":"Hercules"}]},"sentenceCased":true},{"key":"daliborGeneratingCustomizedLowcode2022","type":"article","fields":{"langid":["english"],"abstract":["A digital twin improves our use of a cyber–physical system and understanding of its emerging behavior. To this effect, a digital twin is to be developed and configured and potentially also operated by domain experts, who rarely have a professional software engineering background and for whom easy access and support, e.g., in form of low-code platforms are missing. In this paper, we report on an integrated method for the modeldriven engineering of low-code development platforms for digital twins that enables domain experts to create and operate digital twins for cyber–physical systems using the most appropriate modeling languages. The foundation of this method is (1) a code generation infrastructure for information systems combined with (2) an extensible base architecture for self-adaptive digital twins and (3) reusable language components for their configuration. Using this method, software engineers first configure the information system with the required modeling languages to generate the low-code development platform for digital twins before domain experts leverage the generated platform to create digital twins. This two-step method facilitates creating tailored low-code development platforms as well as creating and operating customized digital twins for a variety of applications."],"author":["Dalibor, Manuela","Heithoff, Malte","Michael, Judith","Netz, Lukas","Pfeiffer, Jérôme","Rumpe, Bernhard","Varga, Simon","Wortmann, Andreas"],"date":["2022-06"],"doi":["10.1016/j.cola.2022.101117"],"issn":["25901184"],"journaltitle":["Journal of Computer Languages"],"keywords":["LOGSEQ"],"pages":["101117"],"title":["Generating customized low-code development platforms for digital twins"],"volume":["70"]},"creators":{"author":[{"lastName":"Dalibor","firstName":"Manuela"},{"lastName":"Heithoff","firstName":"Malte"},{"lastName":"Michael","firstName":"Judith"},{"lastName":"Netz","firstName":"Lukas"},{"lastName":"Pfeiffer","firstName":"Jérôme"},{"lastName":"Rumpe","firstName":"Bernhard"},{"lastName":"Varga","firstName":"Simon"},{"lastName":"Wortmann","firstName":"Andreas"}]},"sentenceCased":true},{"key":"DALOISIO2023103226","type":"article","fields":{"abstract":["Nowadays assuring that search and recommendation systems are fair and do not apply discrimination among any kind of population has become of paramount importance. This is also highlighted by some of the sustainable development goals proposed by the United Nations. Those systems typically rely on machine learning algorithms that solve the classification task. Although the problem of fairness has been widely addressed in binary classification, unfortunately, the fairness of multi-class classification problem needs to be further investigated lacking well-established solutions. For the aforementioned reasons, in this paper, we present the Debiaser for Multiple Variables (DEMV), an approach able to mitigate unbalanced groups bias (i.e., bias caused by an unequal distribution of instances in the population) in both binary and multi-class classification problems with multiple sensitive variables. The proposed method is compared, under several conditions, with a set of well-established baselines using different categories of classifiers. At first we conduct a specific study to understand which is the best generation strategies and their impact on DEMVs ability to improve fairness. Then, we evaluate our method on a heterogeneous set of datasets and we show how it overcomes the established algorithms of the literature in the multi-class classification setting and in the binary classification setting when more than two sensitive variables are involved. Finally, based on the conducted experiments, we discuss strengths and weaknesses of our method and of the other baselines."],"author":["family=Aloisio, given=Giordano, prefix=d', useprefix=true","D'Angelo, Andrea","Di Marco, Antinisca","Stilo, Giovanni"],"date":["2023"],"doi":["10.1016/j.ipm.2022.103226"],"issn":["0306-4573"],"journaltitle":["Inf. Process. Manag."],"keywords":["Bias and Fairness","Equality","Machine learning","Multi-class classification","Preprocessing algorithm"],"number":["2"],"pages":["103226"],"title":["Debiaser for Multiple Variables to enhance fairness in classification tasks"],"volume":["60"]},"creators":{"author":[{"lastName":"Aloisio","firstName":"Giordano","prefix":"d'","useprefix":true},{"lastName":"D'Angelo","firstName":"Andrea"},{"lastName":"Di Marco","firstName":"Antinisca"},{"lastName":"Stilo","firstName":"Giovanni"}]},"sentenceCased":true},{"key":"dalpiazNaturalLanguageProcessing2018","type":"article","fields":{"abstract":["As part of the growing interest in natural language processing for requirements engineering (RE), RE researchers, computational linguists, and industry practitioners met at the First Workshop on Natural Language Processing for Requirements Engineering (NLP4RE 18). This article summarizes the workshop and presents an overview of the discussion held on the field’s future. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Dalpiaz, F.","Ferrari, A.","Franch, X.","Palomares, C."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571242"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"note":["TL;DR \n\nThis article summarizes the workshop and presents an overview of the discussion held on the field’s future at the First Workshop on Natural Language Processing for Requirements Engineering (NLP4RE 18)."],"number":["5"],"pages":["115–119"],"shorttitle":["Natural Language Processing for Requirements Engineering"],"title":["Natural Language Processing for Requirements Engineering: The Best Is Yet to Come"],"volume":["35"]},"creators":{"author":[{"lastName":"Dalpiaz","firstName":"F."},{"lastName":"Ferrari","firstName":"A."},{"lastName":"Franch","firstName":"X."},{"lastName":"Palomares","firstName":"C."}]}},{"key":"damevskiMiningSequencesDeveloper2017","type":"article","fields":{"author":["Damevski, Kostadin","Shepherd, David C.","Schneider, Johannes","Pollock, Lori"],"date":["2017-04-01"],"doi":["10.1109/TSE.2016.2592905"],"issn":["0098-5589, 1939-3520"],"journaltitle":["IEEE Trans. Softw. Eng."],"note":["TL;DR \n\nThis paper identifies usage patterns and smells that contribute to the understanding of the usability of Visual Studio for debugging, code search, and active file navigation, and, more broadly, to theUnderstanding of developer behavior during these software development activities."],"number":["4"],"pages":["359–371"],"title":["Mining Sequences of Developer Interactions in Visual Studio for Usage Smells"],"volume":["43"]},"creators":{"author":[{"lastName":"Damevski","firstName":"Kostadin"},{"lastName":"Shepherd","firstName":"David C."},{"lastName":"Schneider","firstName":"Johannes"},{"lastName":"Pollock","firstName":"Lori"}]}},{"key":"dammFormalSemanticsTraffic2018","type":"incollection","fields":{"author":["Damm, Werner","Möhlmann, Eike","Peikenkamp, Thomas","Rakow, Astrid"],"booktitle":["Principles of Modeling"],"date":["2018"],"doi":["10.1007/978-3-319-95246-8_11"],"editor":["Lohstroh, Marten","Derler, Patricia","Sirjani, Marjan"],"isbn":["978-3-319-95245-1 978-3-319-95246-8"],"keywords":["⛔ No INSPIRE recid found"],"location":["Cham"],"note":["TL;DR \n\nThis paper paves the way for a future scenario catalog-based approach to acceptance testing for highly autonomous vehicles by providing a rigorous formal semantics for a visual specification language of traffic sequence charts to be used for building the scenario catalog."],"pages":["182–205"],"publisher":["Springer International Publishing"],"title":["A Formal Semantics for Traffic Sequence Charts"],"volume":["10760"]},"creators":{"author":[{"lastName":"Damm","firstName":"Werner"},{"lastName":"Möhlmann","firstName":"Eike"},{"lastName":"Peikenkamp","firstName":"Thomas"},{"lastName":"Rakow","firstName":"Astrid"}],"editor":[{"lastName":"Lohstroh","firstName":"Marten"},{"lastName":"Derler","firstName":"Patricia"},{"lastName":"Sirjani","firstName":"Marjan"}]}},{"key":"Dang201415","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Simul. Model. Pract. Theory"],"affiliation":["Faculty of Mechanical Engineering, Nha Trang University, 2 Nguyen Dinh Chieu Street, Nha Trang City, Khanh Hoa 57000, Viet Nam"],"author":["Dang, X.-P."],"correspondence_address1":["Dang, X.-P.; Faculty of Mechanical Engineering, 2 Nguyen Dinh Chieu Street, Nha Trang City, Khanh Hoa 57000, Viet Nam; email: phuongdx@ntu.edu.vn"],"date":["2014"],"document_type":["Article"],"doi":["10.1016/j.simpat.2013.11.003"],"issn":["1569190X"],"journaltitle":["Simul. Model. Pract. Theory"],"note":["cited By 99"],"pages":["15–27"],"source":["Scopus"],"title":["General frameworks for optimization of plastic injection molding process parameters"],"volume":["41"]},"creators":{"author":[{"lastName":"Dang","firstName":"X.-P."}]},"sentenceCased":true},{"key":"Dang202015","type":"inproceedings","fields":{"abstract":["In recent years, Artificial Intelligence has disruptively changed information technology and software engineering with a proliferation of technologies and applications based-on it. However, recent researches show that AI models in general and the most greatest invention since sliced bread-Deep Learning models in particular, are vulnerable to being hacked and can be misused for bad purposes. In this paper, we carry out a brief review of data poisoning attack-one of the two recently dangerous emerging attacks-and the state-of-The-Art defense methods for this problem. Finally, we discuss current challenges and future developments. © 2020 IEEE."],"art_number":["9353086"],"author":["Dang, T.K.","Truong, P.T.T.","Tran, P.T."],"author_keywords":["Adversarial Machine Learning; Poisoning Attack; Secure Learning; Security in Deep Learning"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/ACOMP50827.2020.00010"],"editor":["Le L.-S., Marchese M., Toulouse M., Tran K.D., Dao B."],"isbn":["978-1-72818-167-7"],"keywords":["Application programs","Deep learning","Deep neural networks","Learning models","Network security","Neural networks","Poisoning attacks","Recent researches","State of the art","Technologies and applications"],"note":["cited By 4 \n\nTL;DR \n\nA brief review of data poisoning attack - one of the two recently dangerous emerging attacks - and the state-of-the-art defense methods for this problem are carried out."],"pages":["15–22"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2020 International Conference on Advanced Computing and Applications, ACOMP 2020"],"source":["Scopus"],"title":["Data poisoning attack on deep neural network and some defense methods"]},"creators":{"author":[{"lastName":"Dang","firstName":"T.K."},{"lastName":"Truong","firstName":"P.T.T."},{"lastName":"Tran","firstName":"P.T."}],"editor":[{"lastName":"Le L.-S.","suffix":"Marchese M.","firstName":"Toulouse M., Tran K.D., Dao B."}]},"sentenceCased":true},{"key":"DaniaC16","type":"inproceedings","fields":{"langid":["english"],"author":["Dania, Carolina","Clavel, Manuel"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Proc. ACMIEEE 19th Int. Conf. Model Driven Eng. Lang. Syst. St.-Malo Fr. Oct. 2-7 2016"],"date":["2016"],"editor":["Baudry, Benoit","Combemale, Benoît"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["65–75"],"publisher":["ACM"],"timestamp":["Tue, 06 Nov 2018 16:57:17 +0100"],"title":["OCL2MSFOL: A mapping to many-sorted first-order logic for efficiently checking the satisfiability of OCL constraints"],"url":["http://dl.acm.org/citation.cfm?id=2976774"]},"creators":{"author":[{"lastName":"Dania","firstName":"Carolina"},{"lastName":"Clavel","firstName":"Manuel"}],"editor":[{"lastName":"Baudry","firstName":"Benoit"},{"lastName":"Combemale","firstName":"Benoît"}]},"sentenceCased":true},{"key":"danielUMLtoGraphDBMappingConceptual2016","type":"incollection","fields":{"langid":["english"],"abstract":["The need to store and manipulate large volume of (unstructured) data has led to the development of several NoSQL databases for better scalability. Graph databases are a particular kind of NoSQL databases that have proven their efficiency to store and query highly interconnected data, and have become a promising solution for multiple applications. While the mapping of conceptual schemas to relational databases is a well-studied field of research, there are only few solutions that target conceptual modeling for NoSQL databases and even less focusing on graph databases. This is specially true when dealing with the mapping of business rules and constraints in the conceptual schema. In this article we describe a mapping from UML/OCL conceptual schemas to Blueprints, an abstraction layer on top of a variety of graph databases, and Gremlin, a graph traversal language, via an intermediate Graph metamodel. Tool support is fully available."],"author":["Daniel, Gwendal","Sunyé, Gerson","Cabot, Jordi"],"booktitle":["Conceptual Modeling"],"date":["2016"],"doi":["10.1007/978-3-319-46397-1_33"],"editor":["Comyn-Wattiau, Isabelle","Tanaka, Katsumi","Song, Il-Yeol","Yamamoto, Shuichiro","Saeki, Motoshi"],"isbn":["978-3-319-46396-4 978-3-319-46397-1"],"location":["Cham"],"note":["TL;DR \n\nThis article describes a mapping from UML/OCL conceptual schemas to Blueprints, an abstraction layer on top of a variety of graph databases, and Gremlin, a graph traversal language, via an intermediate Graph metamodel."],"pages":["430–444"],"publisher":["Springer International Publishing"],"shorttitle":["UMLtoGraphDB"],"title":["UMLtoGraphDB: Mapping Conceptual Schemas to Graph Databases"],"volume":["9974"]},"creators":{"author":[{"lastName":"Daniel","firstName":"Gwendal"},{"lastName":"Sunyé","firstName":"Gerson"},{"lastName":"Cabot","firstName":"Jordi"}],"editor":[{"lastName":"Comyn-Wattiau","firstName":"Isabelle"},{"lastName":"Tanaka","firstName":"Katsumi"},{"lastName":"Song","firstName":"Il-Yeol"},{"lastName":"Yamamoto","firstName":"Shuichiro"},{"lastName":"Saeki","firstName":"Motoshi"}]}},{"key":"Danvin2019","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["AIAA Aviation Forum"],"affiliation":["CEA-CESTA, 15 avenue des Sablières, CS 60001, Le Barp Cedex, 33114, France; Von Karman Institute for Fluid Dynamics, 72 Chaussée de Waterloo B-1640, Rhode-Saint-Genèse, Belgium"],"author":["Danvin, F.","Olazabal-Loume, M.","Pinna, F."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.2514/6.2019-2837"],"isbn":["978-1-62410-589-0"],"note":["cited By 3"],"page_count":["14"],"publisher":["American Institute of Aeronautics and Astronautics Inc, AIAA"],"series":["AIAA Aviation 2019 Forum"],"source":["Scopus"],"title":["Laminar to turbulent transition prediction in hypersonic flows with neural networks committee"]},"creators":{"author":[{"lastName":"Danvin","firstName":"F."},{"lastName":"Olazabal-Loume","firstName":"M."},{"lastName":"Pinna","firstName":"F."}]},"sentenceCased":true},{"key":"Daosabah2021324","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Int. J. Web Eng. Technol."],"affiliation":["IMS Team, ADMIR Laboratory, Rabat IT Centre, ENSIAS, Mohammed V University, Rabat, Morocco"],"author":["Daosabah, A.","Guermah, H.","Nassar, M."],"correspondence_address1":["Daosabah, A.; IMS Team, Morocco; email: a.daosabah@gmail.com"],"date":["2021"],"document_type":["Article"],"doi":["10.1504/IJWET.2021.122768"],"issn":["14761289"],"journaltitle":["Int. J. Web Eng. Technol."],"note":["cited By 1"],"number":["4"],"pages":["324–354"],"publisher":["Inderscience Publishers"],"source":["Scopus"],"title":["Dynamic composition of services: An approach driven by the user’s intention and context"],"volume":["16"]},"creators":{"author":[{"lastName":"Daosabah","firstName":"A."},{"lastName":"Guermah","firstName":"H."},{"lastName":"Nassar","firstName":"M."}]},"sentenceCased":true},{"key":"daSilva201915","type":"inproceedings","fields":{"abstract":["To turn big data into actionable knowledge, the adoption of machine learning (ML) methods has proven to be one of the de facto approaches. When elaborating an appropriate ML model for a given task, one typically builds many models and generates several data artifacts. Given the amount of information associated with the developed models performance, their appropriate selection is often difficult. Therefore, appropriately comparing a set of competitive ML models and choosing one according to an arbitrary set of user metrics require systematic solutions. In particular, ML model management is a promising research direction for a more systematic and comprehensive approach for machine learning model selection. Therefore, in this paper, we introduce a conceptual model for ML development. Based on this conceptualization, we introduce our vision toward a knowledge-based model management system oriented to model selection. Copyright © 2019 for this paper by its authors."],"author":["family=Silva, given=D.N.R., prefix=da, useprefix=true","Simões, A.","Cardoso, C.","family=Oliveira, given=D.E.M., prefix=de, useprefix=true","Rittmeyer, J.N.","Wehmuth, K.","Lustosa, H.","Pereira, R.S.","Souto, Y.","Vignoli, L.E.G.","Salles, R.","family=Heleno, S.C., given=Jr., given-i=Jr, prefix=de, useprefix=true","Ziviani, A.","Ogasawara, E.","Delicato, F.C.","family=Pires, given=P.F., prefix=de, useprefix=true","family=Pinto, given=H.L.C.P., prefix=da, useprefix=true","Maia, L.","Porto, F."],"date":["2019"],"document_type":["Conference Paper"],"editor":["Panach J.I., Guizzardi R., Claro D.B."],"issn":["16130073"],"note":["cited By 0"],"pages":["15–27"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"source":["Scopus"],"title":["A conceptual vision toward the management of machine learning models"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074090321&partnerID=40&md5=71c78c0900e41656c1b6f88703cb4f35"],"volume":["2469"]},"creators":{"author":[{"lastName":"Silva","firstName":"D.N.R.","prefix":"da","useprefix":true},{"lastName":"Simões","firstName":"A."},{"lastName":"Cardoso","firstName":"C."},{"lastName":"Oliveira","firstName":"D.E.M.","prefix":"de","useprefix":true},{"lastName":"Rittmeyer","firstName":"J.N."},{"lastName":"Wehmuth","firstName":"K."},{"lastName":"Lustosa","firstName":"H."},{"lastName":"Pereira","firstName":"R.S."},{"lastName":"Souto","firstName":"Y."},{"lastName":"Vignoli","firstName":"L.E.G."},{"lastName":"Salles","firstName":"R."},{"lastName":"family=Heleno","suffix":"S.C.","firstName":"given=Jr., given-i=Jr, prefix=de, useprefix=true"},{"lastName":"Ziviani","firstName":"A."},{"lastName":"Ogasawara","firstName":"E."},{"lastName":"Delicato","firstName":"F.C."},{"lastName":"Pires","firstName":"P.F.","prefix":"de","useprefix":true},{"lastName":"Pinto","firstName":"H.L.C.P.","prefix":"da","useprefix":true},{"lastName":"Maia","firstName":"L."},{"lastName":"Porto","firstName":"F."}],"editor":[{"lastName":"Panach J.I.","suffix":"Guizzardi R.","firstName":"Claro D.B."}]},"sentenceCased":true},{"key":"DataDistributionService","type":"video","fields":{"abstract":["The Data Distribution Service™ (DDS™) is a middleware protocol and API standard for data-centric connectivity from the OMG®. This presentation will cover the use cases of DDS and share example implementations of the DDS standard. DDS integrates the components of a system together, providing low-latency data connectivity, extreme reliability, and a scalable architecture required by business and mission-critical Internet of Things (IoT) applications. In a distributed system, middleware is the software layer that lies between the operating system and applications. It enables the various components of a system to more easily communicate and share data. It simplifies the development of a distributed system by letting software developers focus on the specific purpose of their applications rather than the mechanics of passing information between applications and systems. Presenter: Dr. Gerardo Pardo-Castellote, Co-Chair OMG DDS Special Interest Group, OMG Board of Directors, and CTO, RTI"],"entrysubtype":["video"],"title":["Data Distribution Service™ (DDS™)"],"url":["https://www.youtube.com/watch?v=6iICap5G7rw"],"urldate":["2019-10-20"]},"creators":{}},{"key":"DataistsTaxonomyData","type":"online","fields":{"langid":["american"],"title":["Dataists » A Taxonomy of Data Science"],"url":["http://www.dataists.com/2010/09/a-taxonomy-of-data-science/"],"urldate":["2021-03-18"]},"creators":{}},{"key":"DataMiningCluster","type":"online","fields":{"title":["Data Mining Cluster Analysis"],"url":["http://www.tutorialspoint.com/data_mining/dm_cluster_analysis.htm"],"urldate":["2015-04-22"]},"creators":{}},{"key":"DataModelDesign","type":"online","fields":{"title":["Data Model Design and Best Practices (Part 1) - Talend"],"url":["https://www.talend.com/blog/2017/05/05/data-model-design-best-practices-part-1/"],"urldate":["2018-04-30"]},"creators":{}},{"key":"DataModelingAge","type":"online","fields":{"abstract":["by Jennifer Zaino Hadoop Hbase. MongoDB. Cassandra. Couchbase. Neo4J. Riak. Those are just a few of the sprawling community of NoSQL databases, a category that originally sprang up in response to the internal needs of companies such as Google, Amazon, Facebook, LinkedIn, Yahoo and more – needs for better scalability, lower latency, greater flexibility, and a better price/performance ratio in an age of Big Data and Cloud computing."],"organization":["DATAVERSITY"],"title":["Data Modeling In The Age Of NoSQL And Big Data"],"url":["http://www.dataversity.net/data-modeling-age-nosql-big-data/"],"urldate":["2015-03-26"]},"creators":{}},{"key":"DataModelingDead","type":"online","fields":{"title":["Data Modeling is Dead...Long Live Schema Design! - DATAVERSITY"],"url":["https://www.dataversity.net/data-modeling-dead-long-live-schema-design/"],"urldate":["2019-11-11"]},"creators":{},"sentenceCased":true},{"key":"DataModelingGuidelines","type":"online","fields":{"title":["Data Modeling Guidelines for NoSQL JSON Document Databases | MapR"],"url":["https://mapr.com/blog/data-modeling-guidelines-nosql-json-document-databases/"],"urldate":["2018-05-07"]},"creators":{}},{"key":"DataModelingKey","type":"online","fields":{"abstract":["In Key Value data stores, data is represented as a collection of key–value pairs. The key–value model is one of the simplest non-trivial data models, and richer data models are implemented on top of it. InfoQ spoke with Casey Rosenthal from Basho team about the data modeling concepts and best practices when using these NoSQL databases for data management."],"organization":["InfoQ"],"title":["Data Modeling with Key Value NoSQL Data Stores – Interview with Casey Rosenthal"],"url":["http://www.infoq.com/articles/data-modeling-with-key-value-nosql-data-stores"],"urldate":["2015-03-26"]},"creators":{}},{"key":"DataModelsInternet","type":"online","fields":{"title":["Data models for the Internet of Things"],"url":["http://iot-datamodels.blogspot.it/"],"urldate":["2016-09-27"]},"creators":{},"sentenceCased":true},{"key":"DataPoisoningLLMs","type":"article","fields":{"langid":["english"],"keywords":["LOGSEQ"],"note":["<h1>Annotazioni\n (5/3/2024, 16:02:24)</h1> \n\n- “particular” (“Data Poisoning in LLMs”, p. 1) #ff6666\n <i>You just started, it is not clear what respect to what! </i> \n\n- “simple to contaminate small bits of data” (“Data Poisoning in LLMs”, p. 1) #ffd400\n <i>In what context? </i> \n\n- “Small amounts of poisoned data, which are inputs with triggers (poisoned inputs) combined with attacker-specified outputs (targeted outputs), are injected by the attacker in a data poisoning-based backdoor attack. When the same trigger(s) occur in test inputs during inference, a model trained on a poisoned dataset generates attacker-specified outputs while continuing to function properly on clean inputs” (“Data Poisoning in LLMs”, p. 1) #ffd400\n <i>Can you be more specific with the help of an explanatory example? </i> \n\n- “interfere with the internal learning process that a machine learning model undergoes in order to render it unreliable or incapable of generating the desired output that the system is intended to produce.” (“Data Poisoning in LLMs”, p. 1) #ffd400\n i \n\n- “Research Challenges:” (“Data Poisoning in LLMs”, p. 1) #ff6666\n <i>Can you elaborate and refine these challenges by presenting concrete examples e.g., based on ChatGPT? </i> \n\n- “id ti identify the data which can poisoned to manipulate the outcomes” (“Data Poisoning in LLMs”, p. 1) #ff6666\n i \n\n- “In case of LLMs, unlike the DL/ML models, the input of the data is not clear.” (“Data Poisoning in LLMs”, p. 1) #ffd400\n <i>What do you think? </i> \n\n- “Identifying the input data that can lead to data poisoning in Large Language Models (LLMs) poses a significant research challenge due to the vast and diverse nature of the datasets used to train LLMs.” (“Data Poisoning in LLMs”, p. 2) #ffd400\n <i>If you are referring to ChatGPT or Bird, the problem is even worse: you don't have any access to the training data. </i> \n\n- “He et al. [] r” (“Data Poisoning in LLMs”, p. 2) #ff6666\n <i>All there references are missing. </i> \n\n- “Proposed Methodology” (“Data Poisoning in LLMs”, p. 3) #ff6666\n <i>Can you do a presentation by adding figures distilling the proposed solution's main components? It is necessary to refer to the examples I suggested to add earlier in the document. </i>"],"title":["Data Poisoning in LLMs"]},"creators":{}},{"key":"DataStreamingIoT","type":"online","fields":{"keywords":["Data analysis","data streaming","DONE","internet of things"],"title":["Data Streaming in IoT and Big Data Analytics"],"url":["https://www2.slideshare.net/VincenzoGulisano/data-streaming-in-iot-and-big-data-analytics?qid=9a707bc0-4c0e-41ae-a551-1c8462c82314&v=&b=&from_search=21"],"urldate":["2021-01-05"]},"creators":{}},{"key":"dautovStreamProcessingClustered2022","type":"article","fields":{"langid":["english"],"abstract":["The Internet of Things continuously generates avalanches of raw sensor data to be transferred to the Cloud for processing and storage. Due to network latency and limited bandwidth, this vertical offloading model, however, fails to meet requirements of time-critical data-intensive applications which must act upon generated data with minimum time delays. To address such a limitation, this article proposes a novel distributed architecture enabling stream data processing at the edge of the network, broadening the principle of enabling processing closer to data sources adopted by Fog and Edge Computing. Specifically, this architecture extends the Apache NiFi stream processing middleware with support for run-time clustering of heterogeneous edge devices, such that computational tasks can be horizontally offloaded to peer devices and executed in parallel. As opposed to vertical offloading on the Cloud, the proposed solution does not suffer from increased network latency and is thus able to offer 5-25 times faster response time, as demonstrated by the experiments on a run-time license plate recognition system."],"author":["Dautov, Rustem","Distefano, Salvatore"],"date":["2022-04-01"],"doi":["10.1109/TCC.2020.2983402"],"issn":["2168-7161, 2372-0018"],"journaltitle":["IEEE Trans. Cloud Comput."],"keywords":["LOGSEQ"],"note":["TL;DR \n\nThis architecture extends the Apache NiFi stream processing middleware with support for run-time clustering of heterogeneous edge devices, such that computational tasks can be horizontally offloaded to peer devices and executed in parallel."],"number":["2"],"pages":["885–898"],"title":["Stream Processing on Clustered Edge Devices"],"volume":["10"]},"creators":{"author":[{"lastName":"Dautov","firstName":"Rustem"},{"lastName":"Distefano","firstName":"Salvatore"}]}},{"key":"davidediruscioManagingEvolutionFree2011","type":"inproceedings","fields":{"author":["Davide Di Ruscio","Pelliccione, P"],"booktitle":["V Conf. Ital. Sul Softw. 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Object Technol."],"number":["1"],"pages":["3:1"],"title":["Evaluating the capabilities of Enterprise Architecture modeling tools for Visual Analysis."],"volume":["14"]},"creators":{"author":[{"lastName":"David","firstName":"Naranjo"},{"lastName":"Sánchez","firstName":"Mario"},{"lastName":"Villalobos","firstName":"Jorge"}]},"sentenceCased":true},{"key":"davidStreamingModelTransformations2014","type":"incollection","fields":{"langid":["english"],"abstract":["Streaming model transformations represent a novel class of transformations dealing with models whose elements are continuously produced or modified by a background process [1]. Executing streaming transformations requires efficient techniques to recognize the activated transformation rules on a potentially infinite input stream. Detecting a series of events triggered by compound structural changes is especially challenging for a high volume of rapid modifications, a characteristic of an emerging class of applications built on runtime models."],"author":["Dávid, István","Ráth, István","Varró, Dániel"],"booktitle":["Model-Driven Engineering Languages and Systems"],"date":["2014"],"doi":["10.1007/978-3-319-11653-2_5"],"editor":["Dingel, Juergen","Schulte, Wolfram","Ramos, Isidro","Abrahão, Silvia","Insfran, Emilio"],"isbn":["978-3-319-11652-5 978-3-319-11653-2"],"location":["Cham"],"note":["TL;DR \n\nThis work has shown that detecting a series of events triggered by compound structural changes is especially challenging for a high volume of rapid modifications, a characteristic of an emerging class of applications built on runtime models."],"pages":["68–83"],"publisher":["Springer International Publishing"],"title":["Streaming Model Transformations By Complex Event Processing"],"volume":["8767"]},"creators":{"author":[{"lastName":"Dávid","firstName":"István"},{"lastName":"Ráth","firstName":"István"},{"lastName":"Varró","firstName":"Dániel"}],"editor":[{"lastName":"Dingel","firstName":"Juergen"},{"lastName":"Schulte","firstName":"Wolfram"},{"lastName":"Ramos","firstName":"Isidro"},{"lastName":"Abrahão","firstName":"Silvia"},{"lastName":"Insfran","firstName":"Emilio"}]}},{"key":"davisRelationshipPrecisionrecallROC2006","type":"inproceedings","fields":{"acmid":["1143874"],"author":["Davis, Jesse","Goadrich, Mark"],"booktitle":["Proc. 23rd Int. 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Conf. Softw. Eng. ICSE 13 San Franc. CA USA May 18-26 2013"],"date":["2013"],"doi":["10.1109/ICSE.2013.6606629"],"pages":["832–841"],"timestamp":["Tue, 23 May 2017 01:11:52 +0200"],"title":["Discovering essential code elements in informal documentation"]},"creators":{"author":[{"lastName":"Rigby","firstName":"Peter C."},{"lastName":"Robillard","firstName":"Martin P."}]},"sentenceCased":true},{"key":"DBLP:conf/kbse/Gu0019","type":"inproceedings","fields":{"author":["Gu, Xiaodong","Zhang, Hongyu","Kim, Sunghun"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/conf/kbse/Gu0019.bib"],"booktitle":["34th IEEEACM Int. Conf. Autom. Softw. Eng. 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P."},{"lastName":"Zhang","firstName":"Yongfeng"}]},"sentenceCased":true},{"key":"DBLP:conf/recsys/WuSCTP14","type":"inproceedings","fields":{"author":["Wu, Lili","Shah, Sam","Choi, Sean","Tiwari, Mitul","Posse, Christian"],"booktitle":["RSWeb@RecSys"],"date":["2014"],"note":["TL;DR \n\nThis paper presents LinkedIn’s horizontal collaborative filtering infrastructure, known as browsemaps, which enables rapid development, deployment, and computation of collaborative filtering recommendations for almost any use case on LinkedIn."],"publisher":["CEUR-WS.org"],"series":["CEUR workshop proceedings"],"title":["The browsemaps: Collaborative filtering at LinkedIn"],"volume":["1271"]},"creators":{"author":[{"lastName":"Wu","firstName":"Lili"},{"lastName":"Shah","firstName":"Sam"},{"lastName":"Choi","firstName":"Sean"},{"lastName":"Tiwari","firstName":"Mitul"},{"lastName":"Posse","firstName":"Christian"}]},"sentenceCased":true},{"key":"DBLP:conf/scc2/Fletcher19","type":"inproceedings","fields":{"author":["Fletcher, Kenneth K."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/conf/scc2/Fletcher19.bib"],"booktitle":["Serv. 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SCF 2019 San Diego CA USA June 25-30 2019 Proc."],"date":["2019"],"doi":["10.1007/978-3-030-23554-3\\_1"],"editor":["Ferreira, João Eduardo","Musaev, Aibek","Zhang, Liang-Jie"],"pages":["1–15"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Fri, 05 Jul 2019 09:41:11 +0200"],"title":["A quality-aware web API recommender system for mashup development"],"volume":["11515"]},"creators":{"author":[{"lastName":"Fletcher","firstName":"Kenneth K."}],"editor":[{"lastName":"Ferreira","firstName":"João Eduardo"},{"lastName":"Musaev","firstName":"Aibek"},{"lastName":"Zhang","firstName":"Liang-Jie"}]},"sentenceCased":true},{"key":"DBLP:conf/sigsoft/2005","type":"book","fields":{"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/conf/sigsoft/2005"],"date":["2005"],"editor":["Wermelinger, Michel","Gall, Harald C."],"isbn":["1-59593-014-0"],"note":["TL;DR \n\nESEC/FSE'05 features three exciting keynote addresses by Oscar Nierstrasz (Professor of Computer Science at the University of Bern, Switzerland), Antonio Câmara (CEO of YDreams and Professor at the New University of Lisbon, Portugal), and the two ACM SIGSOFT Outstanding Research Award recipients."],"publisher":["ACM"],"timestamp":["Wed, 01 Apr 2015 20:06:24 +0200"],"title":["Proceedings of the 10th european software engineering conference held jointly with 13th ACM SIGSOFT international symposium on foundations of software engineering, 2005, lisbon, portugal, september 5-9, 2005"]},"creators":{"editor":[{"lastName":"Wermelinger","firstName":"Michel"},{"lastName":"Gall","firstName":"Harald C."}]},"sentenceCased":true},{"key":"DBLP:conf/wcre/AsyrofiT0J20","type":"inproceedings","fields":{"author":["Asyrofi, Muhammad Hilmi","Thung, Ferdian","Lo, David","Jiang, Lingxiao"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/conf/wcre/AsyrofiT0J20.bib"],"booktitle":["27th IEEE Int. Conf. Softw. Anal. Evol. Reengineering SANER 2020 Lond. Can. Febr. 18-21 2020"],"date":["2020"],"doi":["10.1109/SANER48275.2020.9054809"],"note":["TL;DR \n\nGiven an API query that allows type constraints, AUSearch finds code examples in GitHub that contain usages of the specific APIs in the query and highlights the relevant lines of code in the files for easier reference."],"pages":["637–641"],"timestamp":["Thu, 16 Apr 2020 16:52:52 +0200"],"title":["AUSearch: Accurate API usage search in GitHub repositories with type resolution"]},"creators":{"author":[{"lastName":"Asyrofi","firstName":"Muhammad Hilmi"},{"lastName":"Thung","firstName":"Ferdian"},{"lastName":"Lo","firstName":"David"},{"lastName":"Jiang","firstName":"Lingxiao"}]},"sentenceCased":true},{"key":"DBLP:conf/wcre/OguraMHK18","type":"inproceedings","fields":{"author":["Ogura, Naoto","Matsumoto, Shinsuke","Hata, Hideaki","Kusumoto, Shinji"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/conf/wcre/OguraMHK18.bib"],"booktitle":["25th Int. Conf. Softw. Anal. Evol. Reengineering SANER 2018 Campobasso Italy March 20-23 2018"],"date":["2018"],"doi":["10.1109/SANER.2018.8330253"],"editor":["Oliveto, Rocco","Penta, Massimiliano Di","Shepherd, David C."],"note":["TL;DR \n\nA novel tool is proposed, called StyleCoordinator, to solve both of the following problems, which would appear to contradict each other: ensuring a consistent coding style for all source codes managed in a repository and ensuring the ability of developers to use their own coding styles in a local environment."],"pages":["527–531"],"publisher":["IEEE Computer Society"],"timestamp":["Fri, 24 Mar 2023 00:04:44 +0100"],"title":["Bring your own coding style"]},"creators":{"author":[{"lastName":"Ogura","firstName":"Naoto"},{"lastName":"Matsumoto","firstName":"Shinsuke"},{"lastName":"Hata","firstName":"Hideaki"},{"lastName":"Kusumoto","firstName":"Shinji"}],"editor":[{"lastName":"Oliveto","firstName":"Rocco"},{"lastName":"Penta","firstName":"Massimiliano Di"},{"lastName":"Shepherd","firstName":"David C."}]},"sentenceCased":true},{"key":"DBLP:journals/air/SiL20","type":"article","fields":{"author":["Si, Mingdan","Li, Qingshan"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/journals/air/SiL20.bib"],"date":["2020"],"doi":["10.1007/s10462-018-9655-x"],"ids":["si_shilling_2020"],"journaltitle":["Artif. Intell. Rev."],"note":["TL;DR \n\nThis paper briefly discusses the related survey papers about shilling attacks in CFRSs, explains profile injection attack strategies, shilling attack detection schemes and robust recommendation algorithms proposed so far in detail, and briefly explains evaluation metrics of the proposed schemes."],"number":["1"],"pages":["291–319"],"timestamp":["Tue, 16 Jun 2020 17:16:04 +0200"],"title":["Shilling attacks against collaborative recommender systems: A review"],"volume":["53"]},"creators":{"author":[{"lastName":"Si","firstName":"Mingdan"},{"lastName":"Li","firstName":"Qingshan"}]},"sentenceCased":true},{"key":"DBLP:journals/corr/abs-0911-5046","type":"article","fields":{"author":["Pérez-Iglesias, Joaquín","Pérez-Agüera, José R.","Fresno, Víctor","Feinstein, Yuval Z."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/journals/corr/abs-0911-5046"],"date":["2009"],"eprint":["0911.5046"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"note":["TL;DR \n\nThis document describes the BM25 and BM25F implementation using the Lucene Java Framework, both of which have stood out at TREC by their performance and are considered as state-of-the-art in the IR community."],"timestamp":["Mon, 13 Aug 2018 16:46:38 +0200"],"title":["Integrating the probabilistic models BM25/BM25F into lucene"],"url":["http://arxiv.org/abs/0911.5046"],"volume":["abs/0911.5046"]},"creators":{"author":[{"lastName":"Pérez-Iglesias","firstName":"Joaquín"},{"lastName":"Pérez-Agüera","firstName":"José R."},{"lastName":"Fresno","firstName":"Víctor"},{"lastName":"Feinstein","firstName":"Yuval Z."}]},"sentenceCased":true},{"key":"DBLP:journals/corr/abs-1207-4525","type":"article","fields":{"author":["Lacoste-Julien, Simon","Palla, Konstantina","Davies, Alex","Kasneci, Gjergji","Graepel, Thore","Ghahramani, Zoubin"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/journals/corr/abs-1207-4525.bib"],"date":["2012"],"eprint":["1207.4525"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"note":["TL;DR \n\nSimple Greedy Matching (SiGMa), a simple algorithm for aligning knowledge bases with millions of entities and facts, which is an iterative propagation algorithm that leverages both the structural information from the relationship graph and flexible similarity measures between entity properties in a greedy local search, which makes it scalable."],"timestamp":["Mon, 13 Aug 2018 16:46:21 +0200"],"title":["SiGMa: Simple greedy matching for aligning large knowledge bases"],"url":["http://arxiv.org/abs/1207.4525"],"volume":["abs/1207.4525"]},"creators":{"author":[{"lastName":"Lacoste-Julien","firstName":"Simon"},{"lastName":"Palla","firstName":"Konstantina"},{"lastName":"Davies","firstName":"Alex"},{"lastName":"Kasneci","firstName":"Gjergji"},{"lastName":"Graepel","firstName":"Thore"},{"lastName":"Ghahramani","firstName":"Zoubin"}]},"sentenceCased":true},{"key":"DBLP:journals/corr/abs-1812-04894","type":"article","fields":{"author":["Lamothe, Maxime","Shang, Weiyi","Chen, Tse-Hsun"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/journals/corr/abs-1812-04894"],"date":["2018"],"eprint":["1812.04894"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"note":["TL;DR \n\nAn approach that automatically learns API migration patterns from code examples and applies these patterns to the source code of Android apps for API migration is proposed and can be adopted by Android developers to reduce the effort they spend on regularly migrating Android APIs."],"timestamp":["Tue, 01 Jan 2019 15:01:25 +0100"],"title":["A4: Automatically assisting android API migrations using code examples"],"url":["http://arxiv.org/abs/1812.04894"],"volume":["abs/1812.04894"]},"creators":{"author":[{"lastName":"Lamothe","firstName":"Maxime"},{"lastName":"Shang","firstName":"Weiyi"},{"lastName":"Chen","firstName":"Tse-Hsun"}]},"sentenceCased":true},{"key":"DBLP:journals/corr/abs-1909-09436","type":"article","fields":{"author":["Husain, Hamel","Wu, Ho-Hsiang","Gazit, Tiferet","Allamanis, Miltiadis","Brockschmidt, Marc"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/journals/corr/abs-1909-09436.bib"],"date":["2019"],"eprint":["1909.09436"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"note":["TL;DR \n\nThe methodology used to obtain the corpus and expert labels, as well as a number of simple baseline solutions for the task are described."],"timestamp":["Tue, 24 Sep 2019 11:33:51 +0200"],"title":["CodeSearchNet challenge: Evaluating the state of semantic code search"],"url":["http://arxiv.org/abs/1909.09436"],"volume":["abs/1909.09436"]},"creators":{"author":[{"lastName":"Husain","firstName":"Hamel"},{"lastName":"Wu","firstName":"Ho-Hsiang"},{"lastName":"Gazit","firstName":"Tiferet"},{"lastName":"Allamanis","firstName":"Miltiadis"},{"lastName":"Brockschmidt","firstName":"Marc"}]},"sentenceCased":true},{"key":"DBLP:journals/corr/abs-2101-11149","type":"article","fields":{"author":["Xu, Frank F.","Vasilescu, Bogdan","Neubig, Graham"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2021"],"eprint":["2101.11149"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"note":["TL;DR \n\nThis article develops a plugin for the PyCharm IDE that implements a hybrid of code generation and code retrieval functionality and asks developers with various backgrounds to complete 7 varieties of 14 Python programming tasks ranging from basic file manipulation to machine learning or data visualization, with or without the help of the plugin."],"timestamp":["Sun, 31 Jan 2021 17:23:50 +0100"],"title":["In-IDE code generation from natural language: Promise and challenges"],"volume":["abs/2101.11149"]},"creators":{"author":[{"lastName":"Xu","firstName":"Frank F."},{"lastName":"Vasilescu","firstName":"Bogdan"},{"lastName":"Neubig","firstName":"Graham"}]},"sentenceCased":true},{"key":"DBLP:journals/corr/GoodfellowSS14","type":"inproceedings","fields":{"author":["Goodfellow, Ian J.","Shlens, Jonathon","Szegedy, Christian"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/journals/corr/GoodfellowSS14.bib"],"booktitle":["ICLR 2015 San Diego CA USA May 7-9 2015 Conf. Track Proc."],"date":["2015"],"editor":["Bengio, Yoshua","LeCun, Yann"],"note":["TL;DR \n\nIt is argued that the primary cause of neural networks' vulnerability to adversarial perturbation is their linear nature, supported by new quantitative results while giving the first explanation of the most intriguing fact about them: their generalization across architectures and training sets."],"timestamp":["Thu, 25 Jul 2019 14:25:38 +0200"],"title":["Explaining and harnessing adversarial examples"],"url":["http://arxiv.org/abs/1412.6572"]},"creators":{"author":[{"lastName":"Goodfellow","firstName":"Ian J."},{"lastName":"Shlens","firstName":"Jonathon"},{"lastName":"Szegedy","firstName":"Christian"}],"editor":[{"lastName":"Bengio","firstName":"Yoshua"},{"lastName":"LeCun","firstName":"Yann"}]},"sentenceCased":true},{"key":"DBLP:journals/corr/IzmaylovaKSV13","type":"article","fields":{"author":["Izmaylova, Anastasia","Klint, Paul","Shahi, Ashim","Vinju, Jurgen J."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/journals/corr/IzmaylovaKSV13"],"date":["2013"],"eprint":["1312.1188"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"timestamp":["Wed, 07 Jun 2017 14:42:09 +0200"],"title":["M3: An open model for measuring code artifacts"],"url":["http://arxiv.org/abs/1312.1188"],"volume":["abs/1312.1188"]},"creators":{"author":[{"lastName":"Izmaylova","firstName":"Anastasia"},{"lastName":"Klint","firstName":"Paul"},{"lastName":"Shahi","firstName":"Ashim"},{"lastName":"Vinju","firstName":"Jurgen J."}]},"sentenceCased":true},{"key":"DBLP:journals/ese/LoriotMM22","type":"article","fields":{"author":["Loriot, Benjamin","Madeiral, Fernanda","Monperrus, Martin"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/journals/ese/LoriotMM22.bib"],"date":["2022"],"doi":["10.1007/s10664-021-10107-0"],"journaltitle":["Empir. Softw. Eng."],"number":["6"],"pages":["149"],"timestamp":["Mon, 24 Oct 2022 20:51:22 +0200"],"title":["Styler: Learning formatting conventions to repair Checkstyle violations"],"volume":["27"]},"creators":{"author":[{"lastName":"Loriot","firstName":"Benjamin"},{"lastName":"Madeiral","firstName":"Fernanda"},{"lastName":"Monperrus","firstName":"Martin"}]},"sentenceCased":true},{"key":"DBLP:journals/ese/PascarellaBB19","type":"article","fields":{"author":["Pascarella, Luca","Bruntink, Magiel","Bacchelli, Alberto"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/journals/ese/PascarellaBB19.bib"],"date":["2019"],"doi":["10.1007/s10664-019-09694-w"],"journaltitle":["Empir. Softw. 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M.","Milios, Evangelos E."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/journals/ijswis/HliaoutakisVVPM06"],"date":["2006"],"doi":["10.4018/jswis.2006070104"],"journaltitle":["Int. J. Semantic Web Inf. Syst."],"number":["3"],"pages":["55–73"],"timestamp":["Sat, 20 May 2017 00:24:06 +0200"],"title":["Information retrieval by semantic similarity"],"volume":["2"]},"creators":{"author":[{"lastName":"Hliaoutakis","firstName":"Angelos"},{"lastName":"Varelas","firstName":"Giannis"},{"lastName":"Voutsakis","firstName":"Epimenidis"},{"lastName":"Petrakis","firstName":"Euripides G. 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J."],"number":["6"],"pages":["606–634"],"timestamp":["Sun, 02 Oct 2022 15:39:26 +0200"],"title":["Statistical biases in Information Retrieval metrics for recommender systems"],"volume":["20"]},"creators":{"author":[{"lastName":"Bellogín","firstName":"Alejandro"},{"lastName":"Castells","firstName":"Pablo"},{"lastName":"Cantador","firstName":"Iván"}]},"sentenceCased":true},{"key":"DBLP:journals/sigmobile/Shannon01","type":"article","fields":{"author":["Shannon, Claude E."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/journals/sigmobile/Shannon01"],"date":["2001"],"doi":["10.1145/584091.584093"],"journaltitle":["Mob. Comput. Commun. 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I."}]},"sentenceCased":true},{"key":"deconciniLeggereSapere","type":"book","fields":{"author":["DE CONCINI, Alessandro"],"title":["Leggere per Sapere"],"url":["https://d1ysz50cxb9zwl.cloudfront.net/nWyzM3XH0hJ4vIuhHYLNVg0WKjOGYKsr2aaLkQRn2_0BQ0RGaTtLRAK_wruIb4gH/by/4646762/as/file.pdf?Expires=1705862343&Signature=aXo5~ZVrOyAsiHg5~F9z9nYa38tSSbnuWO4MF1pH6qRDesP3TFtgMOknkRaJTGklNhAc-ZEflzTaW1MVO16qo66pltzM8XqFRbMWKLTw-AT8RnfU3nmDM8Imy7DMn8cJh9xYBG6x2HgL~9BBCTIOxg14vqwnmGmw1SHrAdHPd9D48XaQSspxQK1cb1zQDefW2BPDKF9cLP6fwJ0lCxGru8KDRvgxFqiiGaO8j01KFKQqeOYIXZ-uJQ1E6ft2~IV4IHhev-NX-iBoimjpeTDraDn6xouBAmiQ1DxaMMWHq56ENDabV~xdEuPSo6t8tvlD~1T2cF2ecYHB5jFbemKmTA__&Key-Pair-Id=APKAJAERRT46LD6FN4NA"],"urldate":["2024-01-21"]},"creators":{"author":[{"lastName":"DE CONCINI","firstName":"Alessandro"}]}},{"key":"degyurkyAutonomousSystemFoundational2014","type":"book","fields":{"langid":["english"],"abstract":["This book describes-in modern computer science terms-the Level II architecture of the meaning and definition of the process referred to as \"thinking\". It applies the basis of early cognitive science research to the creation of autonomous system architectures-connecting philosophical findings of the past with cutting-edge progress in artificial intelligence. Providing an in-depth introduction to the classical, philosophical theories of cognitive scientists like Immanuel Kant, Arthur Schopenhauer, and G.W.F. Hegel, the book examines the Will System, Reason System, Imagination System, and the C."],"author":["De Gyurky, Szabolcs Michael","Tarbell, Mark A"],"date":["2014"],"isbn":["978-1-118-75749-9 978-1-118-75995-0 978-1-118-29424-6 978-1-299-98883-5"],"location":["Hoboken. N.J."],"publisher":["Wiley"],"title":["The autonomous system a foundational synthesis of the sciences of the mind"],"url":["http://public.eblib.com/choice/publicfullrecord.aspx?p=1465945"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"De Gyurky","firstName":"Szabolcs Michael"},{"lastName":"Tarbell","firstName":"Mark A"}]},"sentenceCased":true},{"key":"dehghaniFacilitatingMigrationMicroservice2022","type":"article","fields":{"langid":["english"],"author":["Dehghani, MohammadHadi","Kolahdouz-Rahimi, Shekoufeh","Tisi, Massimo","Tamzalit, Dalila"],"date":["2022-06"],"doi":["10.1007/s10270-022-00977-3"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"keywords":["GOAL_System-Modernization","notion","TECHNIQUE_ReinforcementLearning"],"number":["3"],"pages":["1115–1133"],"title":["Facilitating the migration to the microservice architecture via model-driven reverse engineering and reinforcement learning"],"volume":["21"]},"creators":{"author":[{"lastName":"Dehghani","firstName":"MohammadHadi"},{"lastName":"Kolahdouz-Rahimi","firstName":"Shekoufeh"},{"lastName":"Tisi","firstName":"Massimo"},{"lastName":"Tamzalit","firstName":"Dalila"}]},"sentenceCased":true},{"key":"dehuryTOSCAdataModelingData2022","type":"article","fields":{"langid":["english"],"abstract":["The serverless platform allows a customer to effectively use cloud resources and pay for the exact amount of used resources. A number of dedicated open source and commercial cloud data management tools are available to handle the massive amount of data. Such modern cloud data management tools are not enough matured to integrate the generic cloud application with the serverless platform due to the lack of mature and stable standards. One of the most popular and mature standards, TOSCA (Topology and Orchestration Specification for Cloud Applications), mainly focuses on application and service portability and automated management of the generic cloud application components. This paper proposes the extension of the TOSCA standard, TOSCAdata, that focuses on the modeling of data pipeline-based cloud applications. Keeping the requirements of modern data pipeline cloud applications, TOSCAdata provides a number of TOSCA models that are independently deployable, schedulable, scalable, and re-usable, while effectively handling the flow and transformation of data in a pipeline manner. We also demonstrate the applicability of proposed TOSCAdata models by taking a web-based cloud application in the context of tourism promotion as a use case scenario."],"author":["Dehury, Chinmaya Kumar","Jakovits, Pelle","Srirama, Satish Narayana","Giotis, Giorgos","Garg, Gaurav"],"date":["2022-04"],"doi":["10.1016/j.jss.2021.111164"],"issn":["01641212"],"journaltitle":["Journal of Systems and Software"],"pages":["111164"],"shorttitle":["TOSCAdata"],"title":["TOSCAdata: Modeling data pipeline applications in TOSCA"],"volume":["186"]},"creators":{"author":[{"lastName":"Dehury","firstName":"Chinmaya Kumar"},{"lastName":"Jakovits","firstName":"Pelle"},{"lastName":"Srirama","firstName":"Satish Narayana"},{"lastName":"Giotis","firstName":"Giorgos"},{"lastName":"Garg","firstName":"Gaurav"}]},"sentenceCased":true},{"key":"delara3rdworkshopFlexibleModel2017","type":"article","fields":{"author":["De Lara, J.","Ruscio, D.D.","Pierantonio, A."],"date":["2017"],"journaltitle":["CEUR Workshop Proc."],"note":["cited By 0 \n\ncited By 0"],"pages":["385–386"],"title":["3rdworkshop on flexible model driven engineering (FlexMDE 2017)"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041447069&partnerID=40&md5=66fef2d9e76c891d78b2ae52d58a6d0a"],"volume":["2019"]},"creators":{"author":[{"lastName":"De Lara","firstName":"J."},{"lastName":"Ruscio","firstName":"D.D."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"delaraPreface1stInternational2020","type":"article","fields":{"author":["De Lara, J.","Di Ruscio, D.","Kolovos, D.","Tisi, M.","Wimmer, M."],"date":["2020"],"ids":["delaraPreface1stInternational2020a"],"journaltitle":["Proc. - 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS-C 2020 - Companion Proc."],"note":["cited By 0 \n\ncited By 0"],"pages":["XXII-XXIII"],"title":["Preface to 1st International Workshop on Modeling in Low-Code Development Platforms (LowCode 2020)"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096765618&partnerID=40&md5=4a22ec01b9bd336223ac732c915f3aef"]},"creators":{"author":[{"lastName":"De Lara","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Kolovos","firstName":"D."},{"lastName":"Tisi","firstName":"M."},{"lastName":"Wimmer","firstName":"M."}]}},{"key":"delaraReusableAbstractionsModeling2013","type":"article","fields":{"langid":["english"],"author":["family=Lara, given=Juan, prefix=de, useprefix=true","Guerra, Esther","Sánchez Cuadrado, Jesús"],"date":["2013-11"],"doi":["10.1016/j.is.2013.06.001"],"issn":["03064379"],"journaltitle":["Inf. Syst."],"note":["TL;DR \n\nThis paper has devised some techniques, based on generic programming and domain-specific meta-modelling, to define generic abstraction operations that can be reused over families of modelling languages sharing certain characteristics, and developed a catalogue of reusable abstractions."],"number":["8"],"pages":["1128–1149"],"title":["Reusable abstractions for modeling languages"],"volume":["38"]},"creators":{"author":[{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Sánchez Cuadrado","firstName":"Jesús"}]},"sentenceCased":true},{"key":"delavegaLavoisierDSLIncreasing2020","type":"article","fields":{"langid":["english"],"author":["family=Vega, given=Alfonso, prefix=de la, useprefix=true","García-Saiz, Diego","Zorrilla, Marta","Sánchez, Pablo"],"date":["2020-10"],"doi":["10.1016/j.cola.2020.100987"],"ids":["DELAVEGA2020100987"],"issn":["25901184"],"journaltitle":["Journal of Computer Languages"],"keywords":["Data formatting","Data mining","Data selection","Domain-specific languages"],"pages":["100987"],"shorttitle":["Lavoisier"],"title":["Lavoisier: A DSL for increasing the level of abstraction of data selection and formatting in data mining"],"volume":["60"]},"creators":{"author":[{"lastName":"Vega","firstName":"Alfonso","prefix":"dela","useprefix":true},{"lastName":"García-Saiz","firstName":"Diego"},{"lastName":"Zorrilla","firstName":"Marta"},{"lastName":"Sánchez","firstName":"Pablo"}]},"sentenceCased":true},{"key":"deldjooAdversarialMachineLearning","type":"article","fields":{"langid":["english"],"author":["Deldjoo, Yashar","Noia, Tommaso Di","Merra, Felice Antonio"],"ids":["DDM20a"],"keywords":["adversarial machine learning","Adversarial Machine Learning","Literature Review","Recommender System"],"note":["TL;DR \n\nAn exhaustive literature review of 60 articles published in major RS and ML journals and conferences is provided to present recent advances on AML-RS for the security of RS and to show another successful application of AML in generative adversarial networks (GANs), which use the core concept of learning in AML for generative applications. \n\nUnder Review"],"pages":["35"],"title":["Adversarial Machine Learning in Recommender Systems: State of the art and Challenges"]},"creators":{"author":[{"lastName":"Deldjoo","firstName":"Yashar"},{"lastName":"Noia","firstName":"Tommaso Di"},{"lastName":"Merra","firstName":"Felice Antonio"}]},"sentenceCased":true},{"key":"deldjooSurveyAdversarialRecommender2021","type":"article","fields":{"langid":["english"],"abstract":["Latent-factor models (LFM) based on collaborative filtering (CF), such as matrix factorization (MF) and deep CF methods, are widely used in modern recommender systems (RS) due to their excellent performance and recommendation accuracy. However, success has been accompanied with a major new arising challenge: Many applications of machine learning (ML) are adversarial in nature [146]. In recent years, it has been shown that these methods are vulnerable to adversarial examples, i.e., subtle but non-random perturbations designed to force recommendation models to produce erroneous outputs. The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models) and (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-dimensional) data distributions. In this survey, we provide an exhaustive literature review of 76 articles published in major RS and ML journals and conferences. This review serves as a reference for the RS community working on the security of RS or on generative models using GANs to improve their quality."],"articleno":["35"],"author":["Deldjoo, Yashar","Noia, Tommaso Di","Merra, Felice Antonio"],"date":["2021-03"],"doi":["10.1145/3439729"],"ids":["10.1145/3439729"],"issn":["0360-0300, 1557-7341"],"issue_date":["March 2021"],"journaltitle":["ACM Comput. Surv."],"keywords":["adversarial machine learning","adversarial perturbation","generative adversarial network","min-max game","privacy","Recommender systems","robustness","security"],"location":["New York, NY, USA"],"number":["2"],"pages":["1–38"],"pagetotal":["38"],"publisher":["Association for Computing Machinery"],"shorttitle":["A Survey on Adversarial Recommender Systems"],"title":["A Survey on Adversarial Recommender Systems: From Attack/Defense Strategies to Generative Adversarial Networks"],"volume":["54"]},"creators":{"author":[{"lastName":"Deldjoo","firstName":"Yashar"},{"lastName":"Noia","firstName":"Tommaso Di"},{"lastName":"Merra","firstName":"Felice Antonio"}]}},{"key":"delemosSoftwareEngineeringSelfadaptive2013","type":"incollection","fields":{"author":["De Lemos, Rogério","Giese, Holger","Müller, Hausi A.","Shaw, Mary","Andersson, Jesper","Litoiu, Marin","Schmerl, Bradley","Tamura, Gabriel","Villegas, Norha M.","Vogel, Thomas","others"],"booktitle":["Software Engineering for Self-Adaptive Systems II"],"date":["2013"],"pages":["1–32"],"publisher":["Springer"],"shorttitle":["Software engineering for self-adaptive systems"],"title":["Software engineering for self-adaptive systems: A second research roadmap"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-35813-5_1"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"De Lemos","firstName":"Rogério"},{"lastName":"Giese","firstName":"Holger"},{"lastName":"Müller","firstName":"Hausi A."},{"lastName":"Shaw","firstName":"Mary"},{"lastName":"Andersson","firstName":"Jesper"},{"lastName":"Litoiu","firstName":"Marin"},{"lastName":"Schmerl","firstName":"Bradley"},{"lastName":"Tamura","firstName":"Gabriel"},{"lastName":"Villegas","firstName":"Norha M."},{"lastName":"Vogel","firstName":"Thomas"},{"lastName":"others"}]},"sentenceCased":true},{"key":"delimaWorkloaddrivenLogicalDesign2015","type":"inproceedings","fields":{"langid":["english"],"author":["family=Lima, given=Claudio, prefix=de, useprefix=true","family=Santos Mello, given=Ronaldo, prefix=dos, useprefix=true"],"booktitle":["Proc. 17th Int. Conf. Inf. Integr. Web-Based Appl. Serv."],"date":["2015-12-11"],"doi":["10.1145/2837185.2837218"],"eventtitle":["iiWAS '15: The 17th International Conference on Information Integration and Web-based Application & Services"],"isbn":["978-1-4503-3491-4"],"location":["Brussels Belgium"],"note":["TL;DR \n\nThis work converts a conceptual modeling into efficient logical representations for a NoSQL document database and demonstrates that the NoSQL logical structure generated by this approach reduces the amount of items accessed by the application queries."],"pages":["1–10"],"publisher":["ACM"],"title":["A workload-driven logical design approach for NoSQL document databases"]},"creators":{"author":[{"lastName":"Lima","firstName":"Claudio","prefix":"de","useprefix":true},{"lastName":"SantosMello","firstName":"Ronaldo","prefix":"dos","useprefix":true}]},"sentenceCased":true},{"key":"dellannaEvaluatingClassifiersSE2023","type":"article","fields":{"langid":["english"],"abstract":["Objective The lack of guidelines for applying and reporting classification techniques for SE research leads to studies in which important research steps may be skipped, key findings might not be identified and shared, and the readers may find reported results (e.g., precision or recall above 90%) that are not a credible representation of the performance in operational contexts. The goal of this paper is to advance ML4SE research by proposing rigorous ways of conducting and reporting research. Results We introduce the ECSER (Evaluating Classifiers in Software Engineering Research) pipeline, which includes a series of steps for conducting and evaluating automated classification research in SE. Then, we conduct two replication studies where we apply ECSER to recent research in requirements engineering and in software testing. Conclusions In addition to demonstrating the applicability of the pipeline, the replication studies demonstrate ECSER’s usefulness: not only do we confirm and strengthen some findings identified by the original authors, but we also discover additional ones. Some of these findings contradict the original ones."],"author":["Dell’Anna, Davide","Aydemir, Fatma Başak","Dalpiaz, Fabiano"],"date":["2023-02"],"doi":["10.1007/s10664-022-10243-1"],"issn":["1382-3256, 1573-7616"],"journaltitle":["Empir Software Eng"],"number":["1"],"pages":["3"],"shorttitle":["Evaluating classifiers in SE research"],"title":["Evaluating classifiers in SE research: The ECSER pipeline and two replication studies"],"volume":["28"]},"creators":{"author":[{"lastName":"Dell’Anna","firstName":"Davide"},{"lastName":"Aydemir","firstName":"Fatma Başak"},{"lastName":"Dalpiaz","firstName":"Fabiano"}]},"sentenceCased":true},{"key":"demuthSupportingCoevolutionMetamodels2013","type":"incollection","fields":{"langid":["english"],"abstract":["Design models must abide by constraints that can come from diverse sources, like metamodels, requirements, or the problem domain. Modelers intent to live by these constraints and thus desire automated mechanism that provide instant feedback on constraint violations. However, typical approaches assume that constraints do not evolve over time, which, unfortunately, is becoming increasingly unrealistic. For example, the co-evolution of metamodels and models requires corresponding constraints to be co-evolved continuously. This demands efficient constraint adaptation mechanisms to ensure that validated constraints are up-to-date. This paper presents an approach based on constraint templates that tackles this evolution scenario by automatically updating constraints. We developed the Cross-Layer Modeler (XLM) approach which relies on incremental consistency-checking. As a case study, we performed evolutions of the UML-metamodel and 21 design models. Our approach is sound and the empirical evaluation shows that it is near instant and scales with increasing model sizes."],"author":["Demuth, Andreas","Lopez-Herrejon, Roberto E.","Egyed, Alexander"],"booktitle":["Model-Driven Engineering Languages and Systems"],"date":["2013"],"editor":["Moreira, Ana","Schätz, Bernhard","Gray, Jeff","Vallecillo, Antonio","Clarke, Peter"],"isbn":["978-3-642-41532-6 978-3-642-41533-3"],"keywords":["software engineering"],"note":["TL;DR \n\nThis paper developed the Cross-Layer Modeler XLM approach which relies on incremental consistency-checking and is sound and the empirical evaluation shows that it is near instant and scales with increasing model sizes."],"number":["8107"],"pages":["287–303"],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture Notes in Computer Science"],"title":["Supporting the Co-evolution of Metamodels and Constraints through Incremental Constraint Management"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-41533-3_18"],"urldate":["2015-03-24"]},"creators":{"author":[{"lastName":"Demuth","firstName":"Andreas"},{"lastName":"Lopez-Herrejon","firstName":"Roberto E."},{"lastName":"Egyed","firstName":"Alexander"}],"editor":[{"lastName":"Moreira","firstName":"Ana"},{"lastName":"Schätz","firstName":"Bernhard"},{"lastName":"Gray","firstName":"Jeff"},{"lastName":"Vallecillo","firstName":"Antonio"},{"lastName":"Clarke","firstName":"Peter"}]}},{"key":"DenilJVV14","type":"inproceedings","fields":{"langid":["english"],"author":["Denil, Joachim","Jukss, Maris","Verbrugge, Clark","Vangheluwe, Hans"],"booktitle":["Syst. Anal. Model. Models Reusability - 8th Int. Conf. SAM"],"date":["2014"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["80–95"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"title":["Search-based model optimization using model transformations"],"volume":["8769"]},"creators":{"author":[{"lastName":"Denil","firstName":"Joachim"},{"lastName":"Jukss","firstName":"Maris"},{"lastName":"Verbrugge","firstName":"Clark"},{"lastName":"Vangheluwe","firstName":"Hans"}]},"sentenceCased":true},{"key":"derakhshanmaneshModelintegratingDevelopmentSoftware2018","type":"article","fields":{"langid":["english"],"author":["Derakhshanmanesh, Mahdi","Ebert, Jürgen","Grieger, Marvin","Engels, Gregor"],"date":["2018-06-16"],"doi":["10.1007/s10270-018-0682-5"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"shorttitle":["Model-integrating development of software systems"],"title":["Model-integrating development of software systems: A flexible component-based approach"]},"creators":{"author":[{"lastName":"Derakhshanmanesh","firstName":"Mahdi"},{"lastName":"Ebert","firstName":"Jürgen"},{"lastName":"Grieger","firstName":"Marvin"},{"lastName":"Engels","firstName":"Gregor"}]},"sentenceCased":true},{"key":"derlerModelingCyberX20132012","type":"article","fields":{"author":["Derler, P.","Lee, E. A.","Vincentelli, A. S."],"date":["2012-01"],"doi":["10.1109/JPROC.2011.2160929"],"issn":["0018-9219, 1558-2256"],"journaltitle":["Proc. IEEE"],"number":["1"],"pages":["13–28"],"title":["Modeling Cyber&#x2013;Physical Systems"],"volume":["100"]},"creators":{"author":[{"lastName":"Derler","firstName":"P."},{"lastName":"Lee","firstName":"E. A."},{"lastName":"Vincentelli","firstName":"A. S."}]}},{"key":"deServiceModellingInternet2011","type":"inproceedings","fields":{"author":["De, Suparna","Barnaghi, Payam","Bauer, Martin","Meissner, Stefan"],"booktitle":["Comput. Sci. Inf. Syst. FedCSIS 2011 Fed. Conf. On"],"date":["2011"],"note":["TL;DR \n\nThis paper presents a semantic modeling approach for different components in an IoT framework and discusses how the model can be integrated into the IoT framework by using automated association mechanisms with physical entities and how the data can be discovered using semantic search and reasoning mechanisms."],"pages":["949–955"],"publisher":["IEEE"],"title":["Service modelling for the Internet of Things"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6078180"],"urldate":["2016-02-09"]},"creators":{"author":[{"lastName":"De","firstName":"Suparna"},{"lastName":"Barnaghi","firstName":"Payam"},{"lastName":"Bauer","firstName":"Martin"},{"lastName":"Meissner","firstName":"Stefan"}]},"sentenceCased":true},{"key":"desouzaRankingCrowdKnowledge2014","type":"inproceedings","fields":{"acmid":["2597146"],"author":["family=Souza, given=Lucas B. L., prefix=de, useprefix=true","Campos, Eduardo C.","Maia, Marcelo de A."],"booktitle":["Proc. 22Nd Int. Conf. Program Comprehension"],"date":["2014"],"isbn":["978-1-4503-2879-1"],"keywords":["crowd knowledge","Q&A services","recommendation systems"],"location":["New York, NY, USA"],"nodoi":["10.1145/2597008.2597146"],"numpages":["11"],"pages":["72–82"],"publisher":["ACM"],"series":["ICPC 2014"],"title":["Ranking crowd knowledge to assist software development"],"url":["http://doi.acm.org/10.1145/2597008.2597146"]},"creators":{"author":[{"lastName":"Souza","firstName":"LucasB.L.","prefix":"de","useprefix":true},{"lastName":"Campos","firstName":"Eduardo C."},{"lastName":"Maia","firstName":"Marcelo de A."}]},"sentenceCased":true},{"key":"dex2jar","type":"misc","fields":{"langid":["american"],"abstract":["dex2jar contains multiple components to work with .dex files."],"date":["2020-03-23"],"note":["Library Catalog: tools.kali.org"],"title":["Dex2jar"],"url":["https://tools.kali.org/reverse-engineering/dex2jar"],"urldate":["2020-03-23"]},"creators":{}},{"key":"dhouibRobotmlDomainspecificLanguage2012","type":"inproceedings","fields":{"author":["Dhouib, Saadia","Kchir, Selma","Stinckwich, Serge","Ziadi, Tewfik","Ziane, Mikal"],"booktitle":["Int. Conf. Simul. Model. Program. Auton. Robots"],"date":["2012"],"pages":["149–160"],"publisher":["Springer"],"title":["Robotml, a domain-specific language to design, simulate and deploy robotic applications"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-34327-8_16"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Dhouib","firstName":"Saadia"},{"lastName":"Kchir","firstName":"Selma"},{"lastName":"Stinckwich","firstName":"Serge"},{"lastName":"Ziadi","firstName":"Tewfik"},{"lastName":"Ziane","firstName":"Mikal"}]},"sentenceCased":true},{"key":"Díaz-Manríquez20175647","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Soft Comput."],"affiliation":["Facultad de Ingeniería y Ciencias, Centro Universitario Victoria, Universidad Autónoma de Tamaulipas, Cd. Victoria, Tamaulipas 87000, Mexico; CINVESTAV-IPN, Unidad Tamaulipas, Parque Científico y Tecnológico TECNOTAM, Km. 5.5 carretera Cd. Victoria-Soto La Marina, Cd. Victoria, Tamaulipas 87130, Mexico; Departamento de Computación, CINVESTAV-IPN, Av. IPN No. 2508, Col. San Pedro Zacatenco, Mexico, DF 07360, Mexico"],"author":["Díaz-Manríquez, A.","Toscano, G.","Coello Coello, C.A."],"correspondence_address1":["Díaz-Manríquez, A.; Facultad de Ingeniería y Ciencias, Mexico; email: amanriquez@uat.edu.mx"],"date":["2017"],"document_type":["Article"],"doi":["10.1007/s00500-016-2140-z"],"issn":["14327643"],"journaltitle":["Soft Comput."],"note":["cited By 32 \n\nTL;DR \n\nAn in-depth comparison study over four of the most popular metamodeling techniques: polynomial response surface, Kriging, radial basis function neural network (RBF), and support vector regression shows that the precision, measured with the ranking preservation indicator, gives a more valuable information for selecting purposes."],"number":["19"],"pages":["5647–5663"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Comparison of metamodeling techniques in evolutionary algorithms"],"volume":["21"]},"creators":{"author":[{"lastName":"Díaz-Manríquez","firstName":"A."},{"lastName":"Toscano","firstName":"G."},{"lastName":"Coello Coello","firstName":"C.A."}]},"sentenceCased":true},{"key":"diceMeasuresAmountEcologic1945","type":"article","fields":{"author":["Dice, Lee R"],"date":["1945"],"journaltitle":["Ecology"],"number":["3"],"pages":["297–302"],"publisher":["Wiley Online Library"],"title":["Measures of the amount of ecologic association between species"],"volume":["26"]},"creators":{"author":[{"lastName":"Dice","firstName":"Lee R"}]},"sentenceCased":true},{"key":"Did32Waterfall2017","type":"article","fields":{"langid":["english"],"date":["2017-01"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"number":["1"],"pages":["7–7"],"title":["Did 32% Waterfall Surprise You?"],"url":["http://ieeexplore.ieee.org/document/7819417/"],"volume":["34"]},"creators":{}},{"key":"dig_role_2005","type":"inproceedings","fields":{"abstract":["Frameworks and libraries change their APIs. Migrating an application to the new API is tedious and disrupts the development process. Although some tools and ideas have been proposed to solve the evolution of APIs, most updates are done manually. To better understand the requirements for migration tools we studied the API changes of three frameworks and one library. We discovered that the changes that break existing applications are not random, but they tend to fall into particular categories. Over 80% of these changes are refactorings. This suggests that refactoring-based migration tools should be used to update applications."],"author":["Dig, D.","Johnson, R."],"booktitle":["21st IEEE Int Conf Softw. Maint. ICSM05"],"date":["2005"],"doi":["10.1109/ICSM.2005.90"],"keywords":["API evolution","application program interfaces","Application software","Computer languages","Computer science","Costs","Operating systems","Programming profession","refactoring-based migration tools","software libraries","Software libraries","software maintenance","Software maintenance","software prototyping","Software systems","software tools"],"note":["TL;DR \n\nIt is discovered that the changes that break existing applications are not random, but they tend to fall into particular categories and refactorings, which suggests that refactoring-based migration tools should be used to update applications."],"pages":["389–398"],"title":["The role of refactorings in API evolution"]},"creators":{"author":[{"lastName":"Dig","firstName":"D."},{"lastName":"Johnson","firstName":"R."}]},"sentenceCased":true},{"key":"dimartinoInternetThingsReference2018","type":"article","fields":{"langid":["english"],"abstract":["The term Internet of Things (IoT) is used as an umbrella that covers several topics, related to the application of technological means to monitor, measure and act upon the environment. As a result, it is difficult to determine a univocal architecture to identify as a reference and several scenarios, involving different sensors, smart devices, networks or gateways, can unfold. The data exchanged within and among IoT frameworks are growing exponentially, and the pervasiveness of such systems brings them to come in possession of very sensitive information: as a consequence, Security and Privacy have become a hot topic on the IoT scenery. Furthermore, due to the great variety of technological solutions which are currently available, interoperability issues are bound to arise, especially when no standard API interface, or communication protocol, has been officially adopted."],"author":["Di Martino, B.","Rak, M.","Ficco, M.","Esposito, A.","Maisto, S.A.","Nacchia, S."],"date":["2018-09"],"doi":["10.1016/j.iot.2018.08.008"],"issn":["25426605"],"journaltitle":["Internet Things"],"pages":["99–112"],"shorttitle":["Internet of things reference architectures, security and interoperability"],"title":["Internet of things reference architectures, security and interoperability: A survey"],"volume":["1–2"]},"creators":{"author":[{"lastName":"Di Martino","firstName":"B."},{"lastName":"Rak","firstName":"M."},{"lastName":"Ficco","firstName":"M."},{"lastName":"Esposito","firstName":"A."},{"lastName":"Maisto","firstName":"S.A."},{"lastName":"Nacchia","firstName":"S."}]},"sentenceCased":true},{"key":"dingSwoogleSearchMetadata2004","type":"inproceedings","fields":{"acmid":["1031289"],"author":["Ding, Li","Finin, Tim","Joshi, Anupam","Pan, Rong","Cost, R. Scott","Peng, Yun","Reddivari, Pavan","Doshi, Vishal","Sachs, Joel"],"booktitle":["Proc. Thirteen. ACM Int. Conf. Inf. Knowl. Manag."],"date":["2004"],"isbn":["1-58113-874-1"],"keywords":["crawler","metadata","rank","search","semantic web"],"location":["New York, NY, USA"],"nodoi":["10.1145/1031171.1031289"],"note":["TL;DR \n\nSwoogle is a crawler-based indexing and retrieval system for the Semantic Web that extracts metadata for each discovered document, and computes relations between documents."],"numpages":["8"],"pages":["652–659"],"publisher":["ACM"],"series":["CIKM '04"],"title":["Swoogle: A search and metadata engine for the semantic web"],"url":["http://doi.acm.org/10.1145/1031171.1031289"]},"creators":{"author":[{"lastName":"Ding","firstName":"Li"},{"lastName":"Finin","firstName":"Tim"},{"lastName":"Joshi","firstName":"Anupam"},{"lastName":"Pan","firstName":"Rong"},{"lastName":"Cost","firstName":"R. Scott"},{"lastName":"Peng","firstName":"Yun"},{"lastName":"Reddivari","firstName":"Pavan"},{"lastName":"Doshi","firstName":"Vishal"},{"lastName":"Sachs","firstName":"Joel"}]},"sentenceCased":true},{"key":"DiNoia:2012:LOD:2362499.2362501","type":"inproceedings","fields":{"acmid":["2362501"],"author":["Di Noia, Tommaso","Mirizzi, Roberto","Ostuni, Vito Claudio","Romito, Davide","Zanker, Markus"],"booktitle":["Proc. 8th Int. Conf. Semantic Syst."],"date":["2012"],"isbn":["978-1-4503-1112-0"],"keywords":["content-based recommender systems","DBpedia","freebase","linked data","LinkedMDB","movielens","precision","recall","semantic web","vector space model"],"location":["New York, NY, USA"],"nodoi":["10.1145/2362499.2362501"],"note":["TL;DR \n\nThis paper implemented a content-based RS that leverages the data available within Linked Open Data datasets (in particular DBpedia, Freebase and LinkedMDB) in order to recommend movies to the end users."],"numpages":["8"],"pages":["1–8"],"publisher":["ACM"],"series":["I-semantics '12"],"title":["Linked open data to support content-based recommender systems"],"url":["http://doi.acm.org/10.1145/2362499.2362501"]},"creators":{"author":[{"lastName":"Di Noia","firstName":"Tommaso"},{"lastName":"Mirizzi","firstName":"Roberto"},{"lastName":"Ostuni","firstName":"Vito Claudio"},{"lastName":"Romito","firstName":"Davide"},{"lastName":"Zanker","firstName":"Markus"}]},"sentenceCased":true},{"key":"DiNoia2014","type":"incollection","fields":{"abstract":["In this chapter we present a report of the ESWC 2014 Challenge on Linked Open Data-enabled Recommender Systems, which consisted of three tasks in the context of book recommendation: rating prediction in cold-start situations, top N recommendations from binary user feedback, and diversity in content-based recommendations. Participants were requested to address the tasks by means of recommendation approaches that made use of Linked Open Data and semantic technologies. In the chapter we describe the challenge motivation, goals and tasks, summarize and compare the nine final participant recommendation approaches, and discuss their experimental results and lessons learned. Finally, we end with some conclusions and potential lines of future research."],"author":["Di Noia, Tommaso","Cantador, Iván","Ostuni, Vito Claudio"],"booktitle":["Semantic web evaluation challenge: SemWebEval 2014 at ESWC 2014, anissaras, crete, greece, may 25-29, 2014, revised selected papers"],"date":["2014"],"doi":["10.1007/978-3-319-12024-9₁7"],"editor":["Presutti, Valentina","Stankovic, Milan","Cambria, Erik","Cantador, Iván","Di Iorio, Angelo","Di Noia, Tommaso","Lange, Christoph","Reforgiato Recupero, Diego","Tordai, Anna"],"isbn":["978-3-319-12024-9"],"location":["Cham"],"note":["TL;DR \n\nThis chapter presents a report of the ESWC 2014 Challenge on Linked Open Data-enabled Recommender Systems, which consisted of three tasks in the context of book recommendation: rating prediction in cold-start situations, top N recommendations from binary user feedback, and diversity in content-based recommendations."],"pages":["129–143"],"publisher":["Springer International Publishing"],"title":["Linked open data-enabled recommender systems: ESWC 2014 challenge on book recommendation"]},"creators":{"author":[{"lastName":"Di Noia","firstName":"Tommaso"},{"lastName":"Cantador","firstName":"Iván"},{"lastName":"Ostuni","firstName":"Vito Claudio"}],"editor":[{"lastName":"Presutti","firstName":"Valentina"},{"lastName":"Stankovic","firstName":"Milan"},{"lastName":"Cambria","firstName":"Erik"},{"lastName":"Cantador","firstName":"Iván"},{"lastName":"Di Iorio","firstName":"Angelo"},{"lastName":"Di Noia","firstName":"Tommaso"},{"lastName":"Lange","firstName":"Christoph"},{"lastName":"Reforgiato Recupero","firstName":"Diego"},{"lastName":"Tordai","firstName":"Anna"}]},"sentenceCased":true},{"key":"dinoiaRecommenderSystemsEuropean2022","type":"article","fields":{"langid":["english"],"author":["Di Noia, Tommaso","Tintarev, Nava","Fatourou, Panagiota","Schedl, Markus"],"date":["2022-04"],"doi":["10.1145/3512728"],"issn":["0001-0782, 1557-7317"],"journaltitle":["Commun. ACM"],"note":["TL;DR \n\nThe EC aims at introducing the first comprehensive legal framework on AI, which will identify specific risks for AI, provide a collection of high-risk application domains, propose specific requirements that AI systems should meet when used in such domains, and define obligations for users and providers."],"number":["4"],"pages":["69–73"],"title":["Recommender systems under European AI regulations"],"volume":["65"]},"creators":{"author":[{"lastName":"Di Noia","firstName":"Tommaso"},{"lastName":"Tintarev","firstName":"Nava"},{"lastName":"Fatourou","firstName":"Panagiota"},{"lastName":"Schedl","firstName":"Markus"}]},"sentenceCased":true},{"key":"DiRocco202170","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - Int. Conf. Model-Driven Eng. Lang. Syst., MODELS"],"abstract":["Nowadays, while modeling environments provide users with facilities to specify different kinds of artifacts, e.g., metamodels, models, and transformations, the possibility of learning from previous modeling experiences and being assisted during modeling tasks remains largely unexplored. In this paper, we propose MORGAN, a recommender system based on a graph neural network (GNN) to assist modelers in performing the specification of metamodels and models. The (meta)model being specified, and the training data are encoded in a graph-based format by exploiting natural language processing (NLP) techniques. Afterward, a graph kernel function uses the extracted graphs to provide modelers with relevant recommendations to complete the partially specified (meta)models. We evaluated MORGAN on real-world datasets using various quality metrics, i.e., precision, recall, and F-measure. The experimental results are encouraging and demonstrate the feasibility of our tool to support modelers while specifying metamodels and models. © 2021 IEEE."],"affiliation":["Università degli Studi dell'Aquila, L'Aquila, Italy"],"author":["Di Rocco, J.","Di Sipio, C.","Di Ruscio, D.","Nguyen, P.T."],"booktitle":["24th Int. Conf. Model Driven Eng. Lang. Syst. MODELS 2021 Fukuoka Jpn. Oct. 10-15 2021"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/MODELS50736.2021.00016"],"ids":["di2021gnn,diroccoGNNbasedRecommenderSystem2021,diroccoGNNbasedRecommenderSystem2021a,diroccoGNNbasedRecommenderSystem2021b,roccoGNNbasedRecommenderSystem2021"],"isbn":["978-1-66543-495-9"],"keywords":["/unread","⛔ No INSPIRE recid found","GOAL_Model-Assistance","Graph neural networks","Graph-based","Graphic methods","Language processing techniques","Meta model","Metamodeling","Modeling","Modeling environments","Modeling task","Natural language processing systems","Network-based","notion","Recommender systems","Specifications","TECHNIQUE_GNN","Training data"],"note":["cited By 2 \n\ncited By 4 \n\ncited By 6 \n\ncited By 6 \n\ncited By 14 \n\nTL;DR \n\nMORGAN, a recommender system based on a graph neural network (GNN) to assist modelers in performing the specification of metamodels and models and evaluated on real-world datasets using various quality metrics, i.e., precision, recall, and F-measures."],"pages":["70–81"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS 2021"],"source":["Scopus"],"title":["A GNN-based recommender system to assist the specification of metamodels and models"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Nguyen","firstName":"P.T."}]},"sentenceCased":true},{"key":"diroccoDevelopmentRecommendationSystems2021","type":"article","fields":{"langid":["english"],"author":["Di Rocco, J.","Di Ruscio, D.","Di Sipio, C.","Nguyen, P.T.","Rubei, R."],"date":["2021"],"doi":["10.1007/s10664-021-09963-7"],"eprint":["2103.06987"],"eprinttype":["arxiv"],"ids":["Rocco2021DevelopmentOR,di_rocco_development_2021,diroccoDevelopmentRecommendationSystems2021a,diroccoDevelopmentRecommendationSystems2021c,roccoDevelopmentRecommendationSystems2021,roccoDevelopmentRecommendationSystems2021a"],"issn":["13823256"],"journaltitle":["Empir. Softw. Eng."],"keywords":["API function calls","Application programming interfaces (API)","Development activity","Development process","Engineering research","Evaluation approach","Open source software","Open systems","Performance measure","Recommendation systems for software engineerings","Recommender systems","Research communities","Techniques and tools"],"note":["cited By 10 \n\ncited By 10 \n\ncited By 12 \n\nTL;DR \n\nThis paper is an experience report to present the knowledge pertinent to the set of recommendation systems developed through the CROSSMINER project, and explains in detail the challenges the team had to deal with, together with the related lessons learned when developing and evaluating these systems."],"number":["4"],"publisher":["Springer"],"title":["Development of recommendation systems for software engineering: The CROSSMINER experience"],"volume":["26"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Rubei","firstName":"R."}]},"sentenceCased":true},{"key":"diroccoFindingNEMORecommender2022","type":"article","fields":{"abstract":["Nowadays, while modeling environments provide users with facilities to specify different kinds of artifacts, e.g., metamodels, models, and transformations, the possibility of learning from previous modeling experiences and being assisted during modeling tasks remains largely unexplored. In this paper, we propose NEMO, a recommender system based on an Encoder-Decoder neural network to assist modelers in performing model editing operations. NEMO learns from past modeling activities and performs predictions employing a deep learning technique. Such an algorithm has been successfully applied in machine translation to convert a text from a language to another foreign language and vice versa. An empirical evaluation on a dataset of BPMN change-based persistent model demonstrates that the technique permits learning from existing operations and effectively predicting the next editing operations with considerably high prediction accuracy. In particular, NEMO gets 0.977 as precision/recall and 0.992 as success rate score by the best performance. © 2022 ACM."],"author":["Di Rocco, J.","Di Sipio, C.","Nguyen, P.T.","Di Ruscio, D.","Pierantonio, A."],"date":["2022"],"doi":["10.1145/3550355.3552459"],"ids":["diroccoFindingNEMORecommender2022a,diroccoFindingNEMORecommender2022b,roccoFindingNEMORecommender2022"],"isbn":["978-1-4503-9466-6"],"journaltitle":["Proc. - 25th ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS 2022"],"keywords":["Deep learning","Editing operations","Encoder-decoder","Forecasting","Learn+","Learning systems","Learning techniques","Machine translations","Meta model","Modeling environments","Modeling operation","Modeling task","Neural-networks","Recommender systems","User profile"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0"],"pages":["154–164"],"publisher":["Association for Computing Machinery, Inc"],"title":["Finding with NEMO: A Recommender System to Forecast the Next Modeling Operations"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Pierantonio","firstName":"A."}]}},{"key":"diroccoHybridRecRecommenderSystem2022","type":"article","fields":{"langid":["english"],"author":["Di Rocco, J.","Di Ruscio, D.","Di Sipio, C.","Nguyen, P.T.","Rubei, R."],"date":["2022"],"doi":["10.1007/s10489-022-03864-y"],"ids":["diroccoHybridRecRecommenderSystem2022a,diroccoHybridRecRecommenderSystem2023"],"issn":["0924669X"],"journaltitle":["Appl. Intell."],"keywords":["Bayesia n networks","Bayesian networks","Bug reports","Codes (symbols)","Collaborative filtering","Github tagging","Mining software","Mining software repository","Program debugging","Reachability","Recommender systems","Short texts","Software repositories","Source codes","Stochastic networks","Stochastic systems"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\nTL;DR \n\nHybridRec, a recommender system based on stochastic and collaborative-filtering techniques to generate more relevant topics for GitHub topics, is built and it is concluded that the conceived framework can be used to help developers increase their projects’ visibility."],"publisher":["Springer"],"title":["HybridRec: A recommender system for tagging GitHub repositories"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Rubei","firstName":"R."}]},"sentenceCased":true},{"key":"diroccoMemoRecRecommenderSystem2022","type":"article","fields":{"author":["DI ROCCO, Juri","DI RUSCIO, Davide","DI SIPIO, Claudio","Nguyen, Phuong T.","Pierantonio, Alfonso"],"date":["2022"],"doi":["10.1007/s10270-022-00994-2"],"ids":["diroccoMemoRecRecommenderSystem2022a,diroccoMemoRecRecommenderSystem2022b,diroccoMemoRecRecommenderSystem2022c,diroccoMemoRecRecommenderSystem2023"],"journaltitle":["Softw. Syst. Model."],"keywords":["Applications domains","Collaborative filtering","Collaborative filtering techniques","Development process","Filtering strategies","Machinery","Meta model","Metaclass","Metamodeling","Model-driven Engineering","Recommender systems","Software design","Structural feature","Whole process"],"note":["cited By 1 \n\ncited By 2 \n\ncited By 2 \n\nTL;DR \n\nThe results demonstrate that MemoRec is capable of suggesting relevant items given a partial metamodel and supporting modelers in their task, and the quality of the work is assessed with respect to different metrics, i.e., success rate, precision, and recall."],"pages":["1–21"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"title":["MemoRec: A recommender system for assisting modelers in specifying metamodels"]},"creators":{"author":[{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"DI SIPIO","firstName":"Claudio"},{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"diroccoNeedBodyKnowledge2021","type":"inproceedings","fields":{"langid":["english"],"author":["Di Rocco, J.","Di Ruscio, D.","Di Sipio, C.","Nguyen, P.T.","Pomo, C."],"booktitle":["CEUR Workshop Proc."],"date":["2021"],"editor":["Anelli V.W., Basile P., Di Noia T., Donini F.M., Musto C., Narducci F., Zanker M., Abdollahpouri H., Bogers T., Mobasher B., Petersen C., Pera M.S."],"ids":["diroccoNeedBodyKnowledge2021b,diroccoNeedBodyKnowledge2021c"],"issn":["16130073"],"keywords":["Applications domains","Body of knowledge","Core set","Model-driven Engineering","Recommender systems","Software engineering","Teachers'"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0"],"publisher":["CEUR-WS"],"title":["On the need for a body of knowledge on recommender systems"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116904185&partnerID=40&md5=0959deaf4805904d6d7e00eeac1b162f"],"volume":["2960"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Pomo","firstName":"C."}],"editor":[{"lastName":"Anelli V.W.","suffix":"Basile P.","firstName":"Di Noia T., Donini F.M., Musto C., Narducci F., Zanker M., Abdollahpouri H., Bogers T., Mobasher B., Petersen C., Pera M.S."}]},"sentenceCased":true},{"key":"diroccoNeedBodyKnowledge2021a","type":"article","fields":{"author":["Di Rocco, J.","Di Ruscio, D.","Di Sipio, C.","Nguyen, P.T.","Pomo, C."],"date":["2021"],"ids":["roccoNeedBodyKnowledge2021"],"journaltitle":["Jt. Workshop Proc. 3rd Ed. Knowl.-Aware Conversational Recomm. Syst. KaRS 5th Ed. Recomm. Complex Environ. ComplexRec Co-Located 15th ACM Conf. Recomm. Syst. RecSys 2021 Virtual Event Amst. Neth. Sept. 25 2021"],"note":["cited By 0 \n\nTL;DR \n\nThis work motivates a BOK for recommender systems and proposes a methodology that can be employed to support the definition of an RSBOK, a precisely curated and organized core set of concepts and practices."],"series":["CEUR Workshop Proceedings"],"title":["On the Need for a Body of Knowledge on Recommender Systems (Short paper)"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116904185&partnerID=40&md5=0959deaf4805904d6d7e00eeac1b162f"],"volume":["2960"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Pomo","firstName":"C."}]},"sentenceCased":true},{"key":"diroccoUsingATLTransformation2016","type":"incollection","fields":{"langid":["english"],"abstract":["In the last years, the increasing complexity of Model-Driven Engineering (MDE) tools and techniques has led to higher demands in terms of computation, interoperability, and configuration management. Harnessing the softwareas-a-service (SaaS) paradigm and shifting applications from local, mono-core implementations to cloud-based architectures is key to enhance scalability and flexibility. To this end, we propose MDEForge: an extensible, collaborative modeling platform that provides remote model management facilities and prevents the user from focussing on time-consuming, and less creative procedures. This demo paper illustrates the extensibility of MDEForge by integrating ATL services for the remote execution, automated testing, and static analysis of ATL transformations. The usefulness of their employment under the SaaS paradigm is demonstrated with a case-study showing a wide range of new application possibilities."],"author":["Di Rocco, Juri","Di Ruscio, Davide","Pierantonio, Alfonso","Cuadrado, Jesús Sánchez","family=Lara, given=Juan, prefix=de, useprefix=true","Guerra, Esther"],"booktitle":["9th International Conference on Theory and Practice of Model Transformations, ICMT 2016 Held as Part of Conference on Software Technologies: Applications and Foundations, STAF 2016"],"date":["2016"],"doi":["10.1007/978-3-319-42064-6_5"],"editor":["Van Gorp, Pieter","Engels, Gregor"],"ids":["diroccoUsingATLTransformation2016a,diroccoUsingATLTransformation2016b,roccoUsingATLTransformation2016"],"isbn":["978-3-319-42063-9 978-3-319-42064-6"],"keywords":["Application programs","Cloud-based architectures","Collaborative model","Configuration management","Integration testing","Model management","Model-driven Engineering","Remote execution","Static analysis Automated testing","Tools and techniques"],"location":["Cham"],"note":["cited By 6 \n\ncited By 6 \n\nTL;DR \n\nThis paper proposes MDEForge: an extensible, collaborative modeling platform that provides remote model management facilities and prevents the user from focussing on time-consuming, and less creative procedures."],"pages":["70–78"],"publisher":["Springer International Publishing"],"series":["Lecture Notes in Computer Science"],"title":["Using ATL Transformation Services in the MDEForge Collaborative Modeling Platform"],"volume":["9765"]},"creators":{"author":[{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Cuadrado","firstName":"Jesús Sánchez"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true},{"lastName":"Guerra","firstName":"Esther"}],"editor":[{"lastName":"Van Gorp","firstName":"Pieter"},{"lastName":"Engels","firstName":"Gregor"}]}},{"key":"DIRUSCIO12","type":"article","fields":{"langid":["english"],"author":["Ruscio, Davide Di","Iovino, Ludovico","Pierantonio, Alfonso"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2012"],"doi":["10.1109/MS.2012.153"],"journaltitle":["IEEE Softw,"],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["6"],"pages":["78–84"],"timestamp":["Mon, 08 Jun 2020 22:31:52 +0200"],"title":["Coupled evolution in model-driven engineering"],"volume":["29"]},"creators":{"author":[{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"diruscioACMInternationalConference2010","type":"article","fields":{"author":["Di Ruscio, D.","Kolovos, D."],"date":["2010"],"ids":["diruscioACMInternationalConference2010a"],"journaltitle":["ACM Int. Conf. Proceeding Ser."],"note":["cited By 0 \n\ncited By 0"],"title":["ACM International Conference Proceeding Series: Foreword"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-77955140503&partnerID=40&md5=26e00eed22f2ba08e5832f36cd6e8f6d"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Kolovos","firstName":"D."}]}},{"key":"diruscioAutomatedCoevolutionGMF2011","type":"inproceedings","fields":{"abstract":["The Eclipse Graphical Modeling (GMF) Framework provides the major approach for implementing visual languages on top of the Eclipse platform. GMF relies on a family of modeling languages to describe abstract syntax, concrete syntax as well as other aspects of the visual language and its implementation in an editor. GMF uses a model-driven approach to map the different GMF models to Java code. The framework, as it stands, lacks support for evolution. In particular, there is no support for propagating changes from the domain model (i.e., the abstract syntax of the visual language) to other editor models. We analyze the resulting co-evolution challenge, and we provide a solution by means of GMF model adapters, which automate the propagation of domain-model changes. These GMF model adapters are special model-to-model transformations that are driven by difference models for domain-model changes."],"author":["DI RUSCIO, Davide","Lammel, R","Pierantonio, Alfonso"],"booktitle":["Softw. Lang. Eng. - Third Int. Conf. SLE 2010 Eindh. Neth. Oct. 12-13 2010 Revis. Sel. Pap."],"date":["2011"],"doi":["10.1007/978-3-642-19440-5_9"],"eprint":["1006.5761"],"eprinttype":["arxiv"],"ids":["diruscioAutomatedCoevolutionGMF2011a,ruscioAutomatedCoevolutionGMF2010,ruscioAutomatedCoevolutionGMF2010a"],"isbn":["978-3-642-19439-9"],"location":["BERLIN HEIDELBERG"],"note":["cited By 42 \n\ncited By 42 \n\nTL;DR \n\nThis work analyzes the resulting co-evolution challenge, and provides a solution by means of GMF model adapters, which automate the propagation of domain-model changes and special model-to-model transformations that are driven by difference models for domain- model changes."],"pages":["143–162"],"publisher":["Springer-Verlag"],"series":["LECTURE NOTES IN COMPUTER SCIENCE"],"title":["Automated Co-evolution of GMF editor models"],"volume":["abs/1006.5761"]},"creators":{"author":[{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Lammel","firstName":"R"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"diruscioAutomaticGenerationDetailed2016","type":"inproceedings","fields":{"author":["DI RUSCIO, Davide","Malavolta, Ivano","Pelliccione, Patrizio","Tivoli, Massimo"],"booktitle":["Proc. ACMIEEE 19th Int. Conf. Model Driven Eng. Lang. Syst. St.-Malo Fr. Oct. 2-7 2016"],"date":["2016"],"doi":["10.1145/2976767.2976794"],"ids":["diruscioAutomaticGenerationDetailed2016a,diruscioAutomaticGenerationDetailed2016b,ruscioAutomaticGenerationDetailed2016"],"isbn":["978-1-4503-4321-3"],"keywords":["Software"],"note":["cited By 23 \n\ncited By 23 \n\nTL;DR \n\nThis paper considers mission specifications expressed through a domain-specific modeling language which can be effectively used by end-users with no technical expertise, e.g., firefighters and rescue workers, and generates the lower level logic that each drone must perform to accomplish the specified mission."],"pages":["45–55"],"publisher":["Association for Computing Machinery, Inc"],"title":["Automatic Generation of detailed Flight Plans from High-level Mission Descriptions"]},"creators":{"author":[{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Malavolta","firstName":"Ivano"},{"lastName":"Pelliccione","firstName":"Patrizio"},{"lastName":"Tivoli","firstName":"Massimo"}]},"sentenceCased":true},{"key":"diruscioCorrectionLowcodeDevelopment2022","type":"article","fields":{"langid":["english"],"author":["Di Ruscio, D.","Kolovos, D.","family=Lara, given=J., prefix=de, useprefix=true","Pierantonio, A.","Tisi, M.","Wimmer, M."],"date":["2022"],"doi":["10.1007/s10270-022-01038-5"],"ids":["diruscioCorrectionLowcodeDevelopment2022a,diruscioCorrectionLowcodeDevelopment2022c,ruscioCorrectionLowcodeDevelopment2022"],"issn":["16191366"],"journaltitle":["Softw. Syst. Model."],"note":["cited By 0 \n\ncited By 0 \n\ncited By 1"],"number":["5"],"pages":["1687"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"title":["Correction to: Low-code development and model-driven engineering: Two sides of the same coin? (Software and Systems Modeling, (2022), 21, 2, (437-446), 10.1007/S10270-021-00970-2)"],"volume":["21"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Kolovos","firstName":"D."},{"lastName":"Lara","firstName":"J.","prefix":"de","useprefix":true},{"lastName":"Pierantonio","firstName":"A."},{"lastName":"Tisi","firstName":"M."},{"lastName":"Wimmer","firstName":"M."}]},"sentenceCased":true},{"key":"diruscioEditorialThemeSection2022","type":"article","fields":{"langid":["english"],"author":["Di Ruscio, D.","Guerra, E.","Tisi, M."],"date":["2022"],"doi":["10.1007/s10270-022-01045-6"],"ids":["diruscioEditorialThemeSection2022a,diruscioEditorialThemeSection2022c,ruscioEditorialThemeSection2022"],"issn":["16191366"],"journaltitle":["Softw. Syst. Model."],"note":["cited By 0 \n\ncited By 0 \n\nTL;DR \n\nThe growing need for secure, trustworthy, and cost-efficient software, as well as recent developments in cloud computing technologies, and the shortage of highly skilled professional software developers have given rise to a new generation of low-code software development platforms, such as Google AppSheet and Microsoft PowerApps."],"number":["5"],"pages":["1957–1958"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"title":["Editorial to theme section on modeling in low-code development platforms"],"volume":["21"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Guerra","firstName":"E."},{"lastName":"Tisi","firstName":"M."}]},"sentenceCased":true},{"key":"diruscioForeward2011","type":"article","fields":{"author":["Di Ruscio, D.","Kolovos, D."],"date":["2011"],"ids":["diruscioForeward2011a"],"journaltitle":["ACM Int. Conf. Proceeding Ser."],"note":["cited By 0 \n\ncited By 0"],"title":["Foreward"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-80051525717&partnerID=40&md5=1803be81852072c0e1a2ad4bc4157532"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Kolovos","firstName":"D."}]}},{"key":"diruscioLowcodeDevelopmentModeldriven2022","type":"article","fields":{"langid":["english"],"author":["Di Ruscio, D.","Kolovos, D.","family=Lara, given=J., prefix=de, useprefix=true","Pierantonio, A.","Tisi, M.","Wimmer, M."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2022"],"doi":["10.1007/s10270-021-00970-2"],"ids":["DBLP:journals/sosym/RuscioKLPTW22,RuscioKLPTW22,diruscioLowcodeDevelopmentModeldriven2022b,diruscioLowcodeDevelopmentModeldriven2022c,diruscioLowcodeDevelopmentModeldriven2022e,diruscioLowcodeDevelopmentModeldriven2022f,ruscioLowcodeDevelopmentModeldriven2022"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found","Code development","Development platform","Low-code development","Manual coding","Model-driven","Model-driven engineering","Model-driven Engineering","No-code development","Professional programmers","Visual development"],"note":["cited By 9 \n\ncited By 11 \n\ncited By 28 \n\nTL;DR \n\nThis expert-voice paper compares and contrast low-code and model-driven approaches, identifying their differences and commonalities, analysing their strong and weak points, and proposing directions for cross-pollination."],"number":["2"],"pages":["437–446"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"timestamp":["Thu, 23 Jun 2022 20:00:12 +0200"],"title":["Low-code development and model-driven engineering: Two sides of the same coin?"],"volume":["21"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Kolovos","firstName":"D."},{"lastName":"Lara","firstName":"J.","prefix":"de","useprefix":true},{"lastName":"Pierantonio","firstName":"A."},{"lastName":"Tisi","firstName":"M."},{"lastName":"Wimmer","firstName":"M."}]},"sentenceCased":true},{"key":"diruscioManagingCoupledEvolution2013","type":"article","fields":{"author":["Di Ruscio, D.","Iovino, L.","Pierantonio, A."],"date":["2013"],"doi":["10.1109/SEAA.2013.22"],"ids":["diruscioManagingCoupledEvolution2013a,ruscioManagingCoupledEvolution2013"],"journaltitle":["Proc. - 39th Euromicro Conf. Ser. Softw. Eng. Adv. Appl. SEAA 2013"],"note":["cited By 12 \n\ncited By 12"],"pages":["114–121"],"title":["Managing the coupled evolution of metamodels and textual concrete syntax specifications"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Iovino","firstName":"L."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"diruscioModelingAssistantManage2023","type":"article","fields":{"abstract":["Context: Model-Driven Engineering helps formalize problem domains by using metamodels. Modeling ecosystems consisting of purposely designed editors, transformations, and code generators are defined on top of the metamodels. Similar to other software artifacts, metamodels can evolve by possibly compromising the validity of existing artifacts. Coupled evolution provides techniques for restoring artifacts’ validity in response to metamodel evolution. Objective: In this paper, we propose the adoption of deprecation in metamodeling to mitigate the difficulties in performing manual model adaptations in response to metamodel evolutions. Moreover, we aim to measure and resolve the technical debt during the co-evolution, which can be seen as the outcome of procrastinating artifact migrations. Methods: We propose a novel approach and supporting tool to manage the concepts of deprecation and technical debt in metamodeling. Results: We conducted a judgment study using the focus group methodology to assess the proposed approach's usefulness in migrating models affected by breaking non-resolvable changes completely. Conclusions: The proposed approach can identify the technical debt in metamodel evolution. Furthermore, it deals with the coupled evolution problem by assisting the modeler through interactive visualization tools, which highlight and quantify the technical dept of the artifacts under analysis that need to be evolved. © 2022 Elsevier B.V."],"author":["Di Ruscio, D.","Di Salle, A.","Iovino, L.","Pierantonio, A."],"date":["2023"],"doi":["10.1016/j.infsof.2022.107146"],"ids":["diruscioModelingAssistantManage2023a"],"issn":["09505849"],"journaltitle":["Inf. Softw. Technol."],"keywords":["Context models","Coupled evolution","Deprecation","MDE","Meta model","Meta-model evolutions","Metamodeling","Model-driven Engineering","Problem domain","Software engineering","Technical debts","Visualization"],"note":["cited By 0"],"publisher":["Elsevier B.V."],"title":["A modeling assistant to manage technical debt in coupled evolution"],"volume":["156"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Di Salle","firstName":"A."},{"lastName":"Iovino","firstName":"L."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"diruscioPreface2014","type":"inproceedings","fields":{"author":["DI RUSCIO, Davide","Varro, Daniel"],"booktitle":["CEUR Workshop Proc."],"date":["2014"],"ids":["diruscioPreface2014a,diruscioPreface2014b,diruscioPreface2014c,diruscioPreface2014d,diruscioPreface2014e,diruscioPreface2014f,diruscioPreface2015,diruscioPreface2015a,kolovosPreface2015,kolovosPreface2015a"],"isbn":["978-3-319-08788-7"],"keywords":["Computer Science (all)","Computer Science Applications1707 Computer Vision and Pattern Recognition","Software","Theoretical Computer Science"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0 \n\nTL;DR \n\nSome of the field’s leaders in atmospheric chemistry, in both the gas and the aerosol phases, provide insights in this volume of Topics in Current Chemistry."],"pages":["VII–VIII"],"publisher":["Association for Computing Machinery, Inc"],"title":["Preface"],"url":["http://springerlink.com/content/0302-9743/copyright/2005/"],"volume":["8568"]},"creators":{"author":[{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Varro","firstName":"Daniel"}]}},{"key":"diruscioPreface2017","type":"article","fields":{"author":["Di Ruscio, D.","Koenig, B."],"date":["2017"],"ids":["diruscioPreface2017a"],"journaltitle":["CEUR Workshop Proc."],"note":["cited By 0 \n\ncited By 0 \n\nTL;DR \n\nSome of the field’s leaders in atmospheric chemistry, in both the gas and the aerosol phases, provide insights in this volume of Topics in Current Chemistry."],"title":["Preface"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033449020&partnerID=40&md5=f48c65bca87745d014af6cc28eb005e9"],"volume":["1955"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Koenig","firstName":"B."}]}},{"key":"diruscioThWorkshopFlexible2018","type":"article","fields":{"author":["Di Ruscio, D.","De Lara, J.","Pierantonio, A."],"date":["2018"],"ids":["diruscioThWorkshopFlexible2018a"],"journaltitle":["CEUR Workshop Proc."],"note":["cited By 0 \n\ncited By 0"],"pages":["201"],"title":["4 th workshop on flexible model-driven engineering (FlexMDE 2018)"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063110971&partnerID=40&md5=705fc127b25951907174123b6397bb90"],"volume":["2245"]},"creators":{"author":[{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"De Lara","firstName":"J."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"disallePILOTSynergyText2022","type":"inproceedings","fields":{"langid":["english"],"author":["Di Salle, A.","Rota, A.","Nguyen, P.T.","Di Ruscio, D.","Fontana, F.A.","Sala, I."],"booktitle":["Proc. - Int. Conf. Tech. Debt 2022 TechDebt 2022"],"date":["2022"],"doi":["10.1145/3524843.3528093"],"ids":["disallePILOTSynergyText2022a,disallePILOTSynergyText2022b,disallePILOTSynergyText2022c,sallePILOTSynergyText2022"],"isbn":["978-1-4503-9304-1"],"keywords":["Additional treatment","Codes (symbols)","Development phasis","Feedforward neural networks","Language processing techniques","Learning algorithms","Natural language processing systems","Natural language processing technique","Natural languages","Neural-networks","Processing Network","Self-admitted technical debt","Semantics","Technical debts","Text processing","Text-processing"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0 \n\nTL;DR \n\nThis work introduces PILOT, a technical debt detector built on top of a combination of different natural language processing (NLP) and machine learning (ML) techniques, and shows that it obtains an encouraging performance and outperforms a well-established baseline."],"pages":["41–45"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["PILOT: Synergy between Text Processing and Neural Networks to Detect Self-Admitted Technical Debt"]},"creators":{"author":[{"lastName":"Di Salle","firstName":"A."},{"lastName":"Rota","firstName":"A."},{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Fontana","firstName":"F.A."},{"lastName":"Sala","firstName":"I."}]}},{"key":"disipioDemocratizingDevelopmentRecommender2020","type":"article","fields":{"langid":["english"],"abstract":["In recent years, recommender systems have gained an increasingly crucial role in software engineering. Such systems allow developers to exploit a plethora of reusable artifacts, including source code and documentation, which can support the development activities. However, recommender systems are complex tools that are difficult to personalize or fine-tune if developers want to improve them for increasing the relevance of the retrievable recommendations."],"author":["Di Sipio, C.","Di Ruscio, D.","Nguyen, P.T."],"date":["2020"],"doi":["10.1145/3417990.3420202"],"eventtitle":["MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems"],"ids":["disipioDemocratizingDevelopmentRecommender2020a,disipioDemocratizingDevelopmentRecommender2020b,sipioDemocratizingDevelopmentRecommender2020"],"isbn":["978-1-4503-8135-2"],"journaltitle":["Proc. - 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS-C 2020 - Companion Proc."],"location":["Virtual Event Canada"],"note":["cited By 11 \n\ncited By 11 \n\nTL;DR \n\nThis paper proposes a low-code development approach to engineering recommender systems by means of a metamodel to represent the peculiar components and dedicated supporting tools are proposed to help developers easily model and build their custom recommender system."],"pages":["471–479"],"publisher":["ACM"],"title":["Democratizing the development of recommender systems by means of low-code platforms"]},"creators":{"author":[{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Nguyen","firstName":"P.T."}]},"sentenceCased":true},{"key":"disipioLowCodeToolSupporting2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["The design of recommender systems (RSs) to support software development encompasses the fulfillment of different steps, including data preprocessing, choice of the most appropriate algorithms, item delivery. Though RSs can alleviate the curse of information overload, existing approaches resemble black-box systems, in which the end-user is not expected to fine-tune or personalize the overall process. In this work, we propose LEV4REC, a low-code environment to assist developers in designing, configuring, and delivering recommender systems. The first step supported by the proposed tool includes defining an initial model that allows for the configuration of the crucial components of the wanted RS. Then, a subsequent phase is performed to finalize the RS design, e.g., to specify configuration parameters. LEV4REC is eventually capable of generating source code for the desired RS. To evaluate the capabilities of the approach, we used LEV4REC to specify two existing RSs built on top of two different recommendation algorithms, i.e., collaborative filtering and supervised machine learning. © 2021 Owner/Author."],"author":["Di Sipio, C.","Di Rocco, J.","Di Ruscio, D.","Nguyen, P.T."],"booktitle":["RecSys 21 Fifteenth ACM Conf. Recomm. Syst. Amst. Neth. 27 Sept. 2021 - 1 Oct. 2021"],"date":["2021"],"doi":["10.1145/3460231.3478885"],"ids":["disipioLowCodeToolSupporting2021a,disipioLowCodeToolSupporting2021b,sipioLowCodeToolSupporting2021"],"isbn":["978-1-4503-8458-2"],"keywords":["Black box system","Codes (symbols)","Collaborative filtering","Configuration parameters","Data preprocessing","End-users","Information overloads","Lowcode","Model-driven","Overall process","Recommender systems","Software design","Source codes","Supervised learning","Tool supporting"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 4 \n\nTL;DR \n\nLEV4REC, a low-code environment to assist developers in designing, configuring, and delivering recommender systems, is proposed and used to specify two existing RSs built on top of two different recommendation algorithms, i.e., collaborative filtering and supervised machine learning."],"pages":["741–744"],"publisher":["Association for Computing Machinery, Inc"],"title":["A Low-Code tool supporting the development of recommender systems"]},"creators":{"author":[{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Nguyen","firstName":"P.T."}]},"sentenceCased":true},{"key":"disipioMORGANModelingRecommender2023","type":"article","fields":{"abstract":["Model-driven engineering (MDE) is an effective means of synchronizing among stakeholders, thereby being a crucial part of the software development life cycle. In recent years, MDE has been on the rise, triggering the need for automatic modeling assistants to support metamodelers during their daily activities. Among others, it is crucial to enable model designers to choose suitable components while working on new (meta)models. In our previous work, we proposed MORGAN, a graph kernel-based recommender system to assist developers in completing models and metamodels. To provide input for the recommendation engine, we convert training data into a graph-based format, making use of various natural language processing (NLP) techniques. The extracted graphs are then fed as input for a recommendation engine based on graph kernel similarity, which performs predictions to provide modelers with relevant recommendations to complete the partially specified (meta)models. In this paper, we extend the proposed tool in different dimensions, resulting in a more advanced recommender system. Firstly, we equip it with the ability to support recommendations for JSON schema that provides a model representation of data handling operations. Secondly, we introduce additional preprocessing steps and a kernel similarity function based on item frequency, aiming to enhance the capabilities, providing more precise recommendations. Thirdly, we study the proposed enhancements, conducting a well-structured evaluation by considering three real-world datasets. Although the increasing size of the training data negatively affects the computation time, the experimental results demonstrate that the newly introduced mechanisms allow MORGAN to improve its recommendations compared to its preceding version. © 2023, The Author(s)."],"author":["Di Sipio, C.","Di Rocco, J.","Di Ruscio, D.","Nguyen, P.T."],"date":["2023"],"doi":["10.1007/s10270-023-01102-8"],"issn":["16191366"],"journaltitle":["Softw. Syst. Model."],"keywords":["Automatic modeling","Daily activity","Data handling","Engines","Graph kernels","Graph-based","Graphic methods","Life cycle","Meta model","Metamodeling","Model-driven Engineering","Models and metamodels","Natural language processing systems","Petroleum reservoir evaluation","Recommender systems","Software design","Software development life-cycle","Training data"],"note":["cited By 0 \n\nTL;DR \n\nThe proposed MORGAN recommender system is equipped with the ability to support recommendations for JSON schema that provides a model representation of data handling operations, and additional preprocessing steps and a kernel similarity function based on item frequency are introduced, aiming to enhance the capabilities, providing more precise recommendations."],"publisher":["Springer Science and Business Media Deutschland GmbH"],"title":["MORGAN: A modeling recommender system based on graph kernel"]},"creators":{"author":[{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Nguyen","firstName":"P.T."}]},"sentenceCased":true},{"key":"disipioMultinomialNaiveBayesian2020","type":"inproceedings","fields":{"langid":["english"],"abstract":["GitHub has become a precious service for storing and managing software source code. Over the last year, 10M new developers have joined the GitHub community, contributing to more than 44M repositories. In order to help developers increase the reachability of their repositories, in 2017 GitHub introduced the possibility to classify them by means of topics. However, assigning wrong topics to a given repository can compromise the possibility of helping other developers reach it and eventually contribute to its development."],"author":["Di Sipio, Claudio","Di Ruscio, Davide","Rubei, Riccardo","Nguyen, Phuong T"],"booktitle":["EASE 20 Eval. Assess. Softw. Eng. Trondheim Nor. April 15-17 2020"],"date":["2020"],"doi":["10.1145/3383219.3383227"],"ids":["disipioMultinomialNaiveBayesian2020a,disipioMultinomialNaiveBayesian2020b,sipioMultinomialNaiveBayesian2020"],"keywords":["GitHub topics","Multinomial Naïve Bayesian network"],"note":["cited By 14 \n\ncited By 14"],"pages":["71–80"],"publisher":["ACM"],"title":["A Multinomial Naive Bayesian (MNB) network to automatically recommend topics for GitHub repositories"]},"creators":{"author":[{"lastName":"Di Sipio","firstName":"Claudio"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Rubei","firstName":"Riccardo"},{"lastName":"Nguyen","firstName":"Phuong T"}]},"sentenceCased":true},{"key":"diskinTraceabilityMappingsFundamental2017","type":"incollection","fields":{"author":["Diskin, Zinovy","Gómez, Abel","Cabot, Jordi"],"booktitle":["Fundamental Approaches to Software Engineering"],"date":["2017"],"doi":["10.1007/978-3-662-54494-5_14"],"editor":["Huisman, Marieke","Rubin, Julia"],"isbn":["978-3-662-54493-8 978-3-662-54494-5"],"location":["Berlin, Heidelberg"],"pages":["247–263"],"publisher":["Springer Berlin Heidelberg"],"title":["Traceability Mappings as a Fundamental Instrument in Model Transformations"],"volume":["10202"]},"creators":{"author":[{"lastName":"Diskin","firstName":"Zinovy"},{"lastName":"Gómez","firstName":"Abel"},{"lastName":"Cabot","firstName":"Jordi"}],"editor":[{"lastName":"Huisman","firstName":"Marieke"},{"lastName":"Rubin","firstName":"Julia"}]}},{"key":"divincenzoEnhancingSyntaxExpressiveness2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["Domain-specific modelling helps tame the complexity of today's application domains by formalizing concepts and their relationships in modelling languages. While meta-editors are widely-used frameworks for implementing graphical editors for such modelling languages, they are best suitable for defining novel topological notations, i.e., syntaxes where the model layout does not contribute to the model semantics. In contrast, many engineering fields, e.g., railways systems or electrical engineering, use notations that, on the one hand, are standard and, on the other hand, are demanding more expressive power than topological syntaxes. In this paper, we discuss the problem of enhancing the expressiveness of modelling editors towards geometric/positional syntaxes. Several potential solutions are experimentally implemented on the jjodel web-based platform with the aim of identifying challenges and opportunities. © 2021 IEEE."],"author":["Di Vincenzo, D.","Di Rocco, J.","Di Ruscio, D.","Pierantonio, A."],"booktitle":["Companion Proc. - 24th Int. Conf. Model-Driven Eng. Lang. Syst. MODELS-C 2021"],"date":["2021"],"doi":["10.1109/MODELS-C53483.2021.00089"],"eprint":["2111.14453"],"eprinttype":["arxiv"],"ids":["divincenzoEnhancingSyntaxExpressiveness2021a,divincenzoEnhancingSyntaxExpressiveness2021b,divincenzoEnhancingSyntaxExpressiveness2021c,vincenzoEnhancingSyntaxExpressiveness2021,vincenzoEnhancingSyntaxExpressiveness2021a"],"isbn":["978-1-66542-484-4"],"keywords":["Applications domains","Component","Domain-specific modelling","Engineering fields","Formatting","Graphical editors","Insert","Model semantics","Modeling languages","Semantics","Style","Styling","Syntactics","Topology"],"note":["cited By 1 \n\ncited By 1 \n\ncited By 1 \n\ncited By 1"],"pages":["586–594"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Enhancing syntax expressiveness in domain-specific modelling"],"volume":["abs/2111.14453"]},"creators":{"author":[{"lastName":"Di Vincenzo","firstName":"D."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"doAmaral20225205","type":"article","fields":{"abstract":["In the context of modern industry, optimization emerges as one of the most powerful tools, allowing decision-makers to allocate their resources more assertively and deal with complex manufacturing problems. Moreover, manufacturing systems usually involve activities’ interdependency and high stochastic levels, which are necessary to associate optimization and simulation techniques to solve problems. Although simulation optimization is a powerful technique, it can converge on a good solution, which often limits its use in day-to-day operations. As an alternative, metamodels may be used to replace simulation models in the optimization process. In recent years, with the development in the machine learning area, algorithms with high learning capacity have emerged, making the metamodel-based simulation optimization (MBSO) a promising study field. Based on the latest theoretical research on the theme, MBSO techniques have been widely used to solve manufacturing problems. However, there is still no consensus about the experimental design, the learning algorithms, and the importance of the hyperparameter optimization step. Then, the article evaluates the performance of six machine learning algorithms trained with and without hyperparameter optimization, two experimental designs, and five different sample sizes to build metamodels in three real manufacturing cases. Based on the results, the random forest algorithm and the random design with 40 × sample size expressed the better performance to metamodels’ development. Furthermore, the hyperparameter optimization step reduced the metamodels’ error in about 32.83%. © 2022, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature."],"author":["family=Amaral, given=J.V.S., prefix=do, useprefix=true","family=Carvalho Miranda, given=R., prefix=de, useprefix=true","Montevechi, J.A.B.","family=Santos, given=C.H., prefix=dos, useprefix=true","Gabriel, G.T."],"coden":["IJATE"],"date":["2022"],"document_type":["Article"],"doi":["10.1007/s00170-022-09072-9"],"issn":["02683768"],"journaltitle":["Int. J. Adv. Manuf. Technol."],"note":["cited By 0 \n\nTL;DR \n\nThe article evaluates the performance of six machine learning algorithms trained with and without hyperparameter optimization, two experimental designs, and five different sample sizes to build metamodels in three real manufacturing cases and finds the random forest algorithm and the random design expressed the better performance to metamadels’ development."],"number":["7-8"],"pages":["5205–5224"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Metamodeling-based simulation optimization in manufacturing problems: A comparative study"],"volume":["120"]},"creators":{"author":[{"lastName":"Amaral","firstName":"J.V.S.","prefix":"do","useprefix":true},{"lastName":"CarvalhoMiranda","firstName":"R.","prefix":"de","useprefix":true},{"lastName":"Montevechi","firstName":"J.A.B."},{"lastName":"Santos","firstName":"C.H.","prefix":"dos","useprefix":true},{"lastName":"Gabriel","firstName":"G.T."}]},"sentenceCased":true},{"key":"doanTooLongDidn2023","type":"inproceedings","fields":{"abstract":["The ability to allow developers to share their source code and collaborate on software projects has made GitHub a widely used open source platform. Each repository in GitHub is generally equipped with a README.MD file to exhibit an overview of the main functionalities. Nevertheless, while offering useful information, README.MD is usually lengthy, requiring time and effort to read and comprehend. Thus, besides README.MD, GitHub also allows its users to add a short description called \"About,\"giving a brief but informative summary about the repository. This enables visitors to quickly grasp the main content and decide whether to continue reading. Unfortunately, due to various reasons-not excluding laziness-oftentimes this field is left blank by developers. This paper proposes GitSum as a novel approach to the summarization of README.MD. GitSum is built on top of BART and T5, two cutting-edge deep learning techniques, learning from existing data to perform recommendations for repositories with a missing description. We test its performance using two datasets collected from GitHub. The evaluation shows that GitSum can generate relevant predictions, outperforming a well-established baseline. © 2023 ACM."],"author":["Doan, T.T.H.","Nguyen, P.T.","Di Rocco, J.","Di Ruscio, D."],"booktitle":["ACM Int. Conf. Proceeding Ser."],"date":["2023"],"doi":["10.1145/3593434.3593448"],"isbn":["9798400700446"],"keywords":["Automatic summarization","Deep learning","Github","Learning systems","MD","Mining software","Mining software repository","Open source software","Open systems","Petroleum reservoir evaluation","README.","Software project","Software repositories","Source codes","Summarization"],"note":["cited By 0 \n\nTL;DR \n\nGitSum is built on top of BART and T5, two cutting-edge deep learning techniques, learning from existing data to perform recommendations for repositories with a missing description, and shows that it can generate relevant predictions, outperforming a well-established baseline."],"pages":["267–272"],"publisher":["Association for Computing Machinery"],"title":["Too long; Didn't read: Automatic summarization of GitHub README.MD with Transformers"]},"creators":{"author":[{"lastName":"Doan","firstName":"T.T.H."},{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."}]},"sentenceCased":true},{"key":"doi:10.1080/21693277.2016.1192517","type":"article","fields":{"author":["Wuest, Thorsten","Weimer, Daniel","Irgens, Christopher","Thoben, Klaus-Dieter"],"date":["2016"],"journaltitle":["Prod. Manuf. Res."],"nodoi":["10.1080/21693277.2016.1192517"],"note":["TL;DR \n\nThis paper contributes in presenting an overview of available machine learning techniques and structuring this rather complicated area with a special focus on the potential benefit, and examples of successful applications in a manufacturing environment."],"number":["1"],"pages":["23–45"],"publisher":["Taylor & Francis"],"title":["Machine learning in manufacturing: Advantages, challenges, and applications"],"volume":["4"]},"creators":{"author":[{"lastName":"Wuest","firstName":"Thorsten"},{"lastName":"Weimer","firstName":"Daniel"},{"lastName":"Irgens","firstName":"Christopher"},{"lastName":"Thoben","firstName":"Klaus-Dieter"}]},"sentenceCased":true},{"key":"doi:10.1089/big.2016.0048","type":"article","fields":{"abstract":["Abstract Recent research has helped to cultivate growing awareness that machine-learning systems fueled by big data can create or exacerbate troubling disparities in society. Much of this research comes from outside of the practicing data science community, leaving its members with little concrete guidance to proactively address these concerns. This article introduces issues of discrimination to the data science community on its own terms. In it, we tour the familiar data-mining process while providing a taxonomy of common practices that have the potential to produce unintended discrimination. We also survey how discrimination is commonly measured, and suggest how familiar development processes can be augmented to mitigate systems' discriminatory potential. We advocate that data scientists should be intentional about modeling and reducing discriminatory outcomes. Without doing so, their efforts will result in perpetuating any systemic discrimination that may exist, but under a misleading veil of data-driven objectivity."],"author":["family=Alessandro, given=Brian, prefix=d', useprefix=true","O'Neil, Cathy","LaGatta, Tom"],"date":["2017"],"doi":["10.1089/big.2016.0048"],"eprint":["https://doi.org/10.1089/big.2016.0048"],"journaltitle":["Big Data"],"note":["PMID: 28632437 \n\nTL;DR \n\nIt is advocated that data scientists should be intentional about modeling and reducing discriminatory outcomes, without doing so, their efforts will result in perpetuating any systemic discrimination that may exist, but under a misleading veil of data-driven objectivity."],"number":["2"],"pages":["120–134"],"title":["Conscientious classification: A data scientist's guide to discrimination-aware classification"],"volume":["5"]},"creators":{"author":[{"lastName":"Alessandro","firstName":"Brian","prefix":"d'","useprefix":true},{"lastName":"O'Neil","firstName":"Cathy"},{"lastName":"LaGatta","firstName":"Tom"}]},"sentenceCased":true},{"key":"dolques2009transformation","type":"article","fields":{"langid":["english"],"author":["Dolques, Xavier","Huchard, Marianne","Nebut, Clémentine"],"date":["2009"],"journaltitle":["Suppl. Proc. ICCS"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper is proposing a method based on FCA using relational descriptions of objects to find transformation rules between two par- ticular syntaxes using transformation examples (transformation traces) as input data."],"pages":["15–29"],"title":["From transformation traces to transformation rules: Assisting model driven engineering approach with formal concept analysis"],"volume":["9"]},"creators":{"author":[{"lastName":"Dolques","firstName":"Xavier"},{"lastName":"Huchard","firstName":"Marianne"},{"lastName":"Nebut","firstName":"Clémentine"}]},"sentenceCased":true},{"key":"Domingos:2012:FUT:2347736.2347755","type":"article","fields":{"acmid":["2347755"],"address":["New York, NY, USA"],"author":["Domingos, Pedro"],"date":["2012-10"],"issn":["0001-0782"],"issue_date":["October 2012"],"journaltitle":["Commun. ACM"],"nodoi":["10.1145/2347736.2347755"],"number":["10"],"numpages":["10"],"pages":["78–87"],"publisher":["ACM"],"title":["A few useful things to know about machine learning"],"volume":["55"]},"creators":{"author":[{"lastName":"Domingos","firstName":"Pedro"}]},"sentenceCased":true},{"key":"Dong2022326","type":"article","fields":{"abstract":["Imbalanced data can always be observed in our daily life and various practical tasks. A lot of well-constructed machine learning methodologies may produce ineffective performance, when conducted on this kind of data. This originates from the produced high training biases that towards the majority class instances. Among all the solutions of this problem, data generation of the minority class is always considered the most effective approach. However, in all the previous works, data are always processed sample-wisely and the distribution of each single data attribute is never noticed. So, in this paper, to estimate the mechanism of how each attribute contributes to its label, we explore the potential connection between the two items by Conditional Generative Adversarial Networks (CGAN) separately and individually. Then, the constructed new instances are purified by a designed attribute-based minimax filter and the survivors are concatenated to form the eventual generated data. In other words, different from the CGAN based data generation way, the proposed approach improves it by additionally considering all the single attribute patterns of the data that to construct new instances. In addition, we extend the binary class imbalanced learning framework to multiple class one. In the experimental part, the improved model is compared against GAN, CGAN and some other standard multiple-class oversampling algorithms on several widely used datasets. Results, in terms of four common measurements, have shown that the proposed approach can produce comparable and always superior performance when compared with the competitors. © 2021 Elsevier B.V."],"author":["Dong, Y.","Xiao, H.","Dong, Y."],"author_keywords":["Attribute/feature pattern learning; Data generation; Generative adversarial network; Multi-class uneven/imbalanced data"],"coden":["NRCGE"],"date":["2022"],"document_type":["Article"],"doi":["10.1016/j.neucom.2021.04.135"],"issn":["09252312"],"journaltitle":["Neurocomputing"],"keywords":["algorithm","Article","attribute feature pattern learning","Attribute/feature pattern learning","conceptual framework","conditional generative adversarial network","Data generation","data processing","Feature pattern","Generative adversarial networks","Imbalanced data","Imbalanced Learning","machine learning","measurement accuracy","measurement precision","multi class imbalanced learning","Multi-class uneven/imbalanced data","Multiple class","Neural networks","Over sampling","Pattern Learning","perception","Performance","random sample","Software engineering","statistical significance"],"note":["cited By 2"],"pages":["326–337"],"publisher":["Elsevier B.V."],"source":["Scopus"],"title":["SA-CGAN: An oversampling method based on single attribute guided conditional GAN for multi-class imbalanced learning"],"volume":["472"]},"creators":{"author":[{"lastName":"Dong","firstName":"Y."},{"lastName":"Xiao","firstName":"H."},{"lastName":"Dong","firstName":"Y."}]},"sentenceCased":true},{"key":"dornenburgPathDevOps2018","type":"article","fields":{"abstract":["IT’s role in the business world has changed dramatically over the past decades. New technologies and techniques let enterprises get much more out of IT, while increasingly sophisticated business models have pushed IT to investigate and deliver novel solutions. Agile development led the way, and now the DevOps and DesignOps movements are hitting the mainstream. IT in businesses is now entirely a team activity. While we still need experts with deep technical knowledge, we must focus on how to get people from all disciplines working together effectively. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Dörnenburg, E."],"date":["2018-09"],"doi":["10.1109/MS.2018.290110337"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"note":["TL;DR \n\nThis article is part of a theme issue on software engineering’s 50th anniversary, which focuses on how to get people from all disciplines working together effectively in IT."],"number":["5"],"pages":["71–75"],"title":["The Path to DevOps"],"volume":["35"]},"creators":{"author":[{"lastName":"Dörnenburg","firstName":"E."}]}},{"key":"Dorodnykh202160","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["CEUR Workshop Proc."],"affiliation":["Matrosov Institute for System Dynamics and Control Theory, Siberian Branch of Russian Academy of Sciences (ISDCT SB RAS), 134, Lermontov str., Irkutsk, 664033, Russian Federation; Moscow State Technical University of Civil Aviation, Irkutsk Branch (MSTUCA), 3, Kommunarov str., Irkutsk, 664003, Russian Federation"],"author":["Dorodnykh, N.O.","Kotlov, Y.V.","Nikolaychuk, O.A.","Popov, V.M.","Yurin, A.Y."],"correspondence_address1":["Yurin, A.Y.; Matrosov Institute for System Dynamics and Control Theory, 134, Lermontov str., Russian Federation; email: iskander@icc.ru"],"date":["2021"],"document_type":["Conference Paper"],"editor":["Bychkov I., Tchernykh A., Feoktistov A."],"issn":["16130073"],"note":["cited By 1 \n\nTL;DR \n\nAn extension of the Prototyping expert systems based on transformations technology, which implements the End-user development, is proposed in the context of the problem to be solved for Sukhoi Superjet aircraft."],"pages":["60–73"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"source":["Scopus"],"title":["End-user development of knowledge bases for semi-automated formation of task cards"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111360450&partnerID=40&md5=0dfb7b7b307c3f0687f5911003a61f5b"],"volume":["2913"]},"creators":{"author":[{"lastName":"Dorodnykh","firstName":"N.O."},{"lastName":"Kotlov","firstName":"Y.V."},{"lastName":"Nikolaychuk","firstName":"O.A."},{"lastName":"Popov","firstName":"V.M."},{"lastName":"Yurin","firstName":"A.Y."}],"editor":[{"lastName":"Bychkov I.","suffix":"Tchernykh A.","firstName":"Feoktistov A."}]},"sentenceCased":true},{"key":"dsouzaWorkshopSoftwareArchitectures","type":"article","fields":{"author":["D’Souza, Meenakshi","Mohalik, Swarup Kumar","Jayaraman, Mahesh Babu"],"title":["Workshop on Software Architectures for Adaptive Autonomous Systems (SAAAS)"],"url":["https://pdfs.semanticscholar.org/b1d6/f9387fdefc8d4eb0054162cb1c040de8d69f.pdf"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"D’Souza","firstName":"Meenakshi"},{"lastName":"Mohalik","firstName":"Swarup Kumar"},{"lastName":"Jayaraman","firstName":"Mahesh Babu"}]}},{"key":"Duala-Ekoko:2012:AAQ:2337223.2337255","type":"inproceedings","fields":{"acmid":["2337255"],"author":["Duala-Ekoko, Ekwa","Robillard, Martin P."],"booktitle":["Proc. 34th Int. Conf. Softw. Eng."],"date":["2012"],"isbn":["978-1-4673-1067-3"],"location":["Piscataway, NJ, USA"],"note":["TL;DR \n\nTwenty different types of questions programmers ask when working with unfamiliar APIs are identified, and new insights are provided to the cause of the difficulties programmers encounter when answering questions about the use of APIs."],"numpages":["11"],"pages":["266–276"],"publisher":["IEEE Press"],"series":["ICSE '12"],"title":["Asking and answering questions about unfamiliar APIs: An exploratory study"],"url":["http://dl.acm.org/citation.cfm?id=2337223.2337255"]},"creators":{"author":[{"lastName":"Duala-Ekoko","firstName":"Ekwa"},{"lastName":"Robillard","firstName":"Martin P."}]},"sentenceCased":true},{"key":"Dubey2020","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["ACM Int. Conf. Proc. Ser."],"affiliation":["Accenture Labs, Bangalore, India"],"art_number":["3385044"],"author":["Dubey, A.","Abhinav, K.","Jain, S.","Arora, V.","Puttaveerana, A."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3385032.3385044"],"isbn":["978-1-4503-7594-8"],"note":["cited By 6 \n\nTL;DR \n\nA solution framework, Human-AI Collaboration (HACO), enables a model-driven development of human-AI teaming systems through graphical user interface and a user study performed to assess the usefulness of HACO, shows that HacO is a promising framework."],"publisher":["Association for Computing Machinery"],"series":["ACM International Conference Proceeding Series"],"source":["Scopus"],"title":["HACO: A framework for developing human-AI teaming"]},"creators":{"author":[{"lastName":"Dubey","firstName":"A."},{"lastName":"Abhinav","firstName":"K."},{"lastName":"Jain","firstName":"S."},{"lastName":"Arora","firstName":"V."},{"lastName":"Puttaveerana","firstName":"A."}]},"sentenceCased":true},{"key":"Dunke2020","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Simul. Model. Pract. Theory"],"affiliation":["Karlsruhe Institute of Technology, Institute of Operations Research, Discrete Optimization and Logistics, Kaiserstr. 12, Karlsruhe, 76131, Germany"],"art_number":["102016"],"author":["Dunke, F.","Nickel, S."],"correspondence_address1":["Dunke, F.; Karlsruhe Institute of Technology, Kaiserstr. 12, Germany; email: fabian.dunke@kit.edu"],"date":["2020"],"document_type":["Article"],"doi":["10.1016/j.simpat.2019.102016"],"issn":["1569190X"],"journaltitle":["Simul. Model. Pract. Theory"],"keywords":["GOAL_Model-simulation","notion"],"note":["cited By 12"],"publisher":["Elsevier B.V."],"source":["Scopus"],"title":["Neural networks for the metamodeling of simulation models with online decision making"],"volume":["99"]},"creators":{"author":[{"lastName":"Dunke","firstName":"F."},{"lastName":"Nickel","firstName":"S."}]},"sentenceCased":true},{"key":"dunlapStudyApplicationSandbox2022","type":"inproceedings","fields":{"langid":["english"],"abstract":["Desktop operating systems, including macOS, Windows 10, and Linux, are adopting the application-based security model pervasive in mobile platforms. In Linux, this transition is part of the movement towards two distribution-independent application platforms: Flatpak and Snap. This paper provides the first analysis of sandbox policies defined for Flatpak and Snap applications, covering 283 applications contained in both platforms. First, we find that 90.1% of Snaps and 58.3% of Flatpak applications studied are contained by tamperproof sandboxes. Further, we find evidence that package maintainers actively attempt to define least-privilege application policies. However, defining policy is difficult and error-prone. When studying the set of matching applications that appear in both Flatpak and Snap app stores, we frequently found policy mismatches: e.g., the Flatpak version has a broad privilege (e.g., file access) that the Snap version does not, or vice versa. This work provides confidence that Flatpak and Snap improve Linux platform security while highlighting opportunities for improvement."],"author":["Dunlap, Trevor","Enck, William","Reaves, Bradley"],"booktitle":["Proc. 27th ACM Symp. Access Control Models Technol."],"date":["2022-06-07"],"doi":["10.1145/3532105.3535016"],"eventtitle":["SACMAT '22: The 27th ACM Symposium on Access Control Models and Technologies"],"isbn":["978-1-4503-9357-7"],"location":["New York NY USA"],"pages":["19–30"],"publisher":["ACM"],"title":["A Study of Application Sandbox Policies in Linux"]},"creators":{"author":[{"lastName":"Dunlap","firstName":"Trevor"},{"lastName":"Enck","firstName":"William"},{"lastName":"Reaves","firstName":"Bradley"}]}},{"key":"duongAutomatedFruitRecognition2020","type":"article","fields":{"author":["Duong, L. T.","Nguyen, P. T.","Di Sipio, C.","Di Ruscio, D."],"date":["2020"],"doi":["10.1016/j.compag.2020.105326"],"ids":["duongAutomatedFruitRecognition2020a,duongAutomatedFruitRecognition2020b"],"journaltitle":["Comput. Electron. Agric."],"note":["cited By 37"],"pages":["105326"],"title":["Automated fruit recognition using EfficientNet and MixNet"],"volume":["171"]},"creators":{"author":[{"lastName":"Duong","firstName":"L. T."},{"lastName":"Nguyen","firstName":"P. T."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Di Ruscio","firstName":"D."}]},"sentenceCased":true},{"key":"Duran22","type":"article","fields":{"langid":["english"],"author":["Durán, Francisco"],"date":["2022-10"],"doi":["10.5381/jot.2022.21.4.a2"],"issn":["1660-1769"],"journaltitle":["J. Object Technol."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["Special Issue dedicated to Antonio Vallecillo on his 60th Birthday \n\nTL;DR \n\nThis paper summarizes the main contributions by Antonio and myself on the possibilities of analysing models, long before they were implemented, and graphically defining the behavior of systems and DSMLs using Maude as back-end tool."],"number":["4"],"pages":["4:1-12"],"title":["Rewriting logic and maude for the formalization and analysis of DSMLs, and the prototyping of MDSE tools"],"volume":["21"],"x-editor":["Lola Burgueno and Martin Gogolla and Richard Paige"]},"creators":{"author":[{"lastName":"Durán","firstName":"Francisco"}]},"sentenceCased":true},{"key":"dustdarDistributedComputingContinuum2022","type":"article","fields":{"author":["Dustdar, Schahram","Casamajor Pujol, Victor","Donta, Praveen Kumar"],"date":["2022"],"doi":["10.1109/TKDE.2022.3142856"],"issn":["1041-4347, 1558-2191, 2326-3865"],"journaltitle":["IEEE Trans. Knowl. Data Eng."],"keywords":["LOGSEQ"],"pages":["1–1"],"title":["On distributed computing continuum systems"]},"creators":{"author":[{"lastName":"Dustdar","firstName":"Schahram"},{"lastName":"Casamajor Pujol","firstName":"Victor"},{"lastName":"Donta","firstName":"Praveen Kumar"}]},"sentenceCased":true},{"key":"duttSelfAwarenessCyberPhysicalSystems2016","type":"inproceedings","fields":{"author":["Dutt, Nikil","TaheriNejad, Nima"],"date":["2016-01"],"doi":["10.1109/VLSID.2016.129"],"isbn":["978-1-4673-8700-2"],"note":["TL;DR \n\nThis tutorial will introduce the concepts surrounding self-awareness in the context of Cyber-Physical Systems (CPS), which is the inherent control function where the environment is sensed, the system is analyzed, and adaptions are applied to respect constraints and achieve desired goals."],"pages":["5–6"],"publisher":["IEEE"],"title":["Self-Awareness in Cyber-Physical Systems"]},"creators":{"author":[{"lastName":"Dutt","firstName":"Nikil"},{"lastName":"TaheriNejad","firstName":"Nima"}]}},{"key":"EASE2021VP","type":"inproceedings","fields":{"author":["AnonymousAuthors"],"date":["2021"],"note":["To appear in conference proceedings"],"title":["Article hidden to conform with the double blind review policy"],"url":["https://bit.ly/3eqNUMG"]},"creators":{"author":[{"literal":"AnonymousAuthors"}]},"sentenceCased":true},{"key":"ebert50YearsSoftware2018","type":"article","fields":{"abstract":["A survey of software professionals worldwide suggests the past, present, and future challenges of software engineering. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Ebert, C."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571228"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nA survey of software professionals worldwide suggests the past, present, and future challenges of software engineering."],"number":["5"],"pages":["94–101"],"shorttitle":["50 Years of Software Engineering"],"title":["50 Years of Software Engineering: Progress and Perils"],"volume":["35"]},"creators":{"author":[{"lastName":"Ebert","firstName":"C."}]}},{"key":"ebertGlobalSoftwareIT2011","type":"book","fields":{"author":["Ebert, Christof"],"date":["2011"],"note":["TL;DR \n\nThis book will provide a more balanced framework for planning globalDevelopment, covering topics such as managing people in distributed sites, managing a project across locations, mitigating the risk of offshoring, processes for global development, practical outsourcing guidelines, collaboration, and communication."],"publisher":["John Wiley & Sons"],"shorttitle":["Global software and IT"],"title":["Global software and IT: A guide to distributed development, projects, and outsourcing"],"url":["http://books.google.com/books?hl=en&lr=&id=Bj7poEQLZOUC&oi=fnd&pg=PT11&dq=%22Time-to-pro%EF%AC%81t+means+that+you+must+cut+out+delays+from+the+introduction%22+%22complexity.+Open+source+software+only+delivers+core+features+and%22+%22For+that+very+reason,+security+breaches+are+typically+%EF%AC%81xed%22+&ots=l5lCIeb6BB&sig=mK3SgFCs5N3Rvnu70r_9cOw0l5I"],"urldate":["2017-06-23"]},"creators":{"author":[{"lastName":"Ebert","firstName":"Christof"}]},"sentenceCased":true},{"key":"echelonBuildingIoTIndustrial","type":"online","fields":{"abstract":["In the first in a two-part series, Echelon’s Robert Dolin describes the requirements that the IP-enabled “Internet of Things” (IoT) must meet to be suitable for use in industrial control network environments."],"author":["Echelon, Robert Dolin"],"organization":["Embedded"],"shorttitle":["Building an IoT for industrial control"],"title":["Building an IoT for industrial control: Part 1 – What is Industrial IoT?"],"url":["http://www.embedded.com/design/real-world-applications/4426952/1/Building-an-IoT-for-industrial-control--Part-1--What-is-Industrial-IoT-"],"urldate":["2016-11-01"]},"creators":{"author":[{"lastName":"Echelon","firstName":"Robert Dolin"}]},"sentenceCased":true},{"key":"ECL","type":"inproceedings","fields":{"author":["Kolovos, Dimitrios S."],"booktitle":["Model Driven Archit. - Found. Appl."],"date":["2009"],"editor":["Paige, Richard F.","Hartman, Alan","Rensink, Arend"],"ids":["10.1007/978-3-642-02674-4_11"],"isbn":["978-3-642-02674-4"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nThe Epsilon Comparison Language (ECL) is presented, a hybrid rule-based language, built atop the Epsilon platform, which enables developers to implement comparison algorithms at a high level of abstraction and execute them in order to identify matches between elements belonging to models of diverse metamodels and modelling technologies."],"pages":["146–157"],"publisher":["Springer Berlin Heidelberg"],"title":["Establishing correspondences between models with the epsilon comparison language"]},"creators":{"author":[{"lastName":"Kolovos","firstName":"Dimitrios S."}],"editor":[{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Hartman","firstName":"Alan"},{"lastName":"Rensink","firstName":"Arend"}]},"sentenceCased":true},{"key":"EclipseSmartHomeFlexible","type":"online","fields":{"title":["Eclipse SmartHome - A Flexible Framework for the Smart Home - Binding development"],"url":["http://www.eclipse.org/smarthome/documentation/development/bindings/how-to.html"],"urldate":["2016-12-08"]},"creators":{},"sentenceCased":true},{"key":"EclipseZoneGettingStarted","type":"online","fields":{"title":["EclipseZone - Getting started with OSGi: Interacting ..."],"url":["http://www.eclipsezone.com/eclipse/forums/m92131032.html"],"urldate":["2016-12-04"]},"creators":{},"sentenceCased":true},{"key":"EditorialBoard2018","type":"article","fields":{"langid":["english"],"date":["2018-09"],"doi":["10.1016/S2542-6605(18)30096-9"],"issn":["25426605"],"journaltitle":["Internet Things"],"pages":["ii"],"title":["Editorial Board"],"volume":["1–2"]},"creators":{}},{"key":"edmunds_focus_1999","type":"article","fields":{"author":["Edmunds, Holly"],"date":["1999-01"],"doi":["10.1108/bl.1999.12.3.46.1"],"issn":["0888-045X"],"journaltitle":["Bottom Line"],"note":["Publisher: Emerald Group Publishing Limited"],"number":["3"],"pages":["46–46"],"title":["The Focus Group Research Handbook"],"volume":["12"]},"creators":{"author":[{"lastName":"Edmunds","firstName":"Holly"}]}},{"key":"efremovIntegratedApproachCommon2015","type":"article","fields":{"langid":["english"],"abstract":["The recent advances in technology enabled transition to the Internet of Things (IoT), in which physical objects around us become an integral part of the global information system. A major technical challenge however is to make these numerous objects interact seamlessly with each other. The latest works related to concepts, such as Web of Things or Social Web of Things, partly address the issue. In our paper we further investigate the topic and point out several problems that need to be efficiently solved for the Internet of Things to work on large scale numbers. One of the main tasks is to make devices easily discoverable. Thus, an efficient way to handle and store their metadata is required. Another problem is connected with providing different models of inter-device communication, asynchronous being the most important, as many of today’s widely used web standards were not designed for it. Finally, we propose a general cloud-based IoT architecture aimed at solving the above-described problems."],"author":["Efremov, Sergey","Pilipenko, Nikolay","Voskov, Leonid"],"date":["2015"],"doi":["10.1016/j.proeng.2015.01.486"],"issn":["18777058"],"journaltitle":["Procedia Engineering"],"note":["TL;DR \n\nThis paper points out several problems that need to be efficiently solved for the Internet of Things to work on large scale numbers and proposes a general cloud-based IoT architecture aimed at solving these problems."],"pages":["1215–1223"],"title":["An Integrated Approach to Common Problems in the Internet of Things"],"volume":["100"]},"creators":{"author":[{"lastName":"Efremov","firstName":"Sergey"},{"lastName":"Pilipenko","firstName":"Nikolay"},{"lastName":"Voskov","firstName":"Leonid"}]}},{"key":"EhrigKT09","type":"article","fields":{"langid":["english"],"author":["Ehrig, Karsten","Küster, Jochen Malte","Taentzer, Gabriele"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2009"],"doi":["10.1007/S10270-008-0095-Y"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["4"],"pages":["479–500"],"timestamp":["Fri, 18 Sep 2020 11:19:18 +0200"],"title":["Generating instance models from meta models"],"volume":["8"]},"creators":{"author":[{"lastName":"Ehrig","firstName":"Karsten"},{"lastName":"Küster","firstName":"Jochen Malte"},{"lastName":"Taentzer","firstName":"Gabriele"}]},"sentenceCased":true},{"key":"Eichhoff2015333","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Artif Intell Eng Des Anal Manuf"],"affiliation":["Institute of Computer-Aided Product Development Systems, University of Stuttgart, Stuttgart, Germany"],"author":["Eichhoff, J.R.","Roller, D."],"coden":["AIEME"],"correspondence_address1":["Eichhoff, J.R.; Institut für Rechnergestützte Ingenieursysteme, Universitätsstrasse 38, Germany; email: julian.eichhoff@informatik.uni-stuttgart.de"],"date":["2015"],"document_type":["Conference Paper"],"doi":["10.1017/S0890060415000372"],"issn":["08900604"],"journaltitle":["Artif. Intell. Eng. Des. Anal. Manuf. AIEDAM"],"note":["cited By 3 \n\nTL;DR \n\nThe authors further review promising machine learning and natural language processing methods for automatic knowledge elicitation and formalization with respect to their implementation for evolutionary design optimization."],"number":["4"],"pages":["333–350"],"publisher":["Cambridge University Press"],"source":["Scopus"],"title":["A survey on automating configuration and parameterization in evolutionary design exploration"],"volume":["29"]},"creators":{"author":[{"lastName":"Eichhoff","firstName":"J.R."},{"lastName":"Roller","firstName":"D."}]},"sentenceCased":true},{"key":"einarssonSmartHomeMLDomainSpecificModeling2017","type":"inproceedings","fields":{"author":["Einarsson, Atli F.","Patreksson, Patrekur","Hamdaqa, Mohammad","Hamou-Lhadj, Abdelwahab"],"date":["2017-06"],"doi":["10.1109/IEEE.ICIOT.2017.35"],"isbn":["978-1-5386-2011-3"],"note":["TL;DR \n\nThis paper shows through an example how to use SmartHomeML to model asmart home service independently from the target smart home provider and then generate Amazon Alexa Skill Adapters and SmartThings SmartApps automatically."],"pages":["82–88"],"publisher":["IEEE"],"shorttitle":["SmartHomeML"],"title":["SmartHomeML: Towards a Domain-Specific Modeling Language for Creating Smart Home Applications"]},"creators":{"author":[{"lastName":"Einarsson","firstName":"Atli F."},{"lastName":"Patreksson","firstName":"Patrekur"},{"lastName":"Hamdaqa","firstName":"Mohammad"},{"lastName":"Hamou-Lhadj","firstName":"Abdelwahab"}]}},{"key":"EisenbergPGW21","type":"inproceedings","fields":{"langid":["english"],"author":["Eisenberg, Martin","Pichler, Hans-Peter","Garmendia, Antonio","Wimmer, Manuel"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["24th Int. Conf. Model Driven Eng. Lang. Syst. MODELS"],"date":["2021"],"doi":["10.1109/MODELS50736.2021.00017"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper applies for the first time reinforcement learning for in-place model transformations with value-based and policy-based techniques and investigates several case studies for validating the feasibility of using reinforcementLearning for model-driven optimization and compares the performance against existing approaches."],"pages":["82–88"],"publisher":["IEEE"],"timestamp":["Wed, 23 Feb 2022 10:19:30 +0100"],"title":["Towards reinforcement learning for in-place model transformations"]},"creators":{"author":[{"lastName":"Eisenberg","firstName":"Martin"},{"lastName":"Pichler","firstName":"Hans-Peter"},{"lastName":"Garmendia","firstName":"Antonio"},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"eisenbergSearchingModelsHybrid2021","type":"article","fields":{"langid":["english"],"abstract":["The Model-Driven Engineering (MDE) [3] paradigm advocates for the use of models as an abstraction layer to represent complex systems. Model transformations are a central technique within MDE [10]. They either modify existing models or create new ones from scratch. Generally, these models should represent an optimal state of the system that has to be found within a large space of possible solutions. Model-driven optimization [1, 2, 4–6, 9] is a research area within MDE that proposes to automatically find optimal solutions which are constructed by a set of transformation rules given certain objectives. In order to search into large solution spaces, model-driven optimization approaches combine the expressiveness of models and domain-specific modeling languages, with the computational effectiveness of Artificial Intelligence (AI) methods to find the best model for a particular scenario."],"author":["Eisenberg, Martin","Pichler, Hans-Peter","Garmendia, Antonio"],"date":["2021"],"keywords":["GOAL-Model_Search","notion","TECHNIQUE_ReinforcementLearning"],"pages":["2"],"title":["Searching for Models with Hybrid AI Techniques"]},"creators":{"author":[{"lastName":"Eisenberg","firstName":"Martin"},{"lastName":"Pichler","firstName":"Hans-Peter"},{"lastName":"Garmendia","firstName":"Antonio"}]}},{"key":"ekaputraOntologyChangeOntologyBased2015","type":"incollection","fields":{"author":["Ekaputra, Fajar Juang"],"booktitle":["The Semantic Web. Latest Advances and New Domains"],"date":["2015"],"editor":["Gandon, Fabien","Sabou, Marta","Sack, Harald","family=Amato, given=Claudia, prefix=d’, useprefix=true","Cudré-Mauroux, Philippe","Zimmermann, Antoine"],"isbn":["978-3-319-18817-1 978-3-319-18818-8"],"location":["Cham"],"note":["TL;DR \n\nThis work discusses the research goals, methods, and evaluation options to address the challenge of ontology change in OBII contexts, and plans to adapt successful techniques proposed both by Semantic Web and Model-Driven Engineering communities."],"pages":["711–720"],"publisher":["Springer International Publishing"],"title":["Ontology Change in Ontology-Based Information Integration Systems"],"url":["http://link.springer.com/10.1007/978-3-319-18818-8_44"],"urldate":["2015-06-24"],"volume":["9088"]},"creators":{"author":[{"lastName":"Ekaputra","firstName":"Fajar Juang"}],"editor":[{"lastName":"Gandon","firstName":"Fabien"},{"lastName":"Sabou","firstName":"Marta"},{"lastName":"Sack","firstName":"Harald"},{"lastName":"Amato","firstName":"Claudia","prefix":"d’","useprefix":true},{"lastName":"Cudré-Mauroux","firstName":"Philippe"},{"lastName":"Zimmermann","firstName":"Antoine"}]}},{"key":"ekstrandLensKitPythonNextGeneration2020","type":"inproceedings","fields":{"langid":["english"],"author":["Ekstrand, Michael D."],"booktitle":["Proc. 29th ACM Int. Conf. Inf. Knowl. Manag."],"date":["2020-10-19"],"doi":["10.1145/3340531.3412778"],"eventtitle":["CIKM '20: The 29th ACM International Conference on Information and Knowledge Management"],"isbn":["978-1-4503-6859-9"],"location":["Virtual Event Ireland"],"note":["TL;DR \n\nThe next generation of the LensKit project is presented, re-envisioning the original tool's objectives as flexible Python package for supporting recommender systems research and development."],"pages":["2999–3006"],"publisher":["ACM"],"shorttitle":["LensKit for Python"],"title":["LensKit for Python: Next-Generation Software for Recommender Systems Experiments"]},"creators":{"author":[{"lastName":"Ekstrand","firstName":"Michael D."}]}},{"key":"Elnagar2020383","type":"article","fields":{"abstract":["Deep Learning (DL) modeling has been a recent topic of interest. With the accelerating need to embed Deep Learning Networks (DLNs) to the Internet of Things (IoT) applications, many DL optimization techniques were developed to enable applying DL to IoTs. However, despite the plethora of DL optimization techniques, there is always a trade-off between accuracy, latency, and cost. Moreover, there are no specific criteria for selecting the best optimization model for a specific scenario. Therefore, this research aims at providing a DL optimization model that eases the selection and re-using DLNs on IoTs. In addition, the research presents an initial design for a DL optimization model management framework. This framework would help organizations choose the optimal DL optimization model that maximizes performance without sacrificing quality. The research would add to the IS design science knowledge as well as the industry by providing insights to many IT managers to apply DLNs to IoTs such as machines and robots. © 2020, Springer Nature Switzerland AG."],"author":["Elnagar, S.","Osei-Bryson, K.-M."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-63396-7_26"],"editor":["Themistocleous M., Papadaki M., Kamal M.M."],"isbn":["9783030633950"],"issn":["18651348"],"journaltitle":["Lect. Notes Bus. Inf. Process."],"note":["cited By 0"],"pages":["383–398"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Towards applying deep learning to the internet of things: A model and a framework"],"volume":["402"]},"creators":{"author":[{"lastName":"Elnagar","firstName":"S."},{"lastName":"Osei-Bryson","firstName":"K.-M."}],"editor":[{"lastName":"Themistocleous M.","suffix":"Papadaki M.","firstName":"Kamal M.M."}]},"sentenceCased":true},{"key":"emf","type":"misc","fields":{"title":["Eclipse EMF"],"url":["https://www.eclipse.org/modeling/emf/"]},"creators":{}},{"key":"EMFFacet","type":"online","fields":{"title":["EMF Facet"],"url":["http://www.eclipse.org/facet/"],"urldate":["2015-09-24"]},"creators":{}},{"key":"EnablingAutonomousApplications","type":"online","fields":{"title":["Enabling Autonomous Applications for IoT - Alta Devices Alta Devices"],"url":["http://www.altadevices.com/energy-harvesting/enabling-autonomous-applications-for-iot/"],"urldate":["2016-09-03"]},"creators":{}},{"key":"EncodingConceptualModels2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["Conceptual models are essential in Software and Information Systems Engineering to meet many purposes since they explicitly represent the subject domains. Machine Learning (ML) approaches have recently been used in conceptual modeling to realize, among others, intelligent modeling assistance, model transformation, and metamodel classification. These works encode models in various ways, making the encoded models suitable for applying ML algorithms. The encodings capture the models’ structure and/or semantics, making this information available to the ML model during training. Therefore, the choice of the encoding for any ML-driven task is crucial for the ML model to learn the relevant contextual information. In this paper, we report findings from a systematic literature review which yields insights into the current research in machine learning for conceptual modeling (ML4CM). The review focuses on the various encodings used in existing ML4CM solutions and provides insights into i) which are the information sources, ii) how is the conceptual model’s structure and/or semantics encoded, iii) why is the model encoded, i.e., for which conceptual modeling task and, iv) which ML algorithms are applied. The results aim to structure the state of the art in encoding conceptual models for ML."],"booktitle":["2021 ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion MODELS-C"],"date":["2021"],"eventtitle":["2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)"],"isbn":["978-1-66542-484-4"],"keywords":["LOGSEQ"],"location":["Fukuoka, Japan"],"publisher":["IEEE"],"title":["Encoding Conceptual Models for Machine Learning: A Systematic Review"]},"creators":{}},{"key":"EngelsHHS00","type":"inproceedings","fields":{"langid":["english"],"author":["Engels, Gregor","Hausmann, Jan Hendrik","Heckel, Reiko","Sauer, Stefan"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["«UML» 2000 - Unified Model. Lang. Adv. Stand. Third Int. Conf. York UK Oct. 2-6 2000 Proc."],"date":["2000"],"doi":["10.1007/3-540-40011-7\\_23"],"editor":["Evans, Andy","Kent, Stuart","Selic, Bran"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThe dynamic meta model extends the well-known static meta model by a specification of the system's dynamics by means of collaboration diagrams, which can be both mathematically rigorous so as to enable formal specifications and proofs and understandable without prior knowledge of heavy mathematic machinery."],"pages":["323–337"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Mon, 24 Jun 2019 12:03:37 +0200"],"title":["Dynamic meta modeling: A graphical approach to the operational semantics of behavioral diagrams in UML"],"volume":["1939"]},"creators":{"author":[{"lastName":"Engels","firstName":"Gregor"},{"lastName":"Hausmann","firstName":"Jan Hendrik"},{"lastName":"Heckel","firstName":"Reiko"},{"lastName":"Sauer","firstName":"Stefan"}],"editor":[{"lastName":"Evans","firstName":"Andy"},{"lastName":"Kent","firstName":"Stuart"},{"lastName":"Selic","firstName":"Bran"}]},"sentenceCased":true},{"key":"enriquezUnifiedModelRepresentation2020","type":"article","fields":{"abstract":["Nowadays, Machine Learning (ML) algorithms are being widely applied in virtually all possible scenarios. However, developing a ML project entails the effort of many ML experts who have to select and configure the appropriate algorithm to process the data to learn from, between other things. Since there exist thousands of algorithms, it becomes a time-consuming and challenging task. To this end, recently, AutoML emerged to provide mechanisms to automate parts of this process. However, most of the efforts focus on applying brute force procedures to try different algorithms or configuration and select the one which gives better results. To make a smarter and more efficient selection, a repository of knowledge is necessary. To this end, this paper proposes (1) an approach towards a common language to consolidate the current distributed knowledge sources related the algorithm selection in ML, and (2) a method to join the knowledge gathered through this language in a unified store that can be exploited later on, and (3) a traceability links maintenance. The preliminary evaluations of this approach allow to create a unified store collecting the knowledge of 13 different sources and to identify a bunch of research lines to conduct. © 2020 River Publishers."],"author":["Enríquez, J.G.","Martínez-Rojas, A.","Lizcano, D.","Jiménez-Ramírez, A."],"date":["2020"],"doi":["10.13052/jwe1540-9589.1929"],"issn":["15409589"],"journaltitle":["J. Web Eng."],"note":["cited By 3 \n\nTL;DR \n\nAn approach towards a common language to consolidate the current distributed knowledge sources related the algorithm selection in ML and a method to join the knowledge gathered through this language in a unified store that can be exploited later on, and a traceability links maintenance."],"number":["2"],"pages":["319–340"],"publisher":["River Publishers"],"title":["A unified model representation of machine learning knowledge"],"volume":["19"]},"creators":{"author":[{"lastName":"Enríquez","firstName":"J.G."},{"lastName":"Martínez-Rojas","firstName":"A."},{"lastName":"Lizcano","firstName":"D."},{"lastName":"Jiménez-Ramírez","firstName":"A."}]},"sentenceCased":true},{"key":"EnterpriseRestaurantCompute","type":"misc","fields":{"keywords":["LOGSEQ"],"title":["Enterprise Restaurant Compute.Pdf"],"url":["https://medium.com/chick-fil-atech/enterprise-restaurant-compute-f5e2fd63d20f"]},"creators":{}},{"key":"Eramo2021303","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - Euromicro Conf. Digit. Syst. Des., DSD"],"affiliation":["University of L’Aquila, L’Aquila, Italy; Johannes Kepler University, Linz, Austria; IMT Atlantique, LS2N (UMR CNRS 6004), Nantes, France; Universitat Oberta de Catalunya, Barcelona, Spain; Softeam, Paris, France; Mälardalen University, Västerås, Sweden"],"author":["Eramo, R.","Muttillo, V.","Berardinelli, L.","Bruneliere, H.","Gomez, A.","Bagnato, A.","Sadovykh, A.","Cicchetti, A."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/DSD53832.2021.00053"],"editor":["Leporati F., Vitabile S., Skavhaug A."],"isbn":["978-1-66542-703-6"],"keywords":["GOAL_Model-Assistance","notion"],"note":["cited By 1 \n\nHIGH LEVEL. NO SPECIFIC TECHNIQUES ARE MENTIONED."],"pages":["303–310"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2021 24th Euromicro Conference on Digital System Design, DSD 2021"],"source":["Scopus"],"title":["AIdoArt: AI-augmented automation for DevOps, a model-based framework for continuous development in cyber-physical systems"]},"creators":{"author":[{"lastName":"Eramo","firstName":"R."},{"lastName":"Muttillo","firstName":"V."},{"lastName":"Berardinelli","firstName":"L."},{"lastName":"Bruneliere","firstName":"H."},{"lastName":"Gomez","firstName":"A."},{"lastName":"Bagnato","firstName":"A."},{"lastName":"Sadovykh","firstName":"A."},{"lastName":"Cicchetti","firstName":"A."}],"editor":[{"lastName":"Leporati F.","suffix":"Vitabile S.","firstName":"Skavhaug A."}]},"sentenceCased":true},{"key":"eramoModeldrivenDesignRuntimeInteraction2019","type":"article","fields":{"langid":["english"],"author":["Eramo, Romina","Marchand de Kerchove, Florent","Colange, Maximilien","Tucci, Michele","Ouy, Julien","Bruneliere, Hugo","Di Ruscio, Davide"],"date":["2019"],"doi":["10.5381/jot.2019.18.2.a1"],"ids":["eramoModeldrivenDesignRuntimeInteraction2019a,eramoModeldrivenDesignRuntimeInteraction2019b,eramoModeldrivenDesignruntimeInteraction2019"],"issn":["1660-1769"],"journaltitle":["JOT"],"keywords":["Critical systems","Design","Interactions","Model-driven engineering","Runtime","Traceability"],"note":["cited By 1 \n\nTL;DR \n\nThis paper presents a model-based approach that has been conceived to analyze runtime data, to produce corresponding traceability models and to automatically infer from them potential design issues that might need to be fixed in order to solve detected system malfunctionings."],"number":["2"],"pages":["1:1"],"shorttitle":["Model-driven Design-Runtime Interaction in Safety Critical System Development"],"title":["Model-driven Design-Runtime Interaction in Safety Critical System Development: An Experience Report."],"volume":["18"]},"creators":{"author":[{"lastName":"Eramo","firstName":"Romina"},{"lastName":"Marchand de Kerchove","firstName":"Florent"},{"lastName":"Colange","firstName":"Maximilien"},{"lastName":"Tucci","firstName":"Michele"},{"lastName":"Ouy","firstName":"Julien"},{"lastName":"Bruneliere","firstName":"Hugo"},{"lastName":"Di Ruscio","firstName":"Davide"}]},"sentenceCased":true},{"key":"erdogmus50YearsSoftware2018","type":"article","fields":{"abstract":["This theme issue on software engineering’s 50th anniversary presents a range of contributions—from pioneers and well-established software engineers, to younger contributors whose imprint on the field is perhaps yet to come. These contributions come in a variety of formats that provide a balanced look at our field’s past, present, and likely future. The topics include both timeless ideas that appeared to fade for a while, only to pop up again in a new incarnation, and entirely new paradigms that have disrupted the field."],"author":["Erdogmus, H.","Medvidović, N.","Paulisch, F."],"date":["2018"],"doi":["10.1109/MS.2018.3571240"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"number":["5"],"pages":["20–24"],"title":["50 Years of Software Engineering"],"volume":["35"]},"creators":{"author":[{"lastName":"Erdogmus","firstName":"H."},{"lastName":"Medvidović","firstName":"N."},{"lastName":"Paulisch","firstName":"F."}]}},{"key":"erdogmusConversationBarryBoehm2018","type":"article","fields":{"langid":["english"],"author":["Erdogmus, Hakan","Medvidovic, Nenad"],"date":["2018-09"],"doi":["10.1109/MS.2018.3571249"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"number":["5"],"pages":["14–19"],"shorttitle":["A Conversation with Barry Boehm"],"title":["A Conversation with Barry Boehm: Recollections from 50 Years of Software Engineering"],"volume":["35"]},"creators":{"author":[{"lastName":"Erdogmus","firstName":"Hakan"},{"lastName":"Medvidovic","firstName":"Nenad"}]}},{"key":"erginLanguageGraphBasedModel2014","type":"incollection","fields":{"author":["Ergin, Hüseyin","Syriani, Eugene"],"booktitle":["Theory and Practice of Model Transformations"],"date":["2014"],"note":["TL;DR \n\nDelTa is a language for expressing design patterns for model transformations that is more abstract than and independent from any existing model transformation language, yet it is expressive enough to define design patterns as guidelines transformation developers can follow."],"pages":["91–105"],"publisher":["Springer"],"title":["Towards a Language for Graph-Based Model Transformation Design Patterns"],"url":["http://link.springer.com/chapter/10.1007/978-3-319-08789-4_7"],"urldate":["2015-09-15"]},"creators":{"author":[{"lastName":"Ergin","firstName":"Hüseyin"},{"lastName":"Syriani","firstName":"Eugene"}]}},{"key":"erlenhovCurrentFutureBots2019","type":"inproceedings","fields":{"author":["Erlenhov, Linda","Gomes de Oliveira Neto, Francisco","Scandariato, Riccardo","Leitner, Philipp"],"booktitle":["2019 IEEEACM 1st Int. Workshop Bots Softw. Eng. BotSE"],"date":["2019-05"],"doi":["10.1109/BotSE.2019.00009"],"eventtitle":["2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)"],"isbn":["978-1-72812-262-5"],"location":["Montreal, QC, Canada"],"pages":["7–11"],"publisher":["IEEE"],"title":["Current and Future Bots in Software Development"]},"creators":{"author":[{"lastName":"Erlenhov","firstName":"Linda"},{"lastName":"Gomes de Oliveira Neto","firstName":"Francisco"},{"lastName":"Scandariato","firstName":"Riccardo"},{"lastName":"Leitner","firstName":"Philipp"}]}},{"key":"ernstAIDrivenDevelopmentHere2022","type":"article","fields":{"langid":["english"],"author":["Ernst, Neil A.","Bavota, Gabriele","Menzies, Tim"],"date":["2022-03"],"doi":["10.1109/MS.2021.3133805"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nArtificial Intelligence Driven Development Environments integrate the power of modern AI into IDEs like Visual Studio Code and JetBrains IntelliJ and come with new challenges to think about, such as bias, legal compliance, security vulnerabilities, and their impact on learn programming."],"number":["2"],"pages":["106–110"],"shorttitle":["AI-Driven Development Is Here"],"title":["AI-Driven Development Is Here: Should You Worry?"],"volume":["39"]},"creators":{"author":[{"lastName":"Ernst","firstName":"Neil A."},{"lastName":"Bavota","firstName":"Gabriele"},{"lastName":"Menzies","firstName":"Tim"}]}},{"key":"escobar-avilaUnsupervisedSoftwareCategorization2015","type":"inproceedings","fields":{"author":["Escobar-Avila, J.","Linares-Vásquez, M.","Haiduc, S."],"booktitle":["2015 IEEE 23rd Int. Conf. Program Comprehension"],"date":["2015-05"],"doi":["10.1109/ICPC.2015.33"],"issn":["1092-8138"],"keywords":["Accuracy","Apache foundation repository","automatic software categorization","bytecode","clustering","Clustering algorithms","Data mining","dirichlet process","Java","Java libraries","learning (artificial intelligence)","program compilers","semantic information","Software","software categorization","Software libraries","software profiles","source code","source code (software)","supervised machine learning","training data","unsupervised algorithm","unsupervised software categorization"],"note":["TL;DR \n\nThis work proposes a novel approach, which overcomes limitations by using semantic information recovered from byte code and an unsupervised algorithm to assign categories to software systems."],"pages":["229–239"],"title":["Unsupervised software categorization using bytecode"]},"creators":{"author":[{"lastName":"Escobar-Avila","firstName":"J."},{"lastName":"Linares-Vásquez","firstName":"M."},{"lastName":"Haiduc","firstName":"S."}]},"sentenceCased":true},{"key":"escottContinuousModernisationPlaybook","type":"article","fields":{"langid":["english"],"author":["Escott, Eban","Tansey, Indi"],"pages":["96"],"title":["The Continuous Modernisation Playbook"]},"creators":{"author":[{"lastName":"Escott","firstName":"Eban"},{"lastName":"Tansey","firstName":"Indi"}]}},{"key":"EserciziDiMemoria","type":"online","fields":{"title":["Esercizi di memoria | CIMEC - Centro Interdipartimentale Mente/Cervello"],"url":["https://www.cimec.unitn.it/1172/esercizi-di-memoria"],"urldate":["2022-07-15"]},"creators":{},"sentenceCased":true},{"key":"espinazopaganQueryingLargeModels2014","type":"article","fields":{"langid":["english"],"author":["Espinazo Pagán, Javier","García Molina, Jesús"],"date":["2014-06"],"doi":["10.1016/j.infsof.2014.01.005"],"issn":["09505849"],"journaltitle":["Inf. Softw. Technol."],"number":["6"],"pages":["586–622"],"title":["Querying large models efficiently"],"volume":["56"]},"creators":{"author":[{"lastName":"Espinazo Pagán","firstName":"Javier"},{"lastName":"García Molina","firstName":"Jesús"}]},"sentenceCased":true},{"key":"Essaidi2013240","type":"book","fields":{"abstract":["Transformation design is a key step in model-driven engineering, and it is a very challenging task, particularly in context of the model-driven data warehouse. Currently, this process is ensured by human experts. The authors propose a new methodology using machine learning techniques to automatically derive these transformation rules. The main goal is to automatically derive the transformation rules to be applied in the model-driven data warehouse process. The proposed solution allows for a simple design of the decision support systems and the reduction of time and costs of development. The authors use the inductive logic programming framework to learn these transformation rules from examples of previous projects. Then, they find that in model-driven data warehouse application, dependencies exist between transformations. Therefore, the authors investigate a new machine learning methodology, learning dependent-concepts, that is suitable to solve this kind of problem. The experimental evaluation shows that the dependent-concept learning approach gives significantly better results. © 2014 by IGI Global. All rights reserved."],"author":["Essaidi, M.","Osmani, A.","Rouveirol, C."],"date":["2013"],"document_type":["Book Chapter"],"doi":["10.4018/978-1-4666-4494-6.ch011"],"isbn":["978-1-4666-4495-3 1-4666-4494-X 978-1-4666-4494-6"],"note":["cited By 0"],"pages":["240–267"],"publisher":["IGI Global"],"source":["Scopus"],"title":["Model-driven data warehouse automation: A dependent-concept learning approach"]},"creators":{"author":[{"lastName":"Essaidi","firstName":"M."},{"lastName":"Osmani","firstName":"A."},{"lastName":"Rouveirol","firstName":"C."}]},"sentenceCased":true},{"key":"Essaidi2014151","type":"book","fields":{"abstract":["This chapter studies a new machine learning application with a possible challenging benchmark for relational learning systems. We are interested in the automation of a model-driven data warehouse using machine learning techniques. The main goal is to automatically derive the transformation rules to be applied in the model-driven process. This aims to reduce the contribution of transformation designers, thereby reducing the time and cost of development. We propose to express the model transformation problem as an Inductive Logic Programming (ILP) one: existing project traces (or project experiences) are used to define the background knowledge and examples. The Aleph ILP engine is used to learn best transformation rules. In our application, we need to deal with several dependent-concepts. Taking into account the work in Predicate Invention, Layered Learning, Cascade Learning and Context Learning, we propose a new methodology that automatically updates the background knowledge of concepts to be learned. Experimental results support the conclusion that our approach is suitable to solve this kind of problem. © 2015 Imperial College Press. All rights reserved."],"author":["Essaidi, M.","Osmani, A.","Rouveirol, C."],"date":["2014"],"document_type":["Book Chapter"],"doi":["10.1142/9781783265091_0017"],"isbn":["978-1-78326-509-1 978-1-78326-508-4"],"note":["cited By 1 \n\nTL;DR \n\nThis paper proposes to express the model transformation problem as an Inductive Logic Programming one: existing project traces are used to define the background knowledge and examples, and the aleph ILP engine is used to learn best transformation rules."],"pages":["151–172"],"publisher":["Imperial College Press"],"source":["Scopus"],"title":["Learning dependent-concepts in ILP: Application to model-driven data warehouses"]},"creators":{"author":[{"lastName":"Essaidi","firstName":"M."},{"lastName":"Osmani","firstName":"A."},{"lastName":"Rouveirol","firstName":"C."}]},"sentenceCased":true},{"key":"Essaidi20162730","type":"book","fields":{"abstract":["Transformation design is a key step in model-driven engineering, and it is a very challenging task, particularly in context of the model-driven data warehouse. Currently, this process is ensured by human experts. The authors propose a new methodology using machine learning techniques to automatically derive these transformation rules. The main goal is to automatically derive the transformation rules to be applied in the model-driven data warehouse process. The proposed solution allows for a simple design of the decision support systems and the reduction of time and costs of development. The authors use the inductive logic programming framework to learn these transformation rules from examples of previous projects. Then, they find that in model-driven data warehouse application, dependencies exist between transformations. Therefore, the authors investigate a new machine learning methodology, learning dependent-concepts, that is suitable to solve this kind of problem. The experimental evaluation shows that the dependent-concept learning approach gives significantly better results. © 2017 by IGI Global. All rights reserved."],"author":["Essaidi, M.","Osmani, A.","Rouveirol, C."],"date":["2016"],"document_type":["Book Chapter"],"doi":["10.4018/978-1-5225-1759-7.ch113"],"isbn":["978-1-5225-1760-3 1-5225-1759-6 978-1-5225-1759-7"],"note":["cited By 0"],"pages":["2730–2758"],"publisher":["IGI Global"],"source":["Scopus"],"title":["Model-driven data warehouse automation: A dependent-concept learning approach"],"volume":["4"]},"creators":{"author":[{"lastName":"Essaidi","firstName":"M."},{"lastName":"Osmani","firstName":"A."},{"lastName":"Rouveirol","firstName":"C."}]},"sentenceCased":true},{"key":"etienChainingModelTransformations2012","type":"article","fields":{"author":["Etien, Anne","Aranega, Vincent","Blanc, Xavier","Paige, Richard F."],"date":["2012"],"doi":["10.1145/2432497.2432500"],"journaltitle":["Proc. First Workshop Anal. Model Transform. - AMT 12"],"pages":["9–14"],"title":["Chaining model transformations"]},"creators":{"author":[{"lastName":"Etien","firstName":"Anne"},{"lastName":"Aranega","firstName":"Vincent"},{"lastName":"Blanc","firstName":"Xavier"},{"lastName":"Paige","firstName":"Richard F."}]},"sentenceCased":true},{"key":"etienCombiningIndependentModel2010","type":"inproceedings","fields":{"abstract":["Model transformation is one of the key principles of Model Driven Engineering. Many approaches have been proposed to design and realize them. However, for all the approaches, model transformations are considered as single entities that can only be chained if their input and output metamodels are compatible. This approach has the major drawback to focus on the satisfaction of the compliance property when building a transformation chain. In this paper we propose a mechanism for combining independent model transformations which jointly work towards a common objective but do not initially handle compatible metamodels. Our proposal is independent of any model transformation approach. It has been validated using Gaspard, an environment dedicated to code generation for embedded systems."],"author":["Etien, Anne","Muller, Alexis","Legrand, Thomas","Blanc, Xavier"],"booktitle":["Proc. 2010 ACM Symp. Appl. Comput."],"date":["2010"],"doi":["10.1145/1774088.1774557"],"isbn":["978-1-60558-639-7"],"location":["New York, NY, USA"],"note":["TL;DR \n\nThis paper proposes a mechanism for combining independent model transformations which jointly work towards a common objective but do not initially handle compatible metamodels."],"pages":["2237–2243"],"publisher":["ACM"],"series":["SAC '10"],"title":["Combining Independent Model Transformations"]},"creators":{"author":[{"lastName":"Etien","firstName":"Anne"},{"lastName":"Muller","firstName":"Alexis"},{"lastName":"Legrand","firstName":"Thomas"},{"lastName":"Blanc","firstName":"Xavier"}]}},{"key":"etienLocalizedModelTransformations2013","type":"article","fields":{"author":["Etien, Anne","Muller, Alexis","Legrand, Thomas","Paige, Richard F."],"date":["2013"],"doi":["10.1007/s10270-013-0379-8"],"journaltitle":["Softw. Syst. Model."],"keywords":["Model transformation","Reusable transformation","software engineering","Transformation chaining"],"title":["Localized model transformations for building large-scale transformations"]},"creators":{"author":[{"lastName":"Etien","firstName":"Anne"},{"lastName":"Muller","firstName":"Alexis"},{"lastName":"Legrand","firstName":"Thomas"},{"lastName":"Paige","firstName":"Richard F."}]},"sentenceCased":true},{"key":"ETL","type":"inproceedings","fields":{"langid":["english"],"author":["Kolovos, Dimitrios S.","Paige, Richard F.","Polack, Fiona A. C."],"booktitle":["Proc ICMT 2008"],"date":["2008"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["46–60"],"publisher":["Springer"],"series":["LNCS"],"title":["The epsilon transformation language"],"volume":["5063"]},"creators":{"author":[{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Polack","firstName":"Fiona A. C."}]},"sentenceCased":true},{"key":"etzlstorferEvolutionModelingEcosystems2017","type":"inproceedings","fields":{"author":["Etzlstorfer, Juergen","Kapsammer, Elisabeth","Schwinger, Wieland"],"date":["2017"],"doi":["10.5220/0006167900900099"],"isbn":["978-989-758-210-3"],"note":["TL;DR \n\nA dedicated evaluation framework for coevolution approaches focusing on aspects relevant in the context of modeling ecosystems, and its application to a representative set of recent approaches is presented."],"pages":["90–99"],"publisher":["SCITEPRESS - Science and Technology Publications"],"shorttitle":["On the Evolution of Modeling Ecosystems"],"title":["On the Evolution of Modeling Ecosystems: An Evaluation of Co-Evolution Approaches:"]},"creators":{"author":[{"lastName":"Etzlstorfer","firstName":"Juergen"},{"lastName":"Kapsammer","firstName":"Elisabeth"},{"lastName":"Schwinger","firstName":"Wieland"}]}},{"key":"Evans2009","type":"article","fields":{"abstract":["This paper describes the design, implementation, and application of a new algorithm to detect cloned code. It operates on the abstract syntax trees formed by many compilers as an intermediate representation. It extends prior work by identifying clones even when arbitrary subtrees have been changed. These subtrees may represent structural rather than simply lexical code differences. In several hundred thousand lines of Java and C# code, 20–50% of the clones that we find involve these structural changes, which are not accounted for by previous methods. Our method also identifies cloning in declarations, so it is somewhat more general than conventional procedural abstraction."],"author":["Evans, William S.","Fraser, Christopher W.","Ma, Fei"],"date":["2009-12-01"],"doi":["10.1007/s11219-009-9074-y"],"issn":["1573-1367"],"journaltitle":["Softw. Qual. J."],"note":["TL;DR \n\nA new algorithm to detect cloned code is described that operates on the abstract syntax trees formed by many compilers as an intermediate representation and extends prior work by identifying clones even when arbitrary subtrees have been changed."],"number":["4"],"pages":["309–330"],"title":["Clone detection via structural abstraction"],"volume":["17"]},"creators":{"author":[{"lastName":"Evans","firstName":"William S."},{"lastName":"Fraser","firstName":"Christopher W."},{"lastName":"Ma","firstName":"Fei"}]},"sentenceCased":true},{"key":"ExemplarsSoftwareEngineering","type":"online","fields":{"title":["Exemplars | Software Engineering for Self-Adaptive Systems"],"url":["https://www.hpi.uni-potsdam.de/giese/public/selfadapt/exemplars/"],"urldate":["2016-09-24"]},"creators":{}},{"key":"ExploreEclipseOSGi","type":"online","fields":{"title":["Explore Eclipse's OSGi console"],"url":["https://www.ibm.com/developerworks/library/os-ecl-osgiconsole/"],"urldate":["2016-12-04"]},"creators":{},"sentenceCased":true},{"key":"ExtractingDomainModels2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["Conceptual models are essential in Software and Information Systems Engineering to meet many purposes since they explicitly represent the subject domains. Machine Learning (ML) approaches have recently been used in conceptual modeling to realize, among others, intelligent modeling assistance, model transformation, and metamodel classification. These works encode models in various ways, making the encoded models suitable for applying ML algorithms. The encodings capture the models’ structure and/or semantics, making this information available to the ML model during training. Therefore, the choice of the encoding for any ML-driven task is crucial for the ML model to learn the relevant contextual information. In this paper, we report findings from a systematic literature review which yields insights into the current research in machine learning for conceptual modeling (ML4CM). The review focuses on the various encodings used in existing ML4CM solutions and provides insights into i) which are the information sources, ii) how is the conceptual model’s structure and/or semantics encoded, iii) why is the model encoded, i.e., for which conceptual modeling task and, iv) which ML algorithms are applied. The results aim to structure the state of the art in encoding conceptual models for ML."],"booktitle":["2021 ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion MODELS-C"],"date":["2021"],"eventtitle":["2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)"],"isbn":["978-1-66542-484-4"],"keywords":["LOGSEQ"],"location":["Fukuoka, Japan"],"publisher":["IEEE"],"title":["Extracting Domain Models from Textual Requirements in the Era of Large Language Models"]},"creators":{}},{"key":"ExtremeDataManagement2019","type":"inproceedings","fields":{"booktitle":["2019 Amity Int. Conf. Artif. Intell. AICAI"],"date":["2019-02"],"doi":["10.1109/AICAI.2019.8701403"],"eventtitle":["2019 Amity International Conference on Artificial Intelligence (AICAI)"],"isbn":["978-1-5386-9346-9"],"location":["Dubai, United Arab Emirates"],"pages":["i-i"],"publisher":["IEEE"],"title":["Extreme Data Management Analysis and Visualization for Exascale Supercomputers and Experimental Facilities"]},"creators":{}},{"key":"fabiofumarolaDataModelingNoSQL14:24:10UTC","type":"unpublished","fields":{"abstract":["The Information Technology have led us into an era where the production,"],"author":["Fabio Fumarola"],"title":["5 Data Modeling for NoSQL 1/2"],"type":["Data & analytics"],"url":["https://www.slideshare.net/fabiofumarola1/data-modeling-for-nosql-12"],"urldate":["2018-04-30"],"year":["14:24:10 UTC"]},"creators":{"author":[{"firstName":"Fabio","lastName":"Fumarola"}]},"sentenceCased":true},{"key":"FacebookOpenSourced","type":"online","fields":{"title":["Facebook Open Sourced this Architecture for Personalized Neural Recommendation Systems | by Jesus Rodriguez | DataSeries | May, 2021 | Medium"],"url":["https://medium.com/dataseries/facebook-open-sourced-this-architecture-for-personalized-neural-recommendation-systems-97db3fef35bb"],"urldate":["2021-06-07"]},"creators":{},"sentenceCased":true},{"key":"falessiApplyingEmpiricalSoftware2010","type":"article","fields":{"langid":["english"],"abstract":["In the last 15 years, software architecture has emerged as an important software engineering field for managing the development and maintenance of large, software-intensive systems. Software architecture community has developed numerous methods, techniques, and tools to support the architecture process (analysis, design, and review). Historically, most advances in software architecture have been driven by talented people and industrial experience, but there is now a growing need to systematically gather empirical evidence about the advantages or otherwise of tools and methods rather than just rely on promotional anecdotes or rhetoric. The aim of this paper is to promote and facilitate the application of the empirical paradigm to software architecture. To this end, we describe the challenges and lessons learned when assessing software architecture research that used controlled experiments, replications, expert opinion, systematic literature reviews, observational studies, and surveys. Our research will support the emergence of a body of knowledge consisting of the more widely-accepted and well-formed software architecture. theories."],"author":["Falessi, Davide","Babar, Muhammad Ali","Cantone, Giovanni","Kruchten, Philippe"],"date":["2010-06"],"doi":["10.1007/s10664-009-9121-0"],"issn":["1382-3256, 1573-7616"],"journaltitle":["Empir Software Eng"],"number":["3"],"pages":["250–276"],"shorttitle":["Applying empirical software engineering to software architecture"],"title":["Applying empirical software engineering to software architecture: Challenges and lessons learned"],"volume":["15"]},"creators":{"author":[{"lastName":"Falessi","firstName":"Davide"},{"lastName":"Babar","firstName":"Muhammad Ali"},{"lastName":"Cantone","firstName":"Giovanni"},{"lastName":"Kruchten","firstName":"Philippe"}]},"sentenceCased":true},{"key":"falzoneModelBasedRapid2018","type":"incollection","fields":{"author":["Falzone, Emanuele","Bernaschina, Carlo"],"booktitle":["Web Engineering"],"date":["2018"],"doi":["10.1007/978-3-319-91662-0_43"],"editor":["Mikkonen, Tommi","Klamma, Ralf","Hernández, Juan"],"isbn":["978-3-319-91661-3 978-3-319-91662-0"],"location":["Cham"],"note":["TL;DR \n\nThe demonstrated approach solves the well-know problem of model driven forward engineering of breaking the automated development cycle when features that cannot be modelled are added manually to the generated code."],"pages":["496–500"],"publisher":["Springer International Publishing"],"title":["Model Based Rapid Prototyping and Evolution of Web Application"],"volume":["10845"]},"creators":{"author":[{"lastName":"Falzone","firstName":"Emanuele"},{"lastName":"Bernaschina","firstName":"Carlo"}],"editor":[{"lastName":"Mikkonen","firstName":"Tommi"},{"lastName":"Klamma","firstName":"Ralf"},{"lastName":"Hernández","firstName":"Juan"}]}},{"key":"families2persons","type":"article","fields":{"author":["Allilaire, Freddy","Jouault, Fr�d�ric"],"date":["2007"],"title":["A simple illustration of model to model transformation"],"url":["https://www.eclipse.org/atl/documentation/old/ATLUseCase_Families2Persons.pdf"]},"creators":{"author":[{"lastName":"Allilaire","firstName":"Freddy"},{"lastName":"Jouault","firstName":"Fr�d�ric"}]},"sentenceCased":true},{"key":"Fang20221151","type":"article","fields":{"abstract":["Cross-modal audiovisual generation is an emerging topic in machine learning. In particular, voice-to-face is one of the most popular research branches, which aims to generate faces from human voice clips. Most recent works in voice-to-face generation do not take emotion information into account. However, it could be widely observed that expressions are the key face attributes to reconstruct sharper and more discriminative faces. In this paper, we propose a novel facial expression GAN (FE-GAN) which takes emotion and expressions into account in face generation. To achieve this goal, we use two auxiliary classifiers to learn more emotion and identity representations between different modalities, respectively. Moreover, we design two discriminators, each focusing on a different aspect of the faces, to measure identity and emotion semantic relevance in generating. The triple loss is designed to make FE-GAN robust to voice variety and keep balance in two different modalities. Extensive experiments are conducted on two real datasets to demonstrate the effectiveness of FE-GAN in both quantitative and qualitative perspectives. The experimental results show that FE-GAN can not only outperform the previous models in terms of FID and IS values, but also generate more realistic face images compared with previous models. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature."],"author":["Fang, Z.","Liu, Z.","Liu, T.","Hung, C.-C.","Xiao, J.","Feng, G."],"author_keywords":["Cross-model generation; Expression reconstruction; Generative adversarial networks; Voice-to-face generation"],"coden":["VICOE"],"date":["2022"],"document_type":["Article"],"doi":["10.1007/s00371-021-02074-w"],"issn":["01782789"],"journaltitle":["Vis. Comput."],"keywords":["Cross-modal","Emerging topics","Emotion semantics","Face generation","Face images","Facial Expressions","Human voice","Interfaces (computer)","Real data sets","Semantics","Software engineering"],"note":["cited By 8 \n\nTL;DR \n\nThis paper proposes a novel facial expression GAN (FE-GAN) which takes emotion and expressions into account in face generation and can not only outperform the previous models in terms of FID and IS values, but also generate more realistic face images compared with previous models."],"number":["3"],"pages":["1151–1164"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Facial expression GAN for voice-driven face generation"],"volume":["38"]},"creators":{"author":[{"lastName":"Fang","firstName":"Z."},{"lastName":"Liu","firstName":"Z."},{"lastName":"Liu","firstName":"T."},{"lastName":"Hung","firstName":"C.-C."},{"lastName":"Xiao","firstName":"J."},{"lastName":"Feng","firstName":"G."}]},"sentenceCased":true},{"key":"fanLargeLanguageModels2023","type":"online","fields":{"abstract":["This paper provides a survey of the emerging area of Large Language Models (LLMs) for Software Engineering (SE). It also sets out open research challenges for the application of LLMs to technical problems faced by software engineers. LLMs' emergent properties bring novelty and creativity with applications right across the spectrum of Software Engineering activities including coding, design, requirements, repair, refactoring, performance improvement, documentation and analytics. However, these very same emergent properties also pose significant technical challenges; we need techniques that can reliably weed out incorrect solutions, such as hallucinations. Our survey reveals the pivotal role that hybrid techniques (traditional SE plus LLMs) have to play in the development and deployment of reliable, efficient and effective LLM-based SE."],"author":["Fan, Angela","Gokkaya, Beliz","Harman, Mark","Lyubarskiy, Mitya","Sengupta, Shubho","Yoo, Shin","Zhang, Jie M."],"date":["2023-11-11"],"eprint":["2310.03533"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Software Engineering","LOGSEQ"],"note":["TL;DR \n\nThis survey reveals the pivotal role that hybrid techniques (traditional SE plus LLMs) have to play in the development and deployment of reliable, efficient and effective LLM-based SE."],"pubstate":["preprint"],"shorttitle":["Large Language Models for Software Engineering"],"title":["Large Language Models for Software Engineering: Survey and Open Problems"],"url":["http://arxiv.org/abs/2310.03533"],"urldate":["2024-01-17"]},"creators":{"author":[{"lastName":"Fan","firstName":"Angela"},{"lastName":"Gokkaya","firstName":"Beliz"},{"lastName":"Harman","firstName":"Mark"},{"lastName":"Lyubarskiy","firstName":"Mitya"},{"lastName":"Sengupta","firstName":"Shubho"},{"lastName":"Yoo","firstName":"Shin"},{"lastName":"Zhang","firstName":"Jie M."}]}},{"key":"Fard2020755","type":"inproceedings","fields":{"abstract":["A growing number of companies rely on machine learning as a key element for gaining a competitive edge from their collected Big Data. An in-database machine learning system can provide many advantages in this scenario, e.g., eliminating the overhead of data transfer, avoiding the maintenance costs of a separate analytical system, and addressing data security and provenance concerns. In this paper, we present our distributed machine learning subsystem within the Vertica database. This subsystem, Vertica-ML, includes machine learning functionalities with SQL API which cover a complete data science workflow as well as model management. We treat machine learning models in Vertica as first-class database objects like tables and views; therefore, they enjoy a similar mechanism for archiving and managing. We explain the architecture of the subsystem, and present a set of experiments to evaluate the performance of the machine learning algorithms implemented on top of it. © 2020 Association for Computing Machinery."],"author":["Fard, A.","Le, A.","Larionov, G.","Dhillon, W.","Bear, C."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3318464.3386137"],"isbn":["978-1-4503-6735-6"],"issn":["07308078"],"note":["cited By 5"],"pages":["755–768"],"publisher":["Association for Computing Machinery"],"series":["Proceedings of the ACM SIGMOD International Conference on Management of Data"],"source":["Scopus"],"title":["Vertica-ML: Distributed machine learning in vertica database"]},"creators":{"author":[{"lastName":"Fard","firstName":"A."},{"lastName":"Le","firstName":"A."},{"lastName":"Larionov","firstName":"G."},{"lastName":"Dhillon","firstName":"W."},{"lastName":"Bear","firstName":"C."}]},"sentenceCased":true},{"key":"faunes2013genetic","type":"inproceedings","fields":{"langid":["english"],"author":["Faunes, Martin","Sahraoui, Houari","Boukadoum, Mounir"],"booktitle":["Theory Pract. Model Transform. ICMT"],"date":["2013"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nA genetic programming-based approach to automatically learn model transformation rules from prior transformation pairs of source-target models used as examples, that does not need fine-grained transformation traces to produce many-to-many rules."],"pages":["17–32"],"title":["Genetic-programming approach to learn model transformation rules from examples"]},"creators":{"author":[{"lastName":"Faunes","firstName":"Martin"},{"lastName":"Sahraoui","firstName":"Houari"},{"lastName":"Boukadoum","firstName":"Mounir"}]},"sentenceCased":true},{"key":"Fayyad201731","type":"inproceedings","fields":{"abstract":["This panel aims to address areas that are widely acknowledged to be of critical importance to the success of Data Science projects and to the healthy growth of KDD/Data Science as a field of scientific research. However, despite this acknowledgement of their criticality, these areas receive insufficient attention in the major conferences in the field. Furthermore, there is a lack of actual actions and tools to address these areas in actual practice. These areas are summarized as follows: 1. Ask any data scientist or machine learning practitioner what they spend the majority of their time working on, and you will most likely get an answer that indicates that 80% to 90% of their time is spent on \"Data Chasing\", \"Data Sourcing\", \"Data Wrangling\", \"Data Cleaning\" and generally what researchers would refer to-often dismissively-as \"Data Preparation\". The process of producing statistical or data mining models from data is typically \"messy\" and certainly lacks management tools to help manage, replicate, reconstruct, and capture all the knowledge that goes in 90% of activities of a Data Scientists. The intensive Data Engineering work that goes into exploring and determining the representation of problem and the significant amount of \"data cleaning\" that ensues creates a plethora of extracts, files, and many artifacts that are only meaningful to the data scientist. 2. The severe lack of Benchmarks in the field, especially ones at big data scale is an impediment to true, objective, measurable progress on performance. The results of each paper are highly dependent on the large degree of freedom an author has on configuring competitive models and on determining which data sets to use (often Data that is not available to others to replicate results on) 3. Monitoring the health of models in production, and deploying models into production environments efficiently and effectively is a black art and often an ignored area. Many models are effectively \"orphans\" with no means of getting appropriate health monitoring. The task of deploying a built model to production is frequently beyond the capabilities of a Data Scientists and the understanding of the IT team. For a typical company, a Machine Learning or Data Science expert is a major investment; yet these people are in such hot demand, that likelihood of churn is high. Typically, when a data scientist is replaced, the process pretty much starts over with a tabula rasa⋯ In fact, I would argue most data scientists coming back to tasks they built themselves 1-2 years before are unable to reconstruct what they did. For this panel, we have selected a unique set of experts who have different experiences and perspectives on these important problems and how they should be dealt with in real environments. It is our hope that the panel discussion will not only produce recommendations on what to do about these painful impediments to successful project deployments, but also serve as an eye opener for the research community to the importance of paying close attention to issues of Data and Model Management in KDD, as well the need to think carefully about the lifecycle of models and how they can be managed, maintained, and deployed systematically. Without addressing these critical deployment and practice issues, our field will be challenged to grow in a healthy and sustainable way. The expert panelists for this panel along with the panel moderator: Usama Fayyad are listed below along with their biographical sketches. © 2017 Copyright held by the owner/author(s)."],"author":["Fayyad, U.M.","Candel, A.","De La Rubia, E.A.","Pafka, S.","Chong, A.","Lee, J.-Y."],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.1145/3097983.3120998"],"isbn":["978-1-4503-4887-4"],"note":["cited By 4"],"pages":["31–32"],"publisher":["Association for Computing Machinery"],"series":["Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining"],"source":["Scopus"],"title":["Benchmarks and process management in data science: Will we ever get over the mess?"],"volume":["Part F129685"]},"creators":{"author":[{"lastName":"Fayyad","firstName":"U.M."},{"lastName":"Candel","firstName":"A."},{"lastName":"De La Rubia","firstName":"E.A."},{"lastName":"Pafka","firstName":"S."},{"lastName":"Chong","firstName":"A."},{"lastName":"Lee","firstName":"J.-Y."}]},"sentenceCased":true},{"key":"fearyMultipleViewsSafetyCritical2016","type":"inproceedings","fields":{"langid":["english"],"author":["Feary, Michael","Martinie, Célia","Palanque, Philippe","Tscheligi, Manfred"],"date":["2016"],"doi":["10.1145/2851581.2886430"],"isbn":["978-1-4503-4082-3"],"note":["TL;DR \n\nThis SIG targets at two problem areas: the engineering of the user interaction with (partly-) autonomous systems: how to design, build and assess autonomous behavior, especially in cases where there is a need to represent on the user interface both autonomous and interactive objects."],"pages":["1069–1072"],"publisher":["ACM Press"],"shorttitle":["Multiple Views on Safety-Critical Automation"],"title":["Multiple Views on Safety-Critical Automation: Aircrafts, Autonomous Vehicles, Air Traffic Management and Satellite Ground Segments Perspectives"]},"creators":{"author":[{"lastName":"Feary","firstName":"Michael"},{"lastName":"Martinie","firstName":"Célia"},{"lastName":"Palanque","firstName":"Philippe"},{"lastName":"Tscheligi","firstName":"Manfred"}]}},{"key":"Febbo2016","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Des. Eng. Tech. Conf."],"affiliation":["Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109, United States"],"author":["Febbo, H.","Ersal, T.","Stein, J.L."],"date":["2016"],"document_type":["Conference Paper"],"doi":["10.1115/DETC2016-60335"],"isbn":["978-0-7918-5013-8"],"note":["cited By 2"],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the ASME Design Engineering Technical Conference"],"source":["Scopus"],"title":["A combined Plant/Controller optimization framework for hybrid vehicles with MPG, emissions and drivability considerations"],"volume":["3"]},"creators":{"author":[{"lastName":"Febbo","firstName":"H."},{"lastName":"Ersal","firstName":"T."},{"lastName":"Stein","firstName":"J.L."}]},"sentenceCased":true},{"key":"felfernigOverviewRecommenderSystems2019","type":"article","fields":{"langid":["english"],"abstract":["The Internet Of Things (IoT) is an emerging paradigm that envisions a networked infrastructure enabling different types of devices to be interconnected. It creates different kinds of artifacts (e.g., services and applications) in various application domains such as health monitoring, sports monitoring, animal monitoring, enhanced retail services, and smart homes. Recommendation technologies can help to more easily identify relevant artifacts and thus will become one of the key technologies in future IoT solutions. In this article, we provide an overview of existing applications of recommendation technologies in the IoT context and present new recommendation techniques on the basis of real-world IoT scenarios."],"author":["Felfernig, Alexander","Polat-Erdeniz, Seda","Uran, Christoph","Reiterer, Stefan","Atas, Muesluem","Tran, Thi Ngoc Trang","Azzoni, Paolo","Kiraly, Csaba","Dolui, Koustabh"],"date":["2019-04"],"doi":["10.1007/s10844-018-0530-7"],"issn":["0925-9902, 1573-7675"],"journaltitle":["J Intell Inf Syst"],"keywords":["internet of things","recommendation systems"],"note":["<b>Yellow Annotations (17/12/2020, 17:05:17)</b> \n\n\"any system that guides a user in a personalized way to interesting or useful objects in a large space of possible options or that produces such objects as output\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=1\">Felfernig et al 2019:285</a>) \n\n\"collaborative filtering and content-based filtering. Collaborative Filtering (Konstan et al. 1997) is using the opinio\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=2\">Felfernig et al 2019:286</a>) \n\n\"IoT workflow development\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=2\">Felfernig et al 2019:286</a>) \n\n\"ecommendation of app\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=2\">Felfernig et al 2019:286</a>) \n\n\"domain-specific scenarios such as food recommendation (\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=2\">Felfernig et al 2019:286</a>) \n\n\"recommender engine can be included to assist users in the configuration of the gateway\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=3\">Felfernig et al 2019:287</a>) \n\n\"in recommending useful applications based on given gateway settings and user interaction protocols.\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=3\">Felfernig et al 2019:287</a>) \n\n\"In the context of wildlife animal monitoring, measuring devices and data collection units (typically drones) have to be selected and parametrized in such a way that the observation area is completely covered\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=3\">Felfernig et al 2019:287</a>) \n\n\"In the context of smart homes, recommendation technologies improve the overall applicability of the installed equipment and can also help to optimize the usage of the available resources (e.g., minimizing power consumption).\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=3\">Felfernig et al 2019:287</a>) \n\n\"recommender systems can help the spectators to determine the current geographical location of certain athletes. This further results in recommended sites at which the athlete can be seen and cheered.\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=3\">Felfernig et al 2019:287</a>) \n\n\"how recommenders can be applied in IoT scenarios and to propose new recommendation approaches for the IoT domain.\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=4\">Felfernig et al 2019:288</a>) \n\n\"existing applications of recommendation technologies in the IoT.\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=4\">Felfernig et al 2019:288</a>) \n\n\"IoT infrastructure, a recommender system does not have to only rely on the preferences of the user but can take into account further information sources.\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=4\">Felfernig et al 2019:288</a>) \n\n\"Alex needs to receive some app, device or communication protocol (BLE, zigbee, etc.) recommendations according to the overall settings on the gateway.\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=5\">Felfernig et al 2019:289</a>) \n\n\"support for choosing the sensors and configuring the system properly.\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=5\">Felfernig et al 2019:289</a>) \n\n\"SEQREQ: Sequences based recommendation\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=11\">Felfernig et al 2019:295</a>) \n\n\"SEQREQ (Sequences based Recommendation) which recommends items based on sequential pattern mini\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=11\">Felfernig et al 2019:295</a>) \n\n\"CONFREQ: Recommendations for configurators\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=13\">Felfernig et al 2019:297</a>) \n\n\"DIAGREQ: recommending diagnoses\" (<a href=\"zotero://open-pdf/library/items/PZH6FFNA?page=16\">Felfernig et al 2019:300</a>)"],"number":["2"],"pages":["285–309"],"title":["An overview of recommender systems in the internet of things"],"volume":["52"]},"creators":{"author":[{"lastName":"Felfernig","firstName":"Alexander"},{"lastName":"Polat-Erdeniz","firstName":"Seda"},{"lastName":"Uran","firstName":"Christoph"},{"lastName":"Reiterer","firstName":"Stefan"},{"lastName":"Atas","firstName":"Muesluem"},{"lastName":"Tran","firstName":"Thi Ngoc Trang"},{"lastName":"Azzoni","firstName":"Paolo"},{"lastName":"Kiraly","firstName":"Csaba"},{"lastName":"Dolui","firstName":"Koustabh"}]},"sentenceCased":true},{"key":"Feng2019368","type":"article","fields":{"abstract":["For engineering applications, the dynamic system responses can be significantly affected by uncertainties in the system parameters including material and geometric properties as well as by uncertainties in the excitations. The reliability of dynamic systems is widely evaluated based on the first-passage theory. To improve the computational efficiency, surrogate models are widely used to approximate the relationship between the system inputs and outputs. In this paper, a new machine learning based metamodel, namely the extended support vector regression (X-SVR), is proposed for the reliability analysis of dynamic systems via utilizing the first-passage theory. Furthermore, the capability of X-SVR is enhanced by a new kernel function developed from the vectorized Gegenbauer polynomial, especially for solving complex engineering problems. Through the proposed approach, the relationship between the extremum of the dynamic responses and the input uncertain parameters is approximated by training the X-SVR model such that the probability of failure can be efficiently predicted without using other computational tools for numerical analysis, such as the finite element analysis (FEM). The feasibility and performance of the proposed surrogate model in dynamic reliability analysis is investigated by comparing it with the conventional ε-insensitive support vector regression (ε-SVR) with Gaussian kernel and Monte Carlo simulation (MSC). Four numerical examples are adopted to evidently demonstrate the practicability and efficiency of the proposed X-SVR method. © 2019 Elsevier Ltd"],"author":["Feng, J.","Liu, L.","Wu, D.","Li, G.","Beer, M.","Gao, W."],"coden":["MSSPE"],"date":["2019"],"document_type":["Article"],"doi":["10.1016/j.ymssp.2019.02.027"],"issn":["08883270"],"journaltitle":["Mech. Syst. Signal Process."],"note":["cited By 37"],"pages":["368–391"],"publisher":["Academic Press"],"source":["Scopus"],"title":["Dynamic reliability analysis using the extended support vector regression (X-SVR)"],"volume":["126"]},"creators":{"author":[{"lastName":"Feng","firstName":"J."},{"lastName":"Liu","firstName":"L."},{"lastName":"Wu","firstName":"D."},{"lastName":"Li","firstName":"G."},{"lastName":"Beer","firstName":"M."},{"lastName":"Gao","firstName":"W."}]},"sentenceCased":true},{"key":"fengCodeBERTPreTrainedModel2020","type":"online","fields":{"abstract":["We present CodeBERT, a bimodal pre-trained model for programming language (PL) and nat-ural language (NL). CodeBERT learns general-purpose representations that support downstream NL-PL applications such as natural language codesearch, code documentation generation, etc. We develop CodeBERT with Transformer-based neural architecture, and train it with a hybrid objective function that incorporates the pre-training task of replaced token detection, which is to detect plausible alternatives sampled from generators. This enables us to utilize both bimodal data of NL-PL pairs and unimodal data, where the former provides input tokens for model training while the latter helps to learn better generators. We evaluate CodeBERT on two NL-PL applications by fine-tuning model parameters. Results show that CodeBERT achieves state-of-the-art performance on both natural language code search and code documentation generation tasks. Furthermore, to investigate what type of knowledge is learned in CodeBERT, we construct a dataset for NL-PL probing, and evaluate in a zero-shot setting where parameters of pre-trained models are fixed. Results show that CodeBERT performs better than previous pre-trained models on NL-PL probing."],"author":["Feng, Zhangyin","Guo, Daya","Tang, Duyu","Duan, Nan","Feng, Xiaocheng","Gong, Ming","Shou, Linjun","Qin, Bing","Liu, Ting","Jiang, Daxin","Zhou, Ming"],"date":["2020-09-18"],"eprint":["2002.08155"],"eprintclass":["cs"],"eprinttype":["arxiv"],"ids":["feng-etal-2020-codebert"],"keywords":["Computer Science - Computation and Language","Computer Science - Programming Languages"],"note":["Comment: Accepted to Findings of EMNLP 2020. 12 pages \n\nTL;DR \n\nThis work develops CodeBERT with Transformer-based neural architecture, and trains it with a hybrid objective function that incorporates the pre-training task of replaced token detection, which is to detect plausible alternatives sampled from generators."],"pubstate":["preprint"],"shorttitle":["CodeBERT"],"title":["CodeBERT: A Pre-Trained Model for Programming and Natural Languages"],"url":["http://arxiv.org/abs/2002.08155"],"urldate":["2023-05-04"]},"creators":{"author":[{"lastName":"Feng","firstName":"Zhangyin"},{"lastName":"Guo","firstName":"Daya"},{"lastName":"Tang","firstName":"Duyu"},{"lastName":"Duan","firstName":"Nan"},{"lastName":"Feng","firstName":"Xiaocheng"},{"lastName":"Gong","firstName":"Ming"},{"lastName":"Shou","firstName":"Linjun"},{"lastName":"Qin","firstName":"Bing"},{"lastName":"Liu","firstName":"Ting"},{"lastName":"Jiang","firstName":"Daxin"},{"lastName":"Zhou","firstName":"Ming"}]}},{"key":"Ferdjoukh20131044","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Int. Conf. Tools Artif. Intell. ICTAI"],"affiliation":["LIRMM, Universit́e Montpellier 2, CNRS, Montpellier, France"],"art_number":["6735367"],"author":["Ferdjoukh, A.","Baert, A.-E.","Chateau, A.","Coletta, R.","Nebut, C."],"coden":["PCTIF"],"correspondence_address1":["LIRMM, , Montpellier, France"],"date":["2013"],"document_type":["Conference Paper"],"doi":["10.1109/ICTAI.2013.156"],"isbn":["978-1-4799-2971-9"],"issn":["10823409"],"keywords":["GOAL_Model-synthesis","notion","TECHNIQUE_CSP"],"note":["cited By 13 \n\nTL;DR \n\nThe generation process is described, which appears to be quicker, more efficient and flexible than any other state-of-the-art approach to metamodel instantiation using CSP."],"pages":["1044–1051"],"series":["Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI"],"source":["Scopus"],"title":["A CSP approach for metamodel instantiation"]},"creators":{"author":[{"lastName":"Ferdjoukh","firstName":"A."},{"lastName":"Baert","firstName":"A.-E."},{"lastName":"Chateau","firstName":"A."},{"lastName":"Coletta","firstName":"R."},{"lastName":"Nebut","firstName":"C."}]},"sentenceCased":true},{"key":"Fernández-Ceniceros2014151","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Adv. Intell. Sys. Comput."],"affiliation":["EDMANS Research Group, University of La Rioja, Logrono, Spain"],"author":["Fernández-Ceniceros, J.","Urraca-Valle, R.","Antoñanzas-Torres, J.","Sanz-Garcia, A."],"date":["2014"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-319-01854-6_16"],"editor":["Abraham A., Corchado E., Zelinka I., Bringas P.G., Herrero A., Baruque B., Quintian H., Corchado E., de Carvalho A.C.P.L.F., Klett F., Zelinka I., Snasel V."],"isbn":["9783319018539"],"issn":["21945357"],"journaltitle":["Adv. Intell. Syst. Comput."],"note":["cited By 1 \n\nTL;DR \n\nThe use of metamodels based on soft computing as an overall approximation system for structures analysis based on artificial neural network as global approximation technique and the parameters for more realistic and informative load-displacement curve including nonlinear effects are estimated for bolted steel lap joints."],"pages":["151–160"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["The application of metamodels based on soft computing to reproduce the behaviour of bolted lap joints in steel structures"],"volume":["239"]},"creators":{"author":[{"lastName":"Fernández-Ceniceros","firstName":"J."},{"lastName":"Urraca-Valle","firstName":"R."},{"lastName":"Antoñanzas-Torres","firstName":"J."},{"lastName":"Sanz-Garcia","firstName":"A."}],"editor":[{"lastName":"Abraham A.","suffix":"Corchado E.","firstName":"Zelinka I., Bringas P.G., Herrero A., Baruque B., Quintian H., Corchado E., de Carvalho A.C.P.L.F., Klett F., Zelinka I., Snasel V."}]},"sentenceCased":true},{"key":"ferryCloudMFApplying2014","type":"inproceedings","fields":{"abstract":["The market of cloud computing encompasses an ever-growing number of cloud providers offering a multitude of infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) solutions. The heterogeneity of these solutions hinders the proper exploitation of cloud computing since it prevents interoperability and promotes vendor lock-in, which increases the complexity of executing and managing multi-cloud applications (i.e., Applications that can be deployed across multiple cloud infrastructures and platforms). Providers of multi-cloud applications seek to exploit the peculiarities of each cloud solution and to combine the delivery models of IaaS and PaaS in order to optimise performance, availability, and cost. In this paper, we show how the Cloud Modelling Framework leverages upon model-driven engineering to tame this complexity by providing: (i) a tool-supported domain-specific language for specifying the provisioning and deployment of multi-cloud applications, and (ii) a models@run-time environment for enacting the provisioning, deployment, and adaptation of these applications. © 2014 IEEE."],"author":["Ferry, N.","Song, H.","Rossini, A.","Chauvel, F.","Solberg, A."],"booktitle":["Proc. - 2014 IEEEACM 7th Int. Conf. Util. Cloud Comput. UCC 2014"],"date":["2014"],"doi":["10.1109/UCC.2014.36"],"isbn":["978-1-4799-7881-6"],"keywords":["Cloud computing","Cloud infrastructures","Cloud providers","Computer programming languages","Delivery models","Domain specific languages","Embedded systems","Infrastructure as a service (IaaS)","Model-driven Engineering","Modeling languages","Modelling framework","Multi-clouds","Platform as a Service (PaaS)","Problem oriented languages","Runtime environments"],"note":["cited By 60 \n\nTL;DR \n\nThis paper shows how the Cloud Modelling Framework leverages upon model-driven engineering to tame this complexity by providing a tool-supported domain-specific language for specifying the provisioning and deployment of multi-cloud applications and a models@run-time environment for enacting the provisioned, deployment, and adaptation of these applications."],"pages":["269–277"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Cloud MF: Applying MDE to tame the complexity of managing multi-cloud applications"]},"creators":{"author":[{"lastName":"Ferry","firstName":"N."},{"lastName":"Song","firstName":"H."},{"lastName":"Rossini","firstName":"A."},{"lastName":"Chauvel","firstName":"F."},{"lastName":"Solberg","firstName":"A."}]},"sentenceCased":true},{"key":"ferryCloudMFModelDrivenManagement2018","type":"article","fields":{"langid":["english"],"author":["Ferry, Nicolas","Chauvel, Franck","Song, Hui","Rossini, Alessandro","Lushpenko, Maksym","Solberg, Arnor"],"date":["2018-01-20"],"doi":["10.1145/3125621"],"issn":["15335399"],"journaltitle":["ACM Trans. Internet Technol."],"number":["2"],"pages":["1–24"],"shorttitle":["CloudMF"],"title":["CloudMF: Model-Driven Management of Multi-Cloud Applications"],"volume":["18"]},"creators":{"author":[{"lastName":"Ferry","firstName":"Nicolas"},{"lastName":"Chauvel","firstName":"Franck"},{"lastName":"Song","firstName":"Hui"},{"lastName":"Rossini","firstName":"Alessandro"},{"lastName":"Lushpenko","firstName":"Maksym"},{"lastName":"Solberg","firstName":"Arnor"}]}},{"key":"Feth2017135","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Fraunhofer Institute for Experimental Software Engineering, Kaiserslautern, Germany"],"author":["Feth, P.","Schneider, D.","Adler, R."],"correspondence_address1":["Feth, P.; Fraunhofer Institute for Experimental Software EngineeringGermany; email: patrik.feth@iese.fraunhofer.de"],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-319-66266-4_9"],"editor":["Bitsch F., Tonetta S., Schoitsch E."],"isbn":["9783319662657"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 10 \n\nTL;DR \n\nThis work presents a conceptual framework and a corresponding metamodel, which are motivated and justified by existing work in the field of runtime safety monitoring, and presents an SSV that is based on the ISO 22839 standard for forward collision mitigation."],"pages":["135–148"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["A conceptual safety supervisor definition and evaluation framework for autonomous Systems"],"volume":["10488 LNCS"]},"creators":{"author":[{"lastName":"Feth","firstName":"P."},{"lastName":"Schneider","firstName":"D."},{"lastName":"Adler","firstName":"R."}],"editor":[{"lastName":"Bitsch F.","suffix":"Tonetta S.","firstName":"Schoitsch E."}]},"sentenceCased":true},{"key":"fischerStackOverflowConsidered2017","type":"article","fields":{"abstract":["Online programming discussion platforms such as Stack Overflow serve as a rich source of information for software developers. Available information include vibrant discussions and oftentimes ready-to-use code snippets. Anecdotes report that software developers copy and paste code snippets from those information sources for convenience reasons. Such behavior results in a constant flow of community-provided code snippets into production software. To date, the impact of this behaviour on code security is unknown. We answer this highly important question by quantifying the proliferation of security-related code snippets from Stack Overflow in Android applications available on Google Play. Access to the rich source of information available on Stack Overflow including ready-to-use code snippets provides huge benefits for software developers. However, when it comes to code security there are some caveats to bear in mind: Due to the complex nature of code security, it is very difficult to provide ready-to-use and secure solutions for every problem. Hence, integrating a security-related code snippet from Stack Overflow into production software requires caution and expertise. Unsurprisingly, we observed insecure code snippets being copied into Android applications millions of users install from Google Play every day. To quantitatively evaluate the extent of this observation, we scanned Stack Overflow for code snippets and evaluated their security score using a stochastic gradient descent classifier. In order to identify code reuse in Android applications, we applied state-of-the-art static analysis. Our results are alarming: 15.4% of the 1.3 million Android applications we analyzed, contained security-related code snippets from Stack Overflow. Out of these 97.9% contain at least one insecure code snippet."],"author":["Fischer, Felix","Böttinger, Konstantin","Xiao, Huang","Stransky, Christian","Acar, Yasemin","Backes, Michael","Fahl, Sascha"],"date":["2017-10-09"],"eprint":["1710.03135"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv171003135 Cs"],"keywords":["Computer Science - Cryptography and Security"],"note":["TL;DR \n\nThis work quantifies the proliferation of security-related code snippets from Stack Overflow in Android applications available on Google Play by quantifying the number of insecure code snippets and evaluated their security score using a stochastic gradient descent classifier."],"shorttitle":["Stack Overflow Considered Harmful?"],"title":["Stack Overflow Considered Harmful? The Impact of Copy&Paste on Android Application Security"],"url":["http://arxiv.org/abs/1710.03135"],"urldate":["2021-06-18"]},"creators":{"author":[{"lastName":"Fischer","firstName":"Felix"},{"lastName":"Böttinger","firstName":"Konstantin"},{"lastName":"Xiao","firstName":"Huang"},{"lastName":"Stransky","firstName":"Christian"},{"lastName":"Acar","firstName":"Yasemin"},{"lastName":"Backes","firstName":"Michael"},{"lastName":"Fahl","firstName":"Sascha"}]}},{"key":"fleckModelTransformationModularization2017","type":"article","fields":{"author":["Fleck, Martin","Troya, Javier","Kessentini, Marouane","Wimmer, Manuel","Alkhazi, Bader"],"date":["2017"],"doi":["10.1109/TSE.2017.2654255"],"issn":["0098-5589, 1939-3520"],"journaltitle":["IEEE Trans. Softw. Eng."],"keywords":["Model transformation","modularization","multi-objective problem","optimization problem"],"note":["TL;DR \n\nThis study proposes an automated search-based approach to modularize model transformations based on higher-order transformations and shows that ATL transformations can be modularized automatically, efficiently, and effectively by this approach."],"pages":["1–1"],"title":["Model Transformation Modularization as a Many-Objective Optimization Problem"]},"creators":{"author":[{"lastName":"Fleck","firstName":"Martin"},{"lastName":"Troya","firstName":"Javier"},{"lastName":"Kessentini","firstName":"Marouane"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Alkhazi","firstName":"Bader"}]}},{"key":"fleder2009blockbuster","type":"article","fields":{"author":["Fleder, Daniel","Hosanagar, Kartik"],"date":["2009"],"journaltitle":["Manag. Sci."],"note":["TL;DR \n\nAn analytical model of recommender systems and their influence on consumer choice is developed to explore the strong, path-dependent interaction between recommendations and sales and is believed to be the first to attempt to isolate the impact ofRecommender systems on long-run sales diversity."],"number":["5"],"pages":["697–712"],"publisher":["INFORMS"],"title":["Blockbuster culture's next rise or fall: The impact of recommender systems on sales diversity"],"volume":["55"]},"creators":{"author":[{"lastName":"Fleder","firstName":"Daniel"},{"lastName":"Hosanagar","firstName":"Kartik"}]},"sentenceCased":true},{"key":"fleureyQualifyingInputTest2007","type":"article","fields":{"author":["Fleurey, Franck","Baudry, Benoit","Muller, Pierre-Alain","Traon, Yves Le"],"date":["2007"],"doi":["10.1007/s10270-007-0074-8"],"journaltitle":["Softw. Syst. Model."],"keywords":["software engineering"],"number":["2"],"pages":["185–203"],"title":["Qualifying input test data for model transformations"],"volume":["8"]},"creators":{"author":[{"lastName":"Fleurey","firstName":"Franck"},{"lastName":"Baudry","firstName":"Benoit"},{"lastName":"Muller","firstName":"Pierre-Alain"},{"lastName":"Traon","firstName":"Yves Le"}]},"sentenceCased":true},{"key":"fogarasScalingLinkbasedSimilarity2005","type":"inproceedings","fields":{"acmid":["1060839"],"author":["Fogaras, Dániel","Rácz, Balázs"],"booktitle":["Proc. 14th Int. Conf. World Wide Web"],"date":["2005"],"isbn":["1-59593-046-9"],"keywords":["fingerprint","link-analysis","scalability","similarity search"],"location":["New York, NY, USA"],"nodoi":["10.1145/1060745.1060839"],"numpages":["10"],"pages":["641–650"],"publisher":["ACM"],"series":["WWW '05"],"title":["Scaling link-based similarity search"],"url":["http://doi.acm.org/10.1145/1060745.1060839"]},"creators":{"author":[{"lastName":"Fogaras","firstName":"Dániel"},{"lastName":"Rácz","firstName":"Balázs"}]},"sentenceCased":true},{"key":"Foreward2011","type":"book","fields":{"date":["2011"],"ids":["Foreward2011a"],"journaltitle":["ACM International Conference Proceeding Series"],"title":["Foreward"]},"creators":{}},{"key":"forsyth_top_2021","type":"misc","fields":{"langid":["english"],"abstract":["Today, more than 200 vendors claimed they offered low-code. But do they really? In this post, discover the benefits of low-code and who can deliver them."],"author":["Forsyth, Alexander"],"date":["2021-01"],"title":["Top 5 Benefits of Low-Code"]},"creators":{"author":[{"lastName":"Forsyth","firstName":"Alexander"}]}},{"key":"FOSDEM2016OSCAR","type":"online","fields":{"title":["FOSDEM 2016 - OSCAR: Address the new challenges of open-source software quality"],"url":["https://fosdem.org/2016/schedule/event/oscar/"],"urldate":["2016-02-09"]},"creators":{},"sentenceCased":true},{"key":"fowkesParameterfreeProbabilisticAPI2016","type":"inproceedings","fields":{"acmid":["2950319"],"author":["Fowkes, Jaroslav","Sutton, Charles"],"booktitle":["Proc. 2016 24th ACM SIGSOFT Int. Symp. Found. Softw. Eng."],"date":["2016"],"ids":["Fowkes:2016:PPA:2950290.2950319"],"isbn":["978-1-4503-4218-6"],"keywords":["API mining","sequential pattern mining"],"location":["New York, NY, USA"],"nodoi":["10.1145/2950290.2950319"],"note":["TL;DR \n\nPAM (Probabilistic API Miner), a near parameter-free probabilistic algorithm for mining the most interesting API call patterns, is presented and it is shown that PAM significantly outperforms both MAPO and UPMiner at retrieving relevant API call sequences from GitHub."],"numpages":["12"],"pages":["254–265"],"publisher":["ACM"],"series":["FSE 2016"],"title":["Parameter-free probabilistic API mining across GitHub"],"url":["http://doi.acm.org/10.1145/2950290.2950319"]},"creators":{"author":[{"lastName":"Fowkes","firstName":"Jaroslav"},{"lastName":"Sutton","firstName":"Charles"}]},"sentenceCased":true},{"key":"frakesTermConflationInformation1984","type":"inproceedings","fields":{"author":["Frakes, William B"],"booktitle":["Proc. 7th Annu. Int. ACM SIGIR Conf. Res. Dev. Inf. Retr."],"date":["1984"],"note":["TL;DR \n\nBased on results of two experiments concerned with term conflation for information retrieval, and the CATALOG retrieval system designed utilizing the results of the experiments,Term conflation can be automated in a retrieval system with no average loss of performance, thus allowing easier and user access to the system."],"organization":["British Computer Society"],"pages":["383–389"],"title":["Term conflation for information retrieval"]},"creators":{"author":[{"lastName":"Frakes","firstName":"William B"}]},"sentenceCased":true},{"key":"FrameworkVerificationModel","type":"article","fields":{"title":["A framework for verification of model transformations"]},"creators":{},"sentenceCased":true},{"key":"franceModelDrivenEngineering2012","type":"book","fields":{"date":["2012"],"editor":["France, Robert"],"eventtitle":["MODELS (Conference)"],"isbn":["978-3-642-33665-2"],"keywords":["Computer software","Conference proceedings","Congresses","Development","Model-driven software architecture","Model-integrated computing"],"location":["Berlin ; New York"],"note":["International conference proceedings \n\nThomas A. Henzinger – Jesús Sánchez-Cuadrado, Juan de Lara Esther Guerra – Florian Noyrit, Sébastien Gérard Bran Selic – Fazle Rabbi Wendy MacCaull – Andres J. Ramirez, Betty H.C. Cheng, Nelly Bencomo Pete Sawyer – Germán H. Alférez Vicente Pelechano – François Fouquet, Grégory Nain, Brice Morin, Erwan Daubert Olivier Barais, Markus Scheidgen, Anatolij Zubow, Joachim Fischer Thomas H. Kolbe – Benoit Combemale, Xavier Thirioux Benoit Baudry – Ábel Hegedüs, Ákos Horváth, István Ráth Dániel Varró – Jean-Marie Favre, Ralf Lämmel Andrei Varanovich Quantitative reactive models / Bottom-up meta-modelling: an interactive approach / FacadeMetamodel: masking UML / T-Square: a domain specific language for rapid workflow development / Relaxing claims: coping with uncertainty while evaluating assumptions at tun time / Dynamic evolution of context-aware systems with models at runtime / An Eclipse modelling framework alternative to meet the Models@Runtime requirements / Automated and transparent model fragmentation for persisting large models / Formally defining and iterating infinite models / Query-driven soft interconnection of EMF Models / Modeling the linguistic architecture of software products Rolf-Helge Pfeiffer Andrzej Wąsowski – Carmine Gravino, Michele Risi, Giuseppe Scanniello Genoveffa Tortora – Alexander Reder Alexander Egyed – Kleinner Farias, Alessandro Garcia Carlos Lucena – Lars Hamann, Oliver Hofrichter Martin Gogolla – Julia Schroeter, Malte Lochau Tim Winkelmann – Martin Fagereng Johansen, Øystein Haugen, Franck Fleurey, Anne Grete Eldegard Torbjørn Syversen – Vinay Kulkarni, Souvik Barat Suman Roychoudhury – Azzam Maraee Mira Balaban – Chris Shaver Edward A. Lee Cross-language support mechanisms significantly aid software development / Do professional developers benefit from design pattern documentation?: a replication in the context of source code comprehension / Incremental consistency checking for complex design rules and larger model changes / Evaluating the impact of aspects on inconsistency detection effort: a controlled experiment / On integrating structure and behavior modeling with OCL / Multi-perspectives on feature models / Generating better partial covering arrays by modeling weights on sub-product lines / Towards business application product lines / Inter-association constraints in UML2: comparative analysis, usage recommendations, and modeling guidelines / The Coroutine model of computation Shahar Maoz Yaniv Sa'ar – Adrian Kuhn, Gail C. Murphy C. Albert Thompson – Yu Sun, Jeff Gray, Karlheinz Bulheller Nicolaus von Baillou – Rick Salay, Shige Wang Vivien Suen – Ethan K. Jackson, Wolfram Schulte Nikolaj Bjørner – Mirco Kuhlmann Martin Gogolla – Fabian Büttner, Marina Egea Jordi Cabot – Carlos A. González Jordi Cabot – Donghwan Shin, Eunkyoung Jee Doo-Hwan Bae – El Arbi Aboussoror, Ileana Ober Iulian Ober – Razieh Behjati, Tao Yue Lionel Briand Assume-guarantee scenarios: semantics and synthesis / An Exploratory study of forces and frictions affecting large-scale model-driven development / A Model-driven approach to support engineering changes in industrial robotics software / Managing related models in vehicle control software development / Detecting specification errors in declarative languages with constraints / From UML and OCL to relational logic and back / On verifying ATL transformations using 'off-the-shelf' SMT solvers / ATLTest: a white-box test generation approach for ATL transformations / Empirical evaluation on FBD model-based test coverage criteria using mutation analysis / Seeing errors: model driven simulation trace visualization / A Modeling approach to support the similarity-based reuse of configuration data Yihan Wu, Gang Huang, Hui Song Ying Zhang – Michael Vierhauser, Paul Grünbacher, Wolfgang Heider, Gerald Holl Daniela Lettner – Hajer Saada, Xavier Dolques, Marianne Huchard, Clémentine Nebut Houari Sahraoui – Vincent Aranega, Anne Etien Sebastien Mosser – Gerd Kainz, Christian Buckl Alois Knoll – Gunnar Schulze, Joanna Chimiak-Opoka Birgit Grammel, Stefan Kastenholz Konrad Voigt – Moisés Castelo Branco, Javier Troya, Krzysztof Czarnecki, Jochen Küster Hagen Völzer – Muhammad Zohaib Iqbal, Shaukat Ali, Tao Yue Lionel Briand – Sagar Sunkle Vinay Kulkarni Model driven configuration of fault tolerance solutions for component-based software system / Applying a consistency checking framework for heterogeneous models and artifacts in industrial product lines / Generation of operational transformation rules from examples of model transformations / Using feature model to build model transformation chains / A Generic approach simplifying model-to-model transformation chains / An Approach for synchronizing UML models and narrative text in literate modeling / Model matching for trace link generation in model-driven software development / Matching business process workflows across abstraction levels / Experiences of applying UML/MARTE on three industrial projects / Cost estimation for model-driven engineering Kleinner Farias, Alessandro Garcia, Jon Whittle, Christina Chavez Carlos Lucena – Jorge Aranda, Daniela Damian Arber Borici – Zille Huma, Christian Gerth, Gregor Engels Oliver Juwig – Shaukat Ali, Tao Yue, Lionel Briand Suneth Walawege – James R. Williams, Frank R. Burton, Richard F. Paige Fiona A.C. Polack – Shiva Nejati, Stefano Di Alesio, Mehrdad Sabetzadeh Lionel Briand – Galina Besova, Sven Walther, Heike Wehrheim Steffen Becker – Lionel Briand, Davide Falessi, Shiva Nejati, Mehrdad Sabetzadeh Tao Yue – Andrea Sindico, Marco Di Natale Alberto Sangiovanni-Vincentelli Evaluating the effort of composing design models: a controlled experiment / Transition to model-driven engineering: what Is revolutionary, what remains the same? / Towards an automatic service discovery for UML-based rich service descriptions / A Product line modeling and configuration methodology to support model-based testing: an industrial case study / Sensitivity analysis in model-driven engineering / Modeling and analysis of CPU usage in safety-critical embedded systems to support stress testing / Weaving-based configuration and modular transformation of multi-layer systems / Research-based innovation: a tale of three projects in model-driven engineering / An Industrial system engineering process integrating model driven architecture and model based design"],"number":["7590"],"pagetotal":["828"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"shorttitle":["Model driven engineering languages and systems"],"title":["Model driven engineering languages and systems: 15th International Conference, MODELS 2012, Innsbruck, Austria, September 30-October 5, 2012: Proceedings"]},"creators":{"editor":[{"lastName":"France","firstName":"Robert"}]},"sentenceCased":true},{"key":"franceProvidingSupportModel2007","type":"inproceedings","fields":{"author":["France, Robert","Fleurey, Franck","Reddy, Raghu","Baudry, Benoit","Ghosh, Sudipto"],"booktitle":["Enterp. Distrib. Object Comput. Conf. 2007 EDOC 2007 11th IEEE Int."],"date":["2007"],"note":["TL;DR \n\nThis paper shows how this can be done by extending the UML metamodel with behavior describing symmetric, signature-based composition of UML model elements, and describes an implementation of the metAModel that supports systematic composition ofUML class models."],"pages":["253–253"],"publisher":["IEEE"],"title":["Providing support for model composition in metamodels"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4383998"],"urldate":["2015-09-24"]},"creators":{"author":[{"lastName":"France","firstName":"Robert"},{"lastName":"Fleurey","firstName":"Franck"},{"lastName":"Reddy","firstName":"Raghu"},{"lastName":"Baudry","firstName":"Benoit"},{"lastName":"Ghosh","firstName":"Sudipto"}]},"sentenceCased":true},{"key":"FranceR07","type":"inproceedings","fields":{"langid":["english"],"author":["France, Robert B.","Rumpe, Bernhard"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Int. Conf. Softw. Eng. ISCE 2007 Workshop Future Softw. Eng. FOSE 2007 May 23-25 2007 Minneap. MN USA"],"date":["2007"],"doi":["10.1109/FOSE.2007.14"],"editor":["Briand, Lionel C.","Wolf, Alexander L."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nIt is argued that full realizations of the MDE vision may not be possible in the near to medium-term primarily because of the wicked problems involved, but attempting to realize the vision will provide insights that can be used to significantly reduce the gap between evolving software complexity and the technologies used to manage complexity."],"pages":["37–54"],"publisher":["IEEE Computer Society"],"timestamp":["Thu, 23 Mar 2023 23:58:12 +0100"],"title":["Model-driven development of complex software: A research roadmap"]},"creators":{"author":[{"lastName":"France","firstName":"Robert B."},{"lastName":"Rumpe","firstName":"Bernhard"}],"editor":[{"lastName":"Briand","firstName":"Lionel C."},{"lastName":"Wolf","firstName":"Alexander L."}]},"sentenceCased":true},{"key":"franceRepositoryModelDriven2007","type":"article","fields":{"author":["France, Robert","Bieman, Jim","Cheng, Betty H. C."],"date":["2007"],"doi":["10.1007/978-3-540-69489-2_38"],"journaltitle":["Models Softw. Eng."],"pages":["311–317"],"title":["Repository for Model Driven Development (ReMoDD)"],"volume":["4364"]},"creators":{"author":[{"lastName":"France","firstName":"Robert"},{"lastName":"Bieman","firstName":"Jim"},{"lastName":"Cheng","firstName":"Betty H. C."}]}},{"key":"franchUsingQualityModels2003","type":"article","fields":{"author":["Franch, Xavier","Carvallo, Juan Pablo"],"date":["2003"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nThis work proposes a methodology for building structured quality models that helps solve the lack of structured and widespread descriptions of software packages and the precise statement of quality requirements, and consequently overall package selection and confidence in the result of the process."],"number":["1"],"pages":["34–41"],"title":["Using quality models in software package selection"],"url":["http://ieeexplore.ieee.org/abstract/document/1159027/"],"urldate":["2017-02-25"],"volume":["20"]},"creators":{"author":[{"lastName":"Franch","firstName":"Xavier"},{"lastName":"Carvallo","firstName":"Juan Pablo"}]},"sentenceCased":true},{"key":"fredericksPlanningOptimizationDynamically2019","type":"article","fields":{"abstract":["The large number of possible configurations of modern software-based systems, combined with the large number of possible environmental situations of such systems, prohibits enumerating all adaptation options at design time and necessitates planning at run time to dynamically identify an appropriate configuration for a situation. While numerous planning techniques exist, they typically assume a detailed state-based model of the system and that the situations that warrant adaptations are known. Both of these assumptions can be violated in complex, real-world systems. As a result, adaptation planning must rely on simple models that capture what can be changed (input parameters) and observed in the system and environment (output and context parameters). We therefore propose planning as optimization: the use of optimization strategies to discover optimal system configurations at runtime for each distinct situation that is also dynamically identified at runtime. We apply our approach to CrowdNav, an open-source traffic routing system with the characteristics of a real-world system. We identify situations via clustering and conduct an empirical study that compares Bayesian optimization and two types of evolutionary optimization (NSGA-II and novelty search) in CrowdNav."],"author":["Fredericks, Erik M.","Gerostathopoulos, Ilias","Krupitzer, Christian","Vogel, Thomas"],"date":["2019-06"],"doi":["10.1109/SASO.2019.00010"],"eprint":["1905.01071"],"eprinttype":["arxiv"],"journaltitle":["2019 IEEE 13th Int. Conf. Self-Adapt. Self-Organ. Syst. SASO"],"note":["TL;DR \n\nCrowdNav is identified via clustering and an empirical study that compares Bayesian optimization and two types of evolutionary optimization (NSGA-II and novelty search) in CrowdNav."],"pages":["1–10"],"shorttitle":["Planning as Optimization"],"title":["Planning as Optimization: Dynamically Discovering Optimal Configurations for Runtime Situations"]},"creators":{"author":[{"lastName":"Fredericks","firstName":"Erik M."},{"lastName":"Gerostathopoulos","firstName":"Ilias"},{"lastName":"Krupitzer","firstName":"Christian"},{"lastName":"Vogel","firstName":"Thomas"}]}},{"key":"fredKnowledgeDiscoveryKnowledge2015","type":"book","fields":{"date":["2015"],"editor":["Fred, Ana","Dietz, Jan L. G.","Aveiro, David","Liu, Kecheng","Filipe, Joaquim"],"isbn":["978-3-319-25839-3 978-3-319-25840-9"],"location":["Cham"],"publisher":["Springer International Publishing"],"series":["Communications in Computer and Information Science"],"title":["Knowledge Discovery, Knowledge Engineering and Knowledge Management"],"url":["http://link.springer.com/10.1007/978-3-319-25840-9"],"urldate":["2015-11-10"],"volume":["553"]},"creators":{"editor":[{"lastName":"Fred","firstName":"Ana"},{"lastName":"Dietz","firstName":"Jan L. G."},{"lastName":"Aveiro","firstName":"David"},{"lastName":"Liu","firstName":"Kecheng"},{"lastName":"Filipe","firstName":"Joaquim"}]}},{"key":"freitasQueryingLinkedData2011","type":"inproceedings","fields":{"acmid":["2026017"],"author":["Freitas, André","Oliveira, João Gabriel","O'Riain, Seán","Curry, Edward","Da Silva, João Carlos Pereira"],"booktitle":["Proc. 16th Int. Conf. Nat. Lang. Process. Inf. Syst."],"date":["2011"],"isbn":["978-3-642-22326-6"],"keywords":["linked data","natural language queries"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nThis work focuses on the investigation of a vocabulary independent natural language query mechanism for Linked Data, using an approach based on the combination of entity search, a Wikipediabased semantic relatedness measure and spreading activation."],"numpages":["12"],"pages":["40–51"],"publisher":["Springer-Verlag"],"series":["NLDB'11"],"title":["Querying linked data using semantic relatedness: A vocabulary independent approach"],"url":["http://dl.acm.org/citation.cfm?id=2026011.2026017"]},"creators":{"author":[{"lastName":"Freitas","firstName":"André"},{"lastName":"Oliveira","firstName":"João Gabriel"},{"lastName":"O'Riain","firstName":"Seán"},{"lastName":"Curry","firstName":"Edward"},{"lastName":"Da Silva","firstName":"João Carlos Pereira"}]},"sentenceCased":true},{"key":"freitasTreoBesteffortNatural2011","type":"inproceedings","fields":{"abstract":["Linked Data promises an unprecedented availability of data on the Web. However, this vision comes together with the associated challenges of querying highly heterogeneous and distributed data. In order to query Linked Data on the Web today, end-users need to be aware of which datasets potentially contain the data and the data model behind these datasets. This query paradigm, deeply attached to the traditional perspective of structured queries over databases, does not suit the heterogeneity and scale of the Web, where it is impractical for data consumers to have an a priori understanding of the structure and location of available datasets. This work describes Treo, a best-effort natural language query mechanism for Linked Data, which focuses on the problem of bridging the semantic gap between end-user natural language queries and Linked Datasets."],"author":["Freitas, André","Oliveira, João","O'Riain, Seán","Curry, Edward","Pereira da Silva, João"],"booktitle":["Proc. 16th Int. Conf. Appl. Nat. Lang. Inf. Syst. NLDB 2011 Poster"],"date":["2011"],"editor":["Muñoz, Rafael","Montoyo, Andrés","Métais, Elisabeth"],"isbn":["978-3-642-22326-6"],"keywords":["LEIdataspace","Linked Data","Natural Language Queries","Treo"],"location":["Berlin, Heidelberg"],"mendeley-tags":["LEIdataspace,Linked Data,Natural Language Queries,Treo"],"nodoi":["10.1007/978-3-642-22327-3"],"pages":["286–289"],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture notes in computer science"],"title":["Treo: Best-effort natural language queries over linked data"],"url":["http://www.edwardcurry.org/publications/Freitas_Treo_NLDB_2011.pdf"],"volume":["6716"]},"creators":{"author":[{"lastName":"Freitas","firstName":"André"},{"lastName":"Oliveira","firstName":"João"},{"lastName":"O'Riain","firstName":"Seán"},{"lastName":"Curry","firstName":"Edward"},{"lastName":"Pereira da Silva","firstName":"João"}],"editor":[{"lastName":"Muñoz","firstName":"Rafael"},{"lastName":"Montoyo","firstName":"Andrés"},{"lastName":"Métais","firstName":"Elisabeth"}]},"sentenceCased":true},{"key":"fritsche2020avoiding","type":"article","fields":{"author":["Fritsche, Lars","Kosiol, Jens","Schürr, Andy","Taentzer, Gabriele"],"date":["2020"],"journaltitle":["Int. J. Softw. Tools Technol. Transf."],"pages":["1–34"],"publisher":["Springer"],"title":["Avoiding unnecessary information loss: Correct and efficient model synchronization based on triple graph grammars"]},"creators":{"author":[{"lastName":"Fritsche","firstName":"Lars"},{"lastName":"Kosiol","firstName":"Jens"},{"lastName":"Schürr","firstName":"Andy"},{"lastName":"Taentzer","firstName":"Gabriele"}]},"sentenceCased":true},{"key":"Froger201932","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Ecole des Mines d’Albi, Campus Jarlard, Albi Cedex 09, 81013, France; Iterop, 1B rue Antoine Lavoisier, Colomiers, 31770, France"],"author":["Froger, M.","Bénaben, F.","Truptil, S.","Boissel-Dallier, N."],"correspondence_address1":["Froger, M.; Ecole des Mines d’Albi, Campus Jarlard, France; email: manon.froger@mines-albi.fr"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-23554-3_3"],"editor":["Ferreira J.E., Musaev A., Zhang L.-J."],"isbn":["9783030235536"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 0 \n\nTL;DR \n\nA business-oriented prototype assisting users in getting certifiable specific business processes is presented, detailing the metamodel used to separately model norms and business’ existing procedures and then, the algorithm envisaged to deduce a corresponding cartography of processes."],"pages":["32–47"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Generating personalized and certifiable workflow designs: A prototype"],"volume":["11515 LNCS"]},"creators":{"author":[{"lastName":"Froger","firstName":"M."},{"lastName":"Bénaben","firstName":"F."},{"lastName":"Truptil","firstName":"S."},{"lastName":"Boissel-Dallier","firstName":"N."}],"editor":[{"lastName":"Ferreira J.E.","suffix":"Musaev A.","firstName":"Zhang L.-J."}]},"sentenceCased":true},{"key":"frostChallengesOpportunitiesAutonomous2010","type":"inproceedings","fields":{"author":["Frost, C."],"booktitle":["Front. Eng. Rep. Lead.-Edge Eng. 2010 Symp."],"date":["2010"],"note":["TL;DR \n\nThe autonomous systems community anticipated that the advanced autonomy demonstrated on Deep Space 1 would soon be pervasive, enabling science missions, making spacecraft more resilient, and reducing operational costs."],"title":["Challenges and opportunities for autonomous systems in space"],"url":["http://books.google.com/books?hl=en&lr=&id=2lH3kI2g2yMC&oi=fnd&pg=PA89&dq=%22encounters+an+unplanned-for+situation,+it+stops+and+waits+for+human+help+(e.g.+it%22+%22of+the+implementation+details,+however,+intelligent+autonomous+systems+are%22+%22The+Roomba+user+provides+high-level+goals+(vacuum+the+floor,+but+don%E2%80%99t+vacuum%22+&ots=ErAPABO1Yh&sig=sSQZsesfdEbvr-v9TCuY3WAQkAk"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Frost","firstName":"C."}]},"sentenceCased":true},{"key":"Fu2021","type":"article","fields":{"abstract":["Deep learning-based methods have achieved notable progress in removing blocking artifacts caused by lossy JPEG compression on images. However, most deep learning-based methods handle this task by designing black-box network architectures to directly learn the relationships between the compressed images and their clean versions. These network architectures are always lack of sufficient interpretability, which limits their further improvements in deblocking performance. To address this issue, in this article, we propose a model-driven deep unfolding method for JPEG artifacts removal, with interpretable network structures. First, we build a maximum posterior (MAP) model for deblocking using convolutional dictionary learning and design an iterative optimization algorithm using proximal operators. Second, we unfold this iterative algorithm into a learnable deep network structure, where each module corresponds to a specific operation of the iterative algorithm. In this way, our network inherits the benefits of both the powerful model ability of data-driven deep learning method and the interpretability of traditional model-driven method. By training the proposed network in an end-to-end manner, all learnable modules can be automatically explored to well characterize the representations of both JPEG artifacts and image content. Experiments on synthetic and real-world datasets show that our method is able to generate competitive or even better deblocking results, compared with state-of-the-art methods both quantitatively and qualitatively. IEEE"],"author":["Fu, X.","Wang, M.","Cao, X.","Ding, X.","Zha, Z."],"date":["2021"],"document_type":["Article"],"doi":["10.1109/TNNLS.2021.3083504"],"issn":["2162237X"],"journaltitle":["IEEE Trans. Neural Netw. Learn. Syst."],"note":["cited By 5 \n\nTL;DR \n\nThis article builds a maximum posterior (MAP) model for deblocking using convolutional dictionary learning and design an iterative optimization algorithm using proximal operators, which unfolds into a learnable deep network structure, where each module corresponds to a specific operation of the iterative algorithm."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["A model-driven deep unfolding method for JPEG artifacts removal"]},"creators":{"author":[{"lastName":"Fu","firstName":"X."},{"lastName":"Wang","firstName":"M."},{"lastName":"Cao","firstName":"X."},{"lastName":"Ding","firstName":"X."},{"lastName":"Zha","firstName":"Z."}]},"sentenceCased":true},{"key":"Fukas202219","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["CEUR Workshop Proc."],"affiliation":["Osnabrück University, Lower Saxony, Osnabrück, Germany; German Research Center for Artificial Intelligence, Lower Saxony, Osnabrück, Germany; Strategion GmbH, Lower Saxony, Osnabrück, Germany"],"author":["Fukas, P."],"correspondence_address1":["Fukas, P.; Osnabrück University, Lower Saxony, Germany; email: philipp.fukas@uni-osnabrueck.de"],"date":["2022"],"document_type":["Conference Paper"],"editor":["Looy A.V., Weber B., Rosemann M."],"issn":["16130073"],"keywords":["notion"],"note":["cited By 0"],"pages":["19–27"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"source":["Scopus"],"title":["The management of artificial intelligence: Developing a framework based on the artificial intelligence maturity principle"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130763237&partnerID=40&md5=0470ee8a2332eeaf51d2d7d78d596809"],"volume":["3139"]},"creators":{"author":[{"lastName":"Fukas","firstName":"P."}],"editor":[{"lastName":"Looy A.V.","suffix":"Weber B.","firstName":"Rosemann M."}]},"sentenceCased":true},{"key":"fumarolaDataModelingRelationships","type":"article","fields":{"langid":["english"],"author":["Fumarola, Dr Fabio"],"pages":["45"],"title":["Data Modeling for Relationships Handling and Data Distribution"]},"creators":{"author":[{"lastName":"Fumarola","firstName":"Dr Fabio"}]}},{"key":"FundingTenders","type":"online","fields":{"title":["Funding & tenders"],"url":["https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/myarea/project/813884/program/31045243/organisation/999859511/roles/edit?name=Lowcomote"],"urldate":["2019-10-30"]},"creators":{},"sentenceCased":true},{"key":"FuTLNP22","type":"inproceedings","fields":{"author":["Fu, Michael","Tantithamthavorn, Chakkrit","Le, Trung","Nguyen, Van","Phung, Dinh Q."],"booktitle":["Proc. 30th ACM Jt. Eur. Softw. Eng. Conf. Symp. Found. Softw. Eng. ESECFSE 2022 Singap. Singap. Novemb. 14-18 2022"],"date":["2022"],"note":["TL;DR \n\nVulRepair is proposed, a T5-based automated software vulnerability repair approach that leverages the pre-training and BPE components to address various technical limitations of prior work, and is considerably more accurate than two baseline approaches."],"pages":["935–947"],"publisher":["ACM"],"title":["VulRepair: A T5-based automated software vulnerability repair"]},"creators":{"author":[{"lastName":"Fu","firstName":"Michael"},{"lastName":"Tantithamthavorn","firstName":"Chakkrit"},{"lastName":"Le","firstName":"Trung"},{"lastName":"Nguyen","firstName":"Van"},{"lastName":"Phung","firstName":"Dinh Q."}]},"sentenceCased":true},{"key":"gadepallyBigDAWGManagingHeterogenous","type":"article","fields":{"langid":["english"],"author":["Gadepally, Dr Vijay"],"pages":["48"],"title":["BigDAWG: Managing Heterogenous Data and Streaming"]},"creators":{"author":[{"lastName":"Gadepally","firstName":"Dr Vijay"}]}},{"key":"gainLowcodeAutoMLaugmentedData2021","type":"article","fields":{"langid":["english"],"abstract":["There is a lack of knowledge concerning the low-code autoML (automated machine learning) frameworks that can be used to enrich data for several purposes concerning either data engineering or software engineering. In this paper, 34 autoML frameworks have been reviewed based on the latest commits and augmentation properties of their GitHub content. The PyCaret framework was the result of the review due to requirements concerning adaptability by Google Colaboratory (Colab) and the BI (business intelligence) tool. Finally, the low-code autoMLaugmented data pipeline from raw data to dashboards and low-code apps has been drawn based on the experiments concerned classifications of the \"Census Income\" dataset. The constructed pipeline preferred the same data to be a ground for different reports, dashboards, and applications. However, the constructed low-code autoML-augmented data pipeline contains changeable building blocks such as libraries and visualisations."],"author":["Gain, Ulla","Hotti, Virpi"],"date":["2021-02-01"],"doi":["10.1088/1742-6596/1828/1/012015"],"issn":["1742-6588, 1742-6596"],"journaltitle":["J. Phys.: Conf. Ser."],"note":["TL;DR \n\n34 autoML frameworks have been reviewed based on the latest commits and augmentation properties of their GitHub content and the PyCaret framework was the result of the review due to requirements concerning adaptability by Google Colaboratory and the BI (business intelligence) tool."],"number":["1"],"pages":["012015"],"title":["Low-code AutoML-augmented Data Pipeline – A Review and Experiments"],"volume":["1828"]},"creators":{"author":[{"lastName":"Gain","firstName":"Ulla"},{"lastName":"Hotti","firstName":"Virpi"}]},"sentenceCased":true},{"key":"galassoCodeSophisticationCode2022","type":"article","fields":{"langid":["english"],"abstract":["A typical approach to programming is to first code the main execution scenario, and then focus on filling out alternative behaviors and corner cases. But, almost always, there exist unusual conditions that trigger atypical behaviors, which are hard to predict in program specifications, and are thus often not coded. In this paper, we consider the problem of detecting and recommending such missing behaviors, a task that we call code sophistication. Previous research on coding assistants usually focuses on recommending code fragments based on specifications of the intended behavior. In contrast, code sophistication happens in the absence of a specification, aiming to help developers complete the logic of their programs with missing and unspecified behaviors. We outline the research challenges to this problem and present early results showing how program logic can be completed by leveraging code structure and information about the usage of input parameters."],"author":["Galasso, Jessie","Famelis, Michalis","Sahraoui, Houari"],"date":["2022-01-19"],"eprint":["2201.07674"],"eprintclass":["cs"],"eprinttype":["arxiv"],"ids":["galassoCodeSophisticationCode2022a"],"journaltitle":["ArXiv220107674 Cs"],"keywords":["GOAL_Model-Assistance","TECHNIQUE_GraphConvolutionalNetworks"],"shorttitle":["Code Sophistication"],"title":["Code Sophistication: From Code Recommendation to Logic Recommendation"],"url":["http://arxiv.org/abs/2201.07674"],"urldate":["2022-01-25"]},"creators":{"author":[{"lastName":"Galasso","firstName":"Jessie"},{"lastName":"Famelis","firstName":"Michalis"},{"lastName":"Sahraoui","firstName":"Houari"}]}},{"key":"gallardoModelingCollaborationProtocols2013","type":"article","fields":{"author":["Gallardo, Jesús","Bravo, Crescencio","Redondo, Miguel A.","family=Lara, given=Juan, prefix=de, useprefix=true"],"date":["2013"],"doi":["10.1016/j.jvlc.2012.10.006"],"journaltitle":["J. Vis. Lang. Comput."],"number":["1"],"pages":["10–23"],"title":["Modeling collaboration protocols for collaborative modeling tools: Experiences and applications"],"volume":["24"]},"creators":{"author":[{"lastName":"Gallardo","firstName":"Jesús"},{"lastName":"Bravo","firstName":"Crescencio"},{"lastName":"Redondo","firstName":"Miguel A."},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true}]},"sentenceCased":true},{"key":"GammaitoniK19","type":"article","fields":{"langid":["english"],"author":["Gammaitoni, Loïc","Kelsen, Pierre"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2019"],"doi":["10.1007/S10270-017-0630-9"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["1"],"pages":["213–247"],"timestamp":["Fri, 18 Sep 2020 11:19:23 +0200"],"title":["F-alloy: A relational model transformation language based on alloy"],"volume":["18"]},"creators":{"author":[{"lastName":"Gammaitoni","firstName":"Loïc"},{"lastName":"Kelsen","firstName":"Pierre"}]},"sentenceCased":true},{"key":"ganserStagedModelEvolution2015","type":"article","fields":{"langid":["english"],"author":["Ganser, Andreas","Lichter, Horst","Roth, Alexander","Rumpe, Bernhard"],"date":["2015-11-25"],"doi":["10.1007/s11219-015-9298-y"],"issn":["0963-9314, 1573-1367"],"journaltitle":["Softw. Qual. J."],"note":["TL;DR \n\nThis study proposes an approach for model evolution in UML model libraries that differs from general model evolution, since it is aimless and triggered by new external requirements."],"title":["Staged model evolution and proactive quality guidance for model libraries"]},"creators":{"author":[{"lastName":"Ganser","firstName":"Andreas"},{"lastName":"Lichter","firstName":"Horst"},{"lastName":"Roth","firstName":"Alexander"},{"lastName":"Rumpe","firstName":"Bernhard"}]},"sentenceCased":true},{"key":"Gao20182627","type":"article","fields":{"abstract":["In this letter, we propose a model-driven deep learning (DL) approach that combines DL with the expert knowledge to replace the existing orthogonal frequency-division multiplexing receiver in wireless communications. Different from the data-driven fully connected deep neural network (FC-DNN) method, we adopt the block-by-block signal processing method that divides the receiver into channel estimation subnet and signal detection subnet. Each subnet is constructed by a DNN and uses the existing simple and traditional solution as initialization. The proposed model-driven DL receiver offers more accurate channel estimation comparing with the linear minimum mean-squared error method and exhibits higher data recovery accuracy comparing with the existing methods and FC-DNN. Simulation results further demonstrate the robustness of the proposed approach in terms of signal-to-noise ratio and its superiority to the FC-DNN approach in the computational complexities or the memory usage. © 1997-2012 IEEE."],"art_number":["8509622"],"author":["Gao, X.","Jin, S.","Wen, C.-K.","Li, G.Y."],"coden":["ICLEF"],"date":["2018"],"document_type":["Article"],"doi":["10.1109/LCOMM.2018.2877965"],"issn":["10897798"],"journaltitle":["IEEE Commun. Lett."],"note":["cited By 113 \n\nTL;DR \n\nThe proposed model-driven DL receiver offers more accurate channel estimation compared with the linear minimum mean-squared error method and exhibits higher data recovery accuracy comparing with the existing methods and FC-DNN."],"number":["12"],"pages":["2627–2630"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["ComNet: Combination of deep learning and expert knowledge in OFDM receivers"],"volume":["22"]},"creators":{"author":[{"lastName":"Gao","firstName":"X."},{"lastName":"Jin","firstName":"S."},{"lastName":"Wen","firstName":"C.-K."},{"lastName":"Li","firstName":"G.Y."}]},"sentenceCased":true},{"key":"GAO2021102556","type":"article","fields":{"abstract":["To improve the efficiency, developers tend to use APIs to avoid reinventing wheels in the development of Apps. However, there are thousands of APIs for various purposes, so it is difficult for developers to identify suitable APIs according to the functionalities to be realized. App stores manage millions of products, which embody the experience and wisdom of developers, and they provide valuable data resource for solving this problem. By summarizing the API usage for the same or similar functionalities in Apps, reusable knowledge can be mined for the API recommendation. In this paper, we utilize the data resource in App stores and provide an API recommendation method for the development of Android Apps. Firstly, by using UI elements as the bridge, we establish mapping relationships between functionalities and APIs. Secondly, we build a framework to describe functionalities of Apps in the same category, and utilize relationships between functionalities and APIs to construct the API knowledge for each node in the framework. Thirdly, we identify nodes according to queried features and show the API knowledge to developers by giving recommendation lists. We conducted experiments based on Google Play, and the result shows that our method has a good recommendation performance."],"author":["Gao, Shanquan","Liu, Lei","Liu, Yuzhou","Liu, Huaxiao","Wang, Yihui"],"date":["2021"],"doi":["10.1016/j.scico.2020.102556"],"issn":["0167-6423"],"journaltitle":["Sci. Comput. Program."],"keywords":["API recommendation","App store mining","Feature extraction","Reusable knowledge","UI analysis"],"pages":["102556"],"title":["API recommendation for the development of Android App features based on the knowledge mined from App stores"],"volume":["202"]},"creators":{"author":[{"lastName":"Gao","firstName":"Shanquan"},{"lastName":"Liu","firstName":"Lei"},{"lastName":"Liu","firstName":"Yuzhou"},{"lastName":"Liu","firstName":"Huaxiao"},{"lastName":"Wang","firstName":"Yihui"}]},"sentenceCased":true},{"key":"Gao2021767","type":"article","fields":{"abstract":["Abstract - Action recognition is a popular research topic in the computer vision and machine learning domains. Although many action recognition methods have been proposed, only a few researchers have focused on cross-domain few-shot action recognition, which must often be performed in real security surveillance. Since the problems of action recognition, domain adaptation, and few-shot learning need to be simultaneously solved, the cross-domain few-shot action recognition task is a challenging problem. To solve these issues, in this work, we develop a novel end-to-end pairwise attentive adversarial spatiotemporal network (PASTN) to perform the cross-domain few-shot action recognition task, in which spatiotemporal information acquisition, few-shot learning, and video domain adaptation are realised in a unified framework. Specifically, the Resnet-50 network is selected as the backbone of the PASTN, and a 3D convolution block is embedded in the top layer of the 2D CNN (ResNet-50) to capture the spatiotemporal representations. Moreover, a novel attentive adversarial network architecture is designed to align the spatiotemporal dynamics actions with higher domain discrepancies. In addition, the pairwise margin discrimination loss is designed for the pairwise network architecture to improve the discrimination of the learned domain-invariant spatiotemporal feature. The results of extensive experiments performed on three public benchmarks of the cross-domain action recognition datasets, including SDAI Action I, SDAI Action II and UCF50-OlympicSport, demonstrate that the proposed PASTN can significantly outperform the state-of-the-art cross-domain action recognition methods in terms of both the accuracy and computational time. Even when only two labelled training samples per category are considered in the office1 scenario of the SDAI Action I dataset, the accuracy of the PASTN is improved by 6.1%, 10.9%, 16.8%, and 14% compared to that of the TA³N , TemporalPooling, I3D, and P3D methods, respectively. © 1992-2012 IEEE."],"art_number":["9268986"],"author":["Gao, Z.","Guo, L.","Guan, W.","Liu, A.-A.","Ren, T.","Chen, S."],"author_keywords":["action recognition; attentive adversarial network; Cross-domain learning; few-shot; pairwise margin discrimination loss; TR3D"],"coden":["IIPRE"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/TIP.2020.3038372"],"issn":["10577149"],"journaltitle":["IEEE Trans. Image Process."],"keywords":["article","artificial intelligence","Artificial intelligence","Australia","case report","China","clinical article","computer vision","Computer vision","convolutional neural network","education","Electrical and information engineerings","human","human experiment","information technology","learning","male","Ministry of Education","National natural science foundation of chinas","natural science","Network architecture","Security surveillance","software","Software engineering","Spatio temporal features","Spatio-temporal dynamics","Spatiotemporal information","Spatiotemporal networks","Supercomputers","videorecording"],"note":["cited By 37 \n\nTL;DR \n\nThe results of extensive experiments performed on three public benchmarks of the cross-domain action recognition datasets demonstrate that the proposed PASTN can significantly outperform the state-of-the-art cross- domain action recognition methods in terms of both the accuracy and computational time."],"pages":["767–782"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["A pairwise attentive adversarial spatiotemporal network for cross-domain few-shot action recognition-R2"],"volume":["30"]},"creators":{"author":[{"lastName":"Gao","firstName":"Z."},{"lastName":"Guo","firstName":"L."},{"lastName":"Guan","firstName":"W."},{"lastName":"Liu","firstName":"A.-A."},{"lastName":"Ren","firstName":"T."},{"lastName":"Chen","firstName":"S."}]},"sentenceCased":true},{"key":"gaoCollaborativeFilteringRecommendation2019","type":"article","fields":{"langid":["english"],"abstract":["With the popularization of Internet of Things (IOT) technology, a large number of multi-source heterogeneous data are constantly generated and collected by cloud platforms, which indicates that the problem of large data in IOT has become increasingly prominent, especially for massive tags and information in IOT which is urgent to use appropriate data mining algorithms to mine the value of these data. A collaborative filtering recommendation algorithm based on multi-information source fusion (CFR-MIF) is proposed where a feature vector and time weight function are introduced to improve the accuracy of top-N recommendation. It can conveniently and effectively process the IoT data, and furthermore integrate, manage and store the massive data collected from different industries and data formats. Besides, It also provides data mining services in the whole IoT realizing prediction and decision-making, which reverses control these sensor networks, so as to control the movement and development process of objective in the Internet of Things. The experimental results based on DeviceLens 1M data set show that the proposed algorithm greatly improves the accuracy of recommendation results, recall rate and F1 value compared with other advanced algorithms."],"author":["Gao, Ying","Ran, Lingxi"],"date":["2019"],"doi":["10.1109/ACCESS.2019.2935224"],"issn":["2169-3536"],"journaltitle":["IEEE Access"],"note":["TL;DR \n\nA collaborative filtering recommendation algorithm based on multi-information source fusion (CFR-MIF) is proposed where a feature vector and time weight function are introduced to improve the accuracy of top-N recommendation."],"pages":["123583–123591"],"title":["Collaborative Filtering Recommendation Algorithm for Heterogeneous Data Mining in the Internet of Things"],"volume":["7"]},"creators":{"author":[{"lastName":"Gao","firstName":"Ying"},{"lastName":"Ran","firstName":"Lingxi"}]}},{"key":"gaoCollaborativeLearningBasedIndustrial2020","type":"article","fields":{"langid":["english"],"abstract":["The industrial Internet of things (IIoT), a new computing mode in Industry 4.0, is deployed to connect IoT devices and use communication technology to respond to control commands and handle industrial data. IIoT is typically employed to improve the efficiency of computing and sensing and can be used in many scenarios, such as intelligent manufacturing and video surveillance. To build an IIoT system, we need a collection of software to manage and monitor each system component when there are large-scale devices. Application programming interface (API) is an effective way to invoke public services provided by different platforms. Developers can invoke different APIs to operate IoT devices without knowing the implementation process. We can design a workflow to configure how and when to invoke target APIs. Thus, APIs are a powerful tool for rapidly developing industrial systems. However, the increasing number of APIs exacerbates the problem of finding suitable APIs. Current related recommendation methods have defects. For example, most existing methods focus on the relation between users and APIs but neglect the valuable relations among the users or APIs themselves. To address these problems, this article studies implicit knowledge in IIoT by using collaborative learning techniques. Considering the increased dimensions and dynamics of IoT devices, we explore the possible relationships between users and between APIs. We enhance the matrix factorization (MF) model with the mined implicit knowledge that are implicit relationships on both sides. We build an ensemble model by using all implicit knowledge. We conduct experiments on a collected real-world dataset and simulate industrial system scenarios. The experimental results verify the effectiveness and superiority of the proposed models."],"author":["Gao, Honghao","Qin, Xi","Barroso, Ramon J. Duran","Hussain, Walayat","Xu, Yueshen","Yin, Yuyu"],"date":["2020"],"doi":["10.1109/TETCI.2020.3023155"],"issn":["2471-285X"],"journaltitle":["IEEE Trans. Emerg. Top. Comput. Intell."],"pages":["1–11"],"shorttitle":["Collaborative Learning-Based Industrial IoT API Recommendation for Software-Defined Devices"],"title":["Collaborative Learning-Based Industrial IoT API Recommendation for Software-Defined Devices: The Implicit Knowledge Discovery Perspective"]},"creators":{"author":[{"lastName":"Gao","firstName":"Honghao"},{"lastName":"Qin","firstName":"Xi"},{"lastName":"Barroso","firstName":"Ramon J. Duran"},{"lastName":"Hussain","firstName":"Walayat"},{"lastName":"Xu","firstName":"Yueshen"},{"lastName":"Yin","firstName":"Yuyu"}]}},{"key":"garavelPreface2022","type":"inproceedings","fields":{"langid":["english"],"author":["Garavel, H.","family=Lara, given=J., prefix=de, useprefix=true","Molina, P.J.","Paige, R.","family=Ruscio, given=D., prefix=di, useprefix=true","Wimmer, M.","Barmpis, K.","Boronat, A.","Boubeta-Puig, J.","Bousse, E.","Le Calvar, T.","García-Domínguez, A.","Hinkel, G.","Horvath, A.","Rensink, A.","Cuadrado, J.S.","Varró, G.","Wei, R."],"booktitle":["CEUR Workshop Proc."],"date":["2022"],"editor":["Boronat A., Garcia-Dominguez A., Hinkel G."],"ids":["garavelPreface2022a,garavelPreface2022b,garavelPreface2022c"],"issn":["16130073"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0"],"publisher":["CEUR-WS"],"title":["Preface"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125368424&partnerID=40&md5=9c5143fc3bae825a245d87831a19c12d"],"volume":["3089"]},"creators":{"author":[{"lastName":"Garavel","firstName":"H."},{"lastName":"Lara","firstName":"J.","prefix":"de","useprefix":true},{"lastName":"Molina","firstName":"P.J."},{"lastName":"Paige","firstName":"R."},{"lastName":"Ruscio","firstName":"D.","prefix":"di","useprefix":true},{"lastName":"Wimmer","firstName":"M."},{"lastName":"Barmpis","firstName":"K."},{"lastName":"Boronat","firstName":"A."},{"lastName":"Boubeta-Puig","firstName":"J."},{"lastName":"Bousse","firstName":"E."},{"lastName":"Le Calvar","firstName":"T."},{"lastName":"García-Domínguez","firstName":"A."},{"lastName":"Hinkel","firstName":"G."},{"lastName":"Horvath","firstName":"A."},{"lastName":"Rensink","firstName":"A."},{"lastName":"Cuadrado","firstName":"J.S."},{"lastName":"Varró","firstName":"G."},{"lastName":"Wei","firstName":"R."}],"editor":[{"lastName":"Boronat A.","suffix":"Garcia-Dominguez A.","firstName":"Hinkel G."}]}},{"key":"garcesEndtoendFinegrainedTraceability","type":"article","fields":{"langid":["english"],"author":["Garces, Victor Guana"],"pages":["155"],"title":["End-to-end Fine-grained Traceability Analysis in Model Transformations and Transformation Chains"]},"creators":{"author":[{"lastName":"Garces","firstName":"Victor Guana"}]},"sentenceCased":true},{"key":"garcia_lightweight_2018","type":"article","fields":{"abstract":["The number of malicious Android apps is increasing rapidly. Android malware can damage or alter other files or settings, install additional applications, and so on. To determine such behaviors, a security analyst can significantly benefit from identifying the family to which an Android malware belongs rather than only detecting if an app is malicious. Techniques for detecting Android malware, and determining their families, lack the ability to handle certain obfuscations that aim to thwart detection. Moreover, some prior techniques face scalability issues, preventing them from detecting malware in a timely manner. To address these challenges, we present a novel machine-learning-based Android malware detection and family identification approach, RevealDroid, that operates without the need to perform complex program analyses or to extract large sets of features. Specifically, our selected features leverage categorized Android API usage, reflection-based features, and features from native binaries of apps. We assess RevealDroid for accuracy, efficiency, and obfuscation resilience using a large dataset consisting of more than 54,000 malicious and benign apps. Our experiments show that RevealDroid achieves an accuracy of 98% in detection of malware and an accuracy of 95% in determination of their families. We further demonstrate RevealDroid’s superiority against state-of-the-art approaches."],"author":["Garcia, Joshua","Hammad, Mahmoud","Malek, Sam"],"date":["2018-01"],"doi":["10.1145/3162625"],"issn":["1049-331X"],"journaltitle":["ACM Trans. Softw. Eng. Methodol."],"keywords":["Android malware","lightweight","machine learning","native code","obfuscation","reflection"],"number":["3"],"pages":["11:1–11:29"],"title":["Lightweight, Obfuscation-Resilient Detection and Family Identification of Android Malware"],"volume":["26"]},"creators":{"author":[{"lastName":"Garcia","firstName":"Joshua"},{"lastName":"Hammad","firstName":"Mahmoud"},{"lastName":"Malek","firstName":"Sam"}]}},{"key":"garcia-dominguezStresstestingRemoteModel2017","type":"article","fields":{"langid":["english"],"abstract":["Recent research in scalable model-driven engineering now allows very large models to be stored and queried. Due to their size, rather than transferring such models over the network in their entirety, it is typically more efficient to access them remotely using networked services (e.g. model repositories, model indexes). Little attention has been paid so far to the nature of these services, and whether they remain responsive with an increasing number of concurrent clients. This paper extends a previous empirical study on the impact of certain key decisions on the scalability of concurrent model queries on two domains, using an Eclipse Connected Data Objects model repository, four configurations of the Hawk model index and a Neo4j-based configuration of the NeoEMF model store. The study evaluates the impact of the network protocol, the API design, the caching layer, the query language and the type of database and analyses the reasons for their varying levels of performance. The design of the API was shown to make a bigger difference compared to the network protocol (HTTP/TCP) used. Where available, the query-specific indexed and derived attributes in Hawk outperformed the comprehensive generic caching in CDO. Finally, the results illustrate the still ongoing evolution of graph databases: two tools using different versions of the same backend had very different performance, with one slower than CDO and the other faster than it."],"author":["Garcia-Dominguez, Antonio","Barmpis, Konstantinos","Kolovos, Dimitrios S.","Wei, Ran","Paige, Richard F."],"date":["2017-06-30"],"doi":["10.1007/s10270-017-0606-9"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"pages":["1–29"],"title":["Stress-testing remote model querying APIs for relational and graph-based stores"]},"creators":{"author":[{"lastName":"Garcia-Dominguez","firstName":"Antonio"},{"lastName":"Barmpis","firstName":"Konstantinos"},{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"Wei","firstName":"Ran"},{"lastName":"Paige","firstName":"Richard F."}]},"sentenceCased":true},{"key":"gargMUDABlueAutomaticCategorization2004","type":"article","fields":{"address":["Los Alamitos, CA, USA"],"author":["Garg, Pankaj K.","Kawaguchi, Shinji","Matsushita, Makoto","Inoue, Katsuro"],"date":["2004"],"issn":["1530-1362"],"journaltitle":["2013 20th Asia-Pac. Softw. Eng. Conf. APSEC"],"nodoi":["doi.ieeecomputersociety.org/10.1109/APSEC.2004.69"],"pages":["184–193"],"publisher":["IEEE Computer Society"],"title":["MUDABlue: An automatic categorization system for open source repositories"]},"creators":{"author":[{"lastName":"Garg","firstName":"Pankaj K."},{"lastName":"Kawaguchi","firstName":"Shinji"},{"lastName":"Matsushita","firstName":"Makoto"},{"lastName":"Inoue","firstName":"Katsuro"}]},"sentenceCased":true},{"key":"Garitselov2012316","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc IEEE Int Conf VLSI Des"],"affiliation":["Nano-Systems Design Laboratory, University of North Texas, Denton, TX, United States; Department of Computer Science and Engineering, University of North Texas, Denton, TX, United States; Department of Engineering Technology, University of North Texas, Denton, TX, United States"],"art_number":["6167771"],"author":["Garitselov, O.","Mohanty, S.P.","Kougianos, E."],"coden":["PIVDE"],"correspondence_address1":["Garitselov, O.; Nano-Systems Design Laboratory, , Denton, TX, United States; email: omg0006@unt.edu"],"date":["2012"],"document_type":["Conference Paper"],"doi":["10.1109/VLSID.2012.90"],"isbn":["978-0-7695-4638-4"],"issn":["10639667"],"note":["cited By 12 \n\nTL;DR \n\nThis paper presents non-polynomial metamodels (surrogate models) using neural networks to reduce the design optimization time of complex nano-CMOS circuit with no sacrifice on accuracy."],"pages":["316–321"],"series":["Proceedings of the IEEE International Conference on VLSI Design"],"source":["Scopus"],"title":["Fast-accurate non-polynomial metamodeling for nano-CMOS PLL design optimization"]},"creators":{"author":[{"lastName":"Garitselov","firstName":"O."},{"lastName":"Mohanty","firstName":"S.P."},{"lastName":"Kougianos","firstName":"E."}]},"sentenceCased":true},{"key":"Garitselov2012580","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - Int. Symp. Qual. Electron. Des., ISQED"],"affiliation":["NanoSystems Design Laboratory, University of North Texas, Denton, TX, United States; Department of Computer Science and Engineering, University of North Texas, Denton, TX, United States; Department of Engineering Technology, University of North Texas, Denton, TX, United States"],"art_number":["6187552"],"author":["Garitselov, O.","Mohanty, S.P.","Kougianos, E.","Okobiah, O."],"correspondence_address1":["Garitselov, O.; NanoSystems Design Laboratory, , Denton, TX, United States; email: omg0006@unt.edu"],"date":["2012"],"document_type":["Conference Paper"],"doi":["10.1109/ISQED.2012.6187552"],"isbn":["978-1-4673-1036-9"],"issn":["19483287"],"note":["cited By 0 \n\nTL;DR \n\nA novel ultra-fast design flow that uses memetic-based optimization algorithms over neural-network based non-polynomial metamodels for design-space exploration and achieves optimal design to two different wireless specifications, WiMax and MMDS is proposed."],"pages":["580–585"],"series":["Proceedings - International Symposium on Quality Electronic Design, ISQED"],"source":["Scopus"],"title":["Metamodel-assisted ultra-fast memetic optimization of a PLL for WiMax and MMDS applications"]},"creators":{"author":[{"lastName":"Garitselov","firstName":"O."},{"lastName":"Mohanty","firstName":"S.P."},{"lastName":"Kougianos","firstName":"E."},{"lastName":"Okobiah","firstName":"O."}]},"sentenceCased":true},{"key":"Garitselov2014221","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Annu. Precis Time Time Interval Syst. Appl. Meet., PTTI"],"affiliation":["Spectracom, Rochester, NY, United States"],"author":["Garitselov, O.","Sohn, D."],"date":["2014"],"document_type":["Conference Paper"],"isbn":["978-1-63439-794-0"],"issn":["23332085"],"note":["cited By 1 \n\nTL;DR \n\nA GNSS-receiver-independent solution that is added to the disciplining algorithm of a Global Positioning System Disciplined Oscillator (GPSDO) System in order to detect and filter abnormalities without introduction of any additional hardware to the timing system."],"pages":["221–227"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings of the Annual Precise Time and Time Interval Systems and Applications Meeting, PTTI"],"source":["Scopus"],"title":["Metamodel-assisted disciplining algorithm for detecting spoofed GNSS time signals"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84943552646&partnerID=40&md5=25e8f3479adee4ec76849112cfa3446f"],"volume":["2014-January"]},"creators":{"author":[{"lastName":"Garitselov","firstName":"O."},{"lastName":"Sohn","firstName":"D."}]},"sentenceCased":true},{"key":"garousiGuidelinesIncludingGrey2019","type":"article","fields":{"langid":["english"],"author":["Garousi, Vahid","Felderer, Michael","Mäntylä, Mika V."],"date":["2019-02"],"doi":["10.1016/j.infsof.2018.09.006"],"ids":["garousiGuidelinesIncludingGrey2019a"],"issn":["09505849"],"journaltitle":["Information and Software Technology"],"pages":["101–121"],"title":["Guidelines for including grey literature and conducting multivocal literature reviews in software engineering"],"volume":["106"]},"creators":{"author":[{"lastName":"Garousi","firstName":"Vahid"},{"lastName":"Felderer","firstName":"Michael"},{"lastName":"Mäntylä","firstName":"Mika V."}]},"sentenceCased":true},{"key":"GASPARIC2017236","type":"article","fields":{"abstract":["Context A set of algorithms exist to generate integrated development environment (IDE) command recommendations. The recommendations are aimed at improving software developer’s interaction with an IDE. Even though the interface is a critical element of every recommender system, we are not aware of any existing graphical user interface to present such recommendations. Objective This paper describes and evaluates a novel design of a graphical user interface to recommend commands within an IDE. The interface contains a description of the suggested command, an explanation of why the command is recommended, and a command usage example. Method The proposed design is based on the analysis of guidelines identified in the literature. Its acceptance and usability were evaluated through a user study with 36 software developers and semi-structured interviews with 11 software developers. Results The results indicate that the suggested interface is well accepted, but it can be further improved. Through the interviews and the implementation of the interface, we identified a series of requirements important for the development of future IDE command recommender systems. Conclusions This paper shows that a convenient graphical user interface is critical to achieve high acceptance of IDE command recommendations. Our work also illustrates steps useful for undertaking user studies related to IDE command recommendations in a practical setting without human intervention. A future step is to evaluate the interface within the business environment, where recommendations are generated and presented in an IDE used by practicing software developers as part of their normal workday."],"author":["Gasparic, Marko","Janes, Andrea","Ricci, Francesco","Murphy, Gail C.","Gurbanov, Tural"],"date":["2017"],"doi":["10.1016/j.infsof.2017.08.006"],"issn":["0950-5849"],"journaltitle":["Inf. Softw. Technol."],"keywords":["Command","Functionality","Integrated development environment","Recommender system","Software development","User interface"],"pages":["236–255"],"title":["A graphical user interface for presenting integrated development environment command recommendations: Design, evaluation, and implementation"],"volume":["92"]},"creators":{"author":[{"lastName":"Gasparic","firstName":"Marko"},{"lastName":"Janes","firstName":"Andrea"},{"lastName":"Ricci","firstName":"Francesco"},{"lastName":"Murphy","firstName":"Gail C."},{"lastName":"Gurbanov","firstName":"Tural"}]},"sentenceCased":true},{"key":"gasparicWhatRecommendationSystems2016","type":"article","fields":{"acmid":["2896211"],"address":["New York, NY, USA"],"author":["Gasparic, Marko","Janes, Andrea"],"date":["2016-03"],"issn":["0164-1212"],"issue_date":["March 2016"],"journaltitle":["J. Syst. Softw."],"keywords":["recommendation systems","Systematic literature review"],"nodoi":["10.1016/j.jss.2015.11.036"],"number":["C"],"numpages":["13"],"pages":["101–113"],"publisher":["Elsevier Science Inc."],"title":["What recommendation systems for software engineering recommend"],"url":["http://dx.doi.org/10.1016/j.jss.2015.11.036"],"volume":["113"]},"creators":{"author":[{"lastName":"Gasparic","firstName":"Marko"},{"lastName":"Janes","firstName":"Andrea"}]},"sentenceCased":true},{"key":"gasparicWhatRecommendationSystems2016a","type":"article","fields":{"langid":["english"],"abstract":["A recommendation system for software engineering (RSSE) is a software application that provides information items estimated to be valuable for a software engineering task in a given context. Present the results of a systematic literature review to reveal the typical functionality offered by existing RSSEs, research gaps, and possible research directions. We evaluated 46 papers studying the benefits, the data requirements, the information and recommendation types, and the effort requirements of RSSE systems. We include papers describing tools that support source code related development published between 2003 and 2013. The results show that RSSEs typically visualize source code artifacts. They aim to improve system quality, make the development process more efficient and less expensive, lower developer’s cognitive load, and help developers to make better decisions. They mainly support reuse actions and debugging, implementation, and maintenance phases. The majority of the systems are reactive. Unexploited opportunities lie in the development of recommender systems outside the source code domain. Furthermore, current RSSE systems use very limited context information and rely on simple models. Context-adapted and proactive behavior could improve the acceptance of RSSE systems in practice."],"author":["Gasparic, Marko","Janes, Andrea"],"date":["2016-03"],"issn":["01641212"],"journaltitle":["J. Syst. Softw."],"nodoi":["10.1016/j.jss.2015.11.036"],"pages":["101–113"],"shorttitle":["What recommendation systems for software engineering recommend"],"title":["What recommendation systems for software engineering recommend: A systematic literature review"],"url":["https://linkinghub.elsevier.com/retrieve/pii/S0164121215002605"],"urldate":["2019-06-13"],"volume":["113"]},"creators":{"author":[{"lastName":"Gasparic","firstName":"Marko"},{"lastName":"Janes","firstName":"Andrea"}]},"sentenceCased":true},{"key":"Ge:2010_catalog_coverage","type":"inproceedings","fields":{"acmid":["1864761"],"author":["Ge, Mouzhi","Delgado-Battenfeld, Carla","Jannach, Dietmar"],"booktitle":["Proc. Fourth ACM Conf. Recomm. Syst."],"date":["2010"],"isbn":["978-1-60558-906-0"],"keywords":["coverage","evaluation metric","recommender system","serendipity"],"location":["New York, NY, USA"],"nodoi":["10.1145/1864708.1864761"],"note":["TL;DR \n\nIt is argued that the new ways of measuring coverage and serendipity reflect the quality impression perceived by the user in a better way than previous metrics thus leading to enhanced user satisfaction."],"numpages":["4"],"pages":["257–260"],"pagetotal":["4"],"publisher":["ACM"],"series":["RecSys '10"],"title":["Beyond accuracy: Evaluating recommender systems by coverage and serendipity"],"url":["http://doi.acm.org/10.1145/1864708.1864761"]},"creators":{"author":[{"lastName":"Ge","firstName":"Mouzhi"},{"lastName":"Delgado-Battenfeld","firstName":"Carla"},{"lastName":"Jannach","firstName":"Dietmar"}]},"sentenceCased":true},{"key":"geDataMiningAnalytics2017","type":"article","fields":{"langid":["english"],"abstract":["Data mining and analytics have played an important role in knowledge discovery and decision making/supports in the process industry over the past several decades. As a computational engine to data mining and analytics, machine learning serves as basic tools for information extraction, data pattern recognition and predictions. From the perspective of machine learning, this paper provides a review on existing data mining and analytics applications in the process industry over the past several decades. The state-of-the-art of data mining and analytics are reviewed through eight unsupervised learning and ten supervised learning algorithms, as well as the application status of semi-supervised learning algorithms. Several perspectives are highlighted and discussed for future researches on data mining and analytics in the process industry."],"author":["Ge, Zhiqiang","Song, Zhihuan","Ding, Steven X.","Huang, Biao"],"date":["2017"],"doi":["10.1109/ACCESS.2017.2756872"],"issn":["2169-3536"],"journaltitle":["IEEE Access"],"note":["<b>Blue Annotations (11/2/2022, 09:06:52)</b> \n\n\"Data mining and analytics have played an important role in knowledge discovery and decision making/supports in the process industry over the past several decades\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=1\">Ge et al 2017:20590</a>) \n\n\"information extraction, data pattern recognition and predictions\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=1\">Ge et al 2017:20590</a>) \n\n\"existing data mining and analytics applications\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=1\">Ge et al 2017:20590</a>) \n\n\"future researches on data mining and analytics in the process industry\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=1\">Ge et al 2017:20590</a>) \n\n\"European Union proposed 20-20-20 goals to achieve a sustainable future, which means 20% increase in energy efciency, 20% reduction of CO2 emissions, and 20% renewables by 2020\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=1\">Ge et al 2017:20590</a>) \n\n\"intelligence into industrial manufacturing process\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=1\">Ge et al 2017:20590</a>) \n\n\"develop smart factories for producing smart products\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=1\">Ge et al 2017:20590</a>) \n\n\"data mining and analytics may serve as a basic tool to promote the process industry from machine automation to information automation and then to knowledge automation\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=1\">Ge et al 2017:20590</a>) \n\n\"data-driven process modeling, monitoring, prediction and control have received much attention in recent years\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=1\">Ge et al 2017:20590</a>) \n\n\"data have rarely been used for detailed analyses, which are instead only used for routinely technical checks and process log fulllments\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=1\">Ge et al 2017:20590</a>) \n\n\"analyzing the patterns of process data and relationships among variables\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=1\">Ge et al 2017:20590</a>) \n\n\"the main aim of data mining and data analyses is to extract useful information from process data, and transfer it to effective knowledge for improvement of understanding and decision supports of the process.\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=2\">Ge et al 2017:20591</a>) \n\n\"four different types of machine learning algorithms\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=2\">Ge et al 2017:20591</a>) \n\n\"the study of pattern recognition and computational learning theory in arti- cial intelligence\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=2\">Ge et al 2017:20591</a>) \n\n\"theory of probability and statistics also plays a very important role in modern machine learning\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=2\">Ge et al 2017:20591</a>) \n\n\"Field of study that gives computers the ability to learn without being explicitly programmed\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=2\">Ge et al 2017:20591</a>) \n\n\"A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=2\">Ge et al 2017:20591</a>) \n\n\"there exists no such a report that details data mining and analytics from the viewpoint of machine learning, although the terminology has been mentioned many times in various papers and books.\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=2\">Ge et al 2017:20591</a>) \n\n\"section IV, some new perspectives on the topic of machine learning applications in the process industry are presented\" (<a href=\"zotero://open-pdf/library/items/8DHPJGXH?page=2\">Ge et al 2017:20591</a>)"],"pages":["20590–20616"],"shorttitle":["Data Mining and Analytics in the Process Industry"],"title":["Data Mining and Analytics in the Process Industry: The Role of Machine Learning"],"volume":["5"]},"creators":{"author":[{"lastName":"Ge","firstName":"Zhiqiang"},{"lastName":"Song","firstName":"Zhihuan"},{"lastName":"Ding","firstName":"Steven X."},{"lastName":"Huang","firstName":"Biao"}]}},{"key":"GeneralizedAutomaticClustering","type":"online","fields":{"title":["A generalized automatic clustering algorithm in a multiobjective framework"],"url":["http://www.sciencedirect.com/science/article/pii/S1568494612003493"],"urldate":["2015-05-07"]},"creators":{},"sentenceCased":true},{"key":"generoBuildingMeasurebasedPrediction2007","type":"article","fields":{"author":["Genero, Marcela","Manso, Esperanza","Visaggio, Aaron","Canfora, Gerardo","Piattini, Mario"],"date":["2007"],"doi":["10.1007/s10664-007-9038-4"],"journaltitle":["Empir. Softw. Eng."],"note":["TL;DR \n\nResults obtained from a controlled experiment and a replica support the idea that useful prediction models for class diagrams understandability and modifiability can be built on the basis of early measures, in particular, measures that capture structural complexity through associations and generalizations."],"number":["5"],"pages":["517–549"],"title":["Building measure-based prediction models for UML class diagram maintainability"],"volume":["12"]},"creators":{"author":[{"lastName":"Genero","firstName":"Marcela"},{"lastName":"Manso","firstName":"Esperanza"},{"lastName":"Visaggio","firstName":"Aaron"},{"lastName":"Canfora","firstName":"Gerardo"},{"lastName":"Piattini","firstName":"Mario"}]},"sentenceCased":true},{"key":"generoSurveyMetricsUML2005","type":"article","fields":{"author":["Genero, Marcela","Piattini, Mario","Calero, Coral"],"date":["2005"],"doi":["10.5381/jot.2005.4.9.a1"],"journaltitle":["J. Object Technol."],"note":["TL;DR \n\nThe primary aim of this work is to present a survey, as complete as possible, of the existing relevant works regarding class diagram metrics so that researchers and practitioners alike may gain broad and ready access to insights for measuring these quality characteristics."],"number":["9"],"pages":["59"],"title":["A Survey of Metrics for UML Class Diagrams."],"volume":["4"]},"creators":{"author":[{"lastName":"Genero","firstName":"Marcela"},{"lastName":"Piattini","firstName":"Mario"},{"lastName":"Calero","firstName":"Coral"}]}},{"key":"gerasimouSoftwareEngineeringIntelligent2019","type":"online","fields":{"abstract":["Software systems are increasingly used in application domains characterised by uncertain environments, evolving requirements and unexpected failures; sudden system malfunctioning raises serious issues of security, safety, loss of comfort or revenue. During operation, these systems will likely need to deal with several unpredictable situations including variations in system performance, sudden changes in system workload and component failures. These situations can cause deviation from the desired system behaviour and require dynamic adaptation of the system behaviour, parameters or architecture. Through using closed-loop control, typically realized with software, intelligent and autonomous software systems can dynamically adapt themselves, without any or with limited human involvement, by identifying abnormal situations, analysing alternative adaptation options, and finally, self-adapting to a suitable new configuration. This report summarises the research carried out during SEfIAS GI Dagstuhl seminar which provided a forum for strengthening interaction and collaboration for early-career researchers and practitioners from the research communities of SEAMS, ICAC/ICCAC, SASO, Self-Aware Computing and AAMAS."],"author":["Gerasimou, Simos","Vogel, Thomas","Diaconescu, Ada"],"date":["2019-04-02"],"eprint":["1904.01518"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Software Engineering"],"note":["Comment: 28 pages \n\nTL;DR \n\nThis report summarises the research carried out during SEfIAS GI Dagstuhl seminar which provided a forum for strengthening interaction and collaboration for early-career researchers and practitioners from the research communities of SEAMS, ICAC/ICCAC, SASO, Self-Aware Computing and AAMAS."],"pubstate":["preprint"],"shorttitle":["Software Engineering for Intelligent and Autonomous Systems"],"title":["Software Engineering for Intelligent and Autonomous Systems: Report from the GI Dagstuhl Seminar 18343"],"url":["http://arxiv.org/abs/1904.01518"],"urldate":["2023-09-28"]},"creators":{"author":[{"lastName":"Gerasimou","firstName":"Simos"},{"lastName":"Vogel","firstName":"Thomas"},{"lastName":"Diaconescu","firstName":"Ada"}]}},{"key":"gerostathopoulosTRAPPedTrafficSelfAdaptive2019","type":"inproceedings","fields":{"langid":["english"],"abstract":["Optimizing the traffic flow in a city is a challenging problem, especially in a future traffic system of self-driving cars and sharing vehicles. This is due to the interactions between the individual traffic agents (vehicles) that compete for the use of the common infrastructure (streets) given traffic dynamics such as stop-and-go effects, changing lanes, and other. The goal of this paper is to provide a solution to the above problem that works in a fully decentralized and participatory way, i.e. autonomous agents collaborate without a centralized data collector and arbitrator. Such a solution should be scalable, privacypreserving, and flexible with respect to the degree of autonomy of agents. A self-adaptive framework to support this research is introduced: TRAPP – Traffic Reconfigurations via Adaptive Participatory Planning. The framework relies on a microscopic traffic simulator, SUMO, for simulating urban mobility scenarios, and on a decentralized multi-agent planning system, EPOS, for decentralized combinatorial optimization, applied here in traffic flows. A data-driven interoperation of the two tools in the proposed framework allows high modularity and customization for experimenting with different scenarios, optimization objectives and agents’ behavior and as such providing new perspectives for resilient future traffic infrastructures."],"author":["Gerostathopoulos, Ilias","Pournaras, Evangelos"],"booktitle":["2019 IEEEACM 14th Int. Symp. Softw. Eng. Adapt. Self-Manag. Syst. SEAMS"],"date":["2019-05"],"doi":["10.1109/SEAMS.2019.00014"],"eventtitle":["2019 IEEE/ACM 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)"],"isbn":["978-1-72813-368-3"],"location":["Montreal, QC, Canada"],"note":["TL;DR \n\nA self-adaptive framework to support this research is introduced: TRAPP – Traffic Reconfigurations via Adaptive Participatory Planning, which relies on a microscopic traffic simulator for simulating urban mobility scenarios, and on a decentralized multi-agent planning system, EPOS, for decentralized combinatorial optimization, applied here in traffic flows."],"pages":["32–38"],"publisher":["IEEE"],"shorttitle":["TRAPPed in Traffic?"],"title":["TRAPPed in Traffic? A Self-Adaptive Framework for Decentralized Traffic Optimization"]},"creators":{"author":[{"lastName":"Gerostathopoulos","firstName":"Ilias"},{"lastName":"Pournaras","firstName":"Evangelos"}]}},{"key":"gessertNoSQLDatabaseSystems2017","type":"article","fields":{"langid":["english"],"abstract":["Today, data is generated and consumed at unprecedented scale. This has lead to novel approaches for scalable data management subsumed under the term “NoSQL” database systems to handle the ever-increasing data volume and request loads. However, the heterogeneity and diversity of the numerous existing systems impede the well-informed selection of a data store appropriate for a given application context. Therefore, this article gives a top-down overview of the field: instead of contrasting the implementation specifics of individual representatives, we propose a comparative classification model that relates functional and non-functional requirements to techniques and algorithms employed in NoSQL databases. This NoSQL Toolbox allows us to derive a simple decision tree to help practitioners and researchers filter potential system candidates based on central application requirements."],"author":["Gessert, Felix","Wingerath, Wolfram","Friedrich, Steffen","Ritter, Norbert"],"date":["2017-07"],"doi":["10.1007/s00450-016-0334-3"],"issn":["1865-2034, 1865-2042"],"journaltitle":["Comput Sci Res Dev"],"keywords":["TYPHONML"],"number":["3-4"],"pages":["353–365"],"shorttitle":["NoSQL database systems"],"title":["NoSQL database systems: A survey and decision guidance"],"volume":["32"]},"creators":{"author":[{"lastName":"Gessert","firstName":"Felix"},{"lastName":"Wingerath","firstName":"Wolfram"},{"lastName":"Friedrich","firstName":"Steffen"},{"lastName":"Ritter","firstName":"Norbert"}]},"sentenceCased":true},{"key":"Ghamizi20201089","type":"inproceedings","fields":{"abstract":["Credit scoring systems are critical FinTech applications that concern the analysis of the creditworthiness of a person or organization. While decisions were previously based on human expertise, they are now increasingly relying on data analysis and machine learning. In this paper, we assess the ability of state-of-the-art adversarial machine learning to craft attacks on a real-world credit scoring system. Interestingly, we find that, while these techniques can generate large numbers of adversarial data, these are practically useless as they all violate domain-specific constraints. In other words, the generated examples are all false positives as they cannot occur in practice. To circumvent this limitation, we propose CoEvA2, a search-based method that generates valid adversarial examples (satisfying the domain constraints). CoEvA2 utilizes multi-objective search in order to simultaneously handle constraints, perform the attack and maximize the overdraft amount requested. We evaluate CoEvA2 on a major bank's real-world system by checking its ability to craft valid attacks. CoEvA2 generates thousands of valid adversarial examples, revealing a high risk for the banking system. Fortunately, by improving the system through adversarial training (based on the produced examples), we increase its robustness and make our attack fail. © 2020 ACM."],"author":["Ghamizi, S.","Cordy, M.","Gubri, M.","Papadakis, M.","Boystov, A.","Le Traon, Y.","Goujon, A."],"author_keywords":["Adversarial attacks; Credit Scoring; FinTech; Random Forest; Search-based"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3368089.3409739"],"editor":["Devanbu P., Cohen M., Zimmermann T."],"isbn":["978-1-4503-7043-1"],"keywords":["Banking systems","Domain constraint","Domain specific","False positive","Human expertise","Machine learning","Multi objective","Real-world system","Software engineering","State of the art"],"note":["cited By 8 \n\nTL;DR \n\nCoEvA2 is proposed, a search-based method that generates valid adversarial examples (satisfying the domain constraints) and utilizes multi-objective search in order to simultaneously handle constraints, perform the attack and maximize the overdraft amount requested."],"pages":["1089–1100"],"publisher":["Association for Computing Machinery, Inc"],"series":["ESEC/FSE 2020 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering"],"source":["Scopus"],"title":["Search-based adversarial testing and improvement of constrained credit scoring systems"]},"creators":{"author":[{"lastName":"Ghamizi","firstName":"S."},{"lastName":"Cordy","firstName":"M."},{"lastName":"Gubri","firstName":"M."},{"lastName":"Papadakis","firstName":"M."},{"lastName":"Boystov","firstName":"A."},{"lastName":"Le Traon","firstName":"Y."},{"lastName":"Goujon","firstName":"A."}],"editor":[{"lastName":"Devanbu P.","suffix":"Cohen M.","firstName":"Zimmermann T."}]},"sentenceCased":true},{"key":"ghannem2013model","type":"inproceedings","fields":{"langid":["english"],"author":["Ghannem, Adnane","El Boussaidi, Ghizlane","Kessentini, Marouane"],"booktitle":["Search Based Softw. Eng. 5th Int. Symp. SSBSE 2013 St Petersburg Russ. August 24-26 2013 Proc. 5"],"date":["2013"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper proposes an approach by adapting the Interactive Genetic Algorithm IGA which enables to interact with users and integrate their feedbacks into a classic GA and uses a fitness function that combines the structural similarity between the analyzed design model and models from a base of examples."],"pages":["96–110"],"title":["Model refactoring using interactive genetic algorithm"]},"creators":{"author":[{"lastName":"Ghannem","firstName":"Adnane"},{"lastName":"El Boussaidi","firstName":"Ghizlane"},{"lastName":"Kessentini","firstName":"Marouane"}]},"sentenceCased":true},{"key":"GhannemKHE18","type":"article","fields":{"langid":["english"],"author":["Ghannem, Adnane","Kessentini, Marouane","Hamdi, Mohammad Salah","El-Boussaidi, Ghizlane"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2018"],"doi":["10.1002/SMR.1916"],"journaltitle":["J. Softw. Evol. Process."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThe Non‐dominated Sorting Genetic Algorithm (NSGA‐II) is used to find a set of representative Pareto optimal solutions that present the best trade‐off between structural and textual similarities of models."],"number":["4"],"timestamp":["Fri, 06 Mar 2020 21:54:32 +0100"],"title":["Model refactoring by example: A multi-objective search based software engineering approach"],"volume":["30"]},"creators":{"author":[{"lastName":"Ghannem","firstName":"Adnane"},{"lastName":"Kessentini","firstName":"Marouane"},{"lastName":"Hamdi","firstName":"Mohammad Salah"},{"lastName":"El-Boussaidi","firstName":"Ghizlane"}]},"sentenceCased":true},{"key":"Gharibi2019","type":"inproceedings","fields":{"abstract":["Developing a deep learning model is an iterative, experimental process that produces tens to hundreds of models before arriving at a satisfactory result. While there has been a surge in the number of software tools that aim to facilitate deep learning, the process of managing the models and their artifacts is still surprisingly challenging and time-consuming. Existing model-management solutions are either tailored for commercial platforms or require significant code changes. In this paper, we introduce a lightweight system, named ModelKB, that can automatically extract and manage the model's metadata and provenance information (e.g., the used datasets and hyperparameters). Our overarching goal is to automate the management of deep learning experiments with minimal user intervention. Moreover, ModelKB provides a stepping stone to facilitate model selection and reproducibility. © 2019 ACM."],"art_number":["3329495"],"author":["Gharibi, G.","Walunj, V.","Alanazi, R.","Rella, S.","Lee, Y."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1145/3329486.3329495"],"isbn":["978-1-4503-6797-4"],"issn":["07308078"],"note":["cited By 5 \n\nTL;DR \n\nA lightweight system that can automatically extract and manage the model's metadata and provenance information (e.g., the used datasets and hyperparameters) and provides a stepping stone to facilitate model selection and reproducibility."],"publisher":["Association for Computing Machinery"],"series":["Proceedings of the ACM SIGMOD International Conference on Management of Data"],"source":["Scopus"],"title":["Automated management of deep learning experiments"]},"creators":{"author":[{"lastName":"Gharibi","firstName":"G."},{"lastName":"Walunj","firstName":"V."},{"lastName":"Alanazi","firstName":"R."},{"lastName":"Rella","firstName":"S."},{"lastName":"Lee","firstName":"Y."}]},"sentenceCased":true},{"key":"Gharibi201928","type":"inproceedings","fields":{"abstract":["Deep Learning has improved the state-of-the-art results in an ever-growing number of domains. This success heavily relies on the development and training of deep learning models, also known as deep neural networks (DNN). Often, developing a DNN is an ad-hoc, iterative process that results in producing tens to hundreds of models before arriving at a satisfactory result. While there has been a surge in the number of tools and frameworks that aim at facilitating deep learning, the issues of model management have been largely ignored. In particular, deep learning practitioners have to manually track their experiments using text files, spreadsheets or folder hierarchies, which is expensive, time-consuming, and error-prone. In this paper, we present our ongoing work and vision towards automating end-to-end model management in deep learning. Specifically, we introduce a tool prototype, named ModelKB, that can automatically (1) extract and store the model's metadata-including its architecture, weights, and configuration; (2) visualize, query, and compare experiments; and (3) reproduce experiments. Our overarching goal is to automate the model management process with minimal user intervention using the user's favorite framework. We report the current status of ModelKB, a pilot user study, and the challenges of automating model management in deep learning. © 2019 IEEE."],"art_number":["8823655"],"author":["Gharibi, G.","Walunj, V.","Rella, S.","Lee, Y."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/RAISE.2019.00013"],"isbn":["978-1-72812-272-4"],"note":["cited By 5"],"pages":["28–34"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2019 IEEE/ACM 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering, RAISE 2019"],"source":["Scopus"],"title":["ModelKB: Towards automated management of the modeling lifecycle in deep learning"]},"creators":{"author":[{"lastName":"Gharibi","firstName":"G."},{"lastName":"Walunj","firstName":"V."},{"lastName":"Rella","firstName":"S."},{"lastName":"Lee","firstName":"Y."}]},"sentenceCased":true},{"key":"Gharibi2021","type":"article","fields":{"abstract":["Deep learning has improved the state-of-the-art results in an ever-growing number of domains. This success heavily relies on the development and training of deep learning models–an experimental, iterative process that produces tens to hundreds of models before arriving at a satisfactory result. While there has been a surge in the number of tools and frameworks that aim at facilitating deep learning, the process of managing the models and their artifacts is still surprisingly challenging and time-consuming. Existing model-management solutions are either tailored for commercial platforms or require significant code changes. Moreover, most of the existing solutions address a single phase of the modeling lifecycle, such as experiment monitoring, while ignoring other essential tasks, such as model deployment. In this paper, we present a software system to facilitate and accelerate the deep learning lifecycle, named ModelKB. ModelKB can automatically manage the modeling lifecycle end-to-end, including (1) monitoring and tracking experiments; (2) visualizing, searching for, and comparing models and experiments; (3) deploying models locally and on the cloud; and (4) sharing and publishing trained models. Moreover, our system provides a stepping-stone for enhanced reproducibility. ModelKB currently supports TensorFlow 2.0, Keras, and PyTorch, and it can be extended to other deep learning frameworks easily. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature."],"art_number":["17"],"author":["Gharibi, G.","Walunj, V.","Nekadi, R.","Marri, R.","Lee, Y."],"coden":["ESENF"],"date":["2021"],"document_type":["Article"],"doi":["10.1007/s10664-020-09894-9"],"issn":["13823256"],"journaltitle":["Empir. Softw. Eng."],"note":["cited By 0 \n\nTL;DR \n\nModelKB can automatically manage the modeling lifecycle end-to-end, including monitoring and tracking experiments; visualizing, searching for, and comparing models and experiments; deploying models locally and on the cloud; and sharing and publishing trained models."],"number":["2"],"publisher":["Springer"],"source":["Scopus"],"title":["Automated end-to-end management of the modeling lifecycle in deep learning"],"volume":["26"]},"creators":{"author":[{"lastName":"Gharibi","firstName":"G."},{"lastName":"Walunj","firstName":"V."},{"lastName":"Nekadi","firstName":"R."},{"lastName":"Marri","firstName":"R."},{"lastName":"Lee","firstName":"Y."}]},"sentenceCased":true},{"key":"Ghasemi2021","type":"article","fields":{"abstract":["Simulation Optimization (SO) techniques refer to a set of methods that have been applied to stochastic optimization problems, structured so that the optimizer(s) are integrated with simulation experiments. Although SO techniques provide promising solutions for large and complex stochastic problems, the simulation model execution is potentially expensive in terms of computation time. Thus, the overall purpose of this research is to advance the evolutionary SO methods literature by researching the use of metamodeling within these techniques. Accordingly, we present a new Evolutionary Learning Based Simulation Optimization (ELBSO) method embedded within Ordinal Optimization. In ELBSO a Machine Learning (ML) based simulation metamodel is created using Genetic Programming (GP) to replace simulation experiments aimed at reducing computation. ELBSO is evaluated on a Stochastic Job Shop Scheduling Problem (SJSSP), which is a well known complex production planning problem in most industries such as semiconductor manufacturing. To build the metamodel from SJSSP instances that replace simulation replications, we employ a novel training vector to train GP. This then is integrated into an evolutionary two-phased Ordinal Optimization approach to optimize an SJSSP which forms the ELBSO method. Using a variety of experimental SJSSP instances, ELBSO is compared with evolutionary optimization methods from the literature and typical dispatching rules. Our findings include the superiority of ELBSO over all other algorithms in terms of the quality of solutions and computation time. Furthermore, the integrated procedures and results provided within this article establish a basis for future SO applications to large and complex stochastic problems. © 2021 Elsevier B.V."],"art_number":["107309"],"author":["Ghasemi, A.","Ashoori, A.","Heavey, C."],"date":["2021"],"document_type":["Article"],"doi":["10.1016/j.asoc.2021.107309"],"issn":["15684946"],"journaltitle":["Appl. Soft Comput."],"note":["cited By 8"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Evolutionary learning based simulation optimization for stochastic job shop scheduling problems"],"volume":["106"]},"creators":{"author":[{"lastName":"Ghasemi","firstName":"A."},{"lastName":"Ashoori","firstName":"A."},{"lastName":"Heavey","firstName":"C."}]},"sentenceCased":true},{"key":"Ghiasi2018101","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Adv Eng Software"],"affiliation":["Department of Civil Engineering, Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran; Mechanical Engineering Department, California Polytechnic State University, One Grand Avenue San Luis ObispoCA 93405, United States; Distinguished Visiting Professor, International Institute for Urban Systems Engineering, Southeast University, Nanjing, 210096, China"],"author":["Ghiasi, R.","Ghasemi, M.R.","Noori, M."],"coden":["AESOD"],"correspondence_address1":["Noori, M.; Mechanical Engineering Department, One Grand Avenue San Luis Obispo, United States; email: contact@mohammadnoori.com"],"date":["2018"],"document_type":["Article"],"doi":["10.1016/j.advengsoft.2018.02.006"],"issn":["09659978"],"journaltitle":["Adv. Eng. Softw."],"keywords":["notion"],"note":["cited By 47"],"pages":["101–112"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Comparative studies of metamodeling and AI-Based techniques in damage detection of structures"],"volume":["125"]},"creators":{"author":[{"lastName":"Ghiasi","firstName":"R."},{"lastName":"Ghasemi","firstName":"M.R."},{"lastName":"Noori","firstName":"M."}]},"sentenceCased":true},{"key":"Ghiasi2018561","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Smart Struct. Syst."],"affiliation":["Department of Civil Engineering, Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran"],"author":["Ghiasi, R.","Ghasemi, M.R."],"correspondence_address1":["Ghasemi, M.R.; Department of Civil Engineering, Iran; email: mrghasemi@eng.usb.ac.ir"],"date":["2018"],"document_type":["Article"],"doi":["10.12989/sss.2018.22.5.561"],"issn":["17381584"],"journaltitle":["Smart Struct. Syst."],"note":["cited By 15"],"number":["5"],"pages":["561–574"],"publisher":["Techno-Press"],"source":["Scopus"],"title":["Optimization-based method for structural damage detection with consideration of uncertainties- a comparative study"],"volume":["22"]},"creators":{"author":[{"lastName":"Ghiasi","firstName":"R."},{"lastName":"Ghasemi","firstName":"M.R."}]},"sentenceCased":true},{"key":"Ghose2001","type":"article","fields":{"abstract":["Taste tests are being increasingly used by marketers to influence consumers to change their preferences toward their brands. This research indicates how perceptual and preferential taste tests can be used in conjunction with visual maps to provide support to marketing managers for making better brand positioning and targeting decisions on the basis of taste for different segments of consumers. An empirical blind taste-test study is used to illustrate the concepts. The preferential taste judgment part of the empirical study is designed to capture violations of the `Independence of Irrelevant Alternatives' (IIA) effect that is commonly observed in consumers' actual purchases. The present paper also uses a hypothetical example to indicate the importance of considering the location of consumer `ideal points' before making formulation changes in a brand as part of a targeting strategy. Various managerial implications of using the suggested perceptual preferential taste-mapping analyses are also discussed. Appropriate measurements of consumer tastes provide insights for identifying and targeting viable market segments."],"author":["Ghose, Sanjoy","Lowengart, Oded"],"date":["2001-08-01"],"doi":["10.1057/palgrave.jt.5740031"],"issn":["1479-1862"],"journaltitle":["J. Target. Meas. Anal. Mark."],"number":["1"],"pages":["26–41"],"title":["Taste tests: Impacts of consumer perceptions and preferences on brand positioning strategies"],"volume":["10"]},"creators":{"author":[{"lastName":"Ghose","firstName":"Sanjoy"},{"lastName":"Lowengart","firstName":"Oded"}]},"sentenceCased":true},{"key":"giacobbeImplementationInfluxDBMonitoring2020","type":"article","fields":{"langid":["english"],"author":["Giacobbe, Maurizio","Chaouch, Chakib","Scarpa, Marco","Puliafito, Antonio"],"date":["2020"],"doi":["10.1007/978-3-030-21005-2_15"],"editor":["Bouhlel, Med Salim","Rovetta, Stefano"],"journaltitle":["Proc. 8th Int. Conf. Sci. Electron. Technol. Inf. Telecommun. SETIT’18 Vol1"],"note":["TL;DR \n\nThis work presents a case study based on the implementation of the InfluxDB time series database for monitoring and analytics in distributed IoT environments to enable IoT-as-a-Service in geo-distributed “smart” ecosystems thus creating new opportunities for heterogeneous stakeholders to meet and define new synergies."],"pages":["155–162"],"title":["An Implementation of InfluxDB for Monitoring and Analytics in Distributed IoT Environments"],"volume":["146"]},"creators":{"author":[{"lastName":"Giacobbe","firstName":"Maurizio"},{"lastName":"Chaouch","firstName":"Chakib"},{"lastName":"Scarpa","firstName":"Marco"},{"lastName":"Puliafito","firstName":"Antonio"}],"editor":[{"lastName":"Bouhlel","firstName":"Med Salim"},{"lastName":"Rovetta","firstName":"Stefano"}]}},{"key":"giannottiEXplainableMachineLearning","type":"article","fields":{"langid":["english"],"author":["Giannotti, Fosca"],"pages":["44"],"title":["eXplainable machine learning for Trustworthy AI"]},"creators":{"author":[{"lastName":"Giannotti","firstName":"Fosca"}]},"sentenceCased":true},{"key":"gibaldiMLAHandbookWriters2009","type":"book","fields":{"langid":["english"],"date":["2009"],"edition":["7th ed"],"editor":["Gibaldi, Joseph","Modern Language Association of America"],"isbn":["978-1-60329-024-1 978-1-60329-025-8"],"location":["New York"],"note":["TL;DR \n\nThe fourth edition of the MLA Handbook presents a comprehensive guide to preparing research papers and contains detailed information on using computers for research and writing and on citing electronic publications."],"pagetotal":["292"],"publisher":["Modern Language Association of America"],"title":["MLA handbook for writers of research papers"]},"creators":{"editor":[{"lastName":"Gibaldi","firstName":"Joseph"},{"firstName":"Modern Language Association of","lastName":"America"}]},"sentenceCased":true},{"key":"Giese2011","type":"inproceedings","fields":{"author":["Gabrysiak","Gregor, Holger Giese, Alexander Lüders","Seibel, Andreas"],"booktitle":["ICSE 2011 Workshop Flex. Model. Tools"],"date":["2011"],"title":["How can metamodels be used flexibly"],"volume":["22"]},"creators":{"author":[{"literal":"Gabrysiak"},{"lastName":"Gregor","suffix":"Holger Giese","firstName":"Alexander Lüders"},{"lastName":"Seibel","firstName":"Andreas"}]},"sentenceCased":true},{"key":"gilWingsIntelligentWorkflowBased2011","type":"article","fields":{"author":["Gil, Yolanda","Ratnakar, Varun","Kim, Jihie","Gonzalez-Calero, Pedro","Groth, Paul","Moody, Joshua","Deelman, Ewa"],"date":["2011-01"],"doi":["10.1109/MIS.2010.9"],"issn":["1541-1672"],"journaltitle":["IEEE Intell. Syst."],"note":["TL;DR \n\nDescribes the Wings intelligent workflow system that assists scientists with designing computational experiments by automatically tracking constraints and ruling out invalid designs, letting scientists focus on their experiments and goals."],"number":["1"],"pages":["62–72"],"shorttitle":["Wings"],"title":["Wings: Intelligent Workflow-Based Design of Computational Experiments"],"volume":["26"]},"creators":{"author":[{"lastName":"Gil","firstName":"Yolanda"},{"lastName":"Ratnakar","firstName":"Varun"},{"lastName":"Kim","firstName":"Jihie"},{"lastName":"Gonzalez-Calero","firstName":"Pedro"},{"lastName":"Groth","firstName":"Paul"},{"lastName":"Moody","firstName":"Joshua"},{"lastName":"Deelman","firstName":"Ewa"}]}},{"key":"giraldoMethodEvaluateQuality2019","type":"article","fields":{"langid":["english"],"abstract":["The model-driven engineering (MDE) paradigm promotes the use of conceptual models in information systems (IS) engineering and research. As engineering products, conceptual models must be of high quality, which applies to both conceptual models and the modelling language used to build them. Quality is a growing concern in the MDE field; however, studies such as Giraldo, F.D. et al. Software Quality Journal, pp. 1–66 (2016b) and Goulão, M. et al. Software Quality Journal, pp. 1–33 (2016) demonstrate the divergence in several approaches that are proposed for addressing this topic. Due to the many challenges, divergences, and trends for quality assessment and assurance in the MDE context, one way to perform a quality evaluation process is to use an approach where the applicability and goals of modelling languages (and artifacts) can be compared with respect to the essential principles of the development of IS. We propose using principles from an IS architecture reference (i.e., the Zachman framework) as a taxonomy that is applied on the modelling languages used in information system development in order to perform analytic procedures. We also demonstrate that this taxonomy can be considered as a formal context for the application of the formal concept analysis (FCA) method. This paper derives formal, methodological, and technological requirements for a modelling language quality evaluation method (MMQEF) with the potential to tackle some of the open MDE quality challenges. In addition, a tool that operationalizes the taxonomic evaluation procedure and the FCA analytic method is also presented. In this work, we discuss how this taxonomy supports analytics that are in modelling languages for quality purposes through its management of the semantics."],"author":["Giraldo, Fáber D.","España, Sergio","Giraldo, William J.","Pastor, Óscar","Krogstie, John"],"date":["2019-09-01"],"doi":["10.1007/s11219-018-9434-6"],"issn":["1573-1367"],"journaltitle":["Software Qual J"],"keywords":["Information systems","Model-driven engineering","Modelling language evaluation","Quality","Reference taxonomy","The MMQEF method"],"note":["TL;DR \n\nThis work proposes using principles from an IS architecture reference as a taxonomy that is applied on the modelling languages used in information system development in order to perform analytic procedures and demonstrates that this taxonomy can be considered as a formal context for the application of the formal concept analysis (FCA) method."],"number":["3"],"pages":["1239–1269"],"title":["A method to evaluate quality of modelling languages based on the Zachman reference taxonomy"],"volume":["27"]},"creators":{"author":[{"lastName":"Giraldo","firstName":"Fáber D."},{"lastName":"España","firstName":"Sergio"},{"lastName":"Giraldo","firstName":"William J."},{"lastName":"Pastor","firstName":"Óscar"},{"lastName":"Krogstie","firstName":"John"}]},"sentenceCased":true},{"key":"Girum2019119","type":"article","fields":{"abstract":["Deep learning has shown unprecedented success in a variety of applications, such as computer vision and medical image analysis. However, there is still potential to improve segmentation in multimodal images by embedding prior knowledge via learning-based shape modeling and registration to learn the modality invariant anatomical structure of organs. For example, in radiotherapy automatic prostate segmentation is essential in prostate cancer diagnosis, therapy, and post-therapy assessment from T2-weighted MR or CT images. In this paper, we present a fully automatic deep generative model-driven multimodal prostate segmentation method using convolutional neural network (DGMNet). The novelty of our method comes with its embedded generative neural network for learning-based shape modeling and its ability to adapt for different imaging modalities via learning-based registration. The proposed method includes a multi-task learning framework that combines a convolutional feature extraction and an embedded regression and classification based shape modeling. This enables the network to predict the deformable shape of an organ. We show that generative neural network-based shape modeling trained on a reliable contrast imaging modality (such as MRI) can be directly applied to low contrast imaging modality (such as CT) to achieve accurate prostate segmentation. The method was evaluated on MRI and CT datasets acquired from different clinical centers with large variations in contrast and scanning protocols. Experimental results reveal that our method can be used to automatically and accurately segment the prostate gland in different imaging modalities. © Springer Nature Switzerland AG 2019."],"author":["Girum, K.B.","Créhange, G.","Hussain, R.","Walker, P.M.","Lalande, A."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-32486-5_15"],"editor":["Nguyen D., Jiang S., Xing L."],"isbn":["9783030324858"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 7 \n\nTL;DR \n\nIt is shown that generative neural network-based shape modeling trained on a reliable contrast Imaging modality can be directly applied to low contrast imaging modality (such as CT) to achieve accurate prostate segmentation."],"pages":["119–127"],"publisher":["Springer"],"source":["Scopus"],"title":["Deep generative model-driven multimodal prostate segmentation in radiotherapy"],"volume":["11850 LNCS"]},"creators":{"author":[{"lastName":"Girum","firstName":"K.B."},{"lastName":"Créhange","firstName":"G."},{"lastName":"Hussain","firstName":"R."},{"lastName":"Walker","firstName":"P.M."},{"lastName":"Lalande","firstName":"A."}],"editor":[{"lastName":"Nguyen D.","suffix":"Jiang S.","firstName":"Xing L."}]},"sentenceCased":true},{"key":"GitHubFacebookresearchDlrm","type":"online","fields":{"title":["GitHub - Facebookresearch/Dlrm: An implementation of a deep learning recommendation model (DLRM)"],"url":["https://github.com/facebookresearch/dlrm"],"urldate":["2021-06-07"]},"creators":{},"sentenceCased":true},{"key":"glauberCollaborativeFilteringVs2019","type":"article","fields":{"abstract":["Recommendation Systems (SR) suggest items exploring user preferences, helping them with the information overload problem. Two approaches to SR have received more prominence, Collaborative Filtering, and Content-Based Filtering. Moreover, even though studies are indicating their advantages and disadvantages, few results empirically prove their characteristics, similarities, and differences. In this work, an experimental methodology is proposed to perform comparisons between recommendation algorithms for different approaches going beyond the \"precision of the predictions\". For the experiments, three algorithms of recommendation were tested: a baseline for Collaborative Filtration and two algorithms for Content-based Filtering that were developed for this evaluation. The experiments demonstrate the behavior of these systems in different data sets, its main characteristics and especially the complementary aspect of the two main approaches."],"author":["Glauber, Rafael","Loula, Angelo"],"date":["2019-12-18"],"eprint":["1912.08932"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv191208932 Cs"],"note":["TL;DR \n\nAn experimental methodology is proposed to perform comparisons between recommendation algorithms for different approaches going beyond the \"precision of the predictions\" and demonstrates the behavior of these systems in different data sets, including the complementary aspect of the two main approaches."],"shorttitle":["Collaborative Filtering vs. Content-Based Filtering"],"title":["Collaborative Filtering vs. Content-Based Filtering: Differences and similarities"],"url":["http://arxiv.org/abs/1912.08932"],"urldate":["2020-01-11"]},"creators":{"author":[{"lastName":"Glauber","firstName":"Rafael"},{"lastName":"Loula","firstName":"Angelo"}]},"sentenceCased":true},{"key":"gleitzeFindingUniversalExecution2021","type":"incollection","fields":{"langid":["english"],"abstract":["When using multiple models to describe a (software) system, one can use a network of model transformations to keep the models consistent after changes. No strategy exists, however, to orchestrate the execution of transformations if the network has an arbitrary topology. In this paper, we analyse how often and in which order transformations need to be executed. We argue why linear execution bounds are too restrictive to be useful in practice and prove that there is no upper bound for the number of necessary executions. To avoid non-termination, we propose a conservative strategy that makes execution failures easier to understand. These insights help developers and users of transformation networks to understand under which circumstances their networks can terminate. Additionally, the proposed strategy helps them to find the cause when a network cannot restore consistency."],"author":["Gleitze, Joshua","Klare, Heiko","Burger, Erik"],"booktitle":["Fundamental Approaches to Software Engineering"],"date":["2021"],"doi":["10.1007/978-3-030-71500-7_5"],"editor":["Guerra, Esther","Stoelinga, Mariëlle"],"isbn":["978-3-030-71499-4 978-3-030-71500-7"],"location":["Cham"],"note":["TL;DR \n\nIt is argued why linear execution bounds are too restrictive to be useful in practice and proved that there is no upper bound for the number of necessary executions."],"pages":["87–107"],"publisher":["Springer International Publishing"],"title":["Finding a Universal Execution Strategy for Model Transformation Networks"],"volume":["12649"]},"creators":{"author":[{"lastName":"Gleitze","firstName":"Joshua"},{"lastName":"Klare","firstName":"Heiko"},{"lastName":"Burger","firstName":"Erik"}],"editor":[{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Stoelinga","firstName":"Mariëlle"}]}},{"key":"gloriaDesignImplementationIoT2017","type":"article","fields":{"langid":["english"],"author":["Glória, André","Cercas, Francisco","Souto, Nuno"],"date":["2017"],"doi":["10.1016/j.procs.2017.05.343"],"issn":["18770509"],"journaltitle":["Procedia Computer Science"],"pages":["568–575"],"title":["Design and implementation of an IoT gateway to create smart environments"],"volume":["109"]},"creators":{"author":[{"lastName":"Glória","firstName":"André"},{"lastName":"Cercas","firstName":"Francisco"},{"lastName":"Souto","firstName":"Nuno"}]},"sentenceCased":true},{"key":"GmailConcettoDi","type":"online","fields":{"title":["Gmail - Concetto di \"Scenario Misto\""],"url":["https://mail.google.com/mail/u/0/?ui=2&ik=c6f0013e0f&view=pt&search=inbox&type=14ce63765de5b01c&msg=14c64feb393c287b&siml=14c64feb393c287b"],"urldate":["2015-04-24"]},"creators":{},"sentenceCased":true},{"key":"gobertConceptualModelingManipulation","type":"article","fields":{"langid":["english"],"abstract":["An increasing number of organisations rely on NoSQL technologies to manage their mission-critical data. However, those technologies were not intended to replace relational database management systems, but rather to complement them. Hence the recent emergence of heterogeneous database architectures, commonly called hybrid polystores, that rely on a combination of several, possibly overlapping relational and NoSQL databases. Unfortunately, there is still a lack of models, methods and tools for data modeling and manipulation in such architectures. With the aim to fill this gap, we present HyDRa, a conceptual framework to design and manipulate hybrid polystores. HyDRa includes a textual modeling language to specify (1) the conceptual schema of the polystore, (2) the physical schemas of each of its databases, and (3) a set of mapping rules to express possibly complex correspondences between the conceptual schema elements and the physical databases. HyDRa provides the generation of a conceptual API, allowing developers to query hybrid polystores at a conceptual level, and to automatically enforce cross-database data integrity constraints. The use of HyDRa is supported by an Eclipse plugin, offering syntax highlighting, auto-completion and conceptual data access API generation."],"author":["Gobert, Maxime","Meurice, Loup","Cleve, Anthony"],"pages":["14"],"title":["Conceptual Modeling and Manipulation of Hybrid Polystores"]},"creators":{"author":[{"lastName":"Gobert","firstName":"Maxime"},{"lastName":"Meurice","firstName":"Loup"},{"lastName":"Cleve","firstName":"Anthony"}]}},{"key":"GogollaBR07","type":"article","fields":{"langid":["english"],"author":["Gogolla, Martin","Büttner, Fabian","Richters, Mark"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2007"],"doi":["10.1016/J.SCICO.2007.01.013"],"journaltitle":["Sci. Comput. Program."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["1-3"],"pages":["27–34"],"timestamp":["Wed, 17 Feb 2021 21:56:03 +0100"],"title":["USE: A UML-based specification environment for validating UML and OCL"],"volume":["69"]},"creators":{"author":[{"lastName":"Gogolla","firstName":"Martin"},{"lastName":"Büttner","firstName":"Fabian"},{"lastName":"Richters","firstName":"Mark"}]},"sentenceCased":true},{"key":"GogollaHD18","type":"article","fields":{"langid":["english"],"author":["Gogolla, Martin","Hilken, Frank","Doan, Khanh-Hoang"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2018"],"doi":["10.1016/J.CL.2017.10.001"],"journaltitle":["Comput. Lang. Syst. Struct."],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["474–511"],"timestamp":["Tue, 11 Feb 2020 17:00:46 +0100"],"title":["Achieving model quality through model validation, verification and exploration"],"volume":["54"]},"creators":{"author":[{"lastName":"Gogolla","firstName":"Martin"},{"lastName":"Hilken","firstName":"Frank"},{"lastName":"Doan","firstName":"Khanh-Hoang"}]},"sentenceCased":true},{"key":"gomez-abajoSystematicEngineeringMutation2020","type":"article","fields":{"langid":["english"],"author":["Gómez-Abajo, Pablo","Guerra, Esther","family=Lara, given=Juan, prefix=de, useprefix=true","Merayo, Mercedes G."],"date":["2020"],"doi":["10.5381/jot.2020.19.3.a5"],"issn":["1660-1769"],"journaltitle":["JOT"],"note":["TL;DR \n\nThis work proposes a methodology and corresponding tool support for the proper engineering of mutation operators, representing the artefacts to be mutated as models, and shows automated support atop the W ODEL tool."],"number":["3"],"pages":["3:1"],"title":["Systematic Engineering of Mutation Operators."],"volume":["19"]},"creators":{"author":[{"lastName":"Gómez-Abajo","firstName":"Pablo"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true},{"lastName":"Merayo","firstName":"Mercedes G."}]}},{"key":"gomez-uribeNetflixRecommenderSystem2015","type":"article","fields":{"acmid":["2843948"],"address":["New York, NY, USA"],"articleno":["13"],"author":["Gomez-Uribe, Carlos A.","Hunt, Neil"],"date":["2015-12"],"issn":["2158-656X"],"issue_date":["January 2016"],"journaltitle":["ACM Trans. Manage. Inf. Syst."],"nodoi":["10.1145/2843948"],"number":["4"],"numpages":["19"],"pages":["13:1-13:19"],"publisher":["ACM"],"title":["The netflix recommender system: Algorithms, business value, and innovation"],"url":["http://doi.acm.org/10.1145/2843948"],"volume":["6"]},"creators":{"author":[{"lastName":"Gomez-Uribe","firstName":"Carlos A."},{"lastName":"Hunt","firstName":"Neil"}]},"sentenceCased":true},{"key":"gomez2012searching","type":"inproceedings","fields":{"langid":["english"],"author":["Gómez, Juan José Cadavid","Baudry, Benoit","Sahraoui, Houari"],"booktitle":["2012 IEEE Fifth Int. Conf. Softw. Test. Verification Valid."],"date":["2012"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper uses simulated annealing to select a set of models in the modeling space captured by a metamodel that satisfies those two objectives and reports on results using two meetamodels from two different domains."],"pages":["131–140"],"title":["Searching the boundaries of a modeling space to test metamodels"]},"creators":{"author":[{"lastName":"Gómez","firstName":"Juan José Cadavid"},{"lastName":"Baudry","firstName":"Benoit"},{"lastName":"Sahraoui","firstName":"Houari"}]},"sentenceCased":true},{"key":"gomezMapBasedTransparentPersistence2015","type":"incollection","fields":{"langid":["english"],"abstract":["The progressive industrial adoption of Model-Driven Engineering (MDE) is fostering the development of large tool ecosystems like the Eclipse Modeling project. These tools are built on top of a set of base technologies that have been primarily designed for small-scale scenarios, where models are manually developed. In particular, efficient runtime manipulation for large-scale models is an under-studied problem and this is hampering the application of MDE to several industrial scenarios. In this paper we introduce and evaluate a map-based persistence model for MDE tools. We use this model to build a transparent persistence layer for modeling tools, on top of a map-based database engine. The layer can be plugged into the Eclipse Modeling Framework, lowering execution times and memory consumption levels of other existing approaches. Empirical tests are performed based on a typical industrial scenario, model-driven reverse engineering, where very large software models originate from the analysis of massive code bases. The layer is freely distributed and can be immediately used for enhancing the scalability of any existing Eclipse Modeling tool."],"author":["Gómez, Abel","Tisi, Massimo","Sunyé, Gerson","Cabot, Jordi"],"booktitle":["Fundamental Approaches to Software Engineering"],"date":["2015-04-11"],"editor":["Egyed, Alexander","Schaefer, Ina"],"isbn":["978-3-662-46674-2 978-3-662-46675-9"],"keywords":["software engineering"],"note":["TL;DR \n\nThis model is used to build a transparent persistence layer for modeling tools, on top of a map-based database engine, which can be plugged into the Eclipse Modeling Framework, lowering execution times and memory consumption levels of other existing approaches."],"number":["9033"],"pages":["19–34"],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture Notes in Computer Science"],"title":["Map-Based Transparent Persistence for Very Large Models"],"url":["http://link.springer.com/chapter/10.1007/978-3-662-46675-9_2"],"urldate":["2015-04-07"]},"creators":{"author":[{"lastName":"Gómez","firstName":"Abel"},{"lastName":"Tisi","firstName":"Massimo"},{"lastName":"Sunyé","firstName":"Gerson"},{"lastName":"Cabot","firstName":"Jordi"}],"editor":[{"lastName":"Egyed","firstName":"Alexander"},{"lastName":"Schaefer","firstName":"Ina"}]}},{"key":"gomezTemporalEMFTemporalMetamodeling2018","type":"incollection","fields":{"langid":["english"],"abstract":["Existing modeling tools provide direct access to the most current version of a model but very limited support to inspect the model state in the past. This typically requires looking for a model version (usually stored in some kind of external versioning system like Git) roughly corresponding to the desired period and using it to manually retrieve the required data. This approximate answer is not enough in scenarios that require a more precise and immediate response to temporal queries like complex collaborative co-engineering processes or runtime models."],"author":["Gómez, Abel","Cabot, Jordi","Wimmer, Manuel"],"booktitle":["Conceptual Modeling"],"date":["2018"],"doi":["10.1007/978-3-030-00847-5_26"],"editor":["Trujillo, Juan C.","Davis, Karen C.","Du, Xiaoyong","Li, Zhanhuai","Ling, Tok Wang","Li, Guoliang","Lee, Mong Li"],"isbn":["978-3-030-00846-8 978-3-030-00847-5"],"location":["Cham"],"note":["TL;DR \n\nExisting modeling tools provide direct access to the most current version of a model but very limited support to inspect the model state in the past, which is not enough in scenarios that require a more precise and immediate response to temporal queries."],"pages":["365–381"],"publisher":["Springer International Publishing"],"shorttitle":["TemporalEMF"],"title":["TemporalEMF: A Temporal Metamodeling Framework"],"volume":["11157"]},"creators":{"author":[{"lastName":"Gómez","firstName":"Abel"},{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Wimmer","firstName":"Manuel"}],"editor":[{"lastName":"Trujillo","firstName":"Juan C."},{"lastName":"Davis","firstName":"Karen C."},{"lastName":"Du","firstName":"Xiaoyong"},{"lastName":"Li","firstName":"Zhanhuai"},{"lastName":"Ling","firstName":"Tok Wang"},{"lastName":"Li","firstName":"Guoliang"},{"lastName":"Lee","firstName":"Mong Li"}]}},{"key":"gonzalezATLTestWhiteBoxTest2012","type":"article","fields":{"author":["González, Carlos A.","Cabot, Jordi"],"date":["2012"],"doi":["10.1007/978-3-642-33666-9_29"],"journaltitle":["Model Driven Eng. Lang. Syst."],"pages":["449–464"],"title":["ATLTest: A White-Box Test Generation Approach for ATL Transformations"],"volume":["7590"]},"creators":{"author":[{"lastName":"González","firstName":"Carlos A."},{"lastName":"Cabot","firstName":"Jordi"}]}},{"key":"Gorodetsky2015765","type":"article","fields":{"langid":["english"],"abbrev_source_title":["J. Comput. Syst. Sci. Int."],"affiliation":["St. Petersburg Institute for Informatics and Automation, Russian Academy of Sciences, 14 Liniya 39, St. Petersburg, Russian Federation; St. Petersburg State Polytechnic University, Polytechnicheskaya ul. 29, St. Petersburg, Russian Federation"],"author":["Gorodetsky, V.I.","Samoylov, V.V.","Trotskii, D.V."],"coden":["JSSIE"],"correspondence_address1":["Gorodetsky, V.I.; St. Petersburg Institute for Informatics and Automation, Russian Academy of Sciences, 14 Liniya 39, Russian Federation"],"date":["2015"],"document_type":["Article"],"doi":["10.1134/S1064230715030089"],"issn":["10642307"],"journaltitle":["J. Comput. Syst. Sci. Int."],"note":["cited By 6 \n\nTL;DR \n\nAn outline of the state of art in the field of behavioral models of artificial intelligence systems is given and a unified semantically interpreted behavioral metamodel in the form of a domain-independent reference ontology and its extensions for two particular practically important classes of applications are proposed."],"number":["5"],"pages":["765–782"],"publisher":["Maik Nauka-Interperiodica Publishing"],"source":["Scopus"],"title":["The reference ontology of collective behavior of autonomous agents and its extensions"],"volume":["54"]},"creators":{"author":[{"lastName":"Gorodetsky","firstName":"V.I."},{"lastName":"Samoylov","firstName":"V.V."},{"lastName":"Trotskii","firstName":"D.V."}]},"sentenceCased":true},{"key":"gorrepotuSub1GHzMiniatureWireless2018","type":"article","fields":{"langid":["english"],"abstract":["Considering the Sub-1 GHz frequency as a solution to address the key requirements in wireless networks as it supports multiple nodes and covers longer distances in contrast to other existing and widely used wireless technologies like GSM, BLE, Bluetooth and WiFi. Consequently the Sub-1 GHz spectrum requires lower power from the transceiver than the 2.4 GHz band making it a great choice for battery operated IoT sensor devices. For deploying nodes to cover large area and long range, sensing devices must be small, energy efficient and cost effective. IoT Sensor devices using the Sub-1 GHz spectrum can handle interference better. The lower frequency ISM bands enable the Sub-1 GHz transmissions to weave better between buildings in an urban environment. This paper deals with the design and development of hardware as well as software of a Sub-1 GHz gateway and miniature sensor node for IoT applications. CC1310 SoC, a Sub-1 GHz family microcontroller is used in the design of Sub-1 GHz, 868 MHz board."],"author":["Gorrepotu, Ramesh","Korivi, Narendra Swaroop","Chandu, Kavitha","Deb, Subimal"],"date":["2018-09"],"doi":["10.1016/j.iot.2018.08.002"],"issn":["25426605"],"journaltitle":["Internet Things"],"pages":["27–39"],"title":["Sub-1GHz miniature wireless sensor node for IoT applications"],"volume":["1–2"]},"creators":{"author":[{"lastName":"Gorrepotu","firstName":"Ramesh"},{"lastName":"Korivi","firstName":"Narendra Swaroop"},{"lastName":"Chandu","firstName":"Kavitha"},{"lastName":"Deb","firstName":"Subimal"}]},"sentenceCased":true},{"key":"goscinskiSpecialIssueDistributed2023","type":"article","fields":{"langid":["english"],"author":["Goscinski, Andrzej","Delicato, Flavia C.","Fortino, Giancarlo","Kobusińska, Anna","Srivastava, Gautam"],"date":["2023-01"],"doi":["10.1016/j.jpdc.2022.09.014"],"issn":["07437315"],"journaltitle":["Journal of Parallel and Distributed Computing"],"pages":["157–162"],"title":["Special issue on Distributed Intelligence at the Edge for the Future Internet of Things"],"volume":["171"]},"creators":{"author":[{"lastName":"Goscinski","firstName":"Andrzej"},{"lastName":"Delicato","firstName":"Flavia C."},{"lastName":"Fortino","firstName":"Giancarlo"},{"lastName":"Kobusińska","firstName":"Anna"},{"lastName":"Srivastava","firstName":"Gautam"}]},"sentenceCased":true},{"key":"gouesBridgingGapResearch2018","type":"article","fields":{"abstract":["Software engineers must solve practical problems under deadline pressure. They rely on the best-codified knowledge available, turning to weaker results and their expert judgment when sound science is unavailable. Meanwhile, software engineering researchers seek fully validated results, resulting in a lag to practical guidance. To bridge this gap, research results should be systematically distilled into actionable guidance in a way that respects differences in strength and scope among the results. Starting with the practitioners’ need for actionable guidance, this article reviews the evolution of software engineering research expectations, identifies types of results and their strengths, and draws on evidence-based medicine for a concrete example of deriving pragmatic guidance from mixed-strength research results. It advances a levels-of-evidence framework to allow researchers to clearly identify the strengths of their claims and the supporting evidence for their results and to work with practitioners to synthesize actionable recommendations from diverse types of evidence. This article is part of a special issue on software engineering’s 50th anniversary."],"author":["Goues, C. L.","Jaspan, C.","Ozkaya, I.","Shaw, M.","Stolee, K. T."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571235"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"number":["5"],"pages":["50–57"],"shorttitle":["Bridging the Gap"],"title":["Bridging the Gap: From Research to Practical Advice"],"volume":["35"]},"creators":{"author":[{"lastName":"Goues","firstName":"C. L."},{"lastName":"Jaspan","firstName":"C."},{"lastName":"Ozkaya","firstName":"I."},{"lastName":"Shaw","firstName":"M."},{"lastName":"Stolee","firstName":"K. T."}]}},{"key":"GrahamjensonListRecommender","type":"online","fields":{"title":["Grahamjenson/List_of_recommender_systems: A List of Recommender Systems and Resources"],"url":["https://github.com/grahamjenson/list_of_recommender_systems"],"urldate":["2017-03-10"]},"creators":{}},{"key":"grayExplicitImplicitModels2022","type":"article","fields":{"langid":["english"],"author":["Gray, Jeff","Rumpe, Bernhard"],"date":["2022-04-07"],"doi":["10.1007/s10270-022-01001-4"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"pages":["s10270-022-01001-4"],"shorttitle":["Explicit versus implicit models"],"title":["Explicit versus implicit models: What are good languages for modeling?"]},"creators":{"author":[{"lastName":"Gray","firstName":"Jeff"},{"lastName":"Rumpe","firstName":"Bernhard"}]},"sentenceCased":true},{"key":"greifenbergEngineeringTaggingLanguages","type":"article","fields":{"author":["Greifenberg, Timo","Look, Markus","Roidl, Sebastian","Rumpe, Bernhard"],"note":["TL;DR \n\nThis paper presents a systematic approach to define a DSL-specific tag language and a corresponding schema language, combining the advantages of both worlds."],"title":["Engineering Tagging Languages for DSLs"],"url":["http://www.se-rwth.de/publications/Engineering-Tagging-Languages-for-DSLs.pdf"],"urldate":["2015-09-24"]},"creators":{"author":[{"lastName":"Greifenberg","firstName":"Timo"},{"lastName":"Look","firstName":"Markus"},{"lastName":"Roidl","firstName":"Sebastian"},{"lastName":"Rumpe","firstName":"Bernhard"}]}},{"key":"grigorevMLOps10Minutes","type":"article","fields":{"langid":["english"],"author":["Grigorev, Alexey"],"pages":["13"],"title":["MLOps in 10 Minutes_ by Alexey Grigorev _ Towards Data Science"]},"creators":{"author":[{"lastName":"Grigorev","firstName":"Alexey"}]}},{"key":"gronback_eclipse_2021","type":"misc","fields":{"langid":["english"],"abstract":["The Eclipse Foundation - home to a global community, the Eclipse IDE, Jakarta EE and over 375 open source projects, including runtimes, tools and frameworks."],"author":["Gronback, Richard"],"date":["2021-03"],"title":["Eclipse Modeling Project | The Eclipse Foundation"]},"creators":{"author":[{"lastName":"Gronback","firstName":"Richard"}]}},{"key":"Grossberg:2013:ART:2405841.2405958","type":"article","fields":{"acmid":["2405958"],"address":["Oxford, UK, UK"],"author":["Grossberg, Stephen"],"date":["2013-01"],"issn":["0893-6080"],"issue_date":["January, 2013"],"journaltitle":["Neural Netw."],"keywords":["Adaptive Resonance Theory","Adaptive timing","Amygdala","Attention","Basal ganglia","Consciousness","Entorhinal cortex","Expectation","Gamma and beta oscillations","Hippocampal cortex","Inferotemporal cortex","Learning","Parietal cortex","Prefrontal cortex","Recognition","reinforcement learning","Speech perception","Synchrony","Working memory"],"nodoi":["10.1016/j.neunet.2012.09.017"],"numpages":["47"],"pages":["1–47"],"publisher":["Elsevier Science Ltd."],"title":["Adaptive resonance theory: How a brain learns to consciously attend, learn, and recognize a changing world"],"url":["http://dx.doi.org/10.1016/j.neunet.2012.09.017"],"volume":["37"]},"creators":{"author":[{"lastName":"Grossberg","firstName":"Stephen"}]},"sentenceCased":true},{"key":"GRuMFlexibleModelDriven","type":"misc","fields":{"keywords":["LOGSEQ"],"title":["GRuM – A Flexible Model-Driven Runtime Monitoring Framework and its Application to Automated Aerial and Ground Vehicls"]},"creators":{},"sentenceCased":true},{"key":"gu_assemble_2022","type":"inproceedings","fields":{"abstract":["Automatic code summarization is beneficial to software development and maintenance since it reduces the burden of manual tasks. Currently, artificial intelligence is undergoing a paradigm shift. The foundation models pretrained on massive data and finetuned to downstream tasks surpass specially customized models. This trend inspired us to consider reusing foundation models instead of learning from scratch. Based on this, we propose a flexible and robust approach for automatic code summarization based on neural networks. We assemble available foundation models, such as CodeBERT and GPT-2, into a single model named AdaMo. Moreover, we utilize Gaussian noise as the simulation of contextual information to optimize the latent representation. Furthermore, we introduce two adaptive schemes from the perspective of knowledge transfer, namely continuous pretraining and intermediate finetuning, and design intermediate stage tasks for general sequence-to-sequence learning. Finally, we evaluate AdaMo against a benchmark dataset for code summarization, by comparing it with state-of-the-art models."],"author":["Gu, Jian","Salza, Pasquale","Gall, Harald C."],"booktitle":["2022 IEEE Int. Conf. Softw. Anal. Evol. Reengineering SANER"],"date":["2022-03"],"doi":["10.1109/SANER53432.2022.00112"],"keywords":["Adaptation models","adaptive scheme","code summarization","Codes","Gaussian noise","Manuals","Market research","Neural networks","transfer learning","Transfer learning","Transformer"],"note":["ISSN: 1534-5351"],"pages":["935–946"],"title":["Assemble Foundation Models for Automatic Code Summarization"]},"creators":{"author":[{"lastName":"Gu","firstName":"Jian"},{"lastName":"Salza","firstName":"Pasquale"},{"lastName":"Gall","firstName":"Harald C."}]}},{"key":"Gu2016DeepAPI","type":"inproceedings","fields":{"author":["Gu, Xiaodong","Zhang, Hongyu","Zhang, Dongmei","Kim, Sunghun"],"booktitle":["24th ACM SIGSOFT Int. Symp. Found. Softw. Eng."],"date":["2016"],"doi":["10.1145/2950290.2950334"],"isbn":["978-1-4503-4218-6"],"location":["New York"],"nodoi":["10.1145/2950290.2950334"],"note":["TL;DR \n\nDeepAPI is proposed, a deep learning based approach to generate API usage sequences for a given natural language query that adapts a neural language model named RNN Encoder-Decoder, and generates an API sequence based on the context vector."],"pages":["631–642"],"publisher":["ACM"],"title":["Deep API learning"]},"creators":{"author":[{"lastName":"Gu","firstName":"Xiaodong"},{"lastName":"Zhang","firstName":"Hongyu"},{"lastName":"Zhang","firstName":"Dongmei"},{"lastName":"Kim","firstName":"Sunghun"}]},"sentenceCased":true},{"key":"Gu2018DeepCode","type":"inproceedings","fields":{"author":["Gu, Xiaodong","Zhang, Hongyu","Kim, Sunghun"],"booktitle":["40th Int. Conf. Softw. Eng."],"date":["2018"],"isbn":["978-1-4503-5638-1"],"location":["New York"],"nodoi":["10.1145/3180155.3180167"],"pages":["933–944"],"publisher":["ACM"],"title":["Deep code search"]},"creators":{"author":[{"lastName":"Gu","firstName":"Xiaodong"},{"lastName":"Zhang","firstName":"Hongyu"},{"lastName":"Kim","firstName":"Sunghun"}]},"sentenceCased":true},{"key":"guanaChainTrackerModelTransformationTrace2014","type":"article","fields":{"author":["Guana, Victor","Stroulia, Eleni"],"date":["2014"],"doi":["10.1007/978-3-319-08789-4_11"],"journaltitle":["Theory Pract. Model Transform."],"note":["TL;DR \n\nThis paper presents ChainTracker, a general conceptual framework, and model-transformation composition analysis tool, that supports developers when maintaining and synchronizing evolving code-generation environments."],"pages":["146–153"],"title":["ChainTracker, a Model-Transformation Trace Analysis Tool for Code-Generation Environments"],"volume":["8568"]},"creators":{"author":[{"lastName":"Guana","firstName":"Victor"},{"lastName":"Stroulia","firstName":"Eleni"}]}},{"key":"guerraAutomatedVerificationModel2012","type":"article","fields":{"author":["Guerra, Esther","Lara, Juan","Wimmer, Manuel","Kappel, Gerti","Kusel, Angelika","Retschitzegger, Werner","Schönböck, Johannes","Schwinger, Wieland"],"date":["2012"],"doi":["10.1007/s10515-012-0102-y"],"journaltitle":["Autom. Softw. Eng."],"note":["TL;DR \n\nA declarative language for the specification of visual contracts is proposed, enabling the verification of transformations defined with any transformation language, i.e., irrespective of the actual transformation language used."],"number":["1"],"pages":["5–46"],"title":["Automated verification of model transformations based on visual contracts"],"volume":["20"]},"creators":{"author":[{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Lara","firstName":"Juan"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Kappel","firstName":"Gerti"},{"lastName":"Kusel","firstName":"Angelika"},{"lastName":"Retschitzegger","firstName":"Werner"},{"lastName":"Schönböck","firstName":"Johannes"},{"lastName":"Schwinger","firstName":"Wieland"}]},"sentenceCased":true},{"key":"GuestEditorialSpecial","type":"online","fields":{"title":["Guest Editorial: Special issue on constrained decision-making in robotics - Online First - Springer"],"url":["http://link.springer.com/article/10.1007/s10514-015-9489-1"],"urldate":["2015-08-19"]},"creators":{},"sentenceCased":true},{"key":"Guha:1998:CEC:276305.276312","type":"article","fields":{"acmid":["276312"],"address":["New York, NY, USA"],"author":["Guha, Sudipto","Rastogi, Rajeev","Shim, Kyuseok"],"date":["1998-06"],"issn":["0163-5808"],"issue_date":["June 1998"],"journaltitle":["SIGMOD Rec."],"nodoi":["10.1145/276305.276312"],"number":["2"],"numpages":["12"],"pages":["73–84"],"publisher":["ACM"],"title":["CURE: An efficient clustering algorithm for large databases"],"url":["http://doi.acm.org/10.1145/276305.276312"],"volume":["27"]},"creators":{"author":[{"lastName":"Guha","firstName":"Sudipto"},{"lastName":"Rastogi","firstName":"Rajeev"},{"lastName":"Shim","firstName":"Kyuseok"}]},"sentenceCased":true},{"key":"GuideIntelligentCode","type":"online","fields":{"title":["A Guide to Intelligent Code Completion Using Eclipse Code Recommenders"],"url":["https://medium.com/codetrails/insert-knowledge-here-a2f71c2862d2"]},"creators":{}},{"key":"GuideLowcodePlatforms","type":"online","fields":{"keywords":["lowcode"],"title":["A Guide to Low-code Platforms - Federico Tomassetti - Software Architect"],"url":["https://tomassetti.me/a-guide-to-low-code-platforms/"],"urldate":["2020-04-08"]},"creators":{}},{"key":"Gunawardana:2009:UAB:1639714.1639735","type":"inproceedings","fields":{"acmid":["1639735"],"author":["Gunawardana, Asela","Meek, Christopher"],"booktitle":["Proc. 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Intell."],"date":["2013"],"isbn":["978-1-57735-633-2"],"location":["Beijing, China"],"numpages":["7"],"pages":["2619–2625"],"publisher":["AAAI Press"],"series":["IJCAI '13"],"title":["A novel bayesian similarity measure for recommender systems"],"url":["http://dl.acm.org/citation.cfm?id=2540128.2540506"]},"creators":{"author":[{"lastName":"Guo","firstName":"Guibing"},{"lastName":"Zhang","firstName":"Jie"},{"lastName":"Yorke-Smith","firstName":"Neil"}]},"sentenceCased":true},{"key":"Guo2015","type":"article","fields":{"langid":["english"],"abbrev_source_title":["ACM Trans. Design Autom. Electron. Syst."],"affiliation":["Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, United States; State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China; National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210023, China; Inria, France; Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China; Beihang University, Beijing, 100191, China"],"art_number":["18"],"author":["Guo, Q.","Chen, T.","Zhou, Z.-H.","Temam, O.","Li, L.","Qian, D.","Chen, Y."],"correspondence_address1":["Chen, Y.; State Key Laboratory of Computer Architecture, China"],"date":["2015"],"document_type":["Article"],"doi":["10.1145/2668118"],"issn":["10844309"],"journaltitle":["ACM Trans. Des. Autom. Electron. Syst."],"note":["cited By 6"],"number":["2"],"publisher":["Association for Computing Machinery"],"source":["Scopus"],"title":["Robust design space modeling"],"volume":["20"]},"creators":{"author":[{"lastName":"Guo","firstName":"Q."},{"lastName":"Chen","firstName":"T."},{"lastName":"Zhou","firstName":"Z.-H."},{"lastName":"Temam","firstName":"O."},{"lastName":"Li","firstName":"L."},{"lastName":"Qian","firstName":"D."},{"lastName":"Chen","firstName":"Y."}]},"sentenceCased":true},{"key":"Guo2022547","type":"article","fields":{"abstract":["In order to achieve reliable communication with a high data rate of massive multiple-input multiple-output (MIMO) systems in frequency division duplex (FDD) mode, the estimated channel state information (CSI) at the receiver needs to be fed back to the transmitter. However, the feedback overhead becomes exorbitant with the increasing number of antennas. In this letter, a two stages low rank (TSLR) CSI feedback scheme for millimeter wave (mmWave) massive MIMO systems is proposed to reduce the feedback overhead based on model-driven deep learning. Besides, we design a deep iterative neural network, named FISTA-Net, by unfolding the fast iterative shrinkage thresholding algorithm (FISTA) to achieve more efficient CSI feedback. Moreover, a shrinkage thresholding network (ST-Net) is designed in FISTA-Net based on the attention mechanism, which can choose the threshold adaptively. Simulation results show that the proposed TSLR CSI feedback scheme and FISTA-Net outperform the existing algorithms in various scenarios. © 1997-2012 IEEE."],"author":["Guo, J.","Wang, L.","Li, F.","Xue, J."],"coden":["ICLEF"],"date":["2022"],"document_type":["Article"],"doi":["10.1109/LCOMM.2021.3138927"],"issn":["10897798"],"journaltitle":["IEEE Commun. Lett."],"note":["cited By 0"],"number":["3"],"pages":["547–551"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["CSI feedback with model-driven deep learning of massive MIMO systems"],"volume":["26"]},"creators":{"author":[{"lastName":"Guo","firstName":"J."},{"lastName":"Wang","firstName":"L."},{"lastName":"Li","firstName":"F."},{"lastName":"Xue","firstName":"J."}]},"sentenceCased":true},{"key":"guoGraphCodeBERTPretrainingCode2021","type":"online","fields":{"abstract":["Pre-trained models for programming language have achieved dramatic empirical improvements on a variety of code-related tasks such as code search, code completion, code summarization, etc. However, existing pre-trained models regard a code snippet as a sequence of tokens, while ignoring the inherent structure of code, which provides crucial code semantics and would enhance the code understanding process. We present GraphCodeBERT, a pre-trained model for programming language that considers the inherent structure of code. Instead of taking syntactic-level structure of code like abstract syntax tree (AST), we use data flow in the pre-training stage, which is a semantic-level structure of code that encodes the relation of \"where-the-value-comes-from\" between variables. Such a semantic-level structure is neat and does not bring an unnecessarily deep hierarchy of AST, the property of which makes the model more efficient. We develop GraphCodeBERT based on Transformer. In addition to using the task of masked language modeling, we introduce two structure-aware pre-training tasks. One is to predict code structure edges, and the other is to align representations between source code and code structure. We implement the model in an efficient way with a graph-guided masked attention function to incorporate the code structure. We evaluate our model on four tasks, including code search, clone detection, code translation, and code refinement. Results show that code structure and newly introduced pre-training tasks can improve GraphCodeBERT and achieves state-of-the-art performance on the four downstream tasks. We further show that the model prefers structure-level attentions over token-level attentions in the task of code search."],"author":["Guo, Daya","Ren, Shuo","Lu, Shuai","Feng, Zhangyin","Tang, Duyu","Liu, Shujie","Zhou, Long","Duan, Nan","Svyatkovskiy, Alexey","Fu, Shengyu","Tufano, Michele","Deng, Shao Kun","Clement, Colin","Drain, Dawn","Sundaresan, Neel","Yin, Jian","Jiang, Daxin","Zhou, Ming"],"date":["2021-09-13"],"eprint":["2009.08366"],"eprintclass":["cs"],"eprinttype":["arxiv"],"ids":["GraphCodeBERT_2021"],"issue":["arXiv:2009.08366"],"keywords":["Computer Science - Computation and Language","Computer Science - Software Engineering"],"note":["arXiv:2009.08366 [cs] \n\nComment: Accepted by ICLR2021"],"pubstate":["preprint"],"shorttitle":["GraphCodeBERT"],"title":["GraphCodeBERT: Pre-training Code Representations with Data Flow"],"url":["http://arxiv.org/abs/2009.08366"],"urldate":["2023-05-04"]},"creators":{"author":[{"lastName":"Guo","firstName":"Daya"},{"lastName":"Ren","firstName":"Shuo"},{"lastName":"Lu","firstName":"Shuai"},{"lastName":"Feng","firstName":"Zhangyin"},{"lastName":"Tang","firstName":"Duyu"},{"lastName":"Liu","firstName":"Shujie"},{"lastName":"Zhou","firstName":"Long"},{"lastName":"Duan","firstName":"Nan"},{"lastName":"Svyatkovskiy","firstName":"Alexey"},{"lastName":"Fu","firstName":"Shengyu"},{"lastName":"Tufano","firstName":"Michele"},{"lastName":"Deng","firstName":"Shao Kun"},{"lastName":"Clement","firstName":"Colin"},{"lastName":"Drain","firstName":"Dawn"},{"lastName":"Sundaresan","firstName":"Neel"},{"lastName":"Yin","firstName":"Jian"},{"lastName":"Jiang","firstName":"Daxin"},{"lastName":"Zhou","firstName":"Ming"}]}},{"key":"guthDetailedAnalysisIoT2018","type":"incollection","fields":{"langid":["english"],"author":["Guth, Jasmin","Breitenbücher, Uwe","Falkenthal, Michael","Fremantle, Paul","Kopp, Oliver","Leymann, Frank","Reinfurt, Lukas"],"booktitle":["Internet of Everything"],"date":["2018"],"doi":["10.1007/978-981-10-5861-5_4"],"editor":["Di Martino, Beniamino","Li, Kuan-Ching","Yang, Laurence T.","Esposito, Antonio"],"isbn":["978-981-10-5860-8 978-981-10-5861-5"],"location":["Singapore"],"note":["TL;DR \n\nIt is shown that the various components of the different platforms can be mapped to an abstract reference architecture, and the effectiveness of this mapping is analyzed."],"pages":["81–101"],"publisher":["Springer Singapore"],"shorttitle":["A Detailed Analysis of IoT Platform Architectures"],"title":["A Detailed Analysis of IoT Platform Architectures: Concepts, Similarities, and Differences"]},"creators":{"author":[{"lastName":"Guth","firstName":"Jasmin"},{"lastName":"Breitenbücher","firstName":"Uwe"},{"lastName":"Falkenthal","firstName":"Michael"},{"lastName":"Fremantle","firstName":"Paul"},{"lastName":"Kopp","firstName":"Oliver"},{"lastName":"Leymann","firstName":"Frank"},{"lastName":"Reinfurt","firstName":"Lukas"}],"editor":[{"lastName":"Di Martino","firstName":"Beniamino"},{"lastName":"Li","firstName":"Kuan-Ching"},{"lastName":"Yang","firstName":"Laurence T."},{"lastName":"Esposito","firstName":"Antonio"}]}},{"key":"Gutierrez20171565","type":"inproceedings","fields":{"abstract":["Honeypots axe decoy cyberdefense systems placed in a network to entice malicious entities into attacking in order to waste attacker resources and learn information about attack behavior or previously unknown exploits. We focus on the strategic selection of various honeypot configurations in order to adapt to an intelligent attacker amidst a dynamic environment. In order to infiltrate networks, attackers leverage various exploits on the system. However, these exploits and the value they provide dynamically change over time as more information is gathered about them. We intro-duce a model that addresses the combinatorial complexity of the honeypot selection problem and allow for these dynamic exploits. To solve this new problem, we map this model to a Multi-Armed Bandit (MAB) problem, which is a class of machine learning problems that maintain balance between exploration and exploitation. We show empirically that both stochastic and adversarial MAB solutions improve over static defense strategies. © Copyright 2017, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved."],"author":["Gutierrez, M.","Kiekintveld, C."],"author_keywords":["Adversarial learning; Exploit; Honeynet; Honeypot; Machine learning; Modelling and simulation"],"date":["2017"],"document_type":["Conference Paper"],"editor":["Durfee E., Winikoff M., Das S., Larson K."],"isbn":["978-1-5108-5507-6"],"issn":["15488403"],"keywords":["Adversarial learning","Autonomous agents","Computer aided software engineering","Exploit","Honeynet","Honeypots","Learning systems","Modelling and simulations","Multi agent systems","Network security","Problem solving","Stochastic systems"],"note":["cited By 3 \n\nTL;DR \n\nThis work introduces a model that addresses the combinatorial complexity of the honeypot selection problem and allows for these dynamic exploits on the system and shows empirically that both stochastic and adversarial MAB solutions improve over static defense strategies."],"pages":["1565–1567"],"publisher":["International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)"],"series":["Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS"],"source":["Scopus"],"title":["Adapting with honeypot configurations to detect evolving exploits"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046433349&partnerID=40&md5=5c01c53b2c7284ad6257e977525865f4"],"volume":["3"]},"creators":{"author":[{"lastName":"Gutierrez","firstName":"M."},{"lastName":"Kiekintveld","firstName":"C."}],"editor":[{"lastName":"Durfee E.","suffix":"Winikoff M.","firstName":"Das S., Larson K."}]},"sentenceCased":true},{"key":"haddadProceedings2005ACM2005","type":"book","fields":{"date":["2005"],"doi":["10.1145/1066677"],"editor":["Haddad, Hisham","Liebrock, Lorie M.","Omicini, Andrea","Wainwright, Roger L."],"isbn":["1-58113-964-0"],"note":["TL;DR \n\nThe symposium provides an avenue for discussion and exchange of new ideas addressing computational algorithms and complex applications, reflected in the spectrum of application areas and tutorials designed to provide a wide range of discussion topics during this event."],"publisher":["ACM"],"title":["Proceedings of the 2005 ACM Symposium on Applied Computing (SAC), Santa Fe, New Mexico, USA, March 13-17, 2005"]},"creators":{"editor":[{"lastName":"Haddad","firstName":"Hisham"},{"lastName":"Liebrock","firstName":"Lorie M."},{"lastName":"Omicini","firstName":"Andrea"},{"lastName":"Wainwright","firstName":"Roger L."}]}},{"key":"hadipourAutomaticWashingSystem2018","type":"article","fields":{"langid":["english"],"abstract":["The illumination of the streets and public area in metropolitan cities is a vital service, which is not only related to the type of the light but also the dirtiness of the surface of the light. In this paper, both subjects are considered to increase the productivity of the light. To achieve this goal, a novel Automatic washing system (AWS) of LED street/public light surface was designed, manufactured and installed practically. The proposed mechanism consists of two main parts comprising mechanical and electrical systems. AWS operates based on internet interconnection technique known as Internet of Things (IoT) with a high productivity. The system has the potential to be designed and employed by four types of control system; (i) using a timer switch, (ii) using a GSM 900, (iii) using a push button manually by an operator, and (iv) using a remote-control module such as GSM, SIM 808 or GPRS/GPS/SMS through the Ethernet network. A practical system has been manufactured and installed in Kermanshah city in Iran, due to its low cost, low maintenance, upgradability, and feasibility of installing different recognition sensors such as rain and dust sensors. © 2018 Elsevier B.V. All rights reserved."],"author":["Hadipour, Morteza","Derakhshandeh, Javad Farrokhi","Shiran, Mohsen Aghazadeh","Rezaei, Reza"],"date":["2018-09"],"doi":["10.1016/j.iot.2018.08.006"],"issn":["25426605"],"journaltitle":["Internet Things"],"pages":["74–80"],"title":["Automatic washing system of LED street lighting via Internet of Things"],"volume":["1–2"]},"creators":{"author":[{"lastName":"Hadipour","firstName":"Morteza"},{"lastName":"Derakhshandeh","firstName":"Javad Farrokhi"},{"lastName":"Shiran","firstName":"Mohsen Aghazadeh"},{"lastName":"Rezaei","firstName":"Reza"}]},"sentenceCased":true},{"key":"hadoop","type":"misc","fields":{"title":["Apache Hadoop"],"url":["https://hadoop.apache.org/"]},"creators":{}},{"key":"HaertelHHLV17","type":"article","fields":{"author":["Härtel, Johannes","Härtel, Lukas","Heinz, Marcel","Lämmel, Ralf","Varanovich, Andrei"],"date":["2017"],"journaltitle":["Art Sci. Eng. Program. J."],"note":["27 pages."],"number":["1"],"title":["Interconnected linguistic architecture"],"volume":["1"]},"creators":{"author":[{"lastName":"Härtel","firstName":"Johannes"},{"lastName":"Härtel","firstName":"Lukas"},{"lastName":"Heinz","firstName":"Marcel"},{"lastName":"Lämmel","firstName":"Ralf"},{"lastName":"Varanovich","firstName":"Andrei"}]},"sentenceCased":true},{"key":"Halkidi01onclustering","type":"article","fields":{"author":["Halkidi, Maria","Batistakis, Yannis","Vazirgiannis, Michalis"],"date":["2001"],"journaltitle":["J. Intell. Inf. Syst."],"pages":["107–145"],"title":["On clustering validation techniques"],"volume":["17"]},"creators":{"author":[{"lastName":"Halkidi","firstName":"Maria"},{"lastName":"Batistakis","firstName":"Yannis"},{"lastName":"Vazirgiannis","firstName":"Michalis"}]},"sentenceCased":true},{"key":"hallWEKADataMining2009","type":"article","fields":{"acmid":["1656278"],"address":["New York, NY, USA"],"author":["Hall, Mark","Frank, Eibe","Holmes, Geoffrey","Pfahringer, Bernhard","Reutemann, Peter","Witten, Ian H."],"date":["2009-11"],"issn":["1931-0145"],"issue_date":["June 2009"],"journaltitle":["SIGKDD Explor. Newsl."],"nodoi":["10.1145/1656274.1656278"],"number":["1"],"numpages":["9"],"pages":["10–18"],"publisher":["ACM"],"title":["The WEKA data mining software: An update"],"url":["http://doi.acm.org/10.1145/1656274.1656278"],"volume":["11"]},"creators":{"author":[{"lastName":"Hall","firstName":"Mark"},{"lastName":"Frank","firstName":"Eibe"},{"lastName":"Holmes","firstName":"Geoffrey"},{"lastName":"Pfahringer","firstName":"Bernhard"},{"lastName":"Reutemann","firstName":"Peter"},{"lastName":"Witten","firstName":"Ian H."}]},"sentenceCased":true},{"key":"hamidModelDrivenMethodologyApproach2014","type":"incollection","fields":{"author":["Hamid, Brahim"],"booktitle":["Model and Data Engineering"],"date":["2014"],"pages":["29–44"],"publisher":["Springer"],"title":["A Model-Driven Methodology Approach for Developing a Repository of Models"],"url":["http://link.springer.com/chapter/10.1007/978-3-319-11587-0_5"],"urldate":["2015-10-29"]},"creators":{"author":[{"lastName":"Hamid","firstName":"Brahim"}]}},{"key":"hamiltonWhatErrorsTell2018","type":"article","fields":{"abstract":["Margaret Hamilton talks about her experiences over the last 60 years and how a “theory of errors” was derived from the errors made along the way. Its axioms of control led to the Universal Systems Language (USL) together with its automation and preventative paradigm, development-before-the-fact. The pressing issues haven’t gone away, largely because the traditional paradigm continues in force. With a preventative paradigm, most errors aren’t allowed into a system in the first place, just by the way the system is defined. Unlike a traditional approach, with a preventative approach the more reliable the system, the higher the productivity in its lifecycle. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Hamilton, M. H."],"date":["2018-09"],"doi":["10.1109/MS.2018.290110447"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"note":["TL;DR \n\nMargaret Hamilton talks about her experiences over the last 60 years and how a “theory of errors” was derived from the errors made along the way, which led to the Universal Systems Language (USL) together with its automation and preventative paradigm, development-before-the-fact."],"number":["5"],"pages":["32–37"],"title":["What the Errors Tell Us"],"volume":["35"]},"creators":{"author":[{"lastName":"Hamilton","firstName":"M. H."}]}},{"key":"hammadDeepCloneModelingClones2020","type":"article","fields":{"abstract":["Programmers often reuse code from source code repositories to reduce the development effort. Code clones are candidates for reuse in exploratory or rapid development, as they represent often repeated functionality in software systems. To facilitate code clone reuse, we propose DeepClone, a novel approach utilizing a deep learning algorithm for modeling code clones to predict the next set of tokens (possibly a complete clone method body) based on the code written so far. The predicted tokens require minimal customization to fit the context. DeepClone applies natural language processing techniques to learn from a large code corpus, and generates code tokens using the model learned. We have quantitatively evaluated our solution to assess (1) our model's quality and its accuracy in token prediction, and (2) its performance and effectiveness in clone method prediction. We also discuss various application scenarios for our approach."],"author":["Hammad, Muhammad","Babur, Önder","Basit, Hamid Abdul","family=Brand, given=Mark, prefix=van den, useprefix=false"],"date":["2020-12-05"],"eprint":["2007.11671"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv200711671 Cs"],"keywords":["Computer Science - Software Engineering"],"note":["Comment: 16 pages"],"shorttitle":["DeepClone"],"title":["DeepClone: Modeling Clones to Generate Code Predictions"],"url":["http://arxiv.org/abs/2007.11671"],"urldate":["2021-02-02"]},"creators":{"author":[{"lastName":"Hammad","firstName":"Muhammad"},{"lastName":"Babur","firstName":"Önder"},{"lastName":"Basit","firstName":"Hamid Abdul"},{"lastName":"Brand","firstName":"Mark","prefix":"vanden","useprefix":false}]}},{"key":"HammoudehGarcia2019329","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - IEEE Int. Conf. Robot. Comput., IRC"],"affiliation":["Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Nobelstr. 12, Stuttgart, 70569, Germany"],"art_number":["8675668"],"author":["Hammoudeh Garcia, N.","Ludtke, M.","Kortik, S.","Kahl, B.","Bordignon, M."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/IRC.2019.00060"],"isbn":["978-1-5386-9245-5"],"note":["cited By 11 \n\nTL;DR \n\nA family of three metamodels to respectively model ROS nodes, communication interfaces, and systems composed from subsystems are presented, used to model ROS systems of arbitrary complexity and generate with correctness guarantees the software artifacts for their composition and deployment."],"pages":["329–336"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 3rd IEEE International Conference on Robotic Computing, IRC 2019"],"source":["Scopus"],"title":["Bootstrapping MDE development from ROS manual code - part 1: Metamodeling"]},"creators":{"author":[{"lastName":"Hammoudeh Garcia","firstName":"N."},{"lastName":"Ludtke","firstName":"M."},{"lastName":"Kortik","firstName":"S."},{"lastName":"Kahl","firstName":"B."},{"lastName":"Bordignon","firstName":"M."}]},"sentenceCased":true},{"key":"Hamrani2021","type":"article","fields":{"abbrev_source_title":["Int. J. Comput. Methods"],"abstract":["This paper presents a machine learning (ML) surrogate modeling for fast processing in meshless/meshfree methods. The main idea is to leverage the universal approximation (UA) propriety of supervised ML models (shallow/deep learning and other regression models) to surrogate the heavy shape function construction in meshless methods. The resulting ML metamodel preserves the same accuracy of the meshless interpolation while avoiding costly matrix inversion operations. The total computation time for solving 3D test simulation problems (using more than 20k nodes) is reduced by a factor of 1k in the case of the Gaussian process (GP) metamodel. © 2021 World Scientific Publishing Company."],"affiliation":["Department of Mechanical and Materials Engineering, Florida International University, Miami, FL, United States; Department of Bioresource Engineering, McGill University, Montreal, QC H9X3V9, Canada; Department of Mechanical Engineering, McGill University, Montreal, QC H3A 0C3, Canada; UR-MPE Université m'Hamed Bougara, rue de la liberté, Boumerdès, 35000, Algeria"],"art_number":["2141022"],"author":["Hamrani, A.","Akbarzadeh, A.","Madramootoo, C.A.","Bouarab, F.Z."],"correspondence_address1":["Hamrani, A.; Department of Mechanical and Materials Engineering, United States; email: hamrani.abderrachid@gmail.com"],"date":["2021"],"document_type":["Article"],"doi":["10.1142/S021987622141022X"],"issn":["02198762"],"journaltitle":["Int. J. Comput. Methods"],"keywords":["notion"],"note":["cited By 0 \n\ncited By 0 \n\nTL;DR \n\nThe main idea is to leverage the universal approximation (UA) propriety of supervised ML models (shallow/deep learning and other regression models) to surrogate the heavy shape function construction in meshless methods."],"publisher":["World Scientific"],"source":["Scopus"],"title":["Machine learning surrogate modeling for meshless methods: Leveraging universal approximation"]},"creators":{"author":[{"lastName":"Hamrani","firstName":"A."},{"lastName":"Akbarzadeh","firstName":"A."},{"lastName":"Madramootoo","firstName":"C.A."},{"lastName":"Bouarab","firstName":"F.Z."}]},"sentenceCased":true},{"key":"Han2019108","type":"article","fields":{"abstract":["Deep neural networks (DNNs) have been achieving excellent performance in many learning tasks. However, recent studies reveal that DNNs are vulnerable to adversarial examples. Fortunately, a random feature nullification (RFN) algorithm is proposed to improve the robustness of DNNs against gradient-based adversarial examples. However, experimental results demonstrate that RFN ruins the availability of DNNs in some cases. To explore more efficient feature nullification (FN) algorithms, we theoretically prove that FN can improve the robustness of DNNs. Moreover, sliding window feature nullification (SWFN) and fixed stride feature nullification (FSFN) algorithms are proposed to improve the robustness of DNNs. The experimental results demonstrate that compared to RFN, the proposed algorithms can maintain the availability of DNNs without decreasing its robustness against gradient-based attacks. © 2019 Elsevier B.V."],"author":["Han, K.","Li, Y.","Hang, J."],"author_keywords":["Adversarial machine learning; Deep learning; Feature nullification; Hadamard product"],"coden":["KNSYE"],"date":["2019"],"document_type":["Article"],"doi":["10.1016/j.knosys.2019.05.007"],"issn":["09507051"],"journaltitle":["Knowl.-Based Syst."],"keywords":["Artificial intelligence","Deep learning","Deep neural networks","Feature nullification","Gradient based","Hadamard products","Knowledge based systems","Learning tasks","Random features","Sliding Window","Software engineering"],"note":["cited By 4"],"pages":["108–116"],"publisher":["Elsevier B.V."],"source":["Scopus"],"title":["Adversary resistant deep neural networks via advanced feature nullification"],"volume":["179"]},"creators":{"author":[{"lastName":"Han","firstName":"K."},{"lastName":"Li","firstName":"Y."},{"lastName":"Hang","firstName":"J."}]},"sentenceCased":true},{"key":"Han20201980","type":"article","fields":{"abstract":["This paper proposes a model-driven deep learning-based downlink channel reconstruction scheme for frequency division duplexing (FDD) massive multi-input multi-output (MIMO) systems. The spatial non-stationarity, which is the key feature of the future extremely large aperture massive MIMO system, is considered. Instead of the channel matrix, the channel model parameters are learned by neural networks to save the overhead and improve the accuracy of channel reconstruction. By viewing the channel as an image, we introduce You Only Look Once (YOLO), a powerful neural network for object detection, to enable a rapid estimation process of the model parameters, including the detection of angles and delays of the paths and the identification of visibility regions of the scatterers. The deep learning-based scheme avoids the complicated iterative process introduced by the algorithm-based parameter extraction methods. A low-complexity algorithm-based refiner further refines the YOLO estimates toward high accuracy. Given the efficiency of model-driven deep learning and the combination of neural network and algorithm, the proposed scheme can rapidly and accurately reconstruct the non-stationary downlink channel. Moreover, the proposed scheme is also applicable to widely concerned stationary systems and achieves comparable reconstruction accuracy as an algorithm-based method with greatly reduced time consumption. © 1983-2012 IEEE."],"art_number":["9110882"],"author":["Han, Y.","Li, M.","Jin, S.","Wen, C.-K.","Ma, X."],"coden":["ISACE"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/JSAC.2020.3000836"],"issn":["07338716"],"journaltitle":["IEEE J. Sel. Areas Commun."],"note":["cited By 10 \n\nTL;DR \n\nSeeing the channel as an image, You Only Look Once (YOLO), a powerful neural network for object detection, is introduced to enable a rapid estimation process of the model parameters, including the detection of angles and delays of the paths and the identification of visibility regions of the scatterers."],"number":["9"],"pages":["1980–1993"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Deep learning-based FDD non-stationary massive MIMO downlink channel reconstruction"],"volume":["38"]},"creators":{"author":[{"lastName":"Han","firstName":"Y."},{"lastName":"Li","firstName":"M."},{"lastName":"Jin","firstName":"S."},{"lastName":"Wen","firstName":"C.-K."},{"lastName":"Ma","firstName":"X."}]},"sentenceCased":true},{"key":"HandsonManageYour","type":"online","fields":{"title":["Hands-on: Manage your devices with Lightweight M2M and connect them to your cloud | EclipseCon Europe 2016"],"url":["https://www.eclipsecon.org/europe2016/session/hands-manage-your-devices-lightweight-m2m-and-connect-them-your-cloud"],"urldate":["2016-09-27"]},"creators":{},"sentenceCased":true},{"key":"happelPotentialsChallengesRecommendation2008","type":"inproceedings","fields":{"langid":["english"],"abstract":["By surveying recommendation systems in software development, we found that existing approaches have been focusing on “you might like what similar developers like” scenarios. However structured artifacts and semantically well-defined development activities bear large potentials for further recommendation scenarios. We introduce a novel “landscape” of software development recommendation systems and line out several scenarios for knowledge sharing and collaboration. Basic challenges are improving context-awareness and particularly addressing information providers."],"author":["Happel, Hans-Jörg","Maalej, Walid"],"booktitle":["Proc. 2008 Int. Workshop Recomm. Syst. Softw. Eng. - RSSE 08"],"date":["2008"],"isbn":["978-1-60558-228-3"],"location":["Atlanta, Georgia"],"nodoi":["10.1145/1454247.1454251"],"note":["TL;DR \n\nA novel \"landscape\" of software development recommendation systems is introduced and several scenarios for knowledge sharing and collaboration are line out."],"pages":["11"],"publisher":["ACM Press"],"title":["Potentials and challenges of recommendation systems for software development"],"url":["http://portal.acm.org/citation.cfm?doid=1454247.1454251"],"urldate":["2019-06-13"]},"creators":{"author":[{"lastName":"Happel","firstName":"Hans-Jörg"},{"lastName":"Maalej","firstName":"Walid"}]},"sentenceCased":true},{"key":"Harel-Canada2020851","type":"inproceedings","fields":{"abstract":["Recent effort to test deep learning systems has produced an intuitive and compelling test criterion called neuron coverage (NC), which resembles the notion of traditional code coverage. NC measures the proportion of neurons activated in a neural network and it is implicitly assumed that increasing NC improves the quality of a test suite. In an attempt to automatically generate a test suite that increases NC, we design a novel diversity promoting regularizer that can be plugged into existing adversarial attack algorithms. We then assess whether such attempts to increase NC could generate a test suite that (1) detects adversarial attacks successfully, (2) produces natural inputs, and (3) is unbiased to particular class predictions. Contrary to expectation, our extensive evaluation finds that increasing NC actually makes it harder to generate an effective test suite: higher neuron coverage leads to fewer defects detected, less natural inputs, and more biased prediction preferences. Our results invoke skepticism that increasing neuron coverage may not be a meaningful objective for generating tests for deep neural networks and call for a new test generation technique that considers defect detection, naturalness, and output impartiality in tandem. © 2020 Owner/Author."],"author":["Harel-Canada, F.","Wang, L.","Gulzar, M.A.","Gu, Q.","Kim, M."],"author_keywords":["Adversarial Attack; Machine Learning; Neuron Coverage; Software Engineering; Testing"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3368089.3409754"],"editor":["Devanbu P., Cohen M., Zimmermann T."],"isbn":["978-1-4503-7043-1"],"keywords":["Class prediction","Code coverage","Deep learning","Deep neural networks","Defect detection","Defects","Learning systems","Neural networks","Neurons","Regularizer","Software engineering","Test criteria","Test generations","Testing"],"note":["cited By 47 \n\nTL;DR \n\nThe results invoke skepticism that increasing neuron coverage may not be a meaningful objective for generating tests for deep neural networks and call for a new test generation technique that considers defect detection, naturalness, and output impartiality in tandem."],"pages":["851–862"],"publisher":["Association for Computing Machinery, Inc"],"series":["ESEC/FSE 2020 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering"],"source":["Scopus"],"title":["Is neuron coverage a meaningful measure for testing deep neural networks?"]},"creators":{"author":[{"lastName":"Harel-Canada","firstName":"F."},{"lastName":"Wang","firstName":"L."},{"lastName":"Gulzar","firstName":"M.A."},{"lastName":"Gu","firstName":"Q."},{"lastName":"Kim","firstName":"M."}],"editor":[{"lastName":"Devanbu P.","suffix":"Cohen M.","firstName":"Zimmermann T."}]},"sentenceCased":true},{"key":"harelAutonomicsSearchFoundation2020","type":"article","fields":{"langid":["english"],"abstract":["Significance Autonomous systems are replacing humans in a variety of tasks, and in the years to come, such systems will become central and crucial to human life. They will include vehicles of all kinds, medical and industrial robots, agricultural and manufacturing facilities, traffic management systems, and much more. While many organizations strive to develop the next generation of trustworthy, cost-effective autonomous systems, a major gap exists between the challenges in developing these and the state of the art. There is a crucial need for a common scientific and engineering foundation for developing these systems, which we term “autonomics.” We believe that such a foundation will dramatically accelerate the deployment and acceptance of high-quality autonomous systems, for the benefit of human society. , The potential benefits of autonomous systems are obvious. However, there are still major issues to be dealt with before developing such systems becomes a commonplace engineering practice, with accepted and trustworthy deliverables. We argue that a solid, evolving, publicly available, community-controlled foundation for developing next-generation autonomous systems is a must, and term the desired foundation “autonomics.” We focus on three main challenges: 1) how to specify autonomous system behavior in the face of unpredictability; 2) how to carry out faithful analysis of system behavior with respect to rich environments that include humans, physical artifacts, and other systems; and 3) how to build such systems by combining executable modeling techniques from software engineering with artificial intelligence and machine learning."],"author":["Harel, David","Marron, Assaf","Sifakis, Joseph"],"date":["2020-07-28"],"doi":["10.1073/pnas.2003162117"],"issn":["0027-8424, 1091-6490"],"journaltitle":["Proc. Natl. Acad. Sci. U.S.A."],"note":["TL;DR \n\nIt is argued that a solid, evolving, publicly available, community-controlled foundation for developing next-generation autonomous systems is a must, and term the desired foundation “autonomics.”"],"number":["30"],"pages":["17491–17498"],"shorttitle":["Autonomics"],"title":["Autonomics: In search of a foundation for next-Generation autonomous systems"],"volume":["117"]},"creators":{"author":[{"lastName":"Harel","firstName":"David"},{"lastName":"Marron","firstName":"Assaf"},{"lastName":"Sifakis","firstName":"Joseph"}]},"sentenceCased":true},{"key":"harelCreatingFoundationNextGeneration2022","type":"article","fields":{"author":["Harel, David","Marron, Assaf","Sifakis, Joseph"],"date":["2022-02"],"doi":["10.1109/MDAT.2021.3069959"],"issn":["2168-2356, 2168-2364"],"journaltitle":["IEEE Des. Test"],"note":["TL;DR \n\nThe need for a new autonomics foundation with a focus on decision-making logic and its processes for building trustworthy autonomous systems is advocated."],"number":["1"],"pages":["49–56"],"title":["Creating a Foundation for Next-Generation Autonomous Systems"],"volume":["39"]},"creators":{"author":[{"lastName":"Harel","firstName":"David"},{"lastName":"Marron","firstName":"Assaf"},{"lastName":"Sifakis","firstName":"Joseph"}]}},{"key":"harelDevelopmentReactiveSystems1985","type":"incollection","fields":{"langid":["english"],"author":["Harel, D.","Pnueli, A."],"booktitle":["Logics and Models of Concurrent Systems"],"date":["1985"],"doi":["10.1007/978-3-642-82453-1_17"],"editor":["Apt, Krzysztof R."],"isbn":["978-3-642-82455-5 978-3-642-82453-1"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nThe recently proposed statechart method is recommended for finding satisfactory methods for behavioral description in reactive systems, observing that most reactive systems cannot be developed in a linear stepwise fashion, but, rather, give rise to a two-dimensional development process, featuring behavioral aspects in the one dimension and implementational ones in the other."],"pages":["477–498"],"publisher":["Springer Berlin Heidelberg"],"title":["On the Development of Reactive Systems"]},"creators":{"author":[{"lastName":"Harel","firstName":"D."},{"lastName":"Pnueli","firstName":"A."}],"editor":[{"lastName":"Apt","firstName":"Krzysztof R."}]}},{"key":"harelLaborDivisionMovable2019","type":"article","fields":{"abstract":["Artificial intelligence (AI) techniques, including, e.g., machine learning, multi-agent collaboration, planning, and heuristic search, are emerging as ever-stronger tools for solving hard problems in real-world applications. Executable specification techniques (ES), including, e.g., Statecharts and scenario-based programming, is a promising development approach, offering intuitiveness, ease of enhancement, compositionality, and amenability to formal analysis. We propose an approach for integrating AI and ES techniques in developing complex intelligent systems, which can greatly simplify agile/spiral development and maintenance processes. The approach calls for automated detection of whether certain goals and sub-goals are met; a clear division between sub-goals solved with AI and those solved with ES; compositional and incremental addition of AI-based or ES-based components, each focusing on a particular gap between a current capability and a well-stated goal; and, iterative refinement of sub-goals solved with AI into smaller sub-sub-goals where some are solved with ES, and some with AI. We describe the principles of the approach and its advantages, as well as key challenges and suggestions for how to tackle them."],"author":["Harel, David","Marron, Assaf","Rosenfeld, Ariel","Vardi, Moshe","Weiss, Gera"],"date":["2019-07-17"],"doi":["10.1609/aaai.v33i01.33019770"],"issn":["2374-3468, 2159-5399"],"journaltitle":["AAAI"],"number":["01"],"pages":["9770–9774"],"shorttitle":["Labor Division with Movable Walls"],"title":["Labor Division with Movable Walls: Composing Executable Specifications with Machine Learning and Search (Blue Sky Idea)"],"volume":["33"]},"creators":{"author":[{"lastName":"Harel","firstName":"David"},{"lastName":"Marron","firstName":"Assaf"},{"lastName":"Rosenfeld","firstName":"Ariel"},{"lastName":"Vardi","firstName":"Moshe"},{"lastName":"Weiss","firstName":"Gera"}]}},{"key":"Hart201228","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Syst. Eng."],"affiliation":["Naval Architecture and Marine Engineering Department, College of Engineering, University of Michigan, Ann Arbor, MI 48105, United States; Michigan Engineering Services, LLC, Ann Arbor, MI 48105, United States"],"author":["Hart, C.G.","He, Z.","Sbragio, R.","Vlahopoulos, N."],"correspondence_address1":["Hart, C.G.3293 Taney Lane, Falls Church, VA 22042, United States; email: hartcg@umich.edu"],"date":["2012"],"document_type":["Article"],"doi":["10.1002/sys.20192"],"issn":["10981241"],"journaltitle":["Syst. Eng."],"note":["cited By 11"],"number":["1"],"pages":["28–40"],"source":["Scopus"],"title":["An advanced cost estimation methodology for engineering systems"],"volume":["15"]},"creators":{"author":[{"lastName":"Hart","firstName":"C.G."},{"lastName":"He","firstName":"Z."},{"lastName":"Sbragio","firstName":"R."},{"lastName":"Vlahopoulos","firstName":"N."}]},"sentenceCased":true},{"key":"hartelClassificationAPIsHierarchical2018","type":"article","fields":{"langid":["english"],"abstract":["APIs can be classified according to the programming domains (e.g., GUIs, databases, collections, or security) that they address. Such classification is vital in searching repositories (e.g., the Maven Central Repository for Java) and for understanding the technology stack used in software projects. We apply hierarchical clustering to a curated suite of Java APIs to compare the computed API clusters with preexisting API classifications. Clustering entails various parameters (e.g., the choice of IDF versus LSI versus LDA). We describe the corresponding variability in terms of a feature model. We exercise all possible configurations to determine the maximum correlation with respect to two baselines: i) a smaller suite of APIs manually classified in previous research; ii) a larger suite of APIs from the Maven Central Repository, thereby taking advantage of crowd-sourced classification while relying on a threshold-based approach for identifying important APIs and versions thereof, subject to an API dependency analysis on GitHub. We discuss the configurations found in this way and we examine the influence of particular features on the correlation between computed clusters and baselines. To this end, we also leverage interactive exploration of the parameter space and the resulting dendrograms. In this manner, we can also identify issues with the use of classifiers (e.g., missing classifiers) in the baselines and limitations of the clustering approach."],"author":["Härtel, Johannes"],"date":["2018"],"note":["TL;DR \n\nThis work applies hierarchical clustering to a curated suite of Java APIs to compare the computed API clusters with preexisting API classifications and examines the influence of particular features on the correlation between computed clusters and baselines."],"pages":["11"],"title":["Classification of APIs by Hierarchical Clustering"]},"creators":{"author":[{"lastName":"Härtel","firstName":"Johannes"}]}},{"key":"Hartmann2019300","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - ACM/IEEE Int. Conf. Model Driven Eng. Lang. Syst., MODELS"],"affiliation":["DataThings, University of Luxembourg, Luxembourg, Luxembourg; Paul Wurth, Luxembourg, Luxembourg; University of Luxembourg, Luxembourg, Luxembourg"],"art_number":["8906948"],"author":["Hartmann, T.","Moawad, A.","Schockaert, C.","Fouquet, F.","Le Traon, Y."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/MODELS.2019.00014"],"editor":["Kessentini M., Yue T., Pretschner A., Voss S., Burgueno L., Burgueno L., Yue T."],"isbn":["978-1-72812-535-0"],"note":["cited By 6"],"pages":["300–305"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems, MODELS 2019"],"source":["Scopus"],"title":["Meta-modelling meta-learning"]},"creators":{"author":[{"lastName":"Hartmann","firstName":"T."},{"lastName":"Moawad","firstName":"A."},{"lastName":"Schockaert","firstName":"C."},{"lastName":"Fouquet","firstName":"F."},{"lastName":"Le Traon","firstName":"Y."}],"editor":[{"lastName":"Kessentini M.","suffix":"Yue T.","firstName":"Pretschner A., Voss S., Burgueno L., Burgueno L., Yue T."}]},"sentenceCased":true},{"key":"hartmannNextEvolutionMDE2017","type":"article","fields":{"langid":["english"],"author":["Hartmann, Thomas","Moawad, Assaad","Fouquet, Francois","Le Traon, Yves"],"date":["2017-05-29"],"doi":["10.1007/s10270-017-0600-2"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"shorttitle":["The next evolution of MDE"],"title":["The next evolution of MDE: A seamless integration of machine learning into domain modeling"]},"creators":{"author":[{"lastName":"Hartmann","firstName":"Thomas"},{"lastName":"Moawad","firstName":"Assaad"},{"lastName":"Fouquet","firstName":"Francois"},{"lastName":"Le Traon","firstName":"Yves"}]},"sentenceCased":true},{"key":"hassamAssistanceSystemOCL2011","type":"article","fields":{"author":["Hassam, Kahina","Sadou, Salah","Gloahec, Vincent Le","Fleurquin, Regis"],"date":["2011"],"doi":["10.1109/CSMR.2011.21"],"journaltitle":["2011 15th Eur. Conf. Softw. Maint. Reengineering"],"pages":["151–160"],"title":["Assistance System for OCL Constraints Adaptation during Metamodel Evolution"]},"creators":{"author":[{"lastName":"Hassam","firstName":"Kahina"},{"lastName":"Sadou","firstName":"Salah"},{"lastName":"Gloahec","firstName":"Vincent Le"},{"lastName":"Fleurquin","firstName":"Regis"}]}},{"key":"hassanRethinkingSoftwareEngineering2024","type":"online","fields":{"abstract":["Foundation models (FMs), such as Large Language Models (LLMs), have revolutionized software development by enabling new use cases and business models. We refer to software built using FMs as FMware. The unique properties of FMware (e.g., prompts, agents, and the need for orchestration), coupled with the intrinsic limitations of FMs (e.g., hallucination) lead to a completely new set of software engineering challenges. Based on our industrial experience, we identified 10 key SE4FMware challenges that have caused enterprise FMware development to be unproductive, costly, and risky. In this paper, we discuss these challenges in detail and state the path for innovation that we envision. Next, we present FMArts, which is our long-term effort towards creating a cradle-to-grave platform for the engineering of trustworthy FMware. Finally, we (i) show how the unique properties of FMArts enabled us to design and develop a complex FMware for a large customer in a timely manner and (ii) discuss the lessons that we learned in doing so. We hope that the disclosure of the aforementioned challenges and our associated efforts to tackle them will not only raise awareness but also promote deeper and further discussions, knowledge sharing, and innovative solutions across the software engineering discipline."],"author":["Hassan, Ahmed E.","Lin, Dayi","Rajbahadur, Gopi Krishnan","Gallaba, Keheliya","Cogo, Filipe R.","Chen, Boyuan","Zhang, Haoxiang","Thangarajah, Kishanthan","Oliva, Gustavo Ansaldi","Lin, Jiahuei","Abdullah, Wali Mohammad","Jiang, Zhen Ming"],"date":["2024-03-03"],"doi":["10.48550/arXiv.2402.15943"],"eprint":["2402.15943"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Software Engineering"],"note":["TL;DR \n\nThis paper identifies 10 key SE4FMware challenges that have caused enterprise FMware development to be unproductive, costly, and risky and presents FMArts, which is the long-term effort towards creating a cradle-to-grave platform for the engineering of trustworthy FMware."],"pubstate":["preprint"],"shorttitle":["Rethinking Software Engineering in the Foundation Model Era"],"title":["Rethinking Software Engineering in the Foundation Model Era: A Curated Catalogue of Challenges in the Development of Trustworthy FMware"]},"creators":{"author":[{"lastName":"Hassan","firstName":"Ahmed E."},{"lastName":"Lin","firstName":"Dayi"},{"lastName":"Rajbahadur","firstName":"Gopi Krishnan"},{"lastName":"Gallaba","firstName":"Keheliya"},{"lastName":"Cogo","firstName":"Filipe R."},{"lastName":"Chen","firstName":"Boyuan"},{"lastName":"Zhang","firstName":"Haoxiang"},{"lastName":"Thangarajah","firstName":"Kishanthan"},{"lastName":"Oliva","firstName":"Gustavo Ansaldi"},{"lastName":"Lin","firstName":"Jiahuei"},{"lastName":"Abdullah","firstName":"Wali Mohammad"},{"lastName":"Jiang","firstName":"Zhen Ming"}]}},{"key":"haugeAdoptionOpenSource2010","type":"article","fields":{"langid":["english"],"author":["Hauge, Øyvind","Ayala, Claudia","Conradi, Reidar"],"date":["2010-11"],"doi":["10.1016/j.infsof.2010.05.008"],"issn":["09505849"],"journaltitle":["Inf. Softw. Technol."],"number":["11"],"pages":["1133–1154"],"title":["Adoption of open source software in software-intensive organizations – A systematic literature review"],"volume":["52"]},"creators":{"author":[{"lastName":"Hauge","firstName":"Øyvind"},{"lastName":"Ayala","firstName":"Claudia"},{"lastName":"Conradi","firstName":"Reidar"}]},"sentenceCased":true},{"key":"haugeEmpiricalStudySelection2009","type":"inproceedings","fields":{"author":["Hauge, Oyvind","Osterlie, Thomas","Sorensen, Carl-Fredrik","Gerea, Marinela"],"booktitle":["Emerg. Trends Free. Source Softw. Res. Dev. 2009 FLOSS09 ICSE Workshop On"],"date":["2009"],"pages":["42–47"],"publisher":["IEEE"],"title":["An empirical study on selection of Open Source Software-Preliminary results"],"url":["http://ieeexplore.ieee.org/abstract/document/5071359/"],"urldate":["2017-02-25"]},"creators":{"author":[{"lastName":"Hauge","firstName":"Oyvind"},{"lastName":"Osterlie","firstName":"Thomas"},{"lastName":"Sorensen","firstName":"Carl-Fredrik"},{"lastName":"Gerea","firstName":"Marinela"}]},"sentenceCased":true},{"key":"haugheyNOSQLDataLake2017","type":"article","fields":{"langid":["english"],"author":["Haughey, Tom"],"date":["2017"],"pages":["28"],"title":["NOSQL and Data Lake Architecture"]},"creators":{"author":[{"lastName":"Haughey","firstName":"Tom"}]}},{"key":"haveliwalaTopicsensitivePageRank2002","type":"inproceedings","fields":{"acmid":["511513"],"author":["Haveliwala, Taher H."],"booktitle":["Proc. 11th Int. Conf. World Wide Web"],"date":["2002"],"isbn":["1-58113-449-5"],"keywords":["link structure","PageRank","personalized search","search","search in context","web graph"],"location":["New York, NY, USA"],"nodoi":["10.1145/511446.511513"],"numpages":["10"],"pages":["517–526"],"publisher":["ACM"],"series":["WWW '02"],"title":["Topic-sensitive PageRank"],"url":["http://doi.acm.org/10.1145/511446.511513"]},"creators":{"author":[{"lastName":"Haveliwala","firstName":"Taher H."}]},"sentenceCased":true},{"key":"HCI-009","type":"article","fields":{"author":["Ekstrand, Michael D.","Riedl, John T.","Konstan, Joseph A."],"date":["2011"],"issn":["1551-3955"],"journaltitle":["Found. Trends® Human–Computer Interact."],"nodoi":["10.1561/1100000009"],"note":["TL;DR \n\nThis study presents an overview of the field of recommender systems with current generation of recommendation methods and examines comprehensively CF systems with its algorithms."],"number":["2"],"pages":["81–173"],"title":["Collaborative filtering recommender systems"],"url":["http://dx.doi.org/10.1561/1100000009"],"volume":["4"]},"creators":{"author":[{"lastName":"Ekstrand","firstName":"Michael D."},{"lastName":"Riedl","firstName":"John T."},{"lastName":"Konstan","firstName":"Joseph A."}]},"sentenceCased":true},{"key":"he0216JSSOFTWARED23011822024","type":"report","fields":{"langid":["english"],"abstract":["Model-driven development is a model-centric software development paradigm that automates the development process by converting high-level models into low-level code and documents. To maintain synchronization between models and code/documents—which can evolve independently—this paper introduces BIT, a bidirectional language that can serve as a conventional template language for model-to-text transformations. However, a BIT program can function as both a printer, generating text by filling template holes with values from the input model, and a parser, putting parsed values back into the model. BIT comprises a surface language for better usability and a core language for formal definition. We define the semantics of the core language based on the theory of bidirectional transformation, and provide the translation from the surface to the core. We present the proof sketch of the well behavedness of BIT as a formal evidence of soundness. We also conduct two preliminary case studies to empirically demonstrate the expressiveness of BIT. Based on the proof and the case studies, BIT covers the major features of existing template languages, and offers sufficient expressiveness to define real-world model-to-text transformations that can be executed bidirectionally and incrementally."],"author":["He, Xiao","Zan, Tao"],"date":["2024"],"doi":["10.2139/ssrn.4686181"],"institution":["SSRN"],"keywords":["LOGSEQ"],"note":["<h1>Annotazioni\n (5/3/2024, 12:21:10)</h1> \n\n- “To maintain synchronization between models and code/documents—which can evolve independently—this paper introduces BIT, a bidirectional language that can serve as a conventional template language for modelto-text transformations.” (He e Zan, 2024, p. 0) #f0ff00\n <i>Does it solve the problem with target protected areas? </i> \n\n- “However, a BIT program can function as both a printer, generating text by filling template holes with values from the input model, and a parser, putting parsed values back into the model.” (He e Zan, 2024, p. 1) #f0ff00\n <i>Is TCS in the related work? </i> \n\n- “very few solutions for synchronizing models and text.” (He e Zan, 2024, p. 2) #f0ff00\n <i>what about boomerang? And TCS? I would have introduced a motivating example to show when and how existing works fall short. </i> \n\n- “Bidirectional transformation (BX) [22, 23, 24, 25, 26, 27, 28] can serve as the foundation of data synchronization. A BX program is a single specification that can be consistently evaluated in” (He e Zan, 2024, p. 3) #f0ff00\n <i>have you considered JTL, QVT relation, etc.? </i> \n\n- “their approach is limited code generation from Ecore models and is not generally applicable.” (He e Zan, 2024, p. 3) #f0ff00\n <i>do you plan to propose an approach that works on any ecosystem further than Ecore? </i> \n\n- “two challenges” (He e Zan, 2024, p. 3) #f0ff00\n <i>it is nessary to give evidence of such issues by showing an explanatory examples that cannot be managed by existing appoaches. </i> \n\n- “As for control directives, Xtend templates support loops (e.g., lines 6–14), conditions (e.g., lines 7–10), and assignments (e.g., lines 5 and 8). Within an Xtend template, other templates may be invoked.” (He e Zan, 2024, p. 5) #00b036\n i \n\n- “Figure 3: Demonstration of BIT template (colored background shows the changed text layout)” (He e Zan, 2024, p. 6) #f0ff00\n <i>what about the attribute no? I think it should be in the parsed output, isn't it? </i> \n\n- “with a lexical rule that guides our approach in the parsing mode. For example, «no|INT» in line 10 indicates that this hole will be filled with a string that is produced by the expression no and conforms to lexical rule INT, where the rule is defined by regular expression -?[0-9]+” (He e Zan, 2024, p. 6) #00b036\n i \n\n- “infer a lexical rule.” (He e Zan, 2024, p. 6) #f0ff00\n <i>how? Is there any default rule that is applied? </i> \n\n- “of the third paragraph will be \"Appreciation\", rather than \"appreciation\", because the first character in the old head is capitalized as \"S\"” (He e Zan, 2024, p. 7) #f0ff00\n <i>that's not clear. What about the \"Some text\" that is ignored and \"Thanks\" is instead in the output. Moreover the management of capital letters is not clear. </i> \n\n- “The BIT approach” (He e Zan, 2024, p. 7) #f0ff00\n <i>very much similar to QVT relation and QVT Core. It is necessary to discuss and compare BIT with respect to QVT technologies. </i> \n\n- “Figure 5: Essential grammar of the surface language” (He e Zan, 2024, p. 8) #f0ff00\n <i>the full grammar is not needed here. You can move it as an appendix and instead you can discuss in this section the peculiar aspects of the language by means of representative and illustrative cases. </i> \n\n- “LexRule is a regular expression or a rule name bound to a regular expression, e.g., ID refers to [_a-zA-Z][_a-zA-Z0-9]*” (He e Zan, 2024, p. 9) #f0ff00\n <i>it is necessary to make explicit what's the relation of what you specify with rules and the corresponding metaclasses, which are supposed to type the instances that can be created by parsing elements with respect to such rules. </i> \n\n- “Case studies” (He e Zan, 2024, p. 26) #f0ff00\n <i>This section needs to be improved by presenting a proper evaluation section, which starts by describing the research questions that the authors want to answer by mens of the performed evaluation. The way related works have been identified is also important. For instance, I don't see among them existing works like QVT, JTL, TCS. </i> \n\n- “General information of the benchmark examples” (He e Zan, 2024, p. 29) #f0ff00\n <i>Instead of presenting the table in terms of examples, I suggest to reorganise the table and thus, the corresponding text, by making explicit the peculiar cases that existing approach have issues in supporting them. Talking about examples is not a proper way to sustain a strong and organized discussion. Thus the examples column needs to be properly refined and decomposed with respect to their peculiar characteristcs. Moreover, I would define a conceptual framework to compare existing approach by identifying peculiar features and discussing their support by the analysed approaches. Such an analysis should be presented earlier in the paper, when motivating the needs for a novel BX template language. I don't see in the table Boomerang neither. If it is because it is not Ecore based, then \"Platform\" is one of the different dimensions that should be considered for the comparison. </i> \n\n- “major features of” (He e Zan, 2024, p. 30) #f0ff00\n <i>what are they? see my previous comments about the conceptual framework for comparison. </i> \n\n- “Left Recursions. Parsers derived from BIT templates cannot handle left recursions. Figure 14 shows a concrete example template containing left recursion. Currently, the tool support of BIT cannot check left recursion statically. It will be our future work to investigate how to detect left recursions in templates by adopting existing techniques in the field of compilers. #[[ #foreach ($woogie in $boogie) nothing will happen to $woogie” (He e Zan, 2024, p. 31) #f0ff00\n <i>left recursion is another dimension. </i> \n\n- “Efficiency” (He e Zan, 2024, p. 31) #f0ff00\n <i>this is another possible dimension but needs to be elaborated more in order to present the problems related to efficiency, and talk existing works also with respect to such a dimension. </i> \n\n- “Specifically” (He e Zan, 2024, p. 32) #f0ff00\n <i>what about Epsilon ECL? </i> \n\n- “Our previous work [20] on bidirectional model transformation proposed a putback-based language which enabled us to define a backward transformation from which a well-behaved BX can be derived.” (He e Zan, 2024, p. 32) #f0ff00\n <i>have you compared with your previous work? </i> \n\n- “a template language for code matching and rewriting. In matching process, Comby interprets a code template and” (He e Zan, 2024, p. 33) #f0ff00\n i \n\n- “verbose text and template extension.” (He e Zan, 2024, p. 34) #f0ff00\n <i>see the comparison comment above. </i>"],"shorttitle":["Bit"],"title":["02-16-JSSOFTWARE-D-23-01182"],"type":["preprint"]},"creators":{"author":[{"lastName":"He","firstName":"Xiao"},{"lastName":"Zan","firstName":"Tao"}]}},{"key":"He201977","type":"article","fields":{"abstract":["Intelligent communication is gradually becoming a mainstream direction. As a major branch of machine learning, deep learning (DL) has been applied in physical layer communications and has demonstrated an impressive performance improvement in recent years. However, most existing works related to DL focus on data-driven approaches, which consider the communication system as a black box and train it by using a huge volume of data. Training a network requires sufficient computing resources and extensive time, both of which are rarely found in communication devices. By contrast, model-driven DL approaches combine communication domain knowledge with DL to reduce the demand for computing resources and training time. This article discusses the recent advancements in model-driven DL approaches in physical layer communications, including transmission schemes, receiver design, and channel information recovery. Several open issues for future research are also highlighted. © 2002-2012 IEEE."],"art_number":["8715338"],"author":["He, H.","Jin, S.","Wen, C.-K.","Gao, F.","Li, G.Y.","Xu, Z."],"coden":["IWCEA"],"date":["2019"],"document_type":["Article"],"doi":["10.1109/MWC.2019.1800447"],"issn":["15361284"],"journaltitle":["IEEE Wirel. Commun."],"note":["cited By 150"],"number":["5"],"pages":["77–83"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Model-driven deep learning for physical layer communications"],"volume":["26"]},"creators":{"author":[{"lastName":"He","firstName":"H."},{"lastName":"Jin","firstName":"S."},{"lastName":"Wen","firstName":"C.-K."},{"lastName":"Gao","firstName":"F."},{"lastName":"Li","firstName":"G.Y."},{"lastName":"Xu","firstName":"Z."}]},"sentenceCased":true},{"key":"He20201702","type":"article","fields":{"abstract":["In this paper, we investigate the model-driven deep learning (DL) for MIMO detection. In particular, the MIMO detector is specially designed by unfolding an iterative algorithm and adding some trainable parameters. Since the number of trainable parameters is much fewer than the data-driven DL based signal detector, the model-driven DL based MIMO detector can be rapidly trained with a much smaller data set. The proposed MIMO detector can be extended to soft-input soft-output detection easily. Furthermore, we investigate joint MIMO channel estimation and signal detection (JCESD), where the detector takes channel estimation error and channel statistics into consideration while channel estimation is refined by detected data and considers the detection error. Based on numerical results, the model-driven DL based MIMO detector significantly improves the performance of corresponding traditional iterative detector, outperforms other DL-based MIMO detectors and exhibits superior robustness to various mismatches. © 1991-2012 IEEE."],"art_number":["9018199"],"author":["He, H.","Wen, C.-K.","Jin, S.","Li, G.Y."],"coden":["ITPRE"],"date":["2020"],"document_type":["Article"],"doi":["10.1109/TSP.2020.2976585"],"issn":["1053587X"],"journaltitle":["IEEE Trans. Signal Process."],"note":["cited By 80 \n\nTL;DR \n\nThe model-driven DL based MIMO detector significantly improves the performance of corresponding traditional iterative detector, outperforms other DL-based M IMO detectors and exhibits superior robustness to various mismatches."],"pages":["1702–1715"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Model-driven deep learning for mimo detection"],"volume":["68"]},"creators":{"author":[{"lastName":"He","firstName":"H."},{"lastName":"Wen","firstName":"C.-K."},{"lastName":"Jin","firstName":"S."},{"lastName":"Li","firstName":"G.Y."}]},"sentenceCased":true},{"key":"He20202216","type":"article","fields":{"abstract":["Massive multiuser multiple-input multiple-output (MU-MIMO) has been the mainstream technology in fifth-generation wireless systems. To reduce high hardware costs and power consumption in massive MU-MIMO, low-resolution digital-to-analog converters (DAC) for each antenna and radio frequency (RF) chain in downlink transmission is used, which brings challenges for precoding design. To circumvent these obstacles, we develop a model-driven deep learning (DL) network for massive MU-MIMO with finite-alphabet precoding in this article. The architecture of the network is specially designed by unfolding an iterative algorithm. Compared with the traditional state-of-the-art techniques, the proposed DL-based precoder shows significant advantages in performance, complexity, and robustness to channel estimation error under Rayleigh fading channel. © 1997-2012 IEEE."],"art_number":["9115718"],"author":["He, H.","Zhang, M.","Jin, S.","Wen, C.-K.","Li, G.Y."],"coden":["ICLEF"],"date":["2020"],"document_type":["Article"],"doi":["10.1109/LCOMM.2020.3002082"],"issn":["10897798"],"journaltitle":["IEEE Commun. Lett."],"note":["cited By 4"],"number":["10"],"pages":["2216–2220"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Model-driven deep learning for massive MU-MIMO with finite-alphabet precoding"],"volume":["24"]},"creators":{"author":[{"lastName":"He","firstName":"H."},{"lastName":"Zhang","firstName":"M."},{"lastName":"Jin","firstName":"S."},{"lastName":"Wen","firstName":"C.-K."},{"lastName":"Li","firstName":"G.Y."}]},"sentenceCased":true},{"key":"He2021","type":"article","fields":{"abstract":["Hyperspectral images (HSIs) are crucial for many research works. Spectral super-resolution (SSR) is a method used to obtain high-spatial-resolution (HR) HSIs from HR multispectral images. Traditional SSR methods include model-driven algorithms and deep learning. By unfolding a variational method, this article proposes an optimization-driven convolutional neural network (CNN) with a deep spatial-spectral prior, resulting in physically interpretable networks. Unlike the fully data-driven CNN, auxiliary spectral response function (SRF) is utilized to guide CNNs to group the bands with spectral relevance. In addition, the channel attention module (CAM) and the reformulated spectral angle mapper loss function are applied to achieve an effective reconstruction model. Finally, experiments on two types of data sets, including natural and remote sensing images, demonstrate the spectral enhancement effect of the proposed method, and also, the classification results on the remote sensing data set verified the validity of the information enhanced by the proposed method. IEEE"],"author":["He, J.","Li, J.","Yuan, Q.","Shen, H.","Zhang, L."],"date":["2021"],"document_type":["Article"],"doi":["10.1109/TNNLS.2021.3056181"],"issn":["2162237X"],"journaltitle":["IEEE Trans. Neural Netw. Learn. Syst."],"note":["cited By 9 \n\nTL;DR \n\nThis article proposes an optimization-driven convolutional neural network with a deep spatial–spectral prior, resulting in physically interpretable networks, and experiments on two types of data sets demonstrate the spectral enhancement effect of the proposed method."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Spectral response function-guided deep optimization-driven network for spectral super-resolution"]},"creators":{"author":[{"lastName":"He","firstName":"J."},{"lastName":"Li","firstName":"J."},{"lastName":"Yuan","firstName":"Q."},{"lastName":"Shen","firstName":"H."},{"lastName":"Zhang","firstName":"L."}]},"sentenceCased":true},{"key":"he2021pyart","type":"misc","fields":{"langid":["english"],"abstract":["API recommendation in real-time is challenging for dynamic languages like Python. Many existing API recommendation techniques are highly effective, but they mainly support static languages. A few Python IDEs provide API recommendation functionalities based on type inference and training on a large corpus of Python libraries and third-party libraries. As such, they may fail to recommend or make poor recommendations when type information is missing or target APIs are projectspecific. In this paper, we propose a novel approach, PyART, to recommending APIs for Python programs in real-time. It features a light-weight analysis to derive so-called optimistic data-flow, which is neither sound nor complete, but simulates the local data-flow information humans can derive. It extracts three kinds of features: data-flow, token similarity, and token co-occurrence, in the context of the program point where a recommendation is solicited. A predictive model is trained on these features using the Random Forest algorithm. Evaluation on 8 popular Python projects demonstrates that PyART can provide effective API recommendations. When historic commits can be leveraged, which is the target scenario of a state-of-theart tool ARIREC, our average top-1 accuracy is over 50% and average top-10 accuracy over 70%, outperforming APIREC and Intellicode (i.e., the recommendation component in Visual Studio) by 28.48%-39.05% for top-1 accuracy and 24.41%-30.49% for top-10 accuracy. In other applications such as when historic comments are not available and cross-project recommendation, PyART also shows better overall performance. The time to make a recommendation is less than a second on average, satisfying the real-time requirement."],"author":["He, Xincheng","Xu, Lei","Zhang, Xiangyu","Hao, Rui","Feng, Yang","Xu, Baowen"],"date":["2021"],"eprint":["2102.04706"],"eprintclass":["cs"],"eprinttype":["arxiv"],"ids":["he_pyart_2021"],"keywords":["Computer Science - Software Engineering"],"note":["arXiv: 2102.04706 \n\narXiv: 2102.04706 \n\nComment: 12 pages \n\nComment: 12 pages \n\nTL;DR \n\nThis paper proposes a novel approach, PyART, to recommend APIs for Python programs in real-time, which features a light-weight analysis to derives so-called optimistic data-flow, which is neither sound nor complete, but simulates the local data- flow information humans can derive."],"shorttitle":["PyART"],"title":["PyART: Python API recommendation in real-time"],"url":["http://arxiv.org/abs/2102.04706"],"urldate":["2021-02-12"]},"creators":{"author":[{"lastName":"He","firstName":"Xincheng"},{"lastName":"Xu","firstName":"Lei"},{"lastName":"Zhang","firstName":"Xiangyu"},{"lastName":"Hao","firstName":"Rui"},{"lastName":"Feng","firstName":"Yang"},{"lastName":"Xu","firstName":"Baowen"}]},"sentenceCased":true},{"key":"hearstSupportVectorMachines1998","type":"article","fields":{"acmid":["630387"],"address":["Piscataway, NJ, USA"],"author":["Hearst, Marti A."],"date":["1998-07"],"issn":["1541-1672"],"issue_date":["July 1998"],"journaltitle":["IEEE Intell. Syst."],"nodoi":["10.1109/5254.708428"],"number":["4"],"numpages":["11"],"pages":["18–28"],"publisher":["IEEE Educational Activities Department"],"title":["Support vector machines"],"url":["http://dx.doi.org/10.1109/5254.708428"],"volume":["13"]},"creators":{"author":[{"lastName":"Hearst","firstName":"Marti A."}]},"sentenceCased":true},{"key":"heAutoMLSurveyStateoftheart2021","type":"article","fields":{"langid":["english"],"author":["He, Xin","Zhao, Kaiyong","Chu, Xiaowen"],"date":["2021-01"],"doi":["10.1016/j.knosys.2020.106622"],"ids":["HE2021106622"],"issn":["09507051"],"journaltitle":["Knowledge-Based Systems"],"keywords":["Automated machine learning (autoML)","Deep learning","Hyperparameter optimization (HPO)","Neural architecture search (NAS)"],"pages":["106622"],"shorttitle":["AutoML"],"title":["AutoML: A survey of the state-of-the-art"],"volume":["212"]},"creators":{"author":[{"lastName":"He","firstName":"Xin"},{"lastName":"Zhao","firstName":"Kaiyong"},{"lastName":"Chu","firstName":"Xiaowen"}]},"sentenceCased":true},{"key":"hein2009model","type":"inproceedings","fields":{"author":["Hein, Christian","Ritter, Tom","Wagner, Michael"],"booktitle":["Workshop Future Trends Model-Driven Dev."],"date":["2009"],"pages":["50–52"],"title":["Model-driven tool integration with modelbus"]},"creators":{"author":[{"lastName":"Hein","firstName":"Christian"},{"lastName":"Ritter","firstName":"Tom"},{"lastName":"Wagner","firstName":"Michael"}]},"sentenceCased":true},{"key":"heitmannUsingLinkedData2010","type":"article","fields":{"abstract":["While recommender systems can greatly enhance the user experience, the entry barriers in terms of data acquisition are very high, making it hard for new service providers to compete with existing recommendation services. This paper proposes to build open recommender systems which can utilise Linked Data to mitigate the new-user, new-item and sparsity problems of collaborative recommender systems. We describe how to aggregate data about object centred sociality from different sources and how to process it for collaborative recommendation. To demonstrate the validity of our approach, we augment the data from a closed collaborative music recommender system with Linked Data, and significantly improve its precision and recall."],"author":["Heitmann, Benjamin","Hayes, Conor"],"date":["2010"],"journaltitle":["Artif. Intell."],"keywords":["lang:ENG","SML-LIB-BIBLIO","technical report ss 10 07"],"mendeley-tags":["SML-LIB-BIBLIO,lang:ENG"],"note":["TL;DR \n\nThis paper proposes to build open recommender systems which can utilise Linked Data to mitigate the new-user, new-item and sparsity problems of collaborativeRecommender systems."],"pages":["76–81"],"title":["Using linked data to build open, collaborative recommender systems"],"url":["http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.174.2755 http://www.aaai.org/ocs/index.php/SSS/SSS10/paper/viewPDFInterstitial/1067/1452"]},"creators":{"author":[{"lastName":"Heitmann","firstName":"Benjamin"},{"lastName":"Hayes","firstName":"Conor"}]},"sentenceCased":true},{"key":"henderson-sellersMultiLevelMetaModellingUnderpin2013","type":"article","fields":{"author":["Henderson-Sellers, Brian","Gonzalez-Perez, Cesar"],"date":["2013"],"doi":["10.1007/978-3-642-36654-3_12"],"journaltitle":["Domain Eng."],"note":["TL;DR \n\nThis chapter provides a solid theoretical foundation for the construction of domain-specific modelling languages that can help define both the abstract and concrete syntax aspects of a meta-modelling paradigm."],"pages":["291–316"],"title":["Multi-Level Meta-Modelling to Underpin the Abstract and Concrete Syntax for Domain-Specific Modelling Languages"]},"creators":{"author":[{"lastName":"Henderson-Sellers","firstName":"Brian"},{"lastName":"Gonzalez-Perez","firstName":"Cesar"}]}},{"key":"Henkel:2005:CCR:1062455.1062512","type":"inproceedings","fields":{"acmid":["1062512"],"author":["Henkel, Johannes","Diwan, Amer"],"booktitle":["Proc. 27th Int. Conf. Softw. Eng."],"date":["2005"],"isbn":["1-58113-963-2"],"keywords":["application programming interfaces","refactoring","software evolution"],"location":["New York, NY, USA"],"nodoi":["10.1145/1062455.1062512"],"numpages":["10"],"pages":["274–283"],"publisher":["ACM"],"series":["ICSE '05"],"title":["CatchUp!: Capturing and replaying refactorings to support API evolution"],"url":["http://doi.acm.org/10.1145/1062455.1062512"]},"creators":{"author":[{"lastName":"Henkel","firstName":"Johannes"},{"lastName":"Diwan","firstName":"Amer"}]},"sentenceCased":true},{"key":"henningenRetrievingSoftwareObjects1991","type":"inproceedings","fields":{"author":["Henningen, Scott"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/conf/sigir/Henningen91"],"booktitle":["Proc. 14th Annu. Int. ACM SIGIR Conf. Res. Dev. Inf. Retr. Chic. Ill. USA Oct. 13-16 1991 Spec. Issue SIGIR Forum"],"date":["1991"],"doi":["10.1145/122860.122886"],"note":["TL;DR \n\nA prototype system named CODEFINDER, which explores issues of retrieving software objects relevant to the design task, is presented and supports human-computer dialogue by providing the means to incrementally construct a query and by providing associative cues that are compatible with human memory retrieval principles."],"pages":["251–260"],"timestamp":["Tue, 06 Nov 2018 11:07:25 +0100"],"title":["Retrieving software objects in an example-based programming environment"]},"creators":{"author":[{"lastName":"Henningen","firstName":"Scott"}]},"sentenceCased":true},{"key":"HenshingArendtBJKT10","type":"inproceedings","fields":{"langid":["english"],"author":["Arendt, Thorsten","Biermann, Enrico","Jurack, Stefan","Krause, Christian","Taentzer, Gabriele"],"booktitle":["Proc 13th Int. Conf. Model Driven Eng. Lang. Syst. Model."],"date":["2010"],"doi":["10.1007/978-3-642-16145-2\\_9"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nHenshin is a new language and associated tool set for in-place transformations of EMF models using pattern-based rules on the lowest level, which can be structured into nested transformation units with well-defined operational semantics."],"pages":["121–135"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"title":["Henshin: Advanced concepts and tools for in-Place EMF model transformations"],"volume":["6394"],"x-editor":["Dorina C. Petriu and Nicolas Rouquette and Øystein Haugen"]},"creators":{"author":[{"lastName":"Arendt","firstName":"Thorsten"},{"lastName":"Biermann","firstName":"Enrico"},{"lastName":"Jurack","firstName":"Stefan"},{"lastName":"Krause","firstName":"Christian"},{"lastName":"Taentzer","firstName":"Gabriele"}]},"sentenceCased":true},{"key":"HereWhatVoicecontrolled","type":"online","fields":{"title":["Here’s what voice-controlled Android home automation looks like [Video]"],"url":["http://www.androidauthority.com/voice-controlled-android-home-automation-video-205316/"],"urldate":["2015-04-16"]},"creators":{},"sentenceCased":true},{"key":"Herrmann201979","type":"inproceedings","fields":{"abstract":["Machine learning based motion modelling methods such as statistical modelling require a large amount of input data. In practice, the management of the data can become a problem in itself for artists who want to control the quality of the motion models. As a solution to this problem, we present a motion data and model management system and integrate it with a statistical motion modelling pipeline. The system is based on a data storage server with a REST interface that enables the efficient storage of different versions of motion data and models. The database system is combined with a motion preprocessing tool that provides functions for batch editing, retargeting and annotation of the data. For the application of the motion models in a game engine, the framework provides a stateful motion synthesis server that can load the models directly from the data storage server. Additionally, the framework makes use of a Kubernetes compute cluster to execute time consuming processes such as the preprocessing and modelling of the data. The system is evaluated in a use case for the simulation of manual assembly workers. © 2019 The Author(s) Eurographics Proceedings © 2019 The Eurographics Association."],"author":["Herrmann, E.","Du, H.","Antakli, A.","Rubinstein, D.","Schubotz, R.","Sprenger, J.","Hosseini, S.","Cheema, N.","Zinnikus, I.","Manns, M.","Fischer, K.","Slusallek, P."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.2312/stag.20191366"],"editor":["Agus M., Corsini M., Pintus R."],"isbn":["978-3-03868-100-7"],"note":["cited By 1 \n\nTL;DR \n\nThis work presents a motion data and model management system and integrate it with a statistical motion modelling pipeline that makes use of a Kubernetes compute cluster to execute time consuming processes such as the preprocessing and modelling of the data."],"pages":["79–88"],"publisher":["Eurographics Association"],"series":["Italian Chapter Conference 2019 - Smart Tools and Apps in computer Graphics, STAG 2019"],"source":["Scopus"],"title":["Motion data and model management for applied statistical motion synthesis"]},"creators":{"author":[{"lastName":"Herrmann","firstName":"E."},{"lastName":"Du","firstName":"H."},{"lastName":"Antakli","firstName":"A."},{"lastName":"Rubinstein","firstName":"D."},{"lastName":"Schubotz","firstName":"R."},{"lastName":"Sprenger","firstName":"J."},{"lastName":"Hosseini","firstName":"S."},{"lastName":"Cheema","firstName":"N."},{"lastName":"Zinnikus","firstName":"I."},{"lastName":"Manns","firstName":"M."},{"lastName":"Fischer","firstName":"K."},{"lastName":"Slusallek","firstName":"P."}],"editor":[{"lastName":"Agus M.","suffix":"Corsini M.","firstName":"Pintus R."}]},"sentenceCased":true},{"key":"Herrmannsdoerfer_2011","type":"incollection","fields":{"langid":["english"],"author":["Herrmannsdoerfer, Markus"],"booktitle":["Software Language Engineering"],"date":["2011"],"doi":["10.1007/978-3-642-19440-5_18"],"editor":["Malloy, Brian","Staab, Steffen","Van Den Brand, Mark"],"isbn":["978-3-642-19439-9"],"keywords":["/unread","⛔ No INSPIRE recid found"],"location":["Berlin, Heidelberg"],"pages":["286–295"],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture notes in computer science"],"title":["COPE – a workbench for the coupled evolution of metamodels and models"],"volume":["6563"]},"creators":{"author":[{"lastName":"Herrmannsdoerfer","firstName":"Markus"}],"editor":[{"lastName":"Malloy","firstName":"Brian"},{"lastName":"Staab","firstName":"Steffen"},{"lastName":"Van Den Brand","firstName":"Mark"}]},"sentenceCased":true},{"key":"HerrmannsdoerferR09","type":"inproceedings","fields":{"langid":["english"],"author":["Herrmannsdoerfer, Markus","Ratiu, Daniel"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Models Softw. Eng. Workshop Symp. MODELS 2009 Denver CO USA Oct. 4-9 2009 Rep. Revis. Sel. Pap."],"date":["2009"],"doi":["10.1007/978-3-642-12261-3\\_20"],"editor":["Ghosh, Sudipto"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper formally characterize metamodel adaptations in terms of the effort needed for model migration, and outlines different possibilities to systematically cope with these kinds of metAModel changes."],"pages":["205–219"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Wed, 23 Feb 2022 12:58:06 +0100"],"title":["Limitations of automating model migration in response to metamodel adaptation"],"volume":["6002"]},"creators":{"author":[{"lastName":"Herrmannsdoerfer","firstName":"Markus"},{"lastName":"Ratiu","firstName":"Daniel"}],"editor":[{"lastName":"Ghosh","firstName":"Sudipto"}]},"sentenceCased":true},{"key":"hidasiSessionbasedRecommendationsRecurrent2015","type":"article","fields":{"author":["Hidasi, Balázs","Karatzoglou, Alexandros","Baltrunas, Linas","Tikk, Domonkos"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/journals/corr/HidasiKBT15"],"date":["2015"],"eprint":["1511.06939"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"note":["TL;DR \n\nIt is argued that by modeling the whole session, more accurate recommendations can be provided by an RNN-based approach for session-based recommendations, and introduced several modifications to classic RNNs such as a ranking loss function that make it more viable for this specific problem."],"timestamp":["Wed, 07 Jun 2017 14:42:57 +0200"],"title":["Session-based recommendations with recurrent neural networks"],"url":["http://arxiv.org/abs/1511.06939"],"volume":["abs/1511.06939"]},"creators":{"author":[{"lastName":"Hidasi","firstName":"Balázs"},{"lastName":"Karatzoglou","firstName":"Alexandros"},{"lastName":"Baltrunas","firstName":"Linas"},{"lastName":"Tikk","firstName":"Domonkos"}]},"sentenceCased":true},{"key":"Hildebrandt2017128","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["CEUR Workshop Proc."],"affiliation":["Technische Universitat Dresden, Database Systems Group, Dresden, Germany; Technische Universitat Dresden, Software Technology Group, Dresden, Germany"],"author":["Hildebrandt, J.","Habich, D.","Kuhn, T.","Damme, P.","Lehner, W."],"date":["2017"],"document_type":["Conference Paper"],"editor":["Cabanillas C., Farshidi S., Espana S."],"issn":["16130073"],"note":["cited By 5"],"pages":["128–141"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"source":["Scopus"],"title":["Metamodeling lightweight data compression algorithms and its application scenarios"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034960838&partnerID=40&md5=33294c448edfceb4dead3c958f0f06de"],"volume":["1979"]},"creators":{"author":[{"lastName":"Hildebrandt","firstName":"J."},{"lastName":"Habich","firstName":"D."},{"lastName":"Kuhn","firstName":"T."},{"lastName":"Damme","firstName":"P."},{"lastName":"Lehner","firstName":"W."}],"editor":[{"lastName":"Cabanillas C.","suffix":"Farshidi S.","firstName":"Espana S."}]},"sentenceCased":true},{"key":"HilkenGBV18","type":"article","fields":{"langid":["english"],"author":["Hilken, Frank","Gogolla, Martin","Burgueño, Loli","Vallecillo, Antonio"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2018"],"doi":["10.1007/S10270-016-0568-3"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nIt is shown how the concept of classifying terms, which are general OCL terms on a class model enriched with OCL constraints can be effectively used in combination with Tracts for testing both directional and bidirectional model transformations and for analyzing their behavior."],"number":["3"],"pages":["885–912"],"timestamp":["Fri, 18 Sep 2020 11:19:16 +0200"],"title":["Testing models and model transformations using classifying terms"],"volume":["17"]},"creators":{"author":[{"lastName":"Hilken","firstName":"Frank"},{"lastName":"Gogolla","firstName":"Martin"},{"lastName":"Burgueño","firstName":"Loli"},{"lastName":"Vallecillo","firstName":"Antonio"}]},"sentenceCased":true},{"key":"hintzeViolinPlotsBox1998","type":"article","fields":{"author":["Hintze, Jerry L.","Ray D. Nelson"],"date":["1998"],"eprint":["https://amstat.tandfonline.com/doi/pdf/10.1080/00031305.1998.10480559"],"journaltitle":["Am. Stat."],"nodoi":["10.1080/00031305.1998.10480559"],"number":["2"],"pages":["181–184"],"publisher":["Taylor & Francis"],"title":["Violin plots: A box plot-density trace synergism"],"url":["https://amstat.tandfonline.com/doi/abs/10.1080/00031305.1998.10480559"],"volume":["52"]},"creators":{"author":[{"lastName":"Hintze","firstName":"Jerry L."},{"literal":"Ray D. Nelson"}]},"sentenceCased":true},{"key":"Hirschberg:1977:ALC:322033.322044","type":"article","fields":{"acmid":["322044"],"address":["New York, NY, USA"],"author":["Hirschberg, Daniel S."],"date":["1977-10"],"issn":["0004-5411"],"issue_date":["Oct. 1977"],"journaltitle":["J. ACM"],"nodoi":["10.1145/322033.322044"],"note":["TL;DR \n\nA lgor i thm is appl icable in the genera l case and requi res O ( p n + n log n) t ime for any input strings o f lengths m and n even though the lower bound on T ime of O ( m n ) need not apply to all inputs."],"number":["4"],"numpages":["12"],"pages":["664–675"],"publisher":["ACM"],"title":["Algorithms for the longest common subsequence problem"],"url":["http://doi.acm.org/10.1145/322033.322044"],"volume":["24"]},"creators":{"author":[{"lastName":"Hirschberg","firstName":"Daniel S."}]},"sentenceCased":true},{"key":"hirzelLowCodeProgrammingModels2022","type":"online","fields":{"abstract":["Traditionally, computer programming has been the prerogative of professional developers using textual programming languages such as C, Java, or Python. Low-code programming promises an alternative: letting citizen developers create programs using visual abstractions, demonstrations, or natural language. While low-code programming is currently getting a lot of attention in industry, the relevant research literature is scattered, and in fact, rarely uses the term \"low-code\". This article brings together low-code literature from various research fields, explaining how techniques work while providing a unified point of view. Low-code has the potential to empower more people to automate tasks by creating computer programs, making them more productive and less dependent on scarce professional software developers."],"author":["Hirzel, Martin"],"date":["2022-05-04"],"eprint":["2205.02282"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Programming Languages","LOGSEQ"],"pubstate":["preprint"],"title":["Low-Code Programming Models"],"url":["http://arxiv.org/abs/2205.02282"],"urldate":["2023-05-17"]},"creators":{"author":[{"lastName":"Hirzel","firstName":"Martin"}]}},{"key":"HitchhikerGuideIoT","type":"online","fields":{"title":["Hitchhiker's Guide to IoT Standards and Protocols - DZone IoT"],"url":["https://dzone.com/articles/hitchhikers-guide-to-iot-standards-and-protocols?edition=216186&utm_source=Spotlight&utm_medium=email&utm_campaign=iot%202016-09-27"],"urldate":["2016-09-27"]},"creators":{}},{"key":"hnetynkaUsingComponentEnsembles2020","type":"inproceedings","fields":{"langid":["english"],"author":["Hnetynka, Petr","Bures, Tomas","Gerostathopoulos, Ilias","Pacovsky, Jan"],"booktitle":["Proc. IEEEACM 15th Int. Symp. Softw. Eng. Adapt. Self-Manag. Syst."],"date":["2020-06-29"],"doi":["10.1145/3387939.3391599"],"eventtitle":["SEAMS '20: IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems"],"isbn":["978-1-4503-7962-5"],"location":["Seoul Republic of Korea"],"note":["TL;DR \n\nThe paper shows how the autonomic component ensembles can easily capture complex collaboration rules and how they can include both controllable autonomic components (i.e. drones) and non-controllable environment agents (flocks of birds in this case)."],"pages":["156–162"],"publisher":["ACM"],"title":["Using component ensembles for modeling autonomic component collaboration in smart farming"]},"creators":{"author":[{"lastName":"Hnetynka","firstName":"Petr"},{"lastName":"Bures","firstName":"Tomas"},{"lastName":"Gerostathopoulos","firstName":"Ilias"},{"lastName":"Pacovsky","firstName":"Jan"}]},"sentenceCased":true},{"key":"hoareRoleFormalTechniques1996","type":"inproceedings","fields":{"author":["Hoare, C. A. R."],"booktitle":["Proc. 18th Int. Conf. Softw. Eng."],"date":["1996"],"pages":["233–234"],"publisher":["IEEE Computer Society"],"shorttitle":["The role of formal techniques"],"title":["The role of formal techniques: Past, current and future or how did software get so reliable without proof?"],"url":["http://dl.acm.org/citation.cfm?id=227765"],"urldate":["2016-11-20"]},"creators":{"author":[{"lastName":"Hoare","firstName":"C. A. R."}]},"sentenceCased":true},{"key":"hodaRiseEvolutionAgile2018","type":"article","fields":{"abstract":["Agile software development has dominated the second half of the past 50 years of software engineering. Retrospectives, one of the most common agile practices, enables reflection on past performance, discussion of current progress, and charting forth directions for future improvement. Because of agile’s burgeoning popularity as the software development model of choice and a significant research subdomain of software engineering, it demands a retrospective of its own. This article provides a historical overview of agile’s main focus areas and a holistic synthesis of its trends, their evolution over the past two decades, agile’s current status, and, forecast from these, agile’s likely future. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Hoda, R.","Salleh, N.","Grundy, J."],"date":["2018-09"],"doi":["10.1109/MS.2018.290111318"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"note":["TL;DR \n\nA historical overview of agile’s main focus areas and a holistic synthesis of its trends, their evolution over the past two decades, agile‘s current status, and, forecast from these, agile's likely future are provided."],"number":["5"],"pages":["58–63"],"title":["The Rise and Evolution of Agile Software Development"],"volume":["35"]},"creators":{"author":[{"lastName":"Hoda","firstName":"R."},{"lastName":"Salleh","firstName":"N."},{"lastName":"Grundy","firstName":"J."}]}},{"key":"hoislCatalogReusableDesign","type":"article","fields":{"langid":["english"],"abstract":["In the process of model-driven development (MDD) of software artifacts, domain-specific modeling languages (DSMLs) are an integral part. They act as the communication vehicle for aligning the requirements of the domain expert with the needs of the software engineer. With the rise of the UML as de facto standard for modeling software systems, MOF/UMLbased DSMLs are now widely used for MDD. This paper documents design decisions from ten DSML projects which are based on the MOF/UML and which we conducted over the last years. We present our experiences in the form of reusable decision templates for all decision points detected in each phase of the DSML development process. Furthermore, we report also on identified decision dependencies which may occur within a single decision or between two decisions."],"author":["Hoisl, Bernhard","Sobernig, Stefan","Schefer-Wenzl, Sigrid","Strembeck, Mark","Baumgrass, Anne"],"note":["TL;DR \n\nThis collection of decision-record documents targets decision makers in DSML development (e.g., DSML engineers, software architects, domain experts) and presents design decisions collected from 90 UML/MOF-based DSML projects."],"pages":["24"],"title":["A Catalog of Reusable Design Decisions for Developing UML- and MOF-based Domain-Specific Modeling Languages"]},"creators":{"author":[{"lastName":"Hoisl","firstName":"Bernhard"},{"lastName":"Sobernig","firstName":"Stefan"},{"lastName":"Schefer-Wenzl","firstName":"Sigrid"},{"lastName":"Strembeck","firstName":"Mark"},{"lastName":"Baumgrass","firstName":"Anne"}]}},{"key":"hollerMachinetomachineInternetThings2014","type":"book","fields":{"langid":["english"],"abstract":["This book outlines the background and overall vision for the Internet of Things (IoT) and M2M communications and services, including major standards. Key technologies are described: Everything from physical instrumentation devices to the cloud infrastructures used to collect data, derive information and map it to current processes, as well as system architectures and regulatory requirements. Real world service use case studies provide the hands-on knowledge needed to successfully develop and implement M2M and IoT technologies sustainably and profitably"],"date":["2014"],"editor":["Höller, Jan"],"isbn":["978-0-12-407684-6 978-0-08-099401-7"],"keywords":["internet of things"],"location":["Amsterdam"],"pagetotal":["331"],"publisher":["Elsevier Academic Press"],"shorttitle":["From machine-to-machine to the Internet of things"],"title":["From machine-to-machine to the Internet of things: Introduction to a new age of intelligence"]},"creators":{"editor":[{"lastName":"Höller","firstName":"Jan"}]},"sentenceCased":true},{"key":"Holm1979a","type":"article","fields":{"author":["Holm, Sture"],"date":["1979"],"journaltitle":["Scand. J. Stat."],"pages":["65–70"],"publisher":["JSTOR"],"title":["A simple sequentially rejective multiple test procedure"]},"creators":{"author":[{"lastName":"Holm","firstName":"Sture"}]},"sentenceCased":true},{"key":"holmes_strathcona_nodate","type":"article","fields":{"langid":["english"],"abstract":["Using the application programming interfaces (API) of large software systems requires developers to understand details about the interfaces that are often not explicitly defined. However, documentation about the API is often incomplete or out of date. Existing systems that make use of the API provide a form of implicit information on how to use that code. Manually searching through existing projects to find relevant source code is tedious and time consuming. We have created the Strathcona Example Recommendation Tool to assist developers in finding relevant fragments of code, or examples, of an API’s use. These examples can be used by developers to provide insight on how they are supposed to interact with the API."],"author":["Holmes, Reid","Walker, Robert J","Murphy, Gail C"],"date":["2015"],"pages":["4"],"title":["Strathcona Example Recommendation Tool"]},"creators":{"author":[{"lastName":"Holmes","firstName":"Reid"},{"lastName":"Walker","firstName":"Robert J"},{"lastName":"Murphy","firstName":"Gail C"}]}},{"key":"holmesStrathconaExampleRecommendation2005","type":"inproceedings","fields":{"author":["Holmes, Reid","Walker, Robert J.","Murphy, Gail C."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/conf/sigsoft/HolmesWM05"],"booktitle":["Proc. 10th Eur. Softw. Eng. Conf. Held Jointly 13th ACM SIGSOFT Int. Symp. Found. Softw. Eng. 2005 Lisbon Port. Sept. 5-9 2005"],"date":["2005"],"doi":["10.1145/1081706.1081744"],"ids":["DBLP:conf/sigsoft/HolmesWM05"],"note":["TL;DR \n\nThe Strathcona Example is created to assist developers in finding relevant fragments of code, or examples, of an API's use and can be used by developers to provide insight on how they are supposed to interact with the API."],"pages":["237–240"],"timestamp":["Tue, 06 Nov 2018 16:59:23 +0100"],"title":["Strathcona example recommendation tool"]},"creators":{"author":[{"lastName":"Holmes","firstName":"Reid"},{"lastName":"Walker","firstName":"Robert J."},{"lastName":"Murphy","firstName":"Gail C."}]},"sentenceCased":true},{"key":"holzmannCodeVault2018","type":"article","fields":{"abstract":["So, what has changed since that first NATO software engineering conference in 1968? Depending on your point of view, nothing much has changed, or everything has changed. The part that didn’t change much is that we still struggle with writing code that’s robust enough to trust. The part that has changed dramatically is the performance of the hardware that runs our code. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Holzmann, G. J."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571225"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"number":["5"],"pages":["85–87"],"title":["Code Vault"],"volume":["35"]},"creators":{"author":[{"lastName":"Holzmann","firstName":"G. J."}]}},{"key":"HomeServerNoob","type":"online","fields":{"title":["Home server noob. Can't get CouchPotato to communicate with Deluge. : HomeServer"],"url":["http://www.reddit.com/r/HomeServer/comments/2r15vh/home_server_noob_cant_get_couchpotato_to/"],"urldate":["2015-04-22"]},"creators":{},"sentenceCased":true},{"key":"HomeSystemsConsulting","type":"online","fields":{"title":["Home Systems Consulting"],"url":["http://www.hsyco.com/"],"urldate":["2015-04-08"]},"creators":{}},{"key":"hong2023metagpt","type":"article","fields":{"langid":["english"],"author":["Hong, Sirui","Zheng, Xiawu","Chen, Jonathan","Cheng, Yuheng","Wang, Jinlin","Zhang, Ceyao","Wang, Zili","Yau, Steven Ka Shing","Lin, Zijuan","Zhou, Liyang","Others"],"date":["2023"],"eprint":["2308.00352"],"eprinttype":["arxiv"],"journaltitle":["arXiv prepr. arXiv:2308,00352"],"keywords":["/unread","⛔ No INSPIRE recid found"],"title":["Metagpt: Meta programming for multi-agent collaborative framework"]},"creators":{"author":[{"lastName":"Hong","firstName":"Sirui"},{"lastName":"Zheng","firstName":"Xiawu"},{"lastName":"Chen","firstName":"Jonathan"},{"lastName":"Cheng","firstName":"Yuheng"},{"lastName":"Wang","firstName":"Jinlin"},{"lastName":"Zhang","firstName":"Ceyao"},{"lastName":"Wang","firstName":"Zili"},{"lastName":"Yau","firstName":"Steven Ka Shing"},{"lastName":"Lin","firstName":"Zijuan"},{"lastName":"Zhou","firstName":"Liyang"},{"literal":"Others"}]},"sentenceCased":true},{"key":"hora_apiwave_2015","type":"inproceedings","fields":{"abstract":["Every day new frameworks and libraries are created and existing ones evolve. To benefit from such newer or improved APIs, client developers should update their applications. In practice, this process presents some challenges: APIs are commonly backward-incompatible (causing client applications to fail when updating) and multiple APIs are available (making it difficult to decide which one to use). To address these challenges, we propose apiwave, a tool that keeps track of API popularity and migration of major frameworks/libraries. The current version includes data about the evolution of top 650 GitHub Java projects, from which 320K APIs were extracted. We also report an experience using apiwave on real-world scenarios."],"author":["Hora, André","Valente, Marco Tulio"],"booktitle":["2015 IEEE Int Conf Softw. Maint. Evol. ICSME"],"date":["2015-09"],"doi":["10.1109/ICSM.2015.7332478"],"keywords":["API migration","API popularity","Apiwave","application program interfaces","Data mining","Databases","GitHub Java project","Java","Libraries","Market research","Software maintenance"],"pages":["321–323"],"shorttitle":["Apiwave"],"title":["Apiwave: Keeping track of API ,Ty and migration"]},"creators":{"author":[{"lastName":"Hora","firstName":"André"},{"lastName":"Valente","firstName":"Marco Tulio"}]},"sentenceCased":true},{"key":"HORIZON2020","type":"online","fields":{"title":["HORIZON 2020"],"url":["http://een.unioncamerepuglia.it/Italiano/News/HORIZON-2020/"],"urldate":["2015-04-08"]},"creators":{}},{"key":"hortBiasMitigationMachine2023","type":"article","fields":{"langid":["english"],"abstract":["This paper provides a comprehensive survey of bias mitigation methods for achieving fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning bias mitigation for ML classifiers. These methods can be distinguished based on their intervention procedure (i.e., pre-processing, in-processing, post-processing) and the technique they apply. We investigate how existing bias mitigation methods are evaluated in the literature. In particular, we consider datasets, metrics and benchmarking. Based on the gathered insights (e.g., What is the most popular fairness metric? How many datasets are used for evaluating bias mitigation methods?), we hope to support practitioners in making informed choices when developing and evaluating new bias mitigation methods."],"author":["Hort, Max","Chen, Zhenpeng","Zhang, Jie M.","Harman, Mark","Sarro, Federica"],"date":["2023-11"],"doi":["10.1145/3631326"],"issn":["2832-0565"],"journaltitle":["ACM J. Responsib. Comput."],"pages":["3631326"],"shorttitle":["Bias Mitigation for Machine Learning Classifiers"],"title":["Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey"]},"creators":{"author":[{"lastName":"Hort","firstName":"Max"},{"lastName":"Chen","firstName":"Zhenpeng"},{"lastName":"Zhang","firstName":"Jie M."},{"lastName":"Harman","firstName":"Mark"},{"lastName":"Sarro","firstName":"Federica"}]}},{"key":"hossainIEEEPressEditorial","type":"article","fields":{"langid":["english"],"author":["Hossain, Ekram","Fortino, Giancarlo","Grier, David Alan","Heirman, Donald","Li, Xiaoou","Molisch, Andreas","Nahavandi, Saeid","Perez, Ray","Reed, Jeffrey","Shafer, Linda","Shahidehpour, Mohammad","Spurgeon, Sarah","Tekalp, Ahmet Murat"],"pages":["693"],"title":["IEEE Press Editorial Board"]},"creators":{"author":[{"lastName":"Hossain","firstName":"Ekram"},{"lastName":"Fortino","firstName":"Giancarlo"},{"lastName":"Grier","firstName":"David Alan"},{"lastName":"Heirman","firstName":"Donald"},{"lastName":"Li","firstName":"Xiaoou"},{"lastName":"Molisch","firstName":"Andreas"},{"lastName":"Nahavandi","firstName":"Saeid"},{"lastName":"Perez","firstName":"Ray"},{"lastName":"Reed","firstName":"Jeffrey"},{"lastName":"Shafer","firstName":"Linda"},{"lastName":"Shahidehpour","firstName":"Mohammad"},{"lastName":"Spurgeon","firstName":"Sarah"},{"lastName":"Tekalp","firstName":"Ahmet Murat"}]}},{"key":"Hou:2013:CCA:2550526.2550556","type":"inproceedings","fields":{"acmid":["2550556"],"author":["Hou, Daqing","Mo, Lingfeng"],"booktitle":["Proc. 2013 IEEE Int. Conf. Softw. Maint."],"date":["2013"],"isbn":["978-0-7695-4981-1"],"keywords":["APIs","AWT/Swing","MALLET","Naive Bayes","Online Forums","Text Categorization"],"location":["Washington, DC, USA"],"nodoi":["10.1109/ICSM.2013.17"],"note":["TL;DR \n\nA study to explore the question as to how well machine learning algorithms can be applied to categorize API discussions based on their content, and investigates factors that impact classification accuracy, including size of the training set and multi-label documents."],"numpages":["10"],"pages":["60–69"],"publisher":["IEEE Computer Society"],"series":["ICSM '13"],"title":["Content categorization of API discussions"],"url":["http://dx.doi.org/10.1109/ICSM.2013.17"]},"creators":{"author":[{"lastName":"Hou","firstName":"Daqing"},{"lastName":"Mo","firstName":"Lingfeng"}]},"sentenceCased":true},{"key":"houLargeLanguageModels2023","type":"online","fields":{"abstract":["Large Language Models (LLMs) have significantly impacted numerous domains, including Software Engineering (SE). Many recent publications have explored LLMs applied to various SE tasks. Nevertheless, a comprehensive understanding of the application, effects, and possible limitations of LLMs on SE is still in its early stages. To bridge this gap, we conducted a systematic literature review on LLM4SE, with a particular focus on understanding how LLMs can be exploited to optimize processes and outcomes. We collect and analyze 229 research papers from 2017 to 2023 to answer four key research questions (RQs). In RQ1, we categorize different LLMs that have been employed in SE tasks, characterizing their distinctive features and uses. In RQ2, we analyze the methods used in data collection, preprocessing, and application highlighting the role of well-curated datasets for successful LLM for SE implementation. RQ3 investigates the strategies employed to optimize and evaluate the performance of LLMs in SE. Finally, RQ4 examines the specific SE tasks where LLMs have shown success to date, illustrating their practical contributions to the field. From the answers to these RQs, we discuss the current state-of-the-art and trends, identifying gaps in existing research, and flagging promising areas for future study."],"author":["Hou, Xinyi","Zhao, Yanjie","Liu, Yue","Yang, Zhou","Wang, Kailong","Li, Li","Luo, Xiapu","Lo, David","Grundy, John","Wang, Haoyu"],"date":["2023-09-12"],"doi":["10.48550/arXiv.2308.10620"],"eprint":["2308.10620"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Software Engineering"],"note":["TL;DR \n\nA systematic literature review on LLM4SE is conducted, with a particular focus on understanding how LLMs can be exploited to optimize processes and outcomes."],"pubstate":["preprint"],"shorttitle":["Large Language Models for Software Engineering"],"title":["Large Language Models for Software Engineering: A Systematic Literature Review"]},"creators":{"author":[{"lastName":"Hou","firstName":"Xinyi"},{"lastName":"Zhao","firstName":"Yanjie"},{"lastName":"Liu","firstName":"Yue"},{"lastName":"Yang","firstName":"Zhou"},{"lastName":"Wang","firstName":"Kailong"},{"lastName":"Li","firstName":"Li"},{"lastName":"Luo","firstName":"Xiapu"},{"lastName":"Lo","firstName":"David"},{"lastName":"Grundy","firstName":"John"},{"lastName":"Wang","firstName":"Haoyu"}]}},{"key":"howard_fastai_2020","type":"article","fields":{"abstract":["fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying patterns of many deep learning and data processing techniques in terms of decoupled abstractions. These abstractions can be expressed concisely and clearly by leveraging the dynamism of the underlying Python language and the flexibility of the PyTorch library. fastai includes: a new type dispatch system for Python along with a semantic type hierarchy for tensors; a GPU-optimized computer vision library which can be extended in pure Python; an optimizer which refactors out the common functionality of modern optimizers into two basic pieces, allowing optimization algorithms to be implemented in 4-5 lines of code; a novel 2-way callback system that can access any part of the data, model, or optimizer and change it at any point during training; a new data block API; and much more. We have used this library to successfully create a complete deep learning course, which we were able to write more quickly than using previous approaches, and the code was more clear. The library is already in wide use in research, industry, and teaching. NB: This paper covers fastai v2, which is currently in pre-release at http://dev.fast.ai/"],"author":["Howard, Jeremy","Gugger, Sylvain"],"date":["2020-02"],"doi":["10.3390/info11020108"],"issn":["2078-2489"],"journaltitle":["Information"],"keywords":["Computer Science - Computer Vision and Pattern Recognition","Computer Science - Machine Learning","Computer Science - Neural and Evolutionary Computing","Statistics - Machine Learning"],"note":["arXiv: 2002.04688 \n\nTL;DR \n\nFastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level component that can be mixed and matched to build new approaches."],"number":["2"],"pages":["108"],"shorttitle":["Fastai"],"title":["Fastai: A Layered API for Deep Learning"],"volume":["11"]},"creators":{"author":[{"lastName":"Howard","firstName":"Jeremy"},{"lastName":"Gugger","firstName":"Sylvain"}]}},{"key":"HowCanUse","type":"online","fields":{"title":["How Can I Use This Method? - IEEE Conference Publication"],"url":["https://ieeexplore.ieee.org/document/7194634/"],"urldate":["2018-07-27"]},"creators":{}},{"key":"HowExactlyMachine","type":"online","fields":{"title":["How exactly is machine learning used in recommendation engines? - Quora"],"url":["https://www.quora.com/How-exactly-is-machine-learning-used-in-recommendation-engines"],"urldate":["2017-03-10"]},"creators":{},"sentenceCased":true},{"key":"HttpPdmaidsDibris","type":"misc","fields":{"title":["<span class=\"nocase\">http://pdm-aids.dibris.unige.it/questionnaire.php</span>"]},"creators":{}},{"key":"Huang:2012:LCD:2343876.2343884","type":"article","fields":{"acmid":["2343884"],"address":["New York, NY, USA"],"author":["Huang, Lan","Milne, David","Frank, Eibe","Witten, Ian H."],"date":["2012-08"],"issn":["1532-2882"],"issue_date":["August 2012"],"journaltitle":["J. Am. Soc. Inf. Sci. Technol."],"keywords":["content analysis","semantic analysis","text mining"],"nodoi":["10.1002/asi.22689"],"note":["TL;DR \n\nA new measure is proposed that assesses similarity at both the lexical and semantic levels, and learns from human judgments how to combine them by using machine-learning techniques, and shows that it improves both classification and clustering performance."],"number":["8"],"numpages":["16"],"pages":["1593–1608"],"publisher":["John Wiley & Sons, Inc."],"title":["Learning a concept-based document similarity measure"],"url":["http://dx.doi.org/10.1002/asi.22689"],"volume":["63"]},"creators":{"author":[{"lastName":"Huang","firstName":"Lan"},{"lastName":"Milne","firstName":"David"},{"lastName":"Frank","firstName":"Eibe"},{"lastName":"Witten","firstName":"Ian H."}]},"sentenceCased":true},{"key":"Huang20221457","type":"article","fields":{"abstract":["Massive machine-type communications (mMTC) are expected to support a large amount of randomly deployed users for short package transmissions. Noncoherent random access provides an efficient and practical multi-access protocol for mMTC, and also poses new challenges for the receiver design. In this paper, we leverage two well-known methods, i.e., message passing and deep learning, to jointly detect the user activity and the desired data for the noncoherent mMTC. First, by exploiting the exact distribution information of the received signal, a generalized approximate message passing (GAMP)-based algorithm is proposed, which is shown to jointly detect the user activity and the desired data by two modules: inter-user interference elimination and data detection for each user. Inspired by the two-module GAMP-based algorithm, we then propose a model-driven deep learning method, which utilizes the deep neural networks (DNNs) to approximate both the two modules. The loss function for training the DNNs is derived by formulating the two-module detection as an unconstrained optimization problem. Simulation results reveal that the proposed GAMP-based algorithm outperforms the proposed deep learning method when the channel distribution is perfectly known, while it suffers from a significant performance degradation for the case with imperfect channel distribution information. © 1983-2012 IEEE."],"author":["Huang, J.","Zhang, H.","Huang, C.","Yang, L.","Zhang, W."],"coden":["ISACE"],"date":["2022"],"document_type":["Article"],"doi":["10.1109/JSAC.2022.3143260"],"issn":["07338716"],"journaltitle":["IEEE J. Sel. Areas Commun."],"note":["cited By 1"],"number":["5"],"pages":["1457–1472"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Noncoherent massive random access for inhomogeneous networks: From message passing to deep learning"],"volume":["40"]},"creators":{"author":[{"lastName":"Huang","firstName":"J."},{"lastName":"Zhang","firstName":"H."},{"lastName":"Huang","firstName":"C."},{"lastName":"Yang","firstName":"L."},{"lastName":"Zhang","firstName":"W."}]},"sentenceCased":true},{"key":"huangSimilarityMeasuresText2008","type":"inproceedings","fields":{"added-at":["2010-01-10T13:17:50.000+0100"],"author":["Huang, A."],"biburl":["http://www.bibsonomy.org/bibtex/22731fc9ee66915a56f9ee14f1436aabf/cdevries"],"booktitle":["Proc. Sixth N. Z. Comput. Sci. Res. Stud. Conf. NZCSRSC2008 Christch. N. Z."],"date":["2008"],"interhash":["b05294a51336b00c449ecaeb25940212"],"intrahash":["2731fc9ee66915a56f9ee14f1436aabf"],"keywords":["clustering measures"],"note":["TL;DR \n\nA wide variety of distance functions and similarity measures have been used for clustering, such as squared Euclidean distance, cosine similarity, and relative entropy, and a comparison of these measures in partitional clustering for text document datasets is compared and analyzed."],"pages":["49–56"],"timestamp":["2010-01-10T13:17:50.000+0100"],"title":["Similarity measures for text document clustering"],"url":["http://scholar.google.com.au/scholar.bib?q=info:enBKVjSSXjQJ:scholar.google.com/&output=citation&hl=en&as_sdt=2000&ct=citation&cd=0"]},"creators":{"author":[{"lastName":"Huang","firstName":"A."}]},"sentenceCased":true},{"key":"huebscherSurveyAutonomicComputing2008","type":"article","fields":{"author":["Huebscher, Markus C.","McCann, Julie A."],"date":["2008"],"journaltitle":["ACM Comput. Surv. CSUR"],"number":["3"],"pages":["7"],"title":["A survey of autonomic Computing—Degrees, models, and applications"],"url":["http://dl.acm.org/citation.cfm?id=1380585"],"urldate":["2016-08-29"],"volume":["40"]},"creators":{"author":[{"lastName":"Huebscher","firstName":"Markus C."},{"lastName":"McCann","firstName":"Julie A."}]},"sentenceCased":true},{"key":"hug_surprise_2020","type":"article","fields":{"langid":["english"],"abstract":["Recommender systems aim at providing users with a list of recommendations of items that a service offers. For example, a video streaming service will typically rely on a recommender system to propose a personalized list of movies or series to each of its users. A typical problem in recommendation is that of rating prediction: given an incomplete dataset of useritem interations which take the form of numerical ratings (e.g. on a scale from 1 to 5), the goal is to predict the missing ratings for all remaining user-item pairs."],"author":["Hug, Nicolas"],"date":["2020-08"],"doi":["10.21105/joss.02174"],"issn":["2475-9066"],"journaltitle":["J. Open Source Softw."],"number":["52"],"pages":["2174"],"shorttitle":["Surprise"],"title":["Surprise: A Python library for recommender systems"],"volume":["5"]},"creators":{"author":[{"lastName":"Hug","firstName":"Nicolas"}]},"sentenceCased":true},{"key":"hulsbuschShowingFullSemantics2010","type":"incollection","fields":{"langid":["english"],"abstract":["Model transformation is a prime technique in modern, model-driven software design. One of the most challenging issues is to show that the semantics of the models is not affected by the transformation. So far, there is hardly any research into this issue, in particular in those cases where the source and target languages are different. In this paper, we are using two different state-of-the-art proof techniques (explicit bisimulation construction versus borrowed contexts) to show bisimilarity preservation of a given model transformation between two simple (self-defined) languages, both of which are equipped with a graph transformation-based operational semantics. The contrast between these proof techniques is interesting because they are based on different model transformation strategies: triple graph grammars versus in situ transformation. We proceed to compare the proofs and discuss scalability to a more realistic setting."],"author":["Hülsbusch, Mathias","König, Barbara","Rensink, Arend","Semenyak, Maria","Soltenborn, Christian","Wehrheim, Heike"],"booktitle":["Integrated Formal Methods"],"date":["2010"],"editor":["Méry, Dominique","Merz, Stephan"],"isbn":["978-3-642-16264-0 978-3-642-16265-7"],"keywords":["software engineering"],"number":["6396"],"pages":["183–198"],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture Notes in Computer Science"],"title":["Showing Full Semantics Preservation in Model Transformation - A Comparison of Techniques"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-16265-7_14"],"urldate":["2015-03-24"]},"creators":{"author":[{"lastName":"Hülsbusch","firstName":"Mathias"},{"lastName":"König","firstName":"Barbara"},{"lastName":"Rensink","firstName":"Arend"},{"lastName":"Semenyak","firstName":"Maria"},{"lastName":"Soltenborn","firstName":"Christian"},{"lastName":"Wehrheim","firstName":"Heike"}],"editor":[{"lastName":"Méry","firstName":"Dominique"},{"lastName":"Merz","firstName":"Stephan"}]}},{"key":"Hundt20191797","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["IEEE Int Conf Intell Rob Syst"],"affiliation":["Johns Hopkins University, Department of Computer Science, United States; NVIDIA, United States"],"art_number":["8967784"],"author":["Hundt, A.","Jain, V.","Lin, C.-H.","Paxton, C.","Hager, G.D."],"coden":["85RBA"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/IROS40897.2019.8967784"],"isbn":["978-1-72814-004-9"],"issn":["21530858"],"note":["cited By 2"],"pages":["1797–1804"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["IEEE International Conference on Intelligent Robots and Systems"],"source":["Scopus"],"title":["The CoSTAR block stacking dataset: Learning with workspace constraints"]},"creators":{"author":[{"lastName":"Hundt","firstName":"A."},{"lastName":"Jain","firstName":"V."},{"lastName":"Lin","firstName":"C.-H."},{"lastName":"Paxton","firstName":"C."},{"lastName":"Hager","firstName":"G.D."}]},"sentenceCased":true},{"key":"hurleySimplifyMachineLearning2020","type":"online","fields":{"langid":["english"],"abstract":["How to use Pipelines to standardize data preprocessing, data transformation, and modeling steps of a machine learning workflow"],"author":["Hurley, David"],"date":["2020-07-02T20:48:29"],"organization":["Medium"],"title":["Simplify Machine Learning Workflows"],"url":["https://towardsdatascience.com/simplify-machine-learning-workflows-e9d4f404aaeb"],"urldate":["2021-03-18"]},"creators":{"author":[{"lastName":"Hurley","firstName":"David"}]}},{"key":"husarAutonomousSystemsModeling2013","type":"article","fields":{"langid":["english"],"author":["Husar, Rosteslaw M.","Stracener, Jerrell"],"date":["2013"],"doi":["10.1016/j.procs.2013.09.268"],"issn":["18770509"],"journaltitle":["Procedia Comput. Sci."],"pages":["242–247"],"title":["Autonomous Systems Modeling During Early Architecture Development"],"volume":["20"]},"creators":{"author":[{"lastName":"Husar","firstName":"Rosteslaw M."},{"lastName":"Stracener","firstName":"Jerrell"}]}},{"key":"hutchinsonEmpiricalAssessmentMDE2011","type":"inproceedings","fields":{"author":["Hutchinson, John","Whittle, Jon","Rouncefield, Mark","Kristoffersen, Steinar"],"booktitle":["Proc. 33rd Int. Conf. Softw. Eng."],"date":["2011"],"note":["TL;DR \n\nUsing largely qualitative questionnaire and interview methods, a range of technical, organizational and social factors that apparently influence organizational responses to MDE are investigated and its perception as a successful or unsuccessful organizational intervention is investigated."],"pages":["471–480"],"publisher":["ACM"],"title":["Empirical assessment of MDE in industry"],"url":["http://dl.acm.org/citation.cfm?id=1985858"],"urldate":["2015-10-29"]},"creators":{"author":[{"lastName":"Hutchinson","firstName":"John"},{"lastName":"Whittle","firstName":"Jon"},{"lastName":"Rouncefield","firstName":"Mark"},{"lastName":"Kristoffersen","firstName":"Steinar"}]},"sentenceCased":true},{"key":"hutchinsonModeldrivenEngineeringPractices2013","type":"article","fields":{"author":["Hutchinson, John","Whittle, Jon","Rouncefield, Mark"],"date":["2013"],"doi":["10.1016/j.scico.2013.03.017"],"journaltitle":["Sci. Comput. Program."],"title":["Model-driven engineering practices in industry: Social, organizational and managerial factors that lead to success or failure"]},"creators":{"author":[{"lastName":"Hutchinson","firstName":"John"},{"lastName":"Whittle","firstName":"Jon"},{"lastName":"Rouncefield","firstName":"Mark"}]},"sentenceCased":true},{"key":"HybridApproachMetamodel","type":"online","fields":{"title":["Hybrid Approach for Metamodel and Model Co-evolution - Springer"],"url":["http://link.springer.com/chapter/10.1007%2F978-3-319-19578-0_46"],"urldate":["2015-07-19"]},"creators":{}},{"key":"Ickin202072","type":"inproceedings","fields":{"abstract":["Quality of Experience (QoE) models need good generalization that necessitates sufficient amount of user-labeled datasets associated with measurements related to underlying QoE factors. However, obtaining QoE datasets is often costly, since they are preferably collected from many subjects with diverse background, and eventually dataset sizes and representations are limited. Models can be improved by sharing and merging those collected local datasets, however regulations such as GDPR make data sharing difficult, as those local user datasets might contain sensitive information about the subjects. A privacy-preserving machine learning approach such as Federated Learning (FL) is a potential candidate that enables sharing of QoE data models between collaborators without exposing ground truth, but only by means of sharing the securely aggregated form of extracted model parameters. While FL can enable a seamless QoE model management, if collaborators do not have the same level of data quality, more iterations of information sharing over a communication channel might be necessary for models to reach an acceptable accuracy. In this paper, we present an ensemble based Bayesian synthetic data generation method for FL, LOO (Leave-One-Out), which reduces the training time by 30% and the network footprint in the communication channel by 60%. © 2020 IEEE."],"art_number":["9165379"],"author":["Ickin, S.","Vandikas, K.","Moradi, F.","Taghia, J.","Hu, W."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/NetSoft48620.2020.9165379"],"editor":["De Turck F., Chemouil P., Zhani M.F., Cerroni W., Pasquini R., Zhu Z., Wauters T."],"isbn":["978-1-72815-684-2"],"note":["cited By 2 \n\nTL;DR \n\nAn ensemble based Bayesian synthetic data generation method for FL, LOO (Leave-One-Out), which reduces the training time by 30% and the network footprint in the communication channel by 60%."],"pages":["72–76"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings of the 2020 IEEE Conference on Network Softwarization: Bridging the Gap Between AI and Network Softwarization, NetSoft 2020"],"source":["Scopus"],"title":["Ensemble-based synthetic data synthesis for federated QoE modeling"]},"creators":{"author":[{"lastName":"Ickin","firstName":"S."},{"lastName":"Vandikas","firstName":"K."},{"lastName":"Moradi","firstName":"F."},{"lastName":"Taghia","firstName":"J."},{"lastName":"Hu","firstName":"W."}],"editor":[{"lastName":"De Turck F.","suffix":"Chemouil P.","firstName":"Zhani M.F., Cerroni W., Pasquini R., Zhu Z., Wauters T."}]},"sentenceCased":true},{"key":"IEEECOMPUTINGEDGE2022","type":"article","fields":{"langid":["english"],"date":["2022-11"],"doi":["10.1109/MS.2022.3210313"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"keywords":["LOGSEQ"],"number":["6"],"pages":["C2-C2"],"title":["IEEE COMPUTING EDGE"],"volume":["39"]},"creators":{}},{"key":"IEEESoftwareBlog","type":"online","fields":{"title":["IEEE Software Blog: Autonomous Computing Systems: The Convergence of Control Theory and Computing Systems"],"url":["http://blog.ieeesoftware.org/2019/07/autonomous-computing-systems.html"],"urldate":["2020-10-05"]},"creators":{}},{"key":"IEEEXploreFullText","type":"online","fields":{"ids":["IEEEXploreFullTexta"],"title":["IEEE Xplore Full-Text PDF:"],"url":["https://ieeexplore-ieee-org.univaq.idm.oclc.org/stamp/stamp.jsp?tp=&arnumber=9845437"],"urldate":["2023-09-27"]},"creators":{}},{"key":"Ige20237","type":"article","fields":{"abstract":["In this research, we focus on the usage of adversarial sampling to test for the fairness in the prediction of deep neural network model across different classes of image in a given dataset. While several framework had been proposed to ensure robustness of machine learning model against adversarial attack, some of which includes adversarial training algorithm. There is still the pitfall that adversarial training algorithm tends to cause disparity in accuracy and robustness among different group. Our research is aimed at using adversarial sampling to test for fairness in the prediction of deep neural network model across different classes or categories of image in a given dataset. We successfully demonstrated a new method of ensuring fairness across various group of input in deep neural network classifier. We trained our neural network model on the original image, and without training our model on the perturbed or attacked image. When we feed the adversarial samplings to our model, it was able to predict the original category/ class of the image the adversarial sample belongs to. We also introduced and used the separation of concern concept from software engineering whereby there is an additional standalone filter layer that filters perturbed image by heavily removing the noise or attack before automatically passing it to the network for classification, we were able to have accuracy of 93.3%. Cifar-10 dataset have ten categories of dataset, and so, in order to account for fairness, we applied our hypothesis across each categories of dataset and were able to get a consistent result and accuracy © 2023, International Journal of Advanced Computer Science and Applications.All Rights Reserved."],"author":["Ige, T.","Marfo, W.","Tonkinson, J.","Adewale, S.","Matti, B.H."],"author_keywords":["adversarial defense; Adversarial machine learning, adversarial attack; adversarial sampling; deep neural network; fairness testing; machine learning fairness"],"date":["2023"],"document_type":["Article"],"doi":["10.14569/IJACSA.2023.0140202"],"issn":["2158107X"],"journaltitle":["Int. J. Adv. Comput. Sci. Appl."],"keywords":["adversarial attack","Adversarial defense","Adversarial machine learning","Adversarial sampling","Deep neural networks","Different class","Fairness testing","Forecasting","Learning algorithms","Learning systems","Machine learning fairness","Machine-learning","Neural network model","Neural network models","Software engineering","Statistical tests","Training algorithms"],"note":["cited By 0 \n\nTL;DR \n\nThis research focuses on the usage of adversarial sampling to test for the fairness in the prediction of deep neural network model across different classes of image in a given dataset and successfully demonstrated a new method of ensuring fairness across various group of input inDeep neural network classifier."],"number":["2"],"pages":["7–13"],"publisher":["Science and Information Organization"],"source":["Scopus"],"title":["Adversarial sampling for fairness testing in deep neural network"],"volume":["14"]},"creators":{"author":[{"lastName":"Ige","firstName":"T."},{"lastName":"Marfo","firstName":"W."},{"lastName":"Tonkinson","firstName":"J."},{"lastName":"Adewale","firstName":"S."},{"lastName":"Matti","firstName":"B.H."}]},"sentenceCased":true},{"key":"iglesiaMAPEKFormalTemplates2015","type":"article","fields":{"author":["Iglesia, Didac Gil De La","Weyns, Danny"],"date":["2015"],"journaltitle":["ACM Trans. Auton. Adapt. Syst. TAAS"],"note":["TL;DR \n\nA set of formally specified MAPE-K templates that encode design expertise for a family of self-adaptive systems and demonstrate the reusability of the formal templates are performed in which final-year Masters students used the templates to design different self- Adaptive systems."],"number":["3"],"pages":["15"],"title":["MAPE-K formal templates to rigorously design behaviors for self-adaptive systems"],"url":["http://dl.acm.org/citation.cfm?id=2724719"],"urldate":["2016-09-19"],"volume":["10"]},"creators":{"author":[{"lastName":"Iglesia","firstName":"Didac Gil De La"},{"lastName":"Weyns","firstName":"Danny"}]},"sentenceCased":true},{"key":"ihirweAssessingQualityLowCode2022","type":"inproceedings","fields":{"abstract":["Over the last few years, industry and academia have proposed several Low-Code and Model-driven Engineering (MDE) platforms to ease the engineering process of the Internet of things (IoT) systems. However, deciding whether such engineering platforms meet the minimum required software quality standards is not straightforward. Software quality can be defined as the degree to which a software system achieves its intended goal. Various software quality standards have been established to aid in the software quality assessment process; however, due to the nature of engineering IoT platforms, such models may not entirely suit the IoT domain. This paper presents a model for assessing the software quality of Low-Code and MDE platforms for engineering IoT platforms. The proposed software quality model is based on and extends the ISO/IEC 25010:2011 software product quality model standard. It is intended to assist IoT practitioners in assessing and establishing quality requirements for engineering IoT platforms. To determine the effectiveness of the proposed model, we used it to evaluate the quality of 17 IoT engineering platforms, and the results obtained are promising. © 2022 IEEE."],"author":["Ihirwe, F.","Di Ruscio, D.","Gianfranceschi, S.","Pierantonio, A."],"booktitle":["IEEE Int. Conf. Softw. Qual. Reliab. Secur. QRS"],"date":["2022"],"doi":["10.1109/QRS57517.2022.00065"],"isbn":["978-1-66547-704-8"],"issn":["26939177"],"keywords":["Assessment process","Code development","Computer software selection and evaluation","Development platform","Engineering process","Internet of things","ISO Standards","Low-code development platform","Model-driven Engineering","Software Quality","Software quality assessment","Software quality standards","Software-systems"],"note":["cited By 0"],"pages":["583–594"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Assessing the Quality of Low-Code and Model-Driven Engineering Platforms for Engineering IoT Systems"],"volume":["2022-December"]},"creators":{"author":[{"lastName":"Ihirwe","firstName":"F."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Gianfranceschi","firstName":"S."},{"lastName":"Pierantonio","firstName":"A."}]}},{"key":"ihirweCloudbasedModelingIoT2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["The current evolution of cloud-based computing opens up a lot of possibilities for software development. In the near future, complex systems in various domains such as Space, Automotive, Internet of Things, and Smart Cities, will be designed, developed, and deployed from cloud-based environments, hence lowering production and maintenance costs. However, in the IoT domain, parts of the system have to run on Edge, Fog, or Cloud, posing significant difficulties in determining what, where, and when to develop. Therefore, this paper conducted a thorough review to investigate where the IoT domain community stands concerning the current trend of moving traditional modeling infrastructures to the cloud. Following an examination of 625 articles, we focus on 22 different cloud-based IoT system development approaches. Moreover, we highlight various opportunities and challenges related to the adoption of cloud-based modeling tools and platforms in the IoT domain. © 2021 IEEE."],"author":["Ihirwe, F.","Indamutsa, A.","Ruscio, D.D.","Mazzini, S.","Pierantonio, A."],"booktitle":["ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion MODELS 2021 Companion Fukuoka Jpn. Oct. 10-15 2021"],"date":["2021"],"doi":["10.1109/MODELS-C53483.2021.00018"],"ids":["ihirweCloudbasedModelingIoT2021a,ihirweCloudbasedModelingIoT2021b,ihirweCloudbasedModelingIoT2021c,ihirweCloudbasedModelingIoT2021d"],"isbn":["978-1-66542-484-4"],"keywords":["Automotives","Based modelling","Cloud based computing","Cloud-based","Cloud-based modeling","Codes (symbols)","Internet of things","Low-code","Maintenance cost","Model-driven Engineering","Production cost","Software design"],"note":["cited By 1 \n\ncited By 1 \n\ncited By 1 \n\ncited By 4 \n\nTL;DR \n\nA thorough review is conducted to investigate where the IoT domain community stands concerning the current trend of moving traditional modeling infrastructures to the cloud and highlights various opportunities and challenges related to the adoption of cloud-based modeling tools and platforms in the IoTdomain."],"pages":["73–82"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Cloud-based modeling in IoT domain: A survey, open challenges and opportunities"]},"creators":{"author":[{"lastName":"Ihirwe","firstName":"F."},{"lastName":"Indamutsa","firstName":"A."},{"lastName":"Ruscio","firstName":"D.D."},{"lastName":"Mazzini","firstName":"S."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"ihirweDomainspecificModelingAnalysis2021","type":"article","fields":{"author":["Ihirwe, Felicien","Ruscio, Davide Di","Mazzini, Silvia","Pierantonio, Alfonso"],"date":["2021"],"eprint":["2109.09244"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"note":["TL;DR \n\nCHESSIoT, a domain-specific modeling environment for complex IoT applications, is introduced and the existing supported real-time analysis mechanism, as well as a proposed code generation approach, are presented."],"title":["A domain-specific modeling and analysis environment for complex IoT applications"],"url":["https://arxiv.org/abs/2109.09244"],"volume":["abs/2109.09244"]},"creators":{"author":[{"lastName":"Ihirwe","firstName":"Felicien"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Mazzini","firstName":"Silvia"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"ihirweLowcodeEngineeringInternet2020","type":"article","fields":{"author":["Ihirwe, F.","Di Ruscio, D.","Mazzini, S.","Pierini, P.","Pierantonio, A."],"date":["2020"],"doi":["10.1145/3417990.3420208"],"eprint":["2009.01876"],"eprinttype":["arxiv"],"ids":["ihirweLowcodeEngineeringInternet2020a,ihirweLowcodeEngineeringInternet2020b,ihirweLowcodeEngineeringInternet2020c"],"journaltitle":["Proc. - 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS-C 2020 - Companion Proc."],"note":["cited By 22 \n\ncited By 22 \n\nTL;DR \n\nBy analyzing sixteen platforms, a corresponding set of features has been identified to represent the functionalities and the services that each analyzed platform can support and identify the limitations of already existing approaches."],"pages":["522–529"],"title":["Low-code engineering for internet of things: A state of research"],"volume":["abs/2009.01876"]},"creators":{"author":[{"lastName":"Ihirwe","firstName":"F."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Mazzini","firstName":"S."},{"lastName":"Pierini","firstName":"P."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"ihirweModelingAnalysisEnvironment2021","type":"inproceedings","fields":{"langid":["english"],"author":["Ihirwe, F.","Di Ruscio, D.","Mazzini, S.","Pierantonio, A."],"booktitle":["CEUR Workshop Proc."],"date":["2021"],"editor":["Iovino L., Kristensen L.M."],"eprint":["2105.14136"],"eprinttype":["arxiv"],"ids":["ihirweModelingAnalysisEnvironment2021a,ihirweModelingAnalysisEnvironment2021b,ihirweModelingAnalysisEnvironment2021c"],"issn":["16130073"],"keywords":["Accident prevention","Analysis verification","CHESSIoT","Creative Commons","Critical condition","Internet of things","Model-driven Engineering","Modelling and analysis","Real-time schedulability analysis","Research communities","Schedulability analysis","Verification-and-validation"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 2"],"pages":["90–104"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"title":["Towards a modeling and analysis environment for industrial IoT systems"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118922446&partnerID=40&md5=447c34972f959432f7aa25e7a47cf771"],"volume":["2999"]},"creators":{"author":[{"lastName":"Ihirwe","firstName":"F."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Mazzini","firstName":"S."},{"lastName":"Pierantonio","firstName":"A."}],"editor":[{"lastName":"Iovino L.","firstName":"Kristensen L.M."}]},"sentenceCased":true},{"key":"ihirweMQTT5GeolocationExtension2021","type":"inproceedings","fields":{"langid":["english"],"author":["Ihirwe, F.","Iovino, G.","Di Ruscio, D."],"booktitle":["2021 44th Int. Conf. Telecommun. Signal Process. TSP 2021"],"date":["2021"],"doi":["10.1109/TSP52935.2021.9522590"],"editor":["N, Herencsar"],"ids":["ihirweMQTT5GeolocationExtension2021a,ihirweMQTT5GeolocationExtension2021b,ihirweMQTT5GeolocationExtension2021c"],"isbn":["978-1-66542-933-7"],"keywords":["Communications channels","Data acquisition","Fog computing","Geolocations","Location","Location-aware application","Message delivery","MQTT5","Wireless networks"],"note":["cited By 1 \n\ncited By 1 \n\ncited By 1 \n\ncited By 1 \n\nTL;DR \n\nA novel extension of the recently released MQTT5 protocol is proposed that will permit message delivery by not only respecting the topics of interest but also in addition to geo-referenced information provided by both publishers and subscribers."],"pages":["100–105"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Towards an MQTT5 geo-location extension for location-aware applications"]},"creators":{"author":[{"lastName":"Ihirwe","firstName":"F."},{"lastName":"Iovino","firstName":"G."},{"lastName":"Di Ruscio","firstName":"D."}],"editor":[{"lastName":"N","firstName":"Herencsar"}]},"sentenceCased":true},{"key":"ilahiChallengesCountermeasuresAdversarial2020","type":"article","fields":{"abstract":["Deep Reinforcement Learning (DRL) has numerous applications in the real world thanks to its outstanding ability in quickly adapting to the surrounding environments. Despite its great advantages, DRL is susceptible to adversarial attacks, which precludes its use in real-life critical systems and applications (e.g., smart grids, traffic controls, and autonomous vehicles) unless its vulnerabilities are addressed and mitigated. Thus, this paper provides a comprehensive survey that discusses emerging attacks in DRL-based systems and the potential countermeasures to defend against these attacks. We first cover some fundamental backgrounds about DRL and present emerging adversarial attacks on machine learning techniques. We then investigate more details of the vulnerabilities that the adversary can exploit to attack DRL along with the state-of-the-art countermeasures to prevent such attacks. Finally, we highlight open issues and research challenges for developing solutions to deal with attacks for DRL-based intelligent systems."],"author":["Ilahi, Inaam","Usama, Muhammad","Qadir, Junaid","Janjua, Muhammad Umar","Al-Fuqaha, Ala","Hoang, Dinh Thai","Niyato, Dusit"],"date":["2020-01-27"],"eprint":["2001.09684"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv200109684 Cs"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Cryptography and Security","Computer Science - Machine Learning"],"note":["TL;DR \n\nThis work investigates the vulnerabilities that an adversary can exploit to attack DRL along with state-of-the-art countermeasures to prevent such attacks and highlights open issues and research challenges for developing solutions to deal with attacks on DRL-based intelligent systems."],"title":["Challenges and Countermeasures for Adversarial Attacks on Deep Reinforcement Learning"],"url":["http://arxiv.org/abs/2001.09684"],"urldate":["2021-04-02"]},"creators":{"author":[{"lastName":"Ilahi","firstName":"Inaam"},{"lastName":"Usama","firstName":"Muhammad"},{"lastName":"Qadir","firstName":"Junaid"},{"lastName":"Janjua","firstName":"Muhammad Umar"},{"lastName":"Al-Fuqaha","firstName":"Ala"},{"lastName":"Hoang","firstName":"Dinh Thai"},{"lastName":"Niyato","firstName":"Dusit"}]}},{"key":"imamDataModelingGuidelines2018","type":"article","fields":{"langid":["english"],"abstract":["Good database design is key to high data availability and consistency in traditional databases, and numerous techniques exist to abet designers in modeling schemas appropriately. These schemas are strictly enforced by traditional database engines. However, with the emergence of schema-free databases (NoSQL) coupled with voluminous and highly diversified datasets (big data), such aid becomes even more important as schemas in NoSQL are enforced by application developers, which requires a high level of competence. Precisely, existing modeling techniques and guides used in traditional databases are insufficient for bigdata storage settings. As a synthesis, new modeling guidelines for NoSQL document-store databases are posed. These guidelines cut across both logical and physical stages of database designs. Each is developed based on solid empirical insights, yet they are prepared to be intuitive to developers and practitioners. To realize this goal, we employ an exploratory approach to the investigation of techniques, empirical methods and expert consultations. We analyze how industry experts prioritize requirements and analyze the relationships between datasets on the one hand and error prospects and awareness on the other hand. Few proprietary guidelines were extracted from a heuristic evaluation of 5 NoSQL databases. In this regard, the proposed guidelines have great potential to function as an imperative instrument of knowledge transfer from academia to NoSQL database modeling practices."],"author":["Imam, Abdullahi Abubakar","Basri, Shuib","Ahmad, Rohiza","Watada, Junzo","T., Maria","Ahmad, Malek"],"date":["2018"],"doi":["10.14569/IJACSA.2018.091066"],"issn":["21565570, 2158107X"],"journaltitle":["ijacsa"],"note":["TL;DR \n\nNew modeling guidelines for NoSQL document-store databases are posed and have great potential to function as an imperative instrument of knowledge transfer from academia to NoSQL database modeling practices."],"number":["10"],"title":["Data Modeling Guidelines for NoSQL Document-Store Databases"],"volume":["9"]},"creators":{"author":[{"lastName":"Imam","firstName":"Abdullahi Abubakar"},{"lastName":"Basri","firstName":"Shuib"},{"lastName":"Ahmad","firstName":"Rohiza"},{"lastName":"Watada","firstName":"Junzo"},{"lastName":"T.","firstName":"Maria"},{"lastName":"Ahmad","firstName":"Malek"}]}},{"key":"incLowCodePlatformRapidly2020","type":"online","fields":{"langid":["american"],"abstract":["This article talks about the importance of low-code platform in the analytics world and Low code vs traditional application development."],"author":["Inc, Gramener"],"date":["2020-10-13T15:41:09+00:00"],"organization":["Gramener Blog"],"shorttitle":["Low-Code Platform"],"title":["Low-Code Platform: Rapidly Build Enterprise-Grade Analytics Apps"],"url":["https://blog.gramener.com/low-code-platform-for-enterprise-analytics-applications/"],"urldate":["2021-03-18"]},"creators":{"author":[{"lastName":"Inc","firstName":"Gramener"}]}},{"key":"indamutsaLowCodeDevelopmentEnvironment2021","type":"article","fields":{"langid":["english"],"abstract":["The current digital transformation in production systems has positioned model-driven engineering (MDE) as a promising development solution to leverage models as first-class entities and support complex systems’ development through dedicated abstractions. Models are specified through domain-specific languages and consumed by dedicated model management services, which implement automation and analysis services. Achieving complex model-driven tasks that involve several model management services and multiple model repositories can be a difficult and error-prone task. For instance, modelers have to identify the proper atomic operations among available services, connect to remote model repositories, and figure out their composition to satisfy the final goal. Different composition proposals have been introduced in MDE even though a satisfactory solution is still missing. In this paper, we propose a low-code development environment to support citizen developers to plan, organize, specify and execute model-management workflows underpinning the development of complex systems. Thus, developers are relieved from managing low-level details, e.g., related to the discovery, orchestration, and integration of the needed model management services. © 2021, IFIP International Federation for Information Processing."],"author":["Indamutsa, A.","Di Ruscio, D.","Pierantonio, A."],"date":["2021"],"doi":["10.1007/978-3-030-85874-2_36"],"editor":["Dolgui A., Bernard A., Lemoine D., von Cieminski G., Romero D."],"ids":["indamutsaLowCodeDevelopmentEnvironment2021a,indamutsaLowCodeDevelopmentEnvironment2021b,indamutsaLowCodeDevelopmentEnvironment2021c"],"isbn":["9783030858735"],"issn":["18684238"],"journaltitle":["Adv. Prod. Manag. Syst. Artif. Intell. Sustain. Resilient Prod. Syst. - IFIP WG 57 Int. Conf. APMS 2021 Nantes Fr. Sept. 5-9 2021 Proc. Part I"],"keywords":["Artificial intelligence","Development solutions","Digital transformation","Domain specific languages","Environmental management","Industrial management","Model repositories","Model-driven Engineering","Multiple-modeling","Problem oriented languages","Production system","Satisfactory solutions"],"note":["cited By 1 \n\ncited By 1 \n\ncited By 1 \n\ncited By 4"],"pages":["342–350"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"series":["IFIP Advances in Information and Communication Technology"],"title":["A Low-Code Development Environment to Orchestrate Model Management Services"],"volume":["630 IFIP"]},"creators":{"author":[{"lastName":"Indamutsa","firstName":"A."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Pierantonio","firstName":"A."}],"editor":[{"lastName":"Dolgui A.","suffix":"Bernard A.","firstName":"Lemoine D., von Cieminski G., Romero D."}]}},{"key":"indamutsaMDEForgeWLCloudbasedDiscovery2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["Model management services play an essential role while developing complex systems by means of model-driven engineering (MDE) practices. They carry out several model management operations (MMOs), including model transformation, validation, comparison, and merging, which are exposed as remotely consumable services. However, the adoption of MMOs on cloud-based model repositories has raised issues related to their discovery and orchestration. Notably, it is an arduous and error-prone task to carry out the composition and execution of complex workflows involving different modeling artefacts consumed by various model management services.This paper presents MDEForgeWL, a complete infrastructure to support the execution of MMO workflows that are remotely available as dedicated services. MDEForgeWL consists of i) a DSL and supporting engine for defining and executing user-defined workflows of model management services, and ii) a cluster infrastructure to register new services and make them available for defining workflows. A prototypical implementation of MDEForgeWL is presented by applying it to an illustrative example. © 2021 IEEE."],"author":["Indamutsa, A.","Rocco, J.D.","Ruscio, D.D.","Pierantonio, A."],"booktitle":["Companion Proc. - 24th Int. Conf. Model-Driven Eng. Lang. Syst. MODELS-C 2021"],"date":["2021"],"doi":["10.1109/MODELS-C53483.2021.00023"],"ids":["indamutsaMDEForgeWLCloudbasedDiscovery2021a,indamutsaMDEForgeWLCloudbasedDiscovery2021b,indamutsaMDEForgeWLCloudbasedDiscovery2021c,indamutsaMDEForgeWLCloudbasedDiscovery2021d"],"isbn":["978-1-66542-484-4"],"keywords":["Cloud-based","Cloud-based model repository","Engines","Management operation","Management service","Model management","Model repositories","Model-driven Engineering","Problem oriented languages","Service discovery","Services composition","Workflow engines"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0 \n\nTL;DR \n\nMDEForgeWL is presented, a complete infrastructure to support the execution of MMO workflows that are remotely available as dedicated services and consists of a DSL and supporting engine for defining and executing user-defined workflows of model management services."],"pages":["118–127"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["MDEForgeWL: Towards cloud-based discovery and composition of model management services"]},"creators":{"author":[{"lastName":"Indamutsa","firstName":"A."},{"lastName":"Rocco","firstName":"J.D."},{"lastName":"Ruscio","firstName":"D.D."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"IndustrialCyberPhysicalSystems","type":"online","fields":{"title":["Industrial Cyber-Physical Systems Center (iCyPhy)"],"url":["http://www.icyphy.org/"],"urldate":["2016-01-26"]},"creators":{}},{"key":"IndustryEclipseKura","type":"online","fields":{"title":["Industry 4.0 with Eclipse Kura | EclipseCon Europe 2016"],"url":["https://www.eclipsecon.org/europe2016/session/industry-40-eclipse-kura"],"urldate":["2016-09-27"]},"creators":{}},{"key":"INFSOFD2300931_R1_reviewerPdf","type":"misc","fields":{"title":["INFSOF-D-23-00931_R1_reviewer.Pdf"]},"creators":{}},{"key":"InternetThingsCS","type":"online","fields":{"title":["Internet of Things [CS Open CourseWare]"],"url":["http://ocw.cs.pub.ro/courses/iot"],"urldate":["2016-09-11"]},"creators":{}},{"key":"InternetThingsRoad","type":"online","fields":{"title":["The Internet of Things is on the Road to Autonomous Driving"],"url":["http://www.intel.com/content/www/us/en/internet-of-things/infographics/iot-autonomous-driving-infographic.html"],"urldate":["2016-09-03"]},"creators":{},"sentenceCased":true},{"key":"IntocpsAuDk","type":"online","fields":{"title":["Into-Cps.Au.Dk"],"url":["http://into-cps.au.dk/"],"urldate":["2016-02-09"]},"creators":{}},{"key":"IntroductionBuildingMachine","type":"online","fields":{"langid":["english"],"abstract":["Chapter 1. Introduction In this first chapter, we will introduce machine learning pipelines and outline all the steps that go into building them. We’ll explain what needs to happen to … - Selection from Building Machine Learning Pipelines [Book]"],"title":["1. Introduction - Building Machine Learning Pipelines [Book]"],"url":["https://www.oreilly.com/library/view/building-machine-learning/9781492053187/ch01.html"],"urldate":["2021-03-18"]},"creators":{}},{"key":"IntroductionControlSystems","type":"online","fields":{"note":["TL;DR \n\nThis significantly revised edition presents a broad introduction to Control Systems and balances new, modern methods with the more classical, and includes an introductory guide to some more recent developments, namely fuzzy logic control and neural networks."],"title":["An Introduction To Control Systems"],"url":["https://www.facstaff.bucknell.edu/mastascu/eControlHTML/Intro/Intro1.html"],"urldate":["2016-11-01"]},"creators":{}},{"key":"IntroductionParallelComputing","type":"online","fields":{"note":["TL;DR \n\nPerformance and Scalability of Parallel Systems, General Issues in Mapping Systolic Systems Onto Parallel Computers, and Speedup Anomalies in Parallel Search Algorithms."],"title":["Introduction to Parallel Computing"],"url":["https://computing.llnl.gov/tutorials/parallel_comp/#Whatis"],"urldate":["2017-02-23"]},"creators":{}},{"key":"IntroduzioneScuolaCultura","type":"online","fields":{"title":["Introduzione - Scuola e cultura"],"url":["https://www.scuola-e-cultura.it/manuale-della-cultura/introduzione.htm"],"urldate":["2022-07-16"]},"creators":{},"sentenceCased":true},{"key":"inverardiProducingSoftwareIntegration2013","type":"inproceedings","fields":{"abstract":["Software is increasingly produced according to a certain goal and by integrating existing software produced by third-parties, typically black-box, and often provided without a machine readable documentation. This implies that development processes of the next future have to explicitly deal with an inherent incompleteness of information about existing software, notably on its behaviour. Therefore, on one side a software producer will less and less know the precise behaviour of a third party software service, on the other side she will need to use it to build her own application. In this paper we present an innovative development process to automatically produce dependable software systems by integrating existing services under uncertainty and according to the specied goal. Moreover, we (i) discuss important challenges that must be faced while producing the kind of systems we are targeting, (ii) give an overview of the state of art related to the identied challenges, and finally (iii) provide research directions to address these challenges."],"author":["Inverardi, P","Autili, M","Di Ruscio, D","Pelliccione, P","Tivoli, M"],"booktitle":["Jt. Meet. Eur. Softw. Eng. Conf. ACM SIGSOFT Symp. Found. Softw. Eng. ESECFSE13 St. Petersburg Russ. Fed. August 18-26 2013"],"date":["2013"],"doi":["10.1145/2491411.2505428"],"ids":["inverardiProducingSoftwareIntegration2013a,inverardiProducingSoftwareIntegration2013b"],"isbn":["978-1-4503-2237-9"],"keywords":["Automated synthesis","Dependable software systems","Model elicitation"],"note":["cited By 5 \n\ncited By 5"],"pages":["2–12"],"publisher":["ACM, Association for Computing Machinery"],"title":["Producing software by integration: Challenges and research directions (keynote)"]},"creators":{"author":[{"lastName":"Inverardi","firstName":"P"},{"lastName":"Autili","firstName":"M"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pelliccione","firstName":"P"},{"lastName":"Tivoli","firstName":"M"}]},"sentenceCased":true},{"key":"IoTSecurityAction","type":"online","fields":{"title":["IoT Security in action! | EclipseCon Europe 2016"],"url":["https://www.eclipsecon.org/europe2016/session/iot-security-action"],"urldate":["2016-09-27"]},"creators":{},"sentenceCased":true},{"key":"IoTVsM2M","type":"online","fields":{"title":["IoT vs. M2M, CPS, WoT....: Are these terms synonyms? | John Soldatos | Pulse | LinkedIn"],"url":["https://www.linkedin.com/pulse/iot-vs-m2m-cps-wot-terms-synonyms-john-soldatos"],"urldate":["2016-08-21"]},"creators":{},"sentenceCased":true},{"key":"Iovino2012OnTI","type":"article","fields":{"author":["Iovino, Ludovico","Pierantonio, Alfonso","Malavolta, Ivano"],"date":["2012"],"journaltitle":["J. Object Technol."],"note":["TL;DR \n\nThe problem of identifying, predicting and evaluating the significance of the metamodel change impact over the existing artifacts is discussed and the approach can be considered as preparatory to any systematic adaptation process."],"pages":["3: 1-33"],"title":["On the impact significance of metamodel evolution in MDE"],"volume":["11"]},"creators":{"author":[{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Malavolta","firstName":"Ivano"}]},"sentenceCased":true},{"key":"IovinoBRH20","type":"article","fields":{"langid":["english"],"abstract":["Domain modeling is a core activity in Model-Driven Engineering, and these models must be correct. A large number of artifacts may be constructed on top of these domain models, such as instance models, transformations, and editors. Similar to any other software artifact, domain models are subject to the introduction of errors during the modeling process. There are a number of existing tools that reduce the burden of manually dealing with correctness issues in models. Although various approaches have been proposed to support the quality assessment of modeling artifacts in the past decade, the quality of the automatically repaired models has not been the focus of repairing processes. In this paper, we propose the integration of an automatic evaluation of domain models based on a quality model with a framework for personalized and automatic model repair. The framework uses reinforcement learning to find the best sequence of actions for repairing a broken model."],"author":["Ludovico, Iovino","Barriga, Angela","Rutle, Adrian","Heldal, Rogardt"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2020"],"doi":["10.5381/jot.2020.19.2.a17"],"issn":["1660-1769"],"journaltitle":["JOT"],"keywords":["/unread","⛔ No INSPIRE recid found","GOAL-Model_Repair","notion","TECHNIQUE_ReinforcementLearning"],"note":["TL;DR \n\nThis paper proposes the integration of an automatic evaluation of domain models based on a quality model with a framework for personalized and automatic model repair, which uses reinforcement learning to find the best sequence of actions for repairing a broken model."],"number":["2"],"pages":["17:1"],"timestamp":["Sat, 09 Apr 2022 12:28:30 +0200"],"title":["Model Repair with Quality-Based Reinforcement Learning."],"volume":["19"]},"creators":{"author":[{"lastName":"Ludovico","firstName":"Iovino"},{"lastName":"Barriga","firstName":"Angela"},{"lastName":"Rutle","firstName":"Adrian"},{"lastName":"Heldal","firstName":"Rogardt"}]}},{"key":"iovinoMetamodelDeprecationManage2020","type":"inproceedings","fields":{"author":["Iovino, L.","Di Salle, A.","Di Ruscio, D.","Pierantonio, A."],"booktitle":["Proc. - 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS-C 2020 - Companion Proc."],"date":["2020"],"doi":["10.1145/3417990.3419625"],"ids":["iovinoMetamodelDeprecationManage2020a,iovinoMetamodelDeprecationManage2020b,iovinoMetamodelDeprecationManage2020c"],"isbn":["978-1-4503-8135-2"],"keywords":["Deprecation","MDE","Metamodeling","Technical debt"],"note":["cited By 0 \n\ncited By 0 \n\nTL;DR \n\nThis paper proposes using deprecation in metamodeling to mitigate the difficulties in performing a class of adaptations that must be operated manually and shows the feasibility of the methods."],"pages":["306–315"],"publisher":["Association for Computing Machinery, Inc"],"title":["Metamodel deprecation to manage technical debt in model co-evolution"]},"creators":{"author":[{"lastName":"Iovino","firstName":"L."},{"lastName":"Di Salle","firstName":"A."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"ISINKAYE2015261","type":"article","fields":{"author":["Isinkaye, F.O.","Folajimi, Y.O.","Ojokoh, B.A."],"date":["2015"],"issn":["1110-8665"],"journaltitle":["Egypt. Inform. J."],"keywords":["Collaborative filtering","Content-based filtering","Evaluation","Hybrid filtering technique","recommendation systems","Recommendation systems"],"nodoi":["https://doi.org/10.1016/j.eij.2015.06.005"],"nonote":["tex.nodoi: https://doi.org/10.1016/j.eij.2015.06.005"],"number":["3"],"pages":["261–273"],"title":["Recommendation systems: Principles, methods and evaluation"],"url":["http://www.sciencedirect.com/science/article/pii/S1110866515000341"],"volume":["16"]},"creators":{"author":[{"lastName":"Isinkaye","firstName":"F.O."},{"lastName":"Folajimi","firstName":"Y.O."},{"lastName":"Ojokoh","firstName":"B.A."}]},"sentenceCased":true},{"key":"islamLeveragingAutomatedSentiment2017","type":"inproceedings","fields":{"author":["Islam, Md Rakibul","Zibran, Minhaz F."],"date":["2017-05"],"doi":["10.1109/MSR.2017.9"],"isbn":["978-1-5386-1544-7"],"note":["TL;DR \n\nSentiStrength-SE, a tool for improved sentiment analysis especially designed for application in the software engineering domain, achieves 73.85% precision and 85% recall, which are significantly higher than a state-of-the-art sentiment analysis tool the authors compare with."],"pages":["203–214"],"publisher":["IEEE"],"title":["Leveraging Automated Sentiment Analysis in Software Engineering"]},"creators":{"author":[{"lastName":"Islam","firstName":"Md Rakibul"},{"lastName":"Zibran","firstName":"Minhaz F."}]}},{"key":"islamSemanticTextSimilarity2008","type":"article","fields":{"acmid":["1376819"],"address":["New York, NY, USA"],"articleno":["10"],"author":["Islam, Aminul","Inkpen, Diana"],"date":["2008-07"],"issn":["1556-4681"],"issue_date":["July 2008"],"journaltitle":["ACM Trans. Knowl. Discov. Data"],"keywords":["corpus-based measures","Semantic similarity of words","similarity of short texts"],"nodoi":["10.1145/1376815.1376819"],"number":["2"],"numpages":["25"],"pages":["10:1-10:25"],"publisher":["ACM"],"title":["Semantic text similarity using corpus-based word similarity and string similarity"],"url":["http://doi.acm.org/10.1145/1376815.1376819"],"volume":["2"]},"creators":{"author":[{"lastName":"Islam","firstName":"Aminul"},{"lastName":"Inkpen","firstName":"Diana"}]},"sentenceCased":true},{"key":"jaccardDistributionFloraAlpine1912","type":"article","fields":{"author":["Jaccard, Paul"],"date":["1912"],"journaltitle":["New Phytol."],"nodoi":["10.1111/j.1469-8137.1912.tb05611.x"],"number":["2"],"pages":["37–50"],"title":["The distribution of the flora in the alpine zone"],"volume":["11"]},"creators":{"author":[{"lastName":"Jaccard","firstName":"Paul"}]},"sentenceCased":true},{"key":"Jackson202090","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Networks Syst."],"affiliation":["Transport and Telecommunication Institute (TTI), Lomonosova iela 1, Riga, Latvia"],"author":["Jackson, I."],"correspondence_address1":["Jackson, I.; Transport and Telecommunication Institute (TTI), Lomonosova iela 1, Latvia; email: jackson.i@tsi.lv"],"date":["2020"],"document_type":["Book Chapter"],"doi":["10.1007/978-3-030-44610-9_10"],"issn":["23673370"],"journaltitle":["Lect. Notes Netw. Syst."],"note":["cited By 0 \n\nTL;DR \n\nThe proposed framework incorporates multilayer perceptron and genetic algorithm and demonstrates the application of this framework to metamodeling of multiproduct production-inventory system with lost-sales and Markov-modulated demand."],"pages":["90–99"],"publisher":["Springer"],"source":["Scopus"],"title":["Neuroevolutionary approach to metamodeling of production-inventory systems with lost-sales and markovian demand"],"volume":["117"]},"creators":{"author":[{"lastName":"Jackson","firstName":"I."}]},"sentenceCased":true},{"key":"Jackson202184","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Networks Syst."],"affiliation":["Transport and Telecommunication Institute (TTI), Lomonosova Iela 1, Riga, Latvia"],"author":["Jackson, I."],"correspondence_address1":["Jackson, I.; Transport and Telecommunication Institute (TTI), Lomonosova Iela 1, Latvia; email: jackson.i@tsi.lv"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-68476-1_8"],"editor":["Kabashkin I., Yatskiv I., Prentkovskis O."],"isbn":["9783030684754"],"issn":["23673370"],"journaltitle":["Lect. Notes Netw. Syst."],"note":["cited By 1 \n\nTL;DR \n\nWhether it is feasible and efficient to combine artificial neural network with genetic algorithm for metamodeling automation of logistic and production systems and the possibility of using the proposed approach to derive optimal control parameters is discussed."],"pages":["84–93"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Neuroevolutionary approach to metamodel-based optimization in production and logistics"],"volume":["195"]},"creators":{"author":[{"lastName":"Jackson","firstName":"I."}],"editor":[{"lastName":"Kabashkin I.","suffix":"Yatskiv I.","firstName":"Prentkovskis O."}]},"sentenceCased":true},{"key":"jacksonAutomaticallyReasoningMetamodeling2015","type":"article","fields":{"langid":["english"],"author":["Jackson, Ethan K.","Levendovszky, Tihamer","Balasubramanian, Daniel"],"date":["2015-02"],"doi":["10.1007/s10270-013-0315-y"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nThis paper presents one approach to this problem: metamodeling frameworks are specified modularly using algebraic data types and constraint logic programming (CLP)."],"number":["1"],"pages":["271–285"],"title":["Automatically reasoning about metamodeling"],"volume":["14"]},"creators":{"author":[{"lastName":"Jackson","firstName":"Ethan K."},{"lastName":"Levendovszky","firstName":"Tihamer"},{"lastName":"Balasubramanian","firstName":"Daniel"}]},"sentenceCased":true},{"key":"jainDataClusteringReview1999","type":"article","fields":{"author":["Jain, Anil K.","Murty, M. Narasimha","Flynn, Patrick J."],"date":["1999"],"ids":["jain1999data"],"journaltitle":["ACM Comput. Surv. CSUR"],"note":["TL;DR \n\nAn overview of pattern clustering methods from a statistical pattern recognition perspective is presented, with a goal of providing useful advice and references to fundamental concepts accessible to the broad community of clustering practitioners."],"number":["3"],"pages":["264–323"],"publisher":["Acm"],"shorttitle":["Data clustering"],"title":["Data clustering: A review"],"url":["http://dl.acm.org/citation.cfm?id=331504"],"urldate":["2015-04-24"],"volume":["31"]},"creators":{"author":[{"lastName":"Jain","firstName":"Anil K."},{"lastName":"Murty","firstName":"M. Narasimha"},{"lastName":"Flynn","firstName":"Patrick J."}]},"sentenceCased":true},{"key":"Jamei2015133","type":"article","fields":{"abstract":["Deployment of smart meters has been greatly increased over the recent years. Most of the installed smart meters have been equipped with Advanced Metering Infrastructure (AMI) which enables a bidirectional wireless communication to gather the usage data from gas, electricity and water meters. The insecure wireless channel used by AMI meters jeopardizes the privacy of costumers and brings up cybersecurity issues since it allows hackers to monitor the energy usage data from different houses. To show the penetrability of the system, Received Signal Strength (RSS) - based localization of smart meters incorporating Maximum Likelihood (ML) estimator has been proposed in this paper. By decoding the received signal from a smart meter, one can localize the unoccupied houses or track the people's daily routines. The effectiveness of the proposed ML location estimator has been examined through MATLAB simulation, under the assumption of a log-normal path loss model and Frequency Shift Keying (FSK) modulation and demodulation. Particle Swarm Optimization (PSO) has been used to find the ML estimation. Finally, the effect of the variance, the number of the sensors and the path loss exponent has been studied on the average Miss Distance Error (MDE). © Springer International Publishing Switzerland 2015."],"author":["Jamei, M.","Sarwat, A.I.","Iyengar, S.S.","Kaleem, F."],"date":["2015"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-319-08422-0_20"],"isbn":["9783319084213"],"issn":["21945357"],"journaltitle":["Adv. Intell. Syst. Comput."],"note":["cited By 2 \n\nTL;DR \n\nTo show the penetrability of the system, Received Signal Strength (RSS) - based localization of smart meters incorporating Maximum Likelihood (ML) estimator has been proposed in this paper."],"pages":["133–139"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Security breach possibility with RSS-Based localization of smart meters incorporating maximum likelihood estimator"],"volume":["1089"]},"creators":{"author":[{"lastName":"Jamei","firstName":"M."},{"lastName":"Sarwat","firstName":"A.I."},{"lastName":"Iyengar","firstName":"S.S."},{"lastName":"Kaleem","firstName":"F."}]},"sentenceCased":true},{"key":"Jamshidi201939","type":"inproceedings","fields":{"abstract":["Modern cyber-physical systems (e.g., robotics systems) are typically composed of physical and software components, the characteristics of which are likely to change over time. Assumptions about parts of the system made at design time may not hold at run time, especially when a system is deployed for long periods (e.g., over decades). Self-adaptation is designed to find reconfigurations of systems to handle such run-time inconsistencies. Planners can be used to find and enact optimal reconfigurations in such an evolving context. However, for systems that are highly configurable, such planning becomes intractable due to the size of the adaptation space. To overcome this challenge, in this paper we explore an approach that (a) uses machine learning to find Pareto-optimal configurations without needing to explore every configuration and (b) restricts the search space to such configurations to make planning tractable. We explore this in the context of robot missions that need to consider task timeliness and energy consumption. An independent evaluation shows that our approach results in high-quality adaptation plans in uncertain and adversarial environments. © 2019 IEEE."],"art_number":["8787014"],"author":["Jamshidi, P.","Camara, J.","Schmerl, B.","Kaestner, C.","Garlan, D."],"author_keywords":["artificial intelligence; Machine learning; quantitative planning; robotics systems; self-adaptive systems"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/SEAMS.2019.00015"],"isbn":["978-1-72813-368-3"],"issn":["21572305"],"keywords":["Adaptive systems","Adversarial environments","Artificial intelligence","Embedded systems","Energy utilization","Learning systems","Machine learning","Optimal reconfigurations","Pareto principle","Pareto-optimal configurations","Robot programming","Robotics","Robotics systems","Search spaces","Self adaptation","Self-adaptive system","Software component","Software engineering"],"note":["cited By 37"],"pages":["39–50"],"publisher":["IEEE Computer Society"],"series":["ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems"],"source":["Scopus"],"title":["Machine learning meets quantitative planning: Enabling self-adaptation in autonomous robots"],"volume":["2019-May"]},"creators":{"author":[{"lastName":"Jamshidi","firstName":"P."},{"lastName":"Camara","firstName":"J."},{"lastName":"Schmerl","firstName":"B."},{"lastName":"Kaestner","firstName":"C."},{"lastName":"Garlan","firstName":"D."}]},"sentenceCased":true},{"key":"Javidan2019602","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Comput.-Aided Civ. Infrastruct. Eng."],"affiliation":["Department of Civil & Architectural Engineering, Sungkyunkwan University, Suwon, South Korea"],"author":["Javidan, M.M.","Kim, J."],"coden":["CCIEF"],"correspondence_address1":["Kim, J.; Department of Civil & Architectural Engineering, South Korea; email: jkim12@skku.edu"],"date":["2019"],"document_type":["Article"],"doi":["10.1111/mice.12436"],"issn":["10939687"],"journaltitle":["Comput.-Aided Civ. Infrastruct. Eng."],"note":["cited By 20"],"number":["7"],"pages":["602–615"],"publisher":["Blackwell Publishing Inc."],"source":["Scopus"],"title":["Variance-based global sensitivity analysis for fuzzy random structural systems"],"volume":["34"]},"creators":{"author":[{"lastName":"Javidan","firstName":"M.M."},{"lastName":"Kim","firstName":"J."}]},"sentenceCased":true},{"key":"jeanjeanIDECodeReifying2021","type":"article","fields":{"langid":["english"],"abstract":["To cope with the ever-growing number of programming languages, manufacturers of Integrated Development Environments (IDE) have recently defined protocols as a way to use and share multiple language services (e.g., auto-completion, type checker, language runtime) in language-agnostic environments (i.e., the user interface provided by the IDE): the most notable are the Language Server Protocol (LSP) for textual editors, and the Debug Adapter Protocol (DAP) for debugging facilities. These protocols rely on a proper specification of the services that are commonly found in the tool support of general-purpose languages, and define a fixed set of capabilities to offer in the IDE. However, new languages appear regularly offering unique constructs (e.g., Domain-Specific Languages), and supported by dedicated services to be offered as new capabilities in IDEs. This trend leads to the multiplication of new protocols, hard to combine and possibly incompatible (e.g., overlap, different technological stacks). Beyond the proposition of specific protocols, the goal of this paper is to stress out the importance of being able to specify language protocols and to offer IDEs to be configured with such protocol specifications. We present our vision by discussing the main concepts for the specification of language protocols, and an approach that can make use of these specifications in order to deploy an IDE as a set of coordinated, individually deployed, language capabilities (e.g., microservice choreography). IDEs went from directly supporting languages to protocols, and we envision in this paper the next step: IDE as Code, where language protocols are created or inferred on demand and serve as support of an adaptation loop taking in charge of the (re)configuration of the IDE."],"author":["Jeanjean, Pierre","Combemale, Benoit","Barais, Olivier"],"date":["2021"],"pages":["6"],"title":["IDE as Code: Reifying Language Protocols as First-Class Citizens"]},"creators":{"author":[{"lastName":"Jeanjean","firstName":"Pierre"},{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Barais","firstName":"Olivier"}]}},{"key":"jeffreyHybridMethodologyAnomaly2024","type":"article","fields":{"abstract":["The rapid adoption of Industry 4.0 has seen Information Technology (IT) networks increasingly merged with Operational Technology (OT) networks, which have traditionally been isolated on air-gapped and fully trusted networks. This increased attack surface has resulted in compromises of Cyber–Physical Systems (CPS) with significant economic and life safety consequences. This paper proposes a hybrid model of anomaly detection of security threats to CPS by blending the signature-based and threshold-based Intrusion Detection Systems (IDS) commonly used in IT networks, with a Machine Learning (ML) model designed to detect behaviour-based anomalies in OT networks. This hybrid model achieves more rapid detection of known threats through signature-based and threshold-based detection strategies, and more accurate detection of unknown threats via behaviour-based anomaly detection using ML algorithms."],"author":["Jeffrey, Nicholas","Tan, Qing","Villar, José R."],"date":["2024-02-01"],"doi":["10.1016/j.neucom.2023.127068"],"issn":["0925-2312"],"journaltitle":["Neurocomputing"],"keywords":["Cyber–Physical Systems","Machine learning","Security threats"],"pages":["127068"],"title":["A hybrid methodology for anomaly detection in Cyber–Physical Systems"],"volume":["568"]},"creators":{"author":[{"lastName":"Jeffrey","firstName":"Nicholas"},{"lastName":"Tan","firstName":"Qing"},{"lastName":"Villar","firstName":"José R."}]},"sentenceCased":true},{"key":"jehSimRankMeasureStructuralcontext2002","type":"inproceedings","fields":{"acmid":["775126"],"author":["Jeh, Glen","Widom, Jennifer"],"booktitle":["Proc. Eighth ACM SIGKDD Int. Conf. Knowl. Discov. Data Min."],"date":["2002"],"isbn":["1-58113-567-X"],"location":["New York, NY, USA"],"nodoi":["10.1145/775047.775126"],"note":["TL;DR \n\nA complementary approach, applicable in any domain with object-to-object relationships, that measures similarity of the structural context in which objects occur, based on their relationships with other objects is proposed."],"numpages":["6"],"pages":["538–543"],"publisher":["ACM"],"series":["KDD '02"],"title":["SimRank: A measure of structural-context similarity"],"url":["http://doi.acm.org/10.1145/775047.775126"]},"creators":{"author":[{"lastName":"Jeh","firstName":"Glen"},{"lastName":"Widom","firstName":"Jennifer"}]},"sentenceCased":true},{"key":"Jeon2022","type":"article","fields":{"abstract":["Wireless systems continue to go towards higher carrier frequencies, including terahertz bands, to take advantage of higher bandwidth channels. At the same time, antenna arrays remain important with continued increases in array elements. Yet, the power consumption of RF and digital circuits can increase proportionally to both the amount of signal bandwidth and the number of antennas. The use of one-bit analog-to-digital converters (ADCs) at the receiver is a cost-and power-efficient solution for wideband and/or massive antenna wireless systems. The nonlinearity of one-bit received signals brings challenges in physical-layer design at the receiver. At the same time, the binary nature of these signals opens new opportunities for artificial intelligence (AI) based physical-layer (PHY) design. This article covers recent progress in incorporating AI into the design of classical PHY techniques and emerging studies on establishing AIinspired frameworks that fundamentally replace classical model-driven techniques with data-driven AI techniques. It concludes with a discussion, including practical challenges and future research directions. IEEE"],"author":["Jeon, Y.","Kim, D.","Hong, S.","Lee, N.","Heath, R.W."],"coden":["ICOMD"],"date":["2022"],"document_type":["Article"],"doi":["10.1109/MCOM.007.2200002"],"issn":["01636804"],"journaltitle":["IEEE Commun. Mag."],"note":["cited By 0 \n\nTL;DR \n\nRecent progress in incorporating AI into the design of classical PHY techniques and emerging studies on establishing AI-inspired frameworks that fundamentally replace classical model-driven techniques with data-driven AI techniques are covered."],"pages":["1–7"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Artificial intelligence for physical-layer design of MIMO communications with one-bit ADCs"]},"creators":{"author":[{"lastName":"Jeon","firstName":"Y."},{"lastName":"Kim","firstName":"D."},{"lastName":"Hong","firstName":"S."},{"lastName":"Lee","firstName":"N."},{"lastName":"Heath","firstName":"R.W."}]},"sentenceCased":true},{"key":"Jha20212374","type":"article","fields":{"abstract":["We propose a Bayesian deep learning framework for model driven online sparse channel estimation task in Multi-user MIMO systems. Tools from Bayesian neural network and stochastic variational Bayesian Inference are utilized to capture aleatoric and epistemic uncertainty estimates. We treat the network prediction as an auxiliary variable to allow inference performance to be unaffected by the stage of training of the network. In addition to providing uncertainty estimates, being Bayesian, the framework enables us the possibility to marginalize over penalty parameters and is well suited for online scenario with changing environments. Our simulations show that the framework is robust to model mismatch, and efficiently captures uncertainty in the predictions. © 1983-2012 IEEE."],"art_number":["9448139"],"author":["Jha, N.K.","Lau, V.K.N."],"coden":["ISACE"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/JSAC.2021.3087249"],"issn":["07338716"],"journaltitle":["IEEE J. Sel. Areas Commun."],"note":["cited By 1 \n\nTL;DR \n\nA Bayesian deep learning framework for model driven online sparse channel estimation task in Multi-user MIMO systems that enables the possibility to marginalize over penalty parameters and is well suited for online scenario with changing environments."],"number":["8"],"pages":["2374–2387"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Online downlink multi-user channel estimation for mmWave systems using bayesian neural network"],"volume":["39"]},"creators":{"author":[{"lastName":"Jha","firstName":"N.K."},{"lastName":"Lau","firstName":"V.K.N."}]},"sentenceCased":true},{"key":"jhaAdversarialMachineLearning","type":"article","fields":{"langid":["english"],"author":["Jha, Somesh"],"keywords":["adversarial machine learning"],"pages":["71"],"title":["Adversarial Machine Learning (AML)"]},"creators":{"author":[{"lastName":"Jha","firstName":"Somesh"}]}},{"key":"Jia2021","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Verif. Valid. Symp., VVS"],"affiliation":["Concordia University, Montreal, Canada; Texas AandM University at Qatar, Doha, Qatar"],"art_number":["VVS2021-65272"],"author":["Jia, B.","Hou, D.","Wang, L.L.","Hassan, I.G."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1115/VVS2021-65272"],"isbn":["978-0-7918-8478-2"],"note":["cited By 0"],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the 2021 ASME Verification and Validation Symposium, VVS 2021"],"source":["Scopus"],"title":["Estimation of room-level cooling energy in Hot/Arid climate by machine learning-based approaches"]},"creators":{"author":[{"lastName":"Jia","firstName":"B."},{"lastName":"Hou","firstName":"D."},{"lastName":"Wang","firstName":"L.L."},{"lastName":"Hassan","firstName":"I.G."}]},"sentenceCased":true},{"key":"Jiang20217655","type":"article","fields":{"abstract":["Orthogonal frequency division multiplexing (OFDM) has been widely applied in many wireless communi- cation systems. The artificial intelligence (AI)-aided OFDM receivers are currently brought to the forefront to replace and improve the traditional OFDM receivers. In this paper, we first compare two AI-aided OFDM receivers, namely, data-driven fully connected deep neural network and model-driven ComNet, through extensive simulation and real-time video transmission using a 5G rapid prototyping system for an over-the-air (OTA) test. We find a performance gap between the simulation and the OTA test caused by the discrepancy between the channel model for offline training and the real environment. We develop a novel online training system, which is called SwitchNet receiver, to address this issue. This receiver has a flexible and extendable architecture and can adapt to real channels by training only several parameters online. From the OTA test, the AI-aided OFDM receivers, especially the SwitchNet receiver, are robust to OTA environments and promising for future communication systems. At the end of this paper, we discuss potential challenges and future research inspired by our initial study in this paper. © 2002-2012 IEEE."],"author":["Jiang, P.","Wang, T.","Han, B.","Gao, X.","Zhang, J.","Wen, C.-K.","Jin, S.","Li, G.Y."],"date":["2021"],"document_type":["Article"],"doi":["10.1109/TWC.2021.3087191"],"issn":["15361276"],"journaltitle":["IEEE Trans. Wirel. Commun."],"note":["cited By 1 \n\nTL;DR \n\nFrom the OTA test, the AI-aided OFDM receivers, especially the SwitchNet receiver, are robust to OTA environments and promising for future communication systems."],"number":["11"],"pages":["7655–7668"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["AI-Aided online adaptive OFDM receiver: Design and experimental results"],"volume":["20"]},"creators":{"author":[{"lastName":"Jiang","firstName":"P."},{"lastName":"Wang","firstName":"T."},{"lastName":"Han","firstName":"B."},{"lastName":"Gao","firstName":"X."},{"lastName":"Zhang","firstName":"J."},{"lastName":"Wen","firstName":"C.-K."},{"lastName":"Jin","firstName":"S."},{"lastName":"Li","firstName":"G.Y."}]},"sentenceCased":true},{"key":"jiangArtPromptASCIIArtbased2024","type":"online","fields":{"abstract":["Safety is critical to the usage of large language models (LLMs). Multiple techniques such as data filtering and supervised fine-tuning have been developed to strengthen LLM safety. However, currently known techniques presume that corpora used for safety alignment of LLMs are solely interpreted by semantics. This assumption, however, does not hold in real-world applications, which leads to severe vulnerabilities in LLMs. For example, users of forums often use ASCII art, a form of text-based art, to convey image information. In this paper, we propose a novel ASCII art-based jailbreak attack and introduce a comprehensive benchmark Vision-in-Text Challenge (ViTC) to evaluate the capabilities of LLMs in recognizing prompts that cannot be solely interpreted by semantics. We show that five SOTA LLMs (GPT-3.5, GPT-4, Gemini, Claude, and Llama2) struggle to recognize prompts provided in the form of ASCII art. Based on this observation, we develop the jailbreak attack ArtPrompt, which leverages the poor performance of LLMs in recognizing ASCII art to bypass safety measures and elicit undesired behaviors from LLMs. ArtPrompt only requires black-box access to the victim LLMs, making it a practical attack. We evaluate ArtPrompt on five SOTA LLMs, and show that ArtPrompt can effectively and efficiently induce undesired behaviors from all five LLMs."],"author":["Jiang, Fengqing","Xu, Zhangchen","Niu, Luyao","Xiang, Zhen","Ramasubramanian, Bhaskar","Li, Bo","Poovendran, Radha"],"date":["2024-02-22"],"doi":["10.48550/arXiv.2402.11753"],"eprint":["2402.11753"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Computation and Language"],"note":["TL;DR \n\nThe jailbreak attack ArtPrompt is developed, which leverages the poor performance of LLMs in recognizing ASCII art to bypass safety measures and elicit undesired behaviors from LLMs."],"pubstate":["preprint"],"shorttitle":["ArtPrompt"],"title":["ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs"]},"creators":{"author":[{"lastName":"Jiang","firstName":"Fengqing"},{"lastName":"Xu","firstName":"Zhangchen"},{"lastName":"Niu","firstName":"Luyao"},{"lastName":"Xiang","firstName":"Zhen"},{"lastName":"Ramasubramanian","firstName":"Bhaskar"},{"lastName":"Li","firstName":"Bo"},{"lastName":"Poovendran","firstName":"Radha"}]}},{"key":"jiangEmpiricalStudyPreTrained2023","type":"online","fields":{"abstract":["Deep Neural Networks (DNNs) are being adopted as components in software systems. Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the-art architectures grow more complex. Following the path of traditional software engineering, machine learning engineers have begun to reuse large-scale pre-trained models (PTMs) and fine-tune these models for downstream tasks. Prior works have studied reuse practices for traditional software packages to guide software engineers towards better package maintenance and dependency management. We lack a similar foundation of knowledge to guide behaviors in pre-trained model ecosystems. In this work, we present the first empirical investigation of PTM reuse. We interviewed 12 practitioners from the most popular PTM ecosystem, Hugging Face, to learn the practices and challenges of PTM reuse. From this data, we model the decision-making process for PTM reuse. Based on the identified practices, we describe useful attributes for model reuse, including provenance, reproducibility, and portability. Three challenges for PTM reuse are missing attributes, discrepancies between claimed and actual performance, and model risks. We substantiate these identified challenges with systematic measurements in the Hugging Face ecosystem. Our work informs future directions on optimizing deep learning ecosystems by automated measuring useful attributes and potential attacks, and envision future research on infrastructure and standardization for model registries."],"author":["Jiang, Wenxin","Synovic, Nicholas","Hyatt, Matt","Schorlemmer, Taylor R.","Sethi, Rohan","Lu, Yung-Hsiang","Thiruvathukal, George K.","Davis, James C."],"date":["2023-03-04"],"doi":["10.48550/arXiv.2303.02552"],"eprint":["2303.02552"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Machine Learning","Computer Science - Software Engineering","LOGSEQ"],"note":["Comment: Proceedings of the ACM/IEEE 45th International Conference on Software Engineering (ICSE) 2023"],"pubstate":["preprint"],"title":["An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry"]},"creators":{"author":[{"lastName":"Jiang","firstName":"Wenxin"},{"lastName":"Synovic","firstName":"Nicholas"},{"lastName":"Hyatt","firstName":"Matt"},{"lastName":"Schorlemmer","firstName":"Taylor R."},{"lastName":"Sethi","firstName":"Rohan"},{"lastName":"Lu","firstName":"Yung-Hsiang"},{"lastName":"Thiruvathukal","firstName":"George K."},{"lastName":"Davis","firstName":"James C."}]}},{"key":"jiangSemanticSimilarityBased1997","type":"inproceedings","fields":{"abstract":["This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better quantified with the computational evidence derived from a distributional analysis of corpus data. Specifically, the proposed measure is a combined approach that inherits the edge-based approach of the edge counting scheme, which is then enhanced by the node-based approach of the information content calculation. When tested on a common data set of word pair similarity ratings, the proposed approach outperforms other computational models. It gives the highest correlation value (r = 0.828) with a benchmark based on human similarity judgements, whereas an upper bound (r = 0.885) is observed when human subjects replicate the same task."],"added-at":["2010-03-12T16:18:27.000+0100"],"author":["Jiang, J.J.","Conrath, D.W."],"biburl":["http://www.bibsonomy.org/bibtex/2c4ffc507dafc908eab62fde53f7e4f7a/sdo"],"booktitle":["Proc Intl Conf Res. Comput. Linguist."],"date":["1997"],"description":["Jiang Conrath Maß"],"interhash":["175ec03ee8c47d4b2d0a083609a78e05"],"intrahash":["c4ffc507dafc908eab62fde53f7e4f7a"],"keywords":["1997 Conrath Jiang JiangConrath folksonomy lexical measure semantic similarity taxonomy"],"note":["TL;DR \n\nThis paper presents a new approach for measuring semantic similarity/distance between words and concepts that combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better quantified with the computational evidence derived from a distributional analysis of corpus data."],"pages":["19–33"],"timestamp":["2010-03-12T16:18:27.000+0100"],"title":["Semantic similarity based on corpus statistics and lexical taxonomy"],"url":["http://www.cse.iitb.ac.in/~cs626-449/Papers/WordSimilarity/4.pdf"]},"creators":{"author":[{"lastName":"Jiang","firstName":"J.J."},{"lastName":"Conrath","firstName":"D.W."}]},"sentenceCased":true},{"key":"jiangWhyHowDevelopers2017","type":"article","fields":{"acmid":["3042043"],"address":["Hingham, MA, USA"],"author":["Jiang, Jing","Lo, David","He, Jiahuan","Xia, Xin","Kochhar, Pavneet Singh","Zhang, Li"],"date":["2017-02"],"issn":["1382-3256"],"issue_date":["February 2017"],"journaltitle":["Empir. Softw Engg"],"keywords":["Fork","GitHub","Open source software"],"nodoi":["10.1007/s10664-016-9436-6"],"note":["TL;DR \n\nThe results show that forking is mainly used for making contributions of original repositories, and it is beneficial for OSS community, and the value of recommendation is shown and provides important insights for GitHub to recommend repositories."],"number":["1"],"numpages":["32"],"pages":["547–578"],"publisher":["Kluwer Academic Publishers"],"title":["Why and how developers fork what from whom in GitHub"],"url":["https://doi.org/10.1007/s10664-016-9436-6"],"volume":["22"]},"creators":{"author":[{"lastName":"Jiang","firstName":"Jing"},{"lastName":"Lo","firstName":"David"},{"lastName":"He","firstName":"Jiahuan"},{"lastName":"Xia","firstName":"Xin"},{"lastName":"Kochhar","firstName":"Pavneet Singh"},{"lastName":"Zhang","firstName":"Li"}]},"sentenceCased":true},{"key":"jilani2014search","type":"inproceedings","fields":{"langid":["english"],"author":["Jilani, Atif Aftab","Iqbal, Muhammad Zohaib","Khan, Muhammad Uzair"],"booktitle":["Theory Pract. Model Transform. 7th Int. Conf. ICMT 2014 Held Part STAF 2014 York UK July 21-22 2014 Proc. 7"],"date":["2014"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["17–24"],"publisher":["Springer"],"title":["A search based test data generation approach for model transformations"]},"creators":{"author":[{"lastName":"Jilani","firstName":"Atif Aftab"},{"lastName":"Iqbal","firstName":"Muhammad Zohaib"},{"lastName":"Khan","firstName":"Muhammad Uzair"}]},"sentenceCased":true},{"key":"Jindal20213202","type":"article","fields":{"abstract":["The goal of this tutorial is to educate the audience about the state of the art in ML for cloud data systems, both in research and in practice. The tutorial is divided in two parts: the progress, and the path forward. Part I covers the recent successes in deploying machine learning solutions for cloud data systems. We will discuss the practical considerations taken into account and the progress made at various levels. The goal is to compare and contrast the promise of ML for systems with the ground actually covered in industry. Finally, Part II discusses practical issues of machine learning in the enterprise covering the generation of explanations, model debugging, model deployment, model management, constraints on eyes-on data usage and anonymization, and a discussion of the technical debt that can accrue through machine learning and models in the enterprise. © The authors."],"author":["Jindal, A.","Interlandi, M."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.14778/3476311.3476408"],"editor":["Dong X.L., Naumann F."],"issn":["21508097"],"journaltitle":["Proc. VLDB Endow."],"note":["cited By 0 \n\nTL;DR \n\nThe goal of this tutorial is to educate the audience about the state of the art in ML for cloud data systems, both in research and in practice, and compare and contrast the promise of ML for systems with the ground actually covered in industry."],"number":["12"],"pages":["3202–3205"],"publisher":["VLDB Endowment"],"source":["Scopus"],"title":["Machine learning for cloud data systems: The progress so far and the path forward"],"volume":["14"]},"creators":{"author":[{"lastName":"Jindal","firstName":"A."},{"lastName":"Interlandi","firstName":"M."}],"editor":[{"lastName":"Dong X.L.","firstName":"Naumann F."}]},"sentenceCased":true},{"key":"jinghanSurveyNoSQLDatabase2011","type":"inproceedings","fields":{"abstract":["With the development of the Internet and cloud computing, there need databases to be able to store and process big data effectively, demand for high-performance when reading and writing, so the traditional relational database is facing many new challenges. Especially in large scale and high-concurrency applications, such as search engines and SNS, using the relational database to store and query dynamic user data has appeared to be inadequate. In this case, NoSQL database created. This paper describes the background, basic characteristics, data model of NoSQL. In addition, this paper classifies NoSQL databases according to the CAP theorem. Finally, the mainstream NoSQL databases are separately described in detail, and extract some properties to help enterprises to choose NoSQL."],"author":["Jing Han","Haihong E","Guan Le","Jian Du"],"booktitle":["2011 6th Int. Conf. Pervasive Comput. Appl."],"date":["2011-10"],"doi":["10.1109/ICPCA.2011.6106531"],"eventtitle":["2011 6th International Conference on Pervasive Computing and Applications"],"keywords":["Big Data","Blogs","CAP theorem","cloud computing","column-oriented","Computational modeling","data model","database","Databases","document","Facebook","high-concurrency applications","Internet","key-value","NoSQL","NoSQL database","query dynamic user data","query processing","relational database","relational databases","Reliability","search engines","SNS","SQL"],"pages":["363–366"],"title":["Survey on NoSQL database"]},"creators":{"author":[{"literal":"Jing Han"},{"literal":"Haihong E"},{"literal":"Guan Le"},{"literal":"Jian Du"}]},"sentenceCased":true},{"key":"jinSurveyFairnessawareRecommender2023","type":"article","fields":{"langid":["english"],"abstract":["As information filtering services, recommender systems have extremely enriched our daily life by providing personalized suggestions and facilitating people in decision-making, which makes them vital and indispensable to human society in the information era. However, as people become more dependent on them, recent studies show that recommender systems potentially own unintentional impacts on society and individuals because of their unfairness (e.g., gender discrimination in job recommendations). To develop trustworthy services, it is crucial to devise fairness-aware recommender systems that can mitigate these bias issues. In this survey, we summarize existing methodologies and practices of fairness in recommender systems. Firstly, we present concepts of fairness in different recommendation scenarios, comprehensively categorize current advances, and introduce typical methods to promote fairness in different stages of recommender systems. Next, after introducing datasets and evaluation metrics applied to assess the fairness of recommender systems, we will delve into the significant influence that fairness-aware recommender systems exert on real-world industrial applications. Subsequently, we highlight the connection between fairness and other principles of trustworthy recommender systems, aiming to consider trustworthiness principles holistically while advocating for fairness. Finally, we summarize this review, spotlighting promising opportunities in comprehending concepts, frameworks, the balance between accuracy and fairness, and the ties with trustworthiness, with the ultimate goal of fostering the development of fairness-aware recommender systems."],"author":["Jin, Di","Wang, Luzhi","Zhang, He","Zheng, Yizhen","Ding, Weiping","Xia, Feng","Pan, Shirui"],"date":["2023-12"],"doi":["10.1016/j.inffus.2023.101906"],"issn":["15662535"],"journaltitle":["Information Fusion"],"note":["TL;DR \n\nA review of existing methodologies and practices of fairness in recommender systems, spotlighting promising opportunities in comprehending concepts, frameworks, the balance between accuracy and fairness, and the ties with trustworthiness with the ultimate goal of fostering the development of fairness-awareRecommender systems."],"pages":["101906"],"title":["A survey on fairness-aware recommender systems"],"volume":["100"]},"creators":{"author":[{"lastName":"Jin","firstName":"Di"},{"lastName":"Wang","firstName":"Luzhi"},{"lastName":"Zhang","firstName":"He"},{"lastName":"Zheng","firstName":"Yizhen"},{"lastName":"Ding","firstName":"Weiping"},{"lastName":"Xia","firstName":"Feng"},{"lastName":"Pan","firstName":"Shirui"}]},"sentenceCased":true},{"key":"johannKiefMorrisInfrastructure2017","type":"article","fields":{"abstract":["Cloud specialist Kief Morris joins Software Engineering Radio host Sven Johann to discuss the benefits of infrastructure as code, including security, auditability, testing, documentation, and traceability."],"author":["Johann, Sven"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["software engineering"],"number":["1"],"pages":["117–120"],"title":["Kief Morris on Infrastructure as Code"],"volume":["34"]},"creators":{"author":[{"lastName":"Johann","firstName":"Sven"}]}},{"key":"JohnKLT23","type":"article","fields":{"langid":["english"],"author":["John, Stefan","Kosiol, Jens","Lambers, Leen","Taentzer, Gabriele"],"date":["2023"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["4"],"pages":["1281–1318"],"title":["A graph-based framework for model-driven optimization facilitating impact analysis of mutation operator properties"],"volume":["22"]},"creators":{"author":[{"lastName":"John","firstName":"Stefan"},{"lastName":"Kosiol","firstName":"Jens"},{"lastName":"Lambers","firstName":"Leen"},{"lastName":"Taentzer","firstName":"Gabriele"}]},"sentenceCased":true},{"key":"JointICTPIAEASchool","type":"online","fields":{"keywords":["grafana","influxdb","internet of things"],"title":["Joint ICTP-IAEA School on LoRa Enabled Radiation and Environmental Monitoring Sensors"],"url":["http://wireless.ictp.it/school_2018/"],"urldate":["2021-01-05"]},"creators":{}},{"key":"JongelingCC19","type":"inproceedings","fields":{"langid":["english"],"author":["Jongeling, Robbert","Carlson, Jan","Cicchetti, Antonio"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["45th Euromicro Conf. Softw. Eng. Adv. Appl. SEAA 2019 Kallithea-Chalkidiki Greece August 28-30 2019"],"date":["2019"],"doi":["10.1109/SEAA.2019.00071"],"editor":["Staron, Miroslaw","Capilla, Rafael","Skavhaug, Amund"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nModel synchronization and tool interoperability are found the most challenging to overcome and the ways in which they are circumvented in practice are detrimental for introducing continuous integration."],"pages":["434–441"],"publisher":["IEEE"],"timestamp":["Mon, 25 Nov 2019 13:49:21 +0100"],"title":["Impediments to introducing continuous integration for model-based development in industry"]},"creators":{"author":[{"lastName":"Jongeling","firstName":"Robbert"},{"lastName":"Carlson","firstName":"Jan"},{"lastName":"Cicchetti","firstName":"Antonio"}],"editor":[{"lastName":"Staron","firstName":"Miroslaw"},{"lastName":"Capilla","firstName":"Rafael"},{"lastName":"Skavhaug","firstName":"Amund"}]},"sentenceCased":true},{"key":"jorro-aragoneses_recolibry_2020","type":"article","fields":{"langid":["english"],"abstract":["Recommendation systems are a key part of almost every modern consumer website. Recommender systems include techniques to filter, explore and rank a huge amount of information and items according to the user’s current interests, and the similarity among users and items. Designing and implementing a recommender system usually requires high programming and machine learning skills. To alleviate these processes we present RecoLibry Suite: a set of intelligent tools to assist different types of users on the development of recommender systems. RecoLibry Suite supports not only the design and development of recommender systems but also its deployment as software as a service. We have evaluated the usability of the proposed tools with real users."],"author":["Jorro-Aragoneses, Jose Luis","Díaz-Agudo, Belén","Recio-García, Juan A.","Jimenez-Díaz, Guillermo"],"date":["2020-06"],"doi":["10.1007/s10515-020-00269-4"],"issn":["0928-8910, 1573-7535"],"journaltitle":["Autom. Softw. Eng."],"note":["TL;DR \n\nRecoLibry Suite is presented: a set of intelligent tools to assist different types of users on the development of recommender systems, and the usability of the proposed tools is evaluated with real users."],"number":["1-2"],"pages":["63–89"],"shorttitle":["RecoLibry Suite"],"title":["RecoLibry Suite: A set of intelligent tools for the development of recommender systems"],"volume":["27"]},"creators":{"author":[{"lastName":"Jorro-Aragoneses","firstName":"Jose Luis"},{"lastName":"Díaz-Agudo","firstName":"Belén"},{"lastName":"Recio-García","firstName":"Juan A."},{"lastName":"Jimenez-Díaz","firstName":"Guillermo"}]},"sentenceCased":true},{"key":"josebaAutomaticImpactAnalysis","type":"article","fields":{"author":["Joseba, Agirre","Leire, Etxeberria","Goiuria, Sagardui"],"journaltitle":["AMT MoDELS 2013"],"title":["Automatic impact analysis of software architecture migration on Model Driven Software Development"]},"creators":{"author":[{"lastName":"Joseba","firstName":"Agirre"},{"lastName":"Leire","firstName":"Etxeberria"},{"lastName":"Goiuria","firstName":"Sagardui"}]},"sentenceCased":true},{"key":"journals/bmcbi/SchlickerDRL06","type":"article","fields":{"added-at":["2009-11-10T00:00:00.000+0100"],"author":["Schlicker, Andreas","Domingues, Francisco S.","Rahnenführer, Jörg","Lengauer, Thomas"],"biburl":["http://www.bibsonomy.org/bibtex/209c4c56514b6a72f7b855ebea6cdacd0/dblp"],"description":["dblp"],"ee":["http://dx.doi.org/10.1186/1471-2105-7-302"],"interhash":["799547cf798d57975c427f4f389a5e0b"],"intrahash":["09c4c56514b6a72f7b855ebea6cdacd0"],"journaltitle":["BMC Bioinformatics"],"keywords":["dblp"],"pages":["302"],"timestamp":["2009-11-10T00:00:00.000+0100"],"title":["A new measure for functional similarity of gene products based on Gene Ontology."],"url":["http://dblp.uni-trier.de/db/journals/bmcbi/bmcbi7.html#SchlickerDRL06"],"volume":["7"],"year":["2009-11-10, 2006"]},"creators":{"author":[{"lastName":"Schlicker","firstName":"Andreas"},{"lastName":"Domingues","firstName":"Francisco S."},{"lastName":"Rahnenführer","firstName":"Jörg"},{"lastName":"Lengauer","firstName":"Thomas"}]},"sentenceCased":true},{"key":"jungBuildingAutomationSmart2013","type":"inproceedings","fields":{"author":["Jung, Markus","Weidinger, J.","Kastner, W.","Olivieri, A."],"date":["2013-03"],"doi":["10.1109/WAINA.2013.200"],"isbn":["978-1-4673-6239-9 978-0-7695-4952-1"],"note":["TL;DR \n\nThe integration approach aims at providing a homogeneous integration layer that can be used to build advanced control scenarios that might arise in the context of smart cities."],"pages":["1361–1367"],"publisher":["IEEE"],"shorttitle":["Building Automation and Smart Cities"],"title":["Building Automation and Smart Cities: An Integration Approach Based on a Service-Oriented Architecture"]},"creators":{"author":[{"lastName":"Jung","firstName":"Markus"},{"lastName":"Weidinger","firstName":"J."},{"lastName":"Kastner","firstName":"W."},{"lastName":"Olivieri","firstName":"A."}]}},{"key":"Jurgelaitis202163","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Adv. Intell. Sys. Comput."],"affiliation":["Informatics Faculty, Kaunas University of Technology, Kaunas, Lithuania"],"author":["Jurgelaitis, M.","Drungilas, V.","Čeponienė, L.","Vaičiukynas, E.","Butkienė, R.","Čeponis, J."],"correspondence_address1":["Jurgelaitis, M.; Informatics Faculty, Lithuania; email: mantas.jurgelaitis@ktu.lt"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-72654-6_7"],"editor":["Rocha A., Adeli H., Moreira F., Correia A.M.R., Dzemyda G."],"isbn":["9783030726539"],"issn":["21945357"],"journaltitle":["Adv. Intell. Syst. Comput."],"note":["cited By 2"],"pages":["63–73"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Smart contract code generation from platform specific model for hyperledger go"],"volume":["1368 AISC"]},"creators":{"author":[{"lastName":"Jurgelaitis","firstName":"M."},{"lastName":"Drungilas","firstName":"V."},{"lastName":"Čeponienė","firstName":"L."},{"lastName":"Vaičiukynas","firstName":"E."},{"lastName":"Butkienė","firstName":"R."},{"lastName":"Čeponis","firstName":"J."}],"editor":[{"lastName":"Rocha A.","suffix":"Adeli H.","firstName":"Moreira F., Correia A.M.R., Dzemyda G."}]},"sentenceCased":true},{"key":"KalliamvakouGBSGD14","type":"inproceedings","fields":{"author":["Kalliamvakou, Eirini","Gousios, Georgios","Blincoe, Kelly","Singer, Leif","Germán, Daniel M.","Damian, Daniela E."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/conf/msr/KalliamvakouGBSGD14.bib"],"booktitle":["11th Work. Conf. Min. Softw. Repos. MSR 2014 Proc. May 31 - June 1 2014 Hyderabad India"],"date":["2014"],"note":["TL;DR \n\nIt is shown, for example, that the majority of the projects are personal and inactive; that GitHub is also being used for free storage and as a Web hosting service; and that almost 40% of all pull requests do not appear as merged, even though they were."],"pages":["92–101"],"timestamp":["Wed, 14 Nov 2018 10:57:56 +0100"],"title":["The promises and perils of mining GitHub"]},"creators":{"author":[{"lastName":"Kalliamvakou","firstName":"Eirini"},{"lastName":"Gousios","firstName":"Georgios"},{"lastName":"Blincoe","firstName":"Kelly"},{"lastName":"Singer","firstName":"Leif"},{"lastName":"Germán","firstName":"Daniel M."},{"lastName":"Damian","firstName":"Daniela E."}]},"sentenceCased":true},{"key":"Kanetaki2021V","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Front. Artif. Intell. Appl."],"affiliation":["University of West Attica, Athens, Greece"],"art_number":["127-136"],"author":["Kanetaki, Z.","Stergiou, C.","Bekas, G.","Troussas, C.","Sgouropoulou, C."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.3233/FAIA210085"],"editor":["Frasson C., Kabassi K., Voulodimos A."],"isbn":["9781643682044"],"issn":["09226389"],"journaltitle":["Front. Artif. Intell. Appl."],"note":["cited By 4 \n\nTL;DR \n\nThis study investigates students’ satisfaction prediction in a first-semester Mechanical Engineering CAD module combined with the evaluation and the effectiveness of specific curriculum reforms."],"pages":["V-VI"],"publisher":["IOS Press BV"],"source":["Scopus"],"title":["Creating a metamodel for predicting learners satisfaction by utilizing an educational information system during COVID-19 pandemic"],"volume":["338"]},"creators":{"author":[{"lastName":"Kanetaki","firstName":"Z."},{"lastName":"Stergiou","firstName":"C."},{"lastName":"Bekas","firstName":"G."},{"lastName":"Troussas","firstName":"C."},{"lastName":"Sgouropoulou","firstName":"C."}],"editor":[{"lastName":"Frasson C.","suffix":"Kabassi K.","firstName":"Voulodimos A."}]},"sentenceCased":true},{"key":"KappelKKKRRSW06","type":"inproceedings","fields":{"langid":["english"],"author":["Kappel, Gerti","Kapsammer, Elisabeth","Kargl, Horst","Kramler, Gerhard","Reiter, Thomas","Retschitzegger, Werner","Schwinger, Wieland","Wimmer, Manuel"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Model Driven Eng. Lang. Syst. 9th Int. Conf. MoDELS 2006 Genova Italy Oct. 1-6 2006 Proc."],"date":["2006"],"doi":["10.1007/11880240\\_37"],"editor":["Nierstrasz, Oscar","Whittle, Jon","Harel, David","Reggio, Gianna"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["528–542"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Tue, 24 May 2022 15:28:49 +0200"],"title":["Lifting metamodels to ontologies: A step to the semantic integration of modeling languages"],"volume":["4199"]},"creators":{"author":[{"lastName":"Kappel","firstName":"Gerti"},{"lastName":"Kapsammer","firstName":"Elisabeth"},{"lastName":"Kargl","firstName":"Horst"},{"lastName":"Kramler","firstName":"Gerhard"},{"lastName":"Reiter","firstName":"Thomas"},{"lastName":"Retschitzegger","firstName":"Werner"},{"lastName":"Schwinger","firstName":"Wieland"},{"lastName":"Wimmer","firstName":"Manuel"}],"editor":[{"lastName":"Nierstrasz","firstName":"Oscar"},{"lastName":"Whittle","firstName":"Jon"},{"lastName":"Harel","firstName":"David"},{"lastName":"Reggio","firstName":"Gianna"}]},"sentenceCased":true},{"key":"kapua","type":"misc","fields":{"title":["Eclipse Kapua"],"url":["https://projects.eclipse.org/projects/iot.kapua"]},"creators":{}},{"key":"karasneh2013online","type":"inproceedings","fields":{"author":["Karasneh, Bilal","Chaudron, Michel RV"],"booktitle":["EESSMOD MoDELS"],"date":["2013"],"pages":["61–66"],"title":["Online Img2UML repository: An online repository for UML models."]},"creators":{"author":[{"lastName":"Karasneh","firstName":"Bilal"},{"lastName":"Chaudron","firstName":"Michel RV"}]},"sentenceCased":true},{"key":"Karatzoglou:2017:DLR:3109859.3109933","type":"inproceedings","fields":{"acmid":["3109933"],"author":["Karatzoglou, Alexandros","Hidasi, Balázs"],"booktitle":["Proc. Elev. ACM Conf. Recomm. Syst."],"date":["2017"],"isbn":["978-1-4503-4652-8"],"keywords":["deep learning","recommender systems"],"location":["New York, NY, USA"],"nodoi":["10.1145/3109859.3109933"],"numpages":["2"],"pages":["396–397"],"publisher":["ACM"],"series":["RecSys '17"],"title":["Deep learning for recommender systems"],"url":["http://doi.acm.org/10.1145/3109859.3109933"]},"creators":{"author":[{"lastName":"Karatzoglou","firstName":"Alexandros"},{"lastName":"Hidasi","firstName":"Balázs"}]},"sentenceCased":true},{"key":"karinHighperformanceComputingContinuum1998","type":"article","fields":{"langid":["english"],"author":["Karin, Sidney","Graham, Susan"],"date":["1998-11"],"doi":["10.1145/287831.287837"],"issn":["0001-0782, 1557-7317"],"journaltitle":["Commun. ACM"],"note":["TL;DR \n\nJust as in the worldwide PC environment, high-end systems are increasingly ubiquitous, continuous, and pervasive, while the emergence of the WorldWide Web has produced another trend—the dynamic use of multiple physical computer systems viewed by the end user as a single system."],"number":["11"],"pages":["32–35"],"title":["The high-performance computing continuum"],"volume":["41"]},"creators":{"author":[{"lastName":"Karin","firstName":"Sidney"},{"lastName":"Graham","firstName":"Susan"}]},"sentenceCased":true},{"key":"karmakar_what_2022","type":"inproceedings","fields":{"abstract":["Pre-trained models of code built on the transformer architecture have performed well on software engineering (SE) tasks such as predictive code generation, code summarization, among others. However, whether the vector representations from these pre-trained models comprehensively encode characteristics of source code well enough to be applicable to a broad spectrum of downstream tasks remains an open question. One way to investigate this is with diagnostic tasks called probes. In this paper, we construct four probing tasks (probing for surface-level, syntactic, structural, and semantic information) for pre-trained code models. We show how probes can be used to identify whether models are deficient in (understanding) certain code properties, characterize different model layers, and get insight into the model sample-efficiency. We probe four models that vary in their expected knowledge of code properties: BERT (pre-trained on English), CodeBERT and CodeBERTa (pre-trained on source code, and natural language documentation), and GraphCodeBERT (pre-trained on source code with dataflow). While GraphCodeBERT performs more consistently overall, we find that BERT performs surprisingly well on some code tasks, which calls for further investigation."],"author":["Karmakar, Anjan","Robbes, Romain"],"booktitle":["Proc. 36th IEEEACM Int. Conf. Autom. Softw. Eng."],"date":["2022-06"],"doi":["10.1109/ASE51524.2021.9678927"],"isbn":["978-1-66540-337-5"],"keywords":["probing","software engineering tasks","source code models","transformers"],"location":["Melbourne, Australia"],"note":["TL;DR \n\nFour probing tasks are constructed (probing for surface-level, syntactic, structural, and semantic information) for pre-trained code models to identify whether models are deficient in (understanding) certain code properties, characterize different model layers, and get insight into the model sample-efficiency."],"pages":["1332–1336"],"publisher":["IEEE Press"],"series":["ASE '21"],"title":["What do pre-trained code models know about code?"]},"creators":{"author":[{"lastName":"Karmakar","firstName":"Anjan"},{"lastName":"Robbes","firstName":"Romain"}]},"sentenceCased":true},{"key":"karsaiDistributedManagedResearch2014","type":"inproceedings","fields":{"author":["Karsai, Gabor","Balasubramanian, Daniel","Dubey, Abhishek","Otte, William R."],"date":["2014-06"],"doi":["10.1109/ISORC.2014.36"],"isbn":["978-1-4799-4430-9"],"pages":["1–8"],"publisher":["IEEE"],"shorttitle":["Distributed and Managed"],"title":["Distributed and Managed: Research Challenges and Opportunities of the Next Generation Cyber-Physical Systems"]},"creators":{"author":[{"lastName":"Karsai","firstName":"Gabor"},{"lastName":"Balasubramanian","firstName":"Daniel"},{"lastName":"Dubey","firstName":"Abhishek"},{"lastName":"Otte","firstName":"William R."}]}},{"key":"karsaiModelintegratedDevelopmentCyberphysical2008","type":"incollection","fields":{"author":["Karsai, Gabor","Sztipanovits, Janos"],"booktitle":["Software Technologies for Embedded and Ubiquitous Systems"],"date":["2008"],"note":["TL;DR \n\nA model-integrated development approach is introduced that addresses the development needs of cyber-physical systems through the pervasive use of models and a complete model-based view is proposed that covers all aspects of the hardware and software components, as well as their interactions."],"pages":["46–54"],"publisher":["Springer"],"title":["Model-integrated development of cyber-physical systems"],"url":["http://link.springer.com/chapter/10.1007/978-3-540-87785-1_5"],"urldate":["2016-03-10"]},"creators":{"author":[{"lastName":"Karsai","firstName":"Gabor"},{"lastName":"Sztipanovits","firstName":"Janos"}]},"sentenceCased":true},{"key":"Karypis:1999:CHC:619043.621303","type":"article","fields":{"acmid":["621303"],"address":["Los Alamitos, CA, USA"],"author":["Karypis, George","Han, Eui-Hong (Sam)","Kumar, Vipin"],"date":["1999-08"],"issn":["0018-9162"],"issue_date":["August 1999"],"journaltitle":["Computer"],"nodoi":["10.1109/2.781637"],"note":["TL;DR \n\nChameleon's key feature is that it accounts for both interconnectivity and closeness in identifying the most similar pair of clusters, which is important for dealing with highly variable clusters."],"number":["8"],"numpages":["8"],"pages":["68–75"],"publisher":["IEEE Computer Society Press"],"title":["Chameleon: Hierarchical clustering using dynamic modeling"],"url":["http://dx.doi.org/10.1109/2.781637"],"volume":["32"]},"creators":{"author":[{"lastName":"Karypis","firstName":"George"},{"lastName":"Han","firstName":"Eui-Hong (Sam)"},{"lastName":"Kumar","firstName":"Vipin"}]},"sentenceCased":true},{"key":"Karypis:2001:EIT:502585.502627","type":"inproceedings","fields":{"acmid":["502627"],"author":["Karypis, George"],"booktitle":["Procs Tenth Int. Conf Inf. Knowl. Manag."],"date":["2001"],"isbn":["1-58113-436-3"],"keywords":["collaborative filtering","recommender system"],"location":["New York, NY, USA"],"numpages":["8"],"pages":["247–254"],"publisher":["ACM"],"series":["CIKM '01"],"title":["Evaluation of item-based top-n recommendation algorithms"]},"creators":{"author":[{"lastName":"Karypis","firstName":"George"}]},"sentenceCased":true},{"key":"KASHFI201937","type":"article","fields":{"langid":["english"],"abstract":["Current studies on User eXperience (UX) integration often do not investigate or reflect on the transition companies go through from only developing Graphical User Interfaces (GUI) to also considering usability and more recently UX. Understanding this transition provides a more holistic and realistic picture of integration and can be a rich source of knowledge for improving UX integration in the software industry. Applying case study and grounded theory research we show that UX integration, like other organizational changes, can include a mixture of planned and emergent initiatives, and is influenced by various intertwined events; not only those that reside inside an organization but also those external to it. We also show that different decisions that are made outside the authority of UX practitioners have an inevitable impact on enabling or prohibiting UX integration. In addition, we found that for a successful integration, practitioners need to explicitly consider and address the characteristics of UX, otherwise, the integration efforts may have a lopsided focus on the pragmatic aspect of UX, consequently, leave the hedonic aspect unaddressed. Based on our findings, we present four lessons learned and five pitfalls companies should consider to go beyond GUI design and usability to also address UX."],"author":["Kashfi, Pariya","Feldt, Robert","Nilsson, Agneta"],"date":["2019"],"doi":["10.1016/j.jss.2019.03.066"],"issn":["0164-1212"],"journaltitle":["J. Syst. Software"],"keywords":["⛔ No INSPIRE recid found","Case study","Grounded theory","Organizational change","Software quality","Usability","User eXperience (UX)"],"pages":["37–58"],"title":["Integrating UX principles and practices into software development organizations: A case study of influencing events"],"volume":["154"]},"creators":{"author":[{"lastName":"Kashfi","firstName":"Pariya"},{"lastName":"Feldt","firstName":"Robert"},{"lastName":"Nilsson","firstName":"Agneta"}]},"sentenceCased":true},{"key":"Kasrin202176","type":"article","fields":{"abstract":["The recent evolution of the Internet of Things into a cyber-physical reality has spawned various challenges from a data management perspective. In addition, IoT platform designers are faced with another set of questions. How can platforms be extended to smoothly integrate new data management functionalities? Currently, data processing related tasks are typically realized by manually developed code and functions which creates difficulties in maintenance and growth. Hence we need to explore other approaches to integration for IoT platforms. In this paper we cover both these aspects: (1) we explore several emerging data management challenges, and (2) we propose an IoT platform integration model that can combine disparate functionalities under one roof. For the first, we focus on the following challenges: sensor data quality, privacy in data streams, machine learning model management, and resource-aware data management. For the second, we propose an information-integration model for IoT platforms. The model revolves around the concept of a Data-Sharing Market where data management functionalities can share and exchange information about their data with other functionalities. In addition, data-sharing markets themselves can be combined into networks of markets where information flows from one market to another, which creates a web of information exchange about data resources. To motivate this work we present a use-case application in smart cities. © 2021, The Author(s)."],"author":["Kasrin, N.","Benabbas, A.","Elmamooz, G.","Nicklas, D.","Steuer, S.","Sünkel, M."],"date":["2021"],"document_type":["Article"],"doi":["10.1007/s42486-020-00054-y"],"issn":["2524521X"],"journaltitle":["CCF Trans. Pervasive Comput. Interact."],"note":["cited By 2"],"number":["1"],"pages":["76–93"],"publisher":["Springer"],"source":["Scopus"],"title":["Data-sharing markets for integrating IoT data processing functionalities"],"volume":["3"]},"creators":{"author":[{"lastName":"Kasrin","firstName":"N."},{"lastName":"Benabbas","firstName":"A."},{"lastName":"Elmamooz","firstName":"G."},{"lastName":"Nicklas","firstName":"D."},{"lastName":"Steuer","firstName":"S."},{"lastName":"Sünkel","firstName":"M."}]},"sentenceCased":true},{"key":"katirtzisSummarizingSoftwareAPI","type":"article","fields":{"langid":["english"],"abstract":["As developers often use third-party libraries to facilitate software development, the lack of proper API documentation for these libraries undermines their reuse potential. And although several approaches extract usage examples for libraries, they are usually tied to specific language implementations, while their produced examples are often redundant and are not presented as concise and readable snippets. In this work, we propose a novel approach that extracts API call sequences from client source code and clusters them to produce a diverse set of source code snippets that effectively covers the target API. We further construct a summarization algorithm to present concise and readable snippets to the users. Upon evaluating our system on software libraries, we indicate that it achieves high coverage in API methods, while the produced snippets are of high quality and closely match handwritten examples."],"author":["Katirtzis, Nikolaos","Diamantopoulos, Themistoklis","Sutton, Charles"],"pages":["17"],"title":["Summarizing Software API Usage Examples using Clustering Techniques"]},"creators":{"author":[{"lastName":"Katirtzis","firstName":"Nikolaos"},{"lastName":"Diamantopoulos","firstName":"Themistoklis"},{"lastName":"Sutton","firstName":"Charles"}]},"sentenceCased":true},{"key":"katsamakasWhyMostOpen2007","type":"inproceedings","fields":{"author":["Katsamakas, Evangelos","Georgantzas, Nicholas"],"booktitle":["Emerg. Trends FLOSS Res. Dev. 2007 FLOSS07 First Int. Workshop On"],"date":["2007"],"pages":["3–3"],"publisher":["IEEE"],"title":["Why most open source development projects do not succeed?"],"url":["http://ieeexplore.ieee.org/abstract/document/4273074/"],"urldate":["2017-06-23"]},"creators":{"author":[{"lastName":"Katsamakas","firstName":"Evangelos"},{"lastName":"Georgantzas","firstName":"Nicholas"}]},"sentenceCased":true},{"key":"katzReluplexEfficientSMT2017","type":"incollection","fields":{"langid":["english"],"author":["Katz, Guy","Barrett, Clark","Dill, David L.","Julian, Kyle","Kochenderfer, Mykel J."],"booktitle":["Computer Aided Verification"],"date":["2017"],"doi":["10.1007/978-3-319-63387-9_5"],"editor":["Majumdar, Rupak","Kunčak, Viktor"],"isbn":["978-3-319-63386-2 978-3-319-63387-9"],"location":["Cham"],"note":["TL;DR \n\nResults show that the novel, scalable, and efficient technique presented can successfully prove properties of networks that are an order of magnitude larger than the largest networks verified using existing methods."],"pages":["97–117"],"publisher":["Springer International Publishing"],"shorttitle":["Reluplex"],"title":["Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks"],"volume":["10426"]},"creators":{"author":[{"lastName":"Katz","firstName":"Guy"},{"lastName":"Barrett","firstName":"Clark"},{"lastName":"Dill","firstName":"David L."},{"lastName":"Julian","firstName":"Kyle"},{"lastName":"Kochenderfer","firstName":"Mykel J."}],"editor":[{"lastName":"Majumdar","firstName":"Rupak"},{"lastName":"Kunčak","firstName":"Viktor"}]}},{"key":"kaufman:clustering1990","type":"book","fields":{"added-at":["2017-11-14T13:30:05.000+0100"],"author":["Kaufman, L.","Rousseeuw, P.J."],"biburl":["https://www.bibsonomy.org/bibtex/254cc9fb0fc88d6057dc9b1ce3feb1293/tomhanika"],"date":["1990"],"description":["Dissertation"],"foo":["bar"],"ids":["opac-b1087461"],"interhash":["119bf8c432712ad3bbc1612759e0b7b4"],"intrahash":["54cc9fb0fc88d6057dc9b1ce3feb1293"],"keywords":["clustering kdd17"],"note":["TL;DR \n\nAn electrical signal transmission system, applicable to the transmission of signals from trackside hot box detector equipment for railroad locomotives and rolling stock, wherein a basic pulse train is transmitted whereof the pulses are of a selected first amplitude and represent a train axle count."],"publisher":["Wiley"],"timestamp":["2017-11-24T16:26:04.000+0100"],"title":["Finding Groups in Data: An introduction to cluster analysis"]},"creators":{"author":[{"lastName":"Kaufman","firstName":"L."},{"lastName":"Rousseeuw","firstName":"P.J."}]},"sentenceCased":true},{"key":"kaufman2009finding","type":"book","fields":{"author":["Kaufman, Leonard","Rousseeuw, Peter J"],"date":["2009"],"publisher":["John Wiley & Sons"],"title":["Finding groups in data: An introduction to cluster analysis"],"volume":["344"]},"creators":{"author":[{"lastName":"Kaufman","firstName":"Leonard"},{"lastName":"Rousseeuw","firstName":"Peter J"}]},"sentenceCased":true},{"key":"KaufmanL1987Cbmo","type":"incollection","fields":{"langid":["english"],"author":["Kaufman, L","Rousseeuw, Peter"],"booktitle":["Statistical data analysis based on the L1 norm and related methods"],"date":["1987"],"isbn":["0-444-70273-3"],"organization":["Dodge, Y"],"pages":["405–416"],"publisher":["North-Holland; Amsterdam"],"title":["Clustering by means of medoids"],"url":["$$Uhttps://lirias.kuleuven.be/retrieve/377090$$DKaufmanRousseeuw_ClusteringByMedoids_L1Norm_1987.pdf [Available for KU Leuven users]"]},"creators":{"author":[{"lastName":"Kaufman","firstName":"L"},{"lastName":"Rousseeuw","firstName":"Peter"}]},"sentenceCased":true},{"key":"Kaur2021671","type":"inproceedings","fields":{"abstract":["Skin cancer is a prevalent kind of cancer, and early diagnosis significantly improves the chance of survival. The purpose of this article is to develop a deep learning feature engineering model with an optimised xg-boost classifier for the purpose of classifying dermal cell pictures and detecting skin cancer. Utilization of Methodology Classification method based on features mapped on nonlinear space using Resnet 50 basis feature engineering, followed by learning via Xg-boost structure optimization. Structure optimization is accomplished by grey wolf optimization. Within the Results The deep learning with xgboost model developed here was evaluated on standard datasets and combined datasets, and the metric accuracy and precision were found to be 98.34 percent and 97.35 percent, respectively. Conclude that a practitioner may use model-driven architecture to rapidly develop deep learning models for skin cancer prediction. © 2021 IEEE."],"author":["Kaur, R.","Kaur, N."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/ComPE53109.2021.9751930"],"editor":["Paul S., Verma J.K."],"isbn":["978-1-66543-656-4"],"note":["cited By 0 \n\nTL;DR \n\nA deep learning feature engineering model with an optimised xg-boost classifier for the purpose of classifying dermal cell pictures and detecting skin cancer and it is concluded that a practitioner may use model-driven architecture to rapidly develop deep learning models for skin cancer prediction."],"pages":["671–675"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["2021 International Conference on Computational Performance Evaluation, ComPE 2021"],"source":["Scopus"],"title":["Improved skin cancer detection classification residual network feature engineering"]},"creators":{"author":[{"lastName":"Kaur","firstName":"R."},{"lastName":"Kaur","firstName":"N."}],"editor":[{"lastName":"Paul S.","firstName":"Verma J.K."}]},"sentenceCased":true},{"key":"kazmanManagingEnergyConsumption2018","type":"article","fields":{"abstract":["A look at the software for an automated weather station shows that energy can be treated like any other architectural quality attribute. It’s no different, from the perspective of architectural design, than modifiability, performance, or availability. It can be modeled and prototyped, and we can reason about the design tradeoffs required to achieve better energy use."],"author":["Kazman, R.","Haziyev, S.","Yakuba, A.","Tamburri, D. A."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571227"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["internet of things"],"number":["5"],"pages":["102–107"],"title":["Managing Energy Consumption as an Architectural Quality Attribute"],"volume":["35"]},"creators":{"author":[{"lastName":"Kazman","firstName":"R."},{"lastName":"Haziyev","firstName":"S."},{"lastName":"Yakuba","firstName":"A."},{"lastName":"Tamburri","firstName":"D. A."}]}},{"key":"Kazmi2017449","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - IEEE/WIC/ACM Int. Conf. Web Intell., WI"],"affiliation":["TCS Research, India"],"art_number":["7817089"],"author":["Kazmi, A.H.","Shroff, G.","Agarwal, P."],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.1109/WI.2016.0072"],"isbn":["978-1-5090-4470-2"],"note":["cited By 8"],"pages":["449–452"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2016 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2016"],"source":["Scopus"],"title":["Generic framework to predict repeat behavior of customers using their transaction history"]},"creators":{"author":[{"lastName":"Kazmi","firstName":"A.H."},{"lastName":"Shroff","firstName":"G."},{"lastName":"Agarwal","firstName":"P."}]},"sentenceCased":true},{"key":"KDMWelcome","type":"online","fields":{"title":["KDM - Welcome"],"url":["http://kdm.dataview.org/"],"urldate":["2018-04-30"]},"creators":{}},{"key":"KeepAllYour","type":"online","fields":{"title":["Keep all your packages up to date with Dependabot - The GitHub Blog"],"url":["https://github.blog/2020-06-01-keep-all-your-packages-up-to-date-with-dependabot/"],"urldate":["2021-01-11"]},"creators":{},"sentenceCased":true},{"key":"kehrerUnderstandComplexChanges","type":"article","fields":{"langid":["english"],"author":["Kehrer, Timo"],"pages":["79"],"title":["Understand complex changes and improve the quality of your UML and domain-specific models"]},"creators":{"author":[{"lastName":"Kehrer","firstName":"Timo"}]},"sentenceCased":true},{"key":"kephartVisionAutonomicComputing2003","type":"article","fields":{"author":["Kephart, Jeffrey O.","Chess, David M."],"date":["2003"],"journaltitle":["Computer"],"note":["TL;DR \n\nA 2001 IBM manifesto noted the almost impossible difficulty of managing current and planned computing systems, which require integrating several heterogeneous environments into corporate-wide computing systems that extend into the Internet."],"number":["1"],"pages":["41–50"],"title":["The vision of autonomic computing"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1160055"],"urldate":["2016-08-26"],"volume":["36"]},"creators":{"author":[{"lastName":"Kephart","firstName":"Jeffrey O."},{"lastName":"Chess","firstName":"David M."}]},"sentenceCased":true},{"key":"kerstenFivePredictionsComing2018","type":"article","fields":{"abstract":["To help celebrate software engineering’s 50th anniversary, department editor Mik Kersten considers how software engineering will evolve over the coming 50 years. His five predictions aren’t intended to be precise; they aim to provide discussion topics for the shape of software engineering trends to come. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Kersten, M."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571232"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["artificial intelligence","software engineering"],"note":["TL;DR \n\nTo help celebrate software engineering’s 50th anniversary, department editor Mik Kersten considers how software engineering will evolve over the coming 50 years and makes five predictions."],"number":["5"],"pages":["7–9"],"title":["Five Predictions for the Coming Decades of Software"],"volume":["35"]},"creators":{"author":[{"lastName":"Kersten","firstName":"M."}]}},{"key":"kessentini2008model","type":"inproceedings","fields":{"langid":["english"],"author":["Kessentini, Marouane","Sahraoui, Houari","Boukadoum, Mounir"],"booktitle":["Int. Conf. Model Driven Eng. Lang. Syst."],"date":["2008"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis approach, named model transformation as optimization by examples (MOTOE), combines transformation blocks extracted from examples to generate a target model and can operate independently from the source and target metamodels."],"pages":["159–173"],"publisher":["Springer"],"title":["Model transformation as an optimization problem"]},"creators":{"author":[{"lastName":"Kessentini","firstName":"Marouane"},{"lastName":"Sahraoui","firstName":"Houari"},{"lastName":"Boukadoum","firstName":"Mounir"}]},"sentenceCased":true},{"key":"KESSENTINI201949","type":"article","fields":{"author":["Kessentini, Wael","Sahraoui, Houari","Wimmer, Manuel"],"date":["2019"],"doi":["10.1016/j.infsof.2018.09.003"],"issn":["0950-5849"],"journaltitle":["Inf. Softw. Technol."],"keywords":["Coupled evolution","Metamodel/model co-evolution","Model migration","Search based software engineering"],"pages":["49–67"],"title":["Automated Metamodel/Model co-evolution: A search-based approach"],"volume":["106"]},"creators":{"author":[{"lastName":"Kessentini","firstName":"Wael"},{"lastName":"Sahraoui","firstName":"Houari"},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"kessentini2022semi","type":"article","fields":{"langid":["english"],"author":["Kessentini, Wael","Alizadeh, Vahid"],"date":["2022"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper proposes an interactive approach that enables designers to select their preference simultaneously in the objective and decision spaces and compared it to existing fully automated and interactive co-evolution techniques."],"number":["5"],"pages":["1853–1876"],"title":["Semi-automated Metamodel/Model co-evolution: A multi-level interactive approach"],"volume":["21"]},"creators":{"author":[{"lastName":"Kessentini","firstName":"Wael"},{"lastName":"Alizadeh","firstName":"Vahid"}]},"sentenceCased":true},{"key":"kessentiniAutomatedCoevolutionMetamodels2018","type":"incollection","fields":{"langid":["english"],"author":["Kessentini, Wael","Sahraoui, Houari","Wimmer, Manuel"],"booktitle":["Search-Based Software Engineering"],"date":["2018"],"doi":["10.1007/978-3-319-99241-9_12"],"editor":["Colanzi, Thelma Elita","McMinn, Phil"],"ids":["kessentini2018automated"],"isbn":["978-3-319-99240-2 978-3-319-99241-9"],"keywords":["/unread","⛔ No INSPIRE recid found"],"location":["Cham"],"note":["TL;DR \n\nThis paper proposes a novel search-based approach to recommend transformation rule changes to make transformations coherent with the new metamodel versions by finding a trade-off between maximizing the coverage of metAModel changes and minimizing the number of static errors in the transformation and thenumber of applied changes to the transformation."],"pages":["229–245"],"publisher":["Springer International Publishing"],"shorttitle":["Automated Co-evolution of Metamodels and Transformation Rules"],"title":["Automated Co-evolution of Metamodels and Transformation Rules: A Search-Based Approach"],"volume":["11036"]},"creators":{"author":[{"lastName":"Kessentini","firstName":"Wael"},{"lastName":"Sahraoui","firstName":"Houari"},{"lastName":"Wimmer","firstName":"Manuel"}],"editor":[{"lastName":"Colanzi","firstName":"Thelma Elita"},{"lastName":"McMinn","firstName":"Phil"}]}},{"key":"kessentiniIntegratingDesignerIntheloop2018","type":"inproceedings","fields":{"langid":["english"],"abstract":["Metamodels evolve even more frequently than programming languages. This evolution process may result in a large number of instance models that are no longer conforming to the revised meta-model. On the one hand, the manual adaptation of models after the metamodels' evolution can be tedious, error-prone, and time-consuming. On the other hand, the automated co-evolution of metamodels/models is challenging especially when new semantics is introduced to the metamodels. In this paper, we propose an interactive multi-objective approach that dynamically adapts and interactively suggests edit operations to developers and takes their feedback into consideration. Our approach uses NSGA-II to find a set of good edit operation sequences that minimizes the number of conformance errors, maximizes the similarity with the initial model (reduce the loss of information) and minimizes the number of proposed edit operations. The designer can approve, modify, or reject each of the recommended edit operations, and this feedback is then used to update the proposed rankings of recommended edit operations. We evaluated our approach on a set of metamodel/model coevolution case studies and compared it to fully automated coevolution techniques."],"author":["Kessentini, Wael","Wimmer, Manuel","Sahraoui, Houari"],"booktitle":["Proc. 21th ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst."],"date":["2018-10-14"],"doi":["10.1145/3239372.3239375"],"eventtitle":["MODELS '18: ACM/IEEE 21th International Conference on Model Driven Engineering Languages and Systems"],"ids":["10.1145/3239372.3239375"],"isbn":["978-1-4503-4949-9"],"keywords":["/unread","⛔ No INSPIRE recid found","Coupled Evolution","Interactive Optimization","Metamodel/Model Co-Evolution","Search Based Software Engineering"],"location":["Copenhagen Denmark"],"note":["TL;DR \n\nThis paper proposes an interactive multi-objective approach that dynamically adapts and interactively suggests edit operations to developers and takes their feedback into consideration, and compared it to fully automated coevolution techniques."],"pages":["101–111"],"pagetotal":["11"],"publisher":["ACM"],"series":["MODELS '18"],"title":["Integrating the Designer in-the-loop for Metamodel/Model Co-Evolution via Interactive Computational Search"]},"creators":{"author":[{"lastName":"Kessentini","firstName":"Wael"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Sahraoui","firstName":"Houari"}]},"sentenceCased":true},{"key":"KessentiniMWOD17","type":"article","fields":{"langid":["english"],"author":["Kessentini, Marouane","Mansoor, Usman","Wimmer, Manuel","Ouni, Ali","Deb, Kalyanmoy"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2017"],"doi":["10.1007/S10664-016-9442-8"],"journaltitle":["Empirical Software Eng."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["2"],"pages":["670–715"],"timestamp":["Tue, 25 Aug 2020 16:58:56 +0200"],"title":["Search-based detection of model level changes"],"volume":["22"]},"creators":{"author":[{"lastName":"Kessentini","firstName":"Marouane"},{"lastName":"Mansoor","firstName":"Usman"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Ouni","firstName":"Ali"},{"lastName":"Deb","firstName":"Kalyanmoy"}]},"sentenceCased":true},{"key":"kessentiniSearchbasedMetamodelMatching2014","type":"article","fields":{"langid":["english"],"abstract":["The use of different domain-specific modeling languages and diverse versions of the same modeling language often entails the need to translate models between the different languages and language versions. The first step in establishing a transformation between two languages is to find their corresponding concepts, i.e., finding correspondences between their metamodel elements. Although, metamodels use heterogeneous terminologies and structures, they often still describe similar language concepts. In this paper, we propose to combine structural metrics (e.g., number of properties per concept) and syntactic metrics to generate correspondences between metamodels. Because metamodel matching requires to cope with a huge search space of possible element combinations, we adapted a local and a global metaheuristic search algorithm to find the best set of correspondences between metamodels. The efficiency and effectiveness of our proposal is evaluated on different matching scenarios based on existing benchmarks. In addition, we compared our technique to state-of-the-art ontology matching and model matching approaches."],"author":["Kessentini, Marouane","Ouni, Ali","Langer, Philip","Wimmer, Manuel","Bechikh, Slim"],"date":["2014-11"],"doi":["10.1016/j.jss.2014.06.040"],"issn":["01641212"],"journaltitle":["J. Syst. Softw."],"note":["TL;DR \n\nThis paper adapted a local and a global metaheuristic search algorithm to find the best set of correspondences between metamodels and compared the technique to state-of-the-art ontology matching and model matching approaches."],"pages":["1–14"],"title":["Search-based metamodel matching with structural and syntactic measures"],"volume":["97"]},"creators":{"author":[{"lastName":"Kessentini","firstName":"Marouane"},{"lastName":"Ouni","firstName":"Ali"},{"lastName":"Langer","firstName":"Philip"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Bechikh","firstName":"Slim"}]},"sentenceCased":true},{"key":"khakpourFormalModelingEvolving2012","type":"article","fields":{"langid":["english"],"author":["Khakpour, Narges","Jalili, Saeed","Talcott, Carolyn","Sirjani, Marjan","Mousavi, MohammadReza"],"date":["2012-11"],"doi":["10.1016/j.scico.2011.09.004"],"issn":["01676423"],"journaltitle":["Sci. Comput. Program."],"number":["1"],"pages":["3–26"],"title":["Formal modeling of evolving self-adaptive systems"],"volume":["78"]},"creators":{"author":[{"lastName":"Khakpour","firstName":"Narges"},{"lastName":"Jalili","firstName":"Saeed"},{"lastName":"Talcott","firstName":"Carolyn"},{"lastName":"Sirjani","firstName":"Marjan"},{"lastName":"Mousavi","firstName":"MohammadReza"}]},"sentenceCased":true},{"key":"khalilSupportingEvolutionUML2013","type":"report","fields":{"author":["Khalil, Amal","Dingel, Juergen"],"date":["2013"],"institution":["Technical Report, School of Computing. Queens University, Canada"],"shorttitle":["Supporting the evolution of UML models in model driven software developmeny"],"title":["Supporting the evolution of UML models in model driven software developmeny: A Survey"],"url":["http://research.cs.queensu.ca/TechReports/Reports/2013-602.pdf"],"urldate":["2015-04-02"]},"creators":{"author":[{"lastName":"Khalil","firstName":"Amal"},{"lastName":"Dingel","firstName":"Juergen"}]},"sentenceCased":true},{"key":"Khan:2016:STS:3004996.3005218","type":"article","fields":{"acmid":["3005218"],"address":["Amsterdam, The Netherlands, The Netherlands"],"author":["Khan, Saif Ur Rehman","Lee, Sai Peck","Ahmad, Raja Wasim","Akhunzada, Adnan","Chang, Victor"],"date":["2016-12"],"issn":["0268-4012"],"issue_date":["December 2016"],"journaltitle":["Int. J. Inf. Manag."],"keywords":["Fault localization","Frameworks","Regression testing","Test suite optimization","Test Suite Reduction"],"nodoi":["10.1016/j.ijinfomgt.2016.05.025"],"number":["6"],"numpages":["13"],"pages":["963–975"],"publisher":["Elsevier Science Publishers B. V."],"title":["A survey on test suite reduction frameworks and tools"],"url":["https://doi.org/10.1016/j.ijinfomgt.2016.05.025"],"volume":["36"]},"creators":{"author":[{"lastName":"Khan","firstName":"Saif Ur Rehman"},{"lastName":"Lee","firstName":"Sai Peck"},{"lastName":"Ahmad","firstName":"Raja Wasim"},{"lastName":"Akhunzada","firstName":"Adnan"},{"lastName":"Chang","firstName":"Victor"}]},"sentenceCased":true},{"key":"Khan2021130","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Annu Rev Control"],"affiliation":["University of Tokyo, Department of Aeronautics and Astronautics, Tokyo, 113-8654, Japan; Japan Aerospace Exploration Agency, Research and Development Directorate, Kanagawa, 252-5210, Japan"],"author":["Khan, S.","Tsutsumi, S.","Yairi, T.","Nakasuka, S."],"coden":["ARCOF"],"correspondence_address1":["Khan, S.; University of Tokyo, Department of Aeronautics and Astronautics, Japan; email: khan@ailab.t.u-tokyo.ac.jp"],"date":["2021"],"document_type":["Article"],"doi":["10.1016/j.arcontrol.2021.04.001"],"issn":["13675788"],"journaltitle":["Annu. Rev. Control"],"note":["cited By 1"],"pages":["130–152"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Robustness of AI-based prognostic and systems health management"],"volume":["51"]},"creators":{"author":[{"lastName":"Khan","firstName":"S."},{"lastName":"Tsutsumi","firstName":"S."},{"lastName":"Yairi","firstName":"T."},{"lastName":"Nakasuka","firstName":"S."}]},"sentenceCased":true},{"key":"khanFederatedLearningInternet2020","type":"article","fields":{"langid":["english"],"abstract":["The Internet of Things (IoT) will be ripe for the deployment of novel machine learning algorithms for both network and application management. However, given the presence of massively distributed and private datasets, it is challenging to use classical centralized learning algorithms in the IoT. To overcome this challenge, federated learning can be a promising solution that enables on-device machine learning without the need to migrate the private end-user data to a central cloud. In federated learning, only learning model updates are transferred between end-devices and the aggregation server. Although federated learning can offer better privacy preservation than centralized machine learning, it has still privacy concerns. In this paper, first, we present the recent advances of federated learning towards enabling federated learning-powered IoT applications. A set of metrics such as sparsification, robustness, quantization, scalability, security, and privacy, is delineated in order to rigorously evaluate the recent advances. Second, we devise a taxonomy for federated learning over IoT networks. Third, we propose two IoT use cases of dispersed federated learning that can offer better privacy preservation than federated learning. Finally, we present several open research challenges with their possible solutions."],"author":["Khan, Latif U.","Saad, Walid","Han, Zhu","Hossain, Ekram","Hong, Choong Seon"],"date":["2020-09-27"],"eprint":["2009.13012"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv200913012 Cs"],"keywords":["federated learning","internet of things"],"note":["Comment: This paper has been submitted to IEEE Communications Surveys and Tutorials"],"shorttitle":["Federated Learning for Internet of Things"],"title":["Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges"],"url":["http://arxiv.org/abs/2009.13012"],"urldate":["2020-12-22"]},"creators":{"author":[{"lastName":"Khan","firstName":"Latif U."},{"lastName":"Saad","firstName":"Walid"},{"lastName":"Han","firstName":"Zhu"},{"lastName":"Hossain","firstName":"Ekram"},{"lastName":"Hong","firstName":"Choong Seon"}]}},{"key":"kharlamovSemanticApproachPolystores2016","type":"inproceedings","fields":{"langid":["english"],"author":["Kharlamov, E.","Mailis, T.","Bereta, K.","Bilidas, D.","Brandt, S.","Jimenez-Ruiz, E.","Lamparter, S.","Neuenstadt, C.","Ozcep, O.","Soylu, A.","Svingos, C.","Xiao, G.","Zheleznyakov, D.","Calvanese, D.","Horrocks, I.","Giese, M.","Ioannidis, Y.","Kotidis, Y.","Moller, R.","Waaler, A."],"date":["2016-12"],"doi":["10.1109/BigData.2016.7840898"],"isbn":["978-1-4673-9005-7"],"pages":["2565–2573"],"publisher":["IEEE"],"title":["A semantic approach to polystores"]},"creators":{"author":[{"lastName":"Kharlamov","firstName":"E."},{"lastName":"Mailis","firstName":"T."},{"lastName":"Bereta","firstName":"K."},{"lastName":"Bilidas","firstName":"D."},{"lastName":"Brandt","firstName":"S."},{"lastName":"Jimenez-Ruiz","firstName":"E."},{"lastName":"Lamparter","firstName":"S."},{"lastName":"Neuenstadt","firstName":"C."},{"lastName":"Ozcep","firstName":"O."},{"lastName":"Soylu","firstName":"A."},{"lastName":"Svingos","firstName":"C."},{"lastName":"Xiao","firstName":"G."},{"lastName":"Zheleznyakov","firstName":"D."},{"lastName":"Calvanese","firstName":"D."},{"lastName":"Horrocks","firstName":"I."},{"lastName":"Giese","firstName":"M."},{"lastName":"Ioannidis","firstName":"Y."},{"lastName":"Kotidis","firstName":"Y."},{"lastName":"Moller","firstName":"R."},{"lastName":"Waaler","firstName":"A."}]},"sentenceCased":true},{"key":"Khaytbaev2020115","type":"article","fields":{"langid":["english"],"abbrev_source_title":["J. ICT Res. Appl."],"affiliation":["Department of Telecommunication Engineering, Tashkent University of Information Technologies named after Muhammad Al-Khwarizmi, A. Temur St., 108, Tashkent, 100084, Uzbekistan"],"author":["Khaytbaev, A.F."],"correspondence_address1":["Khaytbaev, A.F.; Department of Telecommunication Engineering, A. Temur St., 108, Uzbekistan; email: a.xaytbayev1981@inbox.ru"],"date":["2020"],"document_type":["Article"],"doi":["10.5614/itbj.ict.res.appl.2020.14.2.2"],"issn":["23375787"],"journaltitle":["J. ICT Res. Appl."],"note":["cited By 0"],"number":["2"],"pages":["115–133"],"publisher":["Institute for Research and Community Services, Institut Teknologi Bandung"],"source":["Scopus"],"title":["Decision routing problems in a wireless sensor network based on a neural mechanism"],"volume":["14"]},"creators":{"author":[{"lastName":"Khaytbaev","firstName":"A.F."}]},"sentenceCased":true},{"key":"khelladiDetectingComplexChanges2016","type":"article","fields":{"langid":["english"],"author":["Khelladi, Djamel Eddine","Hebig, Regina","Bendraou, Reda","Robin, Jacques","Gervais, Marie-Pierre"],"date":["2016-12"],"doi":["10.1016/j.is.2016.05.002"],"ids":["KHELLADI2016220"],"issn":["03064379"],"journaltitle":["Information Systems"],"pages":["220–241"],"title":["Detecting complex changes and refactorings during (Meta)model evolution"],"volume":["62"]},"creators":{"author":[{"lastName":"Khelladi","firstName":"Djamel Eddine"},{"lastName":"Hebig","firstName":"Regina"},{"lastName":"Bendraou","firstName":"Reda"},{"lastName":"Robin","firstName":"Jacques"},{"lastName":"Gervais","firstName":"Marie-Pierre"}]},"sentenceCased":true},{"key":"khomhSoftwareEngineeringMachineLearning2018","type":"article","fields":{"abstract":["The First Symposium on Software Engineering for Machine Learning Applications (SEMLA) aimed to create a space in which machine learning (ML) and software engineering (SE) experts could come together to discuss challenges, new insights, and practical ideas regarding the engineering of ML and AI-based systems. Key challenges discussed included the accuracy of systems built using ML and AI models, the testing of those systems, industrial applications of AI, and the rift between the ML and SE communities. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Khomh, F.","Adams, B.","Cheng, J.","Fokaefs, M.","Antoniol, G."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571224"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["artificial intelligence","DONE","machine learning","software engineering"],"note":["<b>Gray Annotations (18/12/2020, 00:14:17)</b> \n\n\"difficulty of testing ML and AI systems.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=2\">Khomh et al 2018:82</a>) \n\n<b>Green Annotations (18/12/2020, 00:14:17)</b> \n\n\"we still experience failures and shortcomings in the resulting soft­ ware systems. The main reason is the shift in the development paradigm in­ duced by ML and AI.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=1\">Khomh et al 2018:81</a>) \n\n\"with ML techniques, these rules are inferred from training data (from which the requirements are gener­ ated inductively).\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=1\">Khomh et al 2018:81</a>) \n\n\"This paradigm shift makes reasoning about the be­ havior of software systems with ML components difficult, resulting in software systems that are intrinsi­ cally challenging to test and verify.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=1\">Khomh et al 2018:81</a>) \n\n\"the learned behavior of an ML­based system might be incorrect, even if the learning algorithm is imple­ mented correctly, a situation in which traditional testing techniques are ineffective.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=1\">Khomh et al 2018:81</a>) \n\n\"critical problem is how to effectively develop, test, and evolve such systems, given that they don't have (complete) specifications or even source code corresponding to some of their critical behaviors.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=1\">Khomh et al 2018:81</a>) \n\n<i>TESTING (ML) SYSTEMS THAT LACK SPECIFICATIONS OR EVEN SOURCE CODE (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=1\">note on p.81</a>)</i> \n\n\"AI technology's strength comes from the ability to abstract up from different factors of varia­ tion between environments, to obtain models that can general­ ize and transfer to situations that weren't encountered before\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=2\">Khomh et al 2018:82</a>) \n\n\"AI tech­ nologies' main challenge is\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=2\">Khomh et al 2018:82</a>) \n\n\"he need for sufficient, labeled data to cover all important factors (features) of a given problem.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=2\">Khomh et al 2018:82</a>) \n\n\"AI, in fact, needs more training data than humans do!\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=2\">Khomh et al 2018:82</a>) \n\n\"appli­ cations of AI still risk being limited to domains in which labeled data is cheap.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=2\">Khomh et al 2018:82</a>) \n\n\"instead of touting a \"100 percent self­driving car,\" auto­ motive companies should advertise their products as \"AI­assisted cars,\" with a clear list of the ways in which AI is assisting.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=2\">Khomh et al 2018:82</a>) \n\n\"If a traditional computer science algorithm can solve a problem, we should just use that.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=2\">Khomh et al 2018:82</a>) \n\n\"how can we perform adequate quality assurance (QA) of AI models, given that the number of environments in which the mod­ els will be deployed is unlimited and that the human operator will re­ quire a detailed explanation of any failures?\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=2\">Khomh et al 2018:82</a>) \n\n\"use AI tech­ nology to reduce the search space of the environments to be tested\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=2\">Khomh et al 2018:82</a>) \n\n\"AI impacts the hu­ mans' recommendations, those rec­ ommendations are also a human filter for AI failures.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=3\">Khomh et al 2018:83</a>) \n\n\"Creating an efficient syntax for automatic differentiation that can deliver ease of implementation, per­ formance, usability, and flexibility is important but difficult.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=3\">Khomh et al 2018:83</a>) \n\n<i>CHALLENGES (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=3\">note on p.83</a>)</i> \n\n\"esting and debugging these implementations are also salient challenges.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=3\">Khomh et al 2018:83</a>) \n\n\"How should software develop­ ment teams integrate the AI model lifecycle (training, testing, deploying, evolving, and so on) into their software process?\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=4\">Khomh et al 2018:84</a>) \n\n\"What new roles, artifacts, and activities come into play, and how do they tie into existing agile or DevOps processes?\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=4\">Khomh et al 2018:84</a>) \n\n\"testing\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=4\">Khomh et al 2018:84</a>) \n\n\"intersections\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=4\">Khomh et al 2018:84</a>) \n\n\"critical challenges of as­ suring the quality of AI and software systems in general.\" (<a href=\"zotero://open-pdf/library/items/5486JT7B?page=4\">Khomh et al 2018:84</a>)"],"number":["5"],"pages":["81–84"],"shorttitle":["Software Engineering for Machine-Learning Applications"],"title":["Software Engineering for Machine-Learning Applications: The Road Ahead"],"volume":["35"]},"creators":{"author":[{"lastName":"Khomh","firstName":"F."},{"lastName":"Adams","firstName":"B."},{"lastName":"Cheng","firstName":"J."},{"lastName":"Fokaefs","firstName":"M."},{"lastName":"Antoniol","firstName":"G."}]}},{"key":"Khrouf:2013:HER:2507157.2507171","type":"inproceedings","fields":{"acmid":["2507171"],"author":["Khrouf, Houda","Troncy, Raphaël"],"booktitle":["Proc. 7th ACM Conf. Recomm. Syst."],"date":["2013"],"isbn":["978-1-4503-2409-0"],"keywords":["event recommendation","linked data","lode ontology","user diversity"],"location":["New York, NY, USA"],"nodoi":["10.1145/2507157.2507171"],"note":["TL;DR \n\nThis paper uses a content-based system enriched with Linked Data to overcome the data sparsity, a problem induced by the transiency of events, and incorporates a collaborative filtering to involve the social aspect, an influential feature in decision making."],"numpages":["8"],"pages":["185–192"],"publisher":["ACM"],"series":["RecSys '13"],"title":["Hybrid event recommendation using linked data and user diversity"],"url":["http://doi.acm.org/10.1145/2507157.2507171"]},"creators":{"author":[{"lastName":"Khrouf","firstName":"Houda"},{"lastName":"Troncy","firstName":"Raphaël"}]},"sentenceCased":true},{"key":"khusroRecommenderSystemsIssues2016","type":"incollection","fields":{"abstract":["A recommender system is an Information Retrieval technology that improves access and proactively recommends relevant items to users by considering the users' explicitly mentioned preferences and objective behaviors. A recommender system is one of the major techniques that handle information overload problem of Information Retrieval by suggesting users with appropriate and relevant items. Today, several recommender systems have been developed for different domains however, these are not precise enough to fulfil the information needs of users. Therefore, it is necessary to build high quality recommender systems. In designing such recommenders, designers face several issues and challenges that need proper attention. This paper investigates and reports the current trends, issues, challenges, and research opportunities in developing high-quality recommender systems. If properly followed, these issues and challenges will introduce new research avenues and the goal towards fine-tuned and high-quality recommender systems can be achieved."],"author":["Khusro, Shah","Ali, Zafar","Ullah, Irfan"],"booktitle":["Information science and applications (ICISA) 2016"],"date":["2016"],"doi":["10.1007/978-981-10-0557-2₁12"],"editor":["Kim, Kuinam J.","Joukov, Nikolai"],"isbn":["978-981-10-0557-2"],"location":["Singapore"],"note":["TL;DR \n\nThe current trends, issues, challenges, and research opportunities in developing high-quality recommender systems are investigated and the goal towards fine-tuned and high- quality recommender system can be achieved is achieved."],"pages":["1179–1189"],"publisher":["Springer Singapore"],"title":["Recommender systems: Issues, challenges, and research opportunities"]},"creators":{"author":[{"lastName":"Khusro","firstName":"Shah"},{"lastName":"Ali","firstName":"Zafar"},{"lastName":"Ullah","firstName":"Irfan"}],"editor":[{"lastName":"Kim","firstName":"Kuinam J."},{"lastName":"Joukov","firstName":"Nikolai"}]},"sentenceCased":true},{"key":"kienzleModeldrivenSustainabilityEvaluation2020","type":"article","fields":{"langid":["english"],"author":["Kienzle, Jörg","Mussbacher, Gunter","Combemale, Benoit","Bastin, Lucy","Bencomo, Nelly","Bruel, Jean-Michel","Becker, Christoph","Betz, Stefanie","Chitchyan, Ruzanna","Cheng, Betty H. C.","Klingert, Sonja","Paige, Richard F.","Penzenstadler, Birgit","Seyff, Norbert","Syriani, Eugene","Venters, Colin C."],"date":["2020-02-24"],"doi":["10.1145/3371906"],"issn":["0001-0782, 1557-7317"],"journaltitle":["Commun. ACM"],"number":["3"],"pages":["80–91"],"title":["Toward model-driven sustainability evaluation"],"volume":["63"]},"creators":{"author":[{"lastName":"Kienzle","firstName":"Jörg"},{"lastName":"Mussbacher","firstName":"Gunter"},{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Bastin","firstName":"Lucy"},{"lastName":"Bencomo","firstName":"Nelly"},{"lastName":"Bruel","firstName":"Jean-Michel"},{"lastName":"Becker","firstName":"Christoph"},{"lastName":"Betz","firstName":"Stefanie"},{"lastName":"Chitchyan","firstName":"Ruzanna"},{"lastName":"Cheng","firstName":"Betty H. C."},{"lastName":"Klingert","firstName":"Sonja"},{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Penzenstadler","firstName":"Birgit"},{"lastName":"Seyff","firstName":"Norbert"},{"lastName":"Syriani","firstName":"Eugene"},{"lastName":"Venters","firstName":"Colin C."}]},"sentenceCased":true},{"key":"kienzleSecondWorkingSession","type":"article","fields":{"langid":["english"],"abstract":["Many academic modelling tools have accumulated significant technical debt and lack of the nowadays quality standards. Following on from the success of the 1st working session on a common architecture/infrastructure for modelling tools for teaching, held at MODELS’23, which produced a comprehensive catalogue of requirements for modelling tools for teaching to be published in SoSyM, we propose a 2nd working session to focus on designs and implementations delivering on these requirements. The session will have a short programme of presentations, but will prioritise discussion and consensus-forming to work towards community-owned assets as the foundations for modelling tools for teaching."],"author":["Kienzle, Jorg","Zschaler, Steffen"],"note":["<h1>Annotazioni\n (18/3/2024, 21:55:23)</h1> \n\n- “Second Working Session” (Kienzle e Zschaler, p. 1) #2ea8e5\n <i>test</i> \n\n- “Infrastructure for Modelling Tools for Teac” (Kienzle e Zschaler, p. 1) #5fb236\n <i>test2</i>"],"title":["Second Working Session on a Common Architecture/Infrastructure for Modelling Tools for Teaching"]},"creators":{"author":[{"lastName":"Kienzle","firstName":"Jorg"},{"lastName":"Zschaler","firstName":"Steffen"}]}},{"key":"kim_f_2018","type":"inproceedings","fields":{"langid":["english"],"abstract":["Code search is an unavoidable activity in software development. Various approaches and techniques have been explored in the literature to support code search tasks. Most of these approaches focus on serving user queries provided as natural language free-form input. However, there exists a wide range of use-case scenarios where a code-to-code approach would be most beneficial. For example, research directions in code transplantation, code diversity, patch recommendation can leverage a code-to-code search engine to find essential ingredients for their techniques. In this paper, we propose FaCoY, a novel approach for statically finding code fragments which may be semantically similar to user input code. FaCoY implements a query alternation strategy: instead of directly matching code query tokens with code in the search space, FaCoY first attempts to identify other tokens which may also be relevant in implementing the functional behavior of the input code. With various experiments, we show that (1) FaCoY is more effective than online code-to-code search engines; (2) FaCoY can detect more semantic code clones (i.e., Type-4) in BigCloneBench than the state-of-theart; (3) FaCoY, while static, can detect code fragments which are indeed similar with respect to runtime execution behavior; and (4) FaCoY can be useful in code/patch recommendation."],"author":["Kim, Kisub","Kim, Dongsun","Bissyandé, Tegawendé F.","Choi, Eunjong","Li, Li","Klein, Jacques","Traon, Yves Le"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/conf/icse/KimKBC0KT18"],"booktitle":["Proc. 40th Int. Conf. Softw. Eng. - ICSE 18"],"date":["2018"],"ids":["DBLP:conf/icse/KimKBC0KT18"],"isbn":["978-1-4503-5638-1"],"location":["Gothenburg, Sweden"],"nodoi":["10.1145/3180155.3180187"],"note":["TL;DR \n\nFaCoY is proposed, a novel approach for statically finding code fragments which may be semantically similar to user input code which is more effective than online code-to-code search engines and can be useful in code/patch recommendation."],"pages":["946–957"],"publisher":["ACM Press"],"shorttitle":["F"],"timestamp":["Wed, 21 Nov 2018 12:43:59 +0100"],"title":["FaCoY: A code-to-code search engine"],"url":["http://dl.acm.org/citation.cfm?doid=3180155.3180187"],"urldate":["2019-09-04"]},"creators":{"author":[{"lastName":"Kim","firstName":"Kisub"},{"lastName":"Kim","firstName":"Dongsun"},{"lastName":"Bissyandé","firstName":"Tegawendé F."},{"lastName":"Choi","firstName":"Eunjong"},{"lastName":"Li","firstName":"Li"},{"lastName":"Klein","firstName":"Jacques"},{"lastName":"Traon","firstName":"Yves Le"}]},"sentenceCased":true},{"key":"KIM20081200","type":"article","fields":{"abstract":["The Internet is emerging as a new marketing channel, so understanding the characteristics of online customers’ needs and expectations is considered a prerequisite for activating the consumer-oriented electronic commerce market. In this study, we propose a novel clustering algorithm based on genetic algorithms (GAs) to effectively segment the online shopping market. In general, GAs are believed to be effective on NP-complete global optimization problems, and they can provide good near-optimal solutions in reasonable time. Thus, we believe that a clustering technique with GA can provide a way of finding the relevant clusters more effectively. The research in this paper applied K-means clustering whose initial seeds are optimized by GA, which is called GA K-means, to a real-world online shopping market segmentation case. In this study, we compared the results of GA K-means to those of a simple K-means algorithm and self-organizing maps (SOM). The results showed that GA K-means clustering may improve segmentation performance in comparison to other typical clustering algorithms. In addition, our study validated the usefulness of the proposed model as a preprocessing tool for recommendation systems."],"author":["Kim, Kyoung-jae","Ahn, Hyunchul"],"date":["2008"],"doi":["10.1016/j.eswa.2006.12.025"],"issn":["0957-4174"],"journaltitle":["Expert Syst. Appl."],"keywords":["Case-based reasoning","Genetic algorithms","Market segmentation","Recommender system","Self-organizing maps"],"number":["2"],"pages":["1200–1209"],"title":["A recommender system using GA K-means clustering in an online shopping market"],"volume":["34"]},"creators":{"author":[{"lastName":"Kim","firstName":"Kyoung-jae"},{"lastName":"Ahn","firstName":"Hyunchul"}]},"sentenceCased":true},{"key":"kim2014convolutional","type":"inproceedings","fields":{"added-at":["2017-01-25T12:34:20.000+0100"],"author":["Kim, Yoon"],"bibsource":["dblp computer science bibliography, http://dblp.org"],"biburl":["https://www.bibsonomy.org/bibtex/2ca3690ad4dc124a0e0f30afaa475adb9/albinzehe"],"booktitle":["Proc. 2014 Conf Empir. Methods NLP EMNLP 2014 Oct. 25-29 2014 Doha Qatar"],"date":["2014"],"description":["dblp: BibTeX record conf/emnlp/Kim14"],"interhash":["5a18dcdef0fe1455c8d7d96cee67e2b6"],"intrahash":["ca3690ad4dc124a0e0f30afaa475adb9"],"keywords":["cnn gpu kallimachos ma-zehe mlnlp neuralnet sentimentanalysis"],"note":["TL;DR \n\nThe CNN models discussed herein improve upon the state of the art on 4 out of 7 tasks, which include sentiment analysis and question classification, and are proposed to allow for the use of both task-specific and static vectors."],"pages":["1746–1751"],"timestamp":["2018-06-08T05:08:41.000+0200"],"title":["Convolutional neural networks for sentence classification"]},"creators":{"author":[{"lastName":"Kim","firstName":"Yoon"}]},"sentenceCased":true},{"key":"Kim2022","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Appl. Soft Comput."],"affiliation":["School of Mechanical Engineering, Yonsei University, Seoul, 03722, South Korea"],"art_number":["108934"],"author":["Kim, J.","Lee, J."],"correspondence_address1":["Lee, J.; School of Mechanical Engineering, South Korea; email: jleej@yonsei.ac.kr"],"date":["2022"],"document_type":["Article"],"doi":["10.1016/j.asoc.2022.108934"],"issn":["15684946"],"journaltitle":["Appl. Soft Comput."],"note":["cited By 0"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Instance-based transfer learning method via modified domain-adversarial neural network with influence function: Applications to design metamodeling and fault diagnosis"],"volume":["123"]},"creators":{"author":[{"lastName":"Kim","firstName":"J."},{"lastName":"Lee","firstName":"J."}]},"sentenceCased":true},{"key":"kimLanguageModelsCan2023","type":"online","fields":{"abstract":["Agents capable of carrying out general tasks on a computer can improve efficiency and productivity by automating repetitive tasks and assisting in complex problem-solving. Ideally, such agents should be able to solve new computer tasks presented to them through natural language commands. However, previous approaches to this problem require large amounts of expert demonstrations and task-specific reward functions, both of which are impractical for new tasks. In this work, we show that a pre-trained large language model (LLM) agent can execute computer tasks guided by natural language using a simple prompting scheme where the agent Recursively Criticizes and Improves its output (RCI). The RCI approach significantly outperforms existing LLM methods for automating computer tasks and surpasses supervised learning (SL) and reinforcement learning (RL) approaches on the MiniWoB++ benchmark. We compare multiple LLMs and find that RCI with the InstructGPT-3+RLHF LLM is state-of-the-art on MiniWoB++, using only a handful of demonstrations per task rather than tens of thousands, and without a task-specific reward function. Furthermore, we demonstrate RCI prompting's effectiveness in enhancing LLMs' reasoning abilities on a suite of natural language reasoning tasks, outperforming chain of thought (CoT) prompting with external feedback. We find that RCI combined with CoT performs better than either separately. Our code can be found here: https://github.com/posgnu/rci-agent."],"author":["Kim, Geunwoo","Baldi, Pierre","McAleer, Stephen"],"date":["2023-11-16"],"eprint":["2303.17491"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Computation and Language","Computer Science - Human-Computer Interaction","Computer Science - Machine Learning"],"pubstate":["preprint"],"title":["Language Models can Solve Computer Tasks"],"url":["http://arxiv.org/abs/2303.17491"],"urldate":["2024-01-18"]},"creators":{"author":[{"lastName":"Kim","firstName":"Geunwoo"},{"lastName":"Baldi","firstName":"Pierre"},{"lastName":"McAleer","firstName":"Stephen"}]},"sentenceCased":true},{"key":"kirchhofMontiThingsModelDrivenDevelopment2022","type":"article","fields":{"langid":["english"],"abstract":["Internet of Things (IoT) applications are exposed to harsh conditions due to factors such as device failure, network problems, or implausible sensor values. We investigate how the inherent encapsulation of component and connector (C&C) architectures can be used to develop and deploy reliable IoT applications. Existing C&C languages for the development of IoT applications mainly focus on the description of architectures and the distribution of components to IoT devices. Furthermore, related approaches often pollute the models with low-level implementation details, tying the models to a particular platform and making them harder to understand. In this paper, we introduce MontiThings, a C&C language offering automatic error handling capabilities and a clear separation between business logic and implementation details. The error-handling methods presented in this paper can make C&Cbased IoT applications more reliable without cluttering the business logic with error-handling code that is time-consuming to develop and makes the models hard to understand, especially for non-experts."],"author":["Kirchhof, Jörg Christian","Rumpe, Bernhard","Schmalzing, David","Wortmann, Andreas"],"date":["2022-01"],"doi":["10.1016/j.jss.2021.111087"],"issn":["01641212"],"journaltitle":["Journal of Systems and Software"],"keywords":["LOGSEQ"],"pages":["111087"],"shorttitle":["MontiThings"],"title":["MontiThings: Model-Driven Development and Deployment of Reliable IoT Applications"],"volume":["183"]},"creators":{"author":[{"lastName":"Kirchhof","firstName":"Jörg Christian"},{"lastName":"Rumpe","firstName":"Bernhard"},{"lastName":"Schmalzing","firstName":"David"},{"lastName":"Wortmann","firstName":"Andreas"}]}},{"key":"KitchenhamBLBB11","type":"inproceedings","fields":{"author":["Kitchenham, Barbara A.","Brereton, Pearl","Li, Zhi","Budgen, David","Burn, Andrew James"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/conf/ease/KitchenhamBLBB11.bib"],"booktitle":["15th Int. Conf. Eval. Assess. Softw. Eng. EASE 2011 Durh. UK 11-12 April 2011 Proc."],"date":["2011"],"doi":["10.1049/ic.2011.0006"],"pages":["46–55"],"timestamp":["Fri, 09 Apr 2021 18:54:10 +0200"],"title":["Repeatability of systematic literature reviews"]},"creators":{"author":[{"lastName":"Kitchenham","firstName":"Barbara A."},{"lastName":"Brereton","firstName":"Pearl"},{"lastName":"Li","firstName":"Zhi"},{"lastName":"Budgen","firstName":"David"},{"lastName":"Burn","firstName":"Andrew James"}]},"sentenceCased":true},{"key":"KizhakkeKodakkattu2020553","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Adv. Intell. Sys. Comput."],"affiliation":["Government Engineering College Kozhikode, West Hill P.O., Kozhikode, Kerala 673008, India"],"author":["Kizhakke Kodakkattu, S."],"correspondence_address1":["Kizhakke Kodakkattu, S.; Government Engineering College Kozhikode, West Hill P.O., India; email: saijalkk@gmail.com"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1007/978-981-13-8196-6_48"],"editor":["Venkata Rao R., Taler J."],"isbn":["9789811381959"],"issn":["21945357"],"journaltitle":["Adv. Intell. Syst. Comput."],"note":["cited By 0"],"pages":["553–562"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Design optimization of helicopter rotor with trailing-edge flaps using genetic algorithm"],"volume":["949"]},"creators":{"author":[{"lastName":"Kizhakke Kodakkattu","firstName":"S."}],"editor":[{"lastName":"Venkata Rao R.","firstName":"Taler J."}]},"sentenceCased":true},{"key":"klein_2015","type":"misc","fields":{"langid":["english"],"author":["Klein, John"],"date":["2015-05"],"howpublished":["Carnegie Mellon University, Software Engineering Institute's Insights (blog)"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["Accessed: 2024-Mar-5"],"title":["Model driven engineering: Automatic code generation and beyond"],"url":["https://insights.sei.cmu.edu/blog/model-driven-engineering-automatic-code-generation-and-beyond/"]},"creators":{"author":[{"lastName":"Klein","firstName":"John"}]},"sentenceCased":true},{"key":"kleppe2003mda","type":"book","fields":{"langid":["english"],"author":["Kleppe, A.G.","Warmer, J.B.","Bast, W."],"date":["2003"],"isbn":["978-0-321-19442-8"],"keywords":["/unread","⛔ No INSPIRE recid found"],"lccn":["2003043725"],"publisher":["Addison-Wesley"],"series":["Addison-Wesley object technology series"],"title":["MDA explained: The model driven architecture : Practice and promise"],"url":["https://books.google.es/books?id=nC6oS5xQGukC"]},"creators":{"author":[{"lastName":"Kleppe","firstName":"A.G."},{"lastName":"Warmer","firstName":"J.B."},{"lastName":"Bast","firstName":"W."}]},"sentenceCased":true},{"key":"KlingJWBC12","type":"inproceedings","fields":{"author":["Kling, Wolfgang","Jouault, Frédéric","Wagelaar, Dennis","Brambilla, Marco","Cabot, Jordi"],"booktitle":["Proc. SLE 2011"],"date":["2012"],"pages":["180–200"],"publisher":["Springer"],"series":["LNCS"],"title":["MoScript: A DSL for querying and manipulating model repositories"],"volume":["6940"]},"creators":{"author":[{"lastName":"Kling","firstName":"Wolfgang"},{"lastName":"Jouault","firstName":"Frédéric"},{"lastName":"Wagelaar","firstName":"Dennis"},{"lastName":"Brambilla","firstName":"Marco"},{"lastName":"Cabot","firstName":"Jordi"}]},"sentenceCased":true},{"key":"koch_semi-automated_2017","type":"inproceedings","fields":{"abstract":["Modern applications are often split into separate client and server tiers that communicate via message passing over the network. One well-understood threat to privacy for such applications is the leakage of sensitive user information either in transit or at the server. In response, an array of defensive techniques have been developed to identify or block unintended or malicious information leakage. However, prior work has primarily considered privacy leaks originating at the client directed at the server, while leakage in the reverse direction – from the server to the client – is comparatively under-studied. The question of whether and to what degree this leakage constitutes a threat remains an open question. We answer this question in the affirmative with Hush, a technique for semi-automatically identifying Server-based InFormation OvershariNg (SIFON) vulnerabilities in multi-tier applications. In particular, the technique detects SIFON vulnerabilities using a heuristic that overshared sensitive information from server-side APIs will not be displayed by the application's user interface. The technique first performs a scalable static program analysis to screen applications for potential vulnerabilities, and then attempts to confirm these candidates as true vulnerabilities with a partially-automated dynamic analysis. Our evaluation over a large corpus of Android applications demonstrates the effectiveness of the technique by discovering several previously-unknown SIFON vulnerabilities in eight applications."],"author":["Koch, William","Chaabane, Abdelberi","Egele, Manuel","Robertson, William","Kirda, Engin"],"booktitle":["Proc. 26th ACM SIGSOFT Int. Symp. Softw. Test. Anal."],"date":["2017-07"],"doi":["10.1145/3092703.3092708"],"isbn":["978-1-4503-5076-1"],"keywords":["Android testing","information leakage","software analysis"],"location":["New York, NY, USA"],"note":["TL;DR \n\nHush is a technique for semi-automatically identifying Server-based InFormation OvershariNg (SIFON) vulnerabilities in multi-tier applications using a heuristic that overshared sensitive information from server-side APIs will not be displayed by the application's user interface."],"pages":["147–157"],"publisher":["Association for Computing Machinery"],"series":["ISSTA 2017"],"title":["Semi-automated discovery of server-based information oversharing vulnerabilities in Android applications"]},"creators":{"author":[{"lastName":"Koch","firstName":"William"},{"lastName":"Chaabane","firstName":"Abdelberi"},{"lastName":"Egele","firstName":"Manuel"},{"lastName":"Robertson","firstName":"William"},{"lastName":"Kirda","firstName":"Engin"}]},"sentenceCased":true},{"key":"Kochovski2021215","type":"article","fields":{"abstract":["The new wave of Artificial Intelligence (AI) implementation has made it possible to deploy and (re)use AI models seamlessly. Modern software engineering techniques make it possible to containerize and orchestrate AI services globally, and across the whole computing continuum from the Cloud to the Edge. However, the data processed by AI services may be subject to various privacy and governance constraints, and thus subject to governmental regulations. In this work we present an advanced Smart Contract that is built to achieve regulatory compliance in cross-border AI model sharing between the European Union and the Republic of Korea. Key feature of the Smart Contract are specially developed oracle adapters that are used to achieve fine-grained control on AI model management. © 2021, Springer Nature Switzerland AG."],"author":["Kochovski, P.","Kum, S.","Moon, J.","Vujić, A.","Stankovski, V."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-92916-9_20"],"editor":["Tserpes K., Banares J.A., Tuffin B., Altmann J., Ben-Yehuda O.A., Stankovski V., Djemame K."],"isbn":["9783030929152"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 0"],"pages":["215–222"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Smart contract for cross-border AI model management"],"volume":["13072 LNCS"]},"creators":{"author":[{"lastName":"Kochovski","firstName":"P."},{"lastName":"Kum","firstName":"S."},{"lastName":"Moon","firstName":"J."},{"lastName":"Vujić","firstName":"A."},{"lastName":"Stankovski","firstName":"V."}],"editor":[{"lastName":"Tserpes K.","suffix":"Banares J.A.","firstName":"Tuffin B., Altmann J., Ben-Yehuda O.A., Stankovski V., Djemame K."}]},"sentenceCased":true},{"key":"koegel2010emfstore","type":"inproceedings","fields":{"langid":["english"],"author":["Koegel, Maximilian","Helming, Jonas"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["2010 ACMIEEE 32nd Int. Conf. Softw. Eng."],"date":["2010"],"doi":["10.1145/1810295.1810364"],"ids":["KoegelH10"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nEMFStore is a Software Configuration Management system tailored to the specific requirements for versioning models that employs operation-based change tracking, conflict detection and merging."],"organization":["IEEE"],"pages":["307–308"],"publisher":["ACM"],"timestamp":["Tue, 06 Nov 2018 11:06:56 +0100"],"title":["EMFStore: A model repository for EMF models"],"volume":["2"]},"creators":{"author":[{"lastName":"Koegel","firstName":"Maximilian"},{"lastName":"Helming","firstName":"Jonas"}]},"sentenceCased":true},{"key":"KoegelHLHD10","type":"inproceedings","fields":{"langid":["english"],"author":["Koegel, Maximilian","Herrmannsdoerfer, Markus","Li, Yang","Helming, Jonas","David, Jörn"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Proc. 14th IEEE Int. Enterp. Distrib. Object Comput. Conf. EDOC 2010 Vitória Braz. 25-29 Oct. 2010"],"date":["2010"],"doi":["10.1109/EDOC.2010.15"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["163–172"],"publisher":["IEEE Computer Society"],"timestamp":["Fri, 24 Mar 2023 00:04:50 +0100"],"title":["Comparing state- and operation-based change tracking on models"]},"creators":{"author":[{"lastName":"Koegel","firstName":"Maximilian"},{"lastName":"Herrmannsdoerfer","firstName":"Markus"},{"lastName":"Li","firstName":"Yang"},{"lastName":"Helming","firstName":"Jonas"},{"lastName":"David","firstName":"Jörn"}]},"sentenceCased":true},{"key":"Kohavi:1995:SCB:1643031.1643047","type":"inproceedings","fields":{"acmid":["1643047"],"author":["Kohavi, Ron"],"booktitle":["Proc. 14th Int. Jt. Conf. Artif. Intell. - Vol. 2"],"date":["1995"],"isbn":["1-55860-363-8"],"location":["San Francisco, CA, USA"],"numpages":["7"],"pages":["1137–1143"],"publisher":["Morgan Kaufmann Publishers Inc."],"series":["IJCAI'95"],"title":["A study of cross-validation and bootstrap for accuracy estimation and model selection"],"url":["http://dl.acm.org/citation.cfm?id=1643031.1643047"]},"creators":{"author":[{"lastName":"Kohavi","firstName":"Ron"}]},"sentenceCased":true},{"key":"kokalyPrefaceJOTIssue2022","type":"article","fields":{"author":["Kokaly, Sahar","Ruscio, Davide Di"],"date":["2022"],"doi":["10.5381/jot.2022.21.3.e1"],"journaltitle":["J. Object Technol."],"number":["3"],"pages":["1–4"],"title":["Preface to the JOT issue on 18th European Conference on Modelling Foundations and Applications (ECMFA 2022)"],"volume":["21"]},"creators":{"author":[{"lastName":"Kokaly","firstName":"Sahar"},{"lastName":"Ruscio","firstName":"Davide Di"}]},"sentenceCased":true},{"key":"kolahdouz-rahimiEvaluationModelTransformation2014","type":"article","fields":{"langid":["english"],"author":["Kolahdouz-Rahimi, S.","Lano, K.","Pillay, S.","Troya, J.","Van Gorp, P."],"date":["2014-06"],"doi":["10.1016/j.scico.2013.07.013"],"issn":["01676423"],"journaltitle":["Sci. Comput. Program."],"pages":["5–40"],"title":["Evaluation of model transformation approaches for model refactoring"],"volume":["85"]},"creators":{"author":[{"lastName":"Kolahdouz-Rahimi","firstName":"S."},{"lastName":"Lano","firstName":"K."},{"lastName":"Pillay","firstName":"S."},{"lastName":"Troya","firstName":"J."},{"lastName":"Van Gorp","firstName":"P."}]},"sentenceCased":true},{"key":"kolovosCEURWorkshopProceedings2015","type":"article","fields":{"author":["Kolovos, D.","Di Ruscio, D.","Matragkas, N.","Cuadrado, J.S.","Rath, I.","Tisi, M."],"date":["2015"],"ids":["kolovosCEURWorkshopProceedings2015a"],"journaltitle":["CEUR Workshop Proc."],"note":["cited By 1 \n\ncited By 1"],"title":["CEUR Workshop Proceedings"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938634077&partnerID=40&md5=4fdd9c5a6a15ac65fad0a31a6aac77a9"],"volume":["1406"]},"creators":{"author":[{"lastName":"Kolovos","firstName":"D."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Matragkas","firstName":"N."},{"lastName":"Cuadrado","firstName":"J.S."},{"lastName":"Rath","firstName":"I."},{"lastName":"Tisi","firstName":"M."}]}},{"key":"kolovosCollaborativeModeldrivenSoftware2009","type":"inproceedings","fields":{"author":["family=Kolovos, given=DS, given-i=DS","Di Ruscio, D","Pierantonio, A","family=Paige, given=RF, given-i=RF"],"booktitle":["Proc. 40th Int. Conf. Softw. Eng. ICSE 2018 Gothenbg. Swed. May 27 - June 03 2018"],"date":["2009"],"doi":["10.1109/CVSM.2009.5071714"],"ids":["10.1109/CVSM.2009.5071714,5071714,kolovosDifferentModelsModel2009a,kolovosDifferentModelsModel2009b,kolovosDifferentModelsModel2009c"],"issn":["null"],"keywords":["Algorithm design and analysis","computational complexity","Computational complexity","Computer science","Conferences","Context modeling","Control system synthesis","Environmental management","graph theory","model differencing process","model driven engineering","Model driven engineering","model matching","simulation languages","Unified modeling language","Visualization"],"note":["cited By 159 \n\ncited By 159 \n\nTL;DR \n\nResearchers and practitioners can use the results for identifying existing research/technical gaps to attack, better scoping their own contributions, or understanding existing ones for identifying, classifying, and understanding existing collaborative MDSE approaches."],"numpages":["6"],"pages":["1–6"],"title":["Collaborative model-driven software engineering: A classification framework and a research map"]},"creators":{"author":[{"lastName":"Kolovos","firstName":"DS","initial":"DS"},{"lastName":"Di Ruscio","firstName":"D"},{"lastName":"Pierantonio","firstName":"A"},{"lastName":"Paige","firstName":"RF","initial":"RF"}]},"sentenceCased":true},{"key":"kolovosDomainspecificLanguagesDesign2019","type":"inproceedings","fields":{"langid":["english"],"abstract":["The need for levels of availability and scalability beyond those supported by relational databases has led to the emergence of a new generation of purpose-specific databases grouped under the term NoSQL. In general, NoSQL databases are designed with horizontal scalability as a primary concern and deliver increased availability and fault tolerance at a cost of temporary inconsistency and reduced durability of data. To balance the requirements for data consistency and availability, organisations increasingly migrate towards hybrid data persistence architectures comprising both relational and NoSQL databases. The consensus is that this trend will only become stronger in the future; critical data will continue to be stored in ACID (largely relational) databases while non-critical data will be progressively migrated to high-availability NoSQL databases."],"author":["Kolovos, Dimitris S","Medhat, Fady","Paige, Richard F","Di Ruscio, Davide","family=Storm, given=Tijs, prefix=ven der, useprefix=true","Scholze, Sebastian","Zolotas, Athanasios"],"booktitle":["11th Workshop Model. Softw. Eng. MiSE’2019 Hosted ICSE 2019"],"date":["2019"],"note":["TL;DR \n\nA model-based methodology developed in the context of the EC-funded H2020 TYPHON project for designing, developing, querying and evolving such scalable architectures for persistence, analytics and monitoring of large volumes of hybrid data, in a systematic and disciplined manner is outlined."],"title":["Domain-specific Languages for the Design, Deployment and Manipulation of Heterogeneous Databases"],"url":["http://vps.diruscio.org/nc/s/tCdFXFci6FWeXjw"]},"creators":{"author":[{"lastName":"Kolovos","firstName":"Dimitris S"},{"lastName":"Medhat","firstName":"Fady"},{"lastName":"Paige","firstName":"Richard F"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Storm","firstName":"Tijs","prefix":"vender","useprefix":true},{"lastName":"Scholze","firstName":"Sebastian"},{"lastName":"Zolotas","firstName":"Athanasios"}]},"sentenceCased":true},{"key":"kolovosDomainspecificLanguagesDesign2019a","type":"inproceedings","fields":{"author":["Kolovos, D.","Medhat, F.","Paige, R.","Di Ruscio, D.","Van Der Storm, T.","Scholze, S.","Zolotas, A."],"booktitle":["Proc. - 2019 IEEEACM 11th Int. Workshop Model. Softw. Eng. MiSE 2019"],"date":["2019"],"doi":["10.1109/MiSE.2019.00021"],"ids":["kolovosDomainspecificLanguagesDesign2019b,kolovosDomainspecificLanguagesDesign2019c,kolovosDomainspecificLanguagesDesign2019d"],"isbn":["978-1-72812-231-1"],"keywords":["Domain-specific languages","Hybrid persistence","Model-driven engineering","Non-relational databases","Relational databases"],"note":["cited By 8 \n\ncited By 8 \n\nTL;DR \n\nA model-based methodology developed in the context of the EC-funded H2020 TYPHON project for designing, developing, querying and evolving such scalable architectures for persistence, analytics and monitoring of large volumes of hybrid data, in a systematic and disciplined manner is outlined."],"pages":["89–92"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Domain-specific languages for the design, deployment and manipulation of heterogeneous databases"]},"creators":{"author":[{"lastName":"Kolovos","firstName":"D."},{"lastName":"Medhat","firstName":"F."},{"lastName":"Paige","firstName":"R."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Van Der Storm","firstName":"T."},{"lastName":"Scholze","firstName":"S."},{"lastName":"Zolotas","firstName":"A."}]},"sentenceCased":true},{"key":"kolovosEugeniaDisciplinedAutomated2015","type":"article","fields":{"langid":["english"],"author":["Kolovos, Dimitrios S.","García-Domínguez, Antonio","Rose, Louis M.","Paige, Richard F."],"date":["2015-02-26"],"doi":["10.1007/s10270-015-0455-3"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nEugenia, an open-source tool that implements the proposed approach to metamodel annotation and model transformation techniques can help to manage the complexity of GMF and EMF and deliver significant productivity, quality, and maintainability benefits."],"shorttitle":["Eugenia"],"title":["Eugenia: Towards disciplined and automated development of GMF-based graphical model editors"]},"creators":{"author":[{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"García-Domínguez","firstName":"Antonio"},{"lastName":"Rose","firstName":"Louis M."},{"lastName":"Paige","firstName":"Richard F."}]},"sentenceCased":true},{"key":"KolovosG22","type":"inproceedings","fields":{"langid":["english"],"author":["Kolovos, Dimitris S.","García-Domínguez, Antonio"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Proc. 25th Int. Conf. Model Driven Eng. Lang. Syst. Companion Proc. MODELS 2022 Montr. Quebec Can. Oct. 23-28 2022"],"date":["2022"],"doi":["10.1145/3550356.3556507"],"editor":["Kühn, Thomas","Sousa, Vasco"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nAn overview of the capabilities and the architecture of the Epsilon Playground, an open-source and publicly-available web application that enables users to experiment with metamodelling, modelling and common model management activities from the convenience of their web browser."],"pages":["131–137"],"publisher":["ACM"],"timestamp":["Mon, 26 Jun 2023 20:42:07 +0200"],"title":["The epsilon playground"]},"creators":{"author":[{"lastName":"Kolovos","firstName":"Dimitris S."},{"lastName":"García-Domínguez","firstName":"Antonio"}],"editor":[{"lastName":"Kühn","firstName":"Thomas"},{"lastName":"Sousa","firstName":"Vasco"}]},"sentenceCased":true},{"key":"kolovosProceedings2ndWorkshop2014","type":"book","fields":{"date":["2014"],"editor":["Kolovos, Dimitris S.","Ruscio, Davide Di","Matragkas, Nicholas Drivalos","family=Lara, given=Juan, prefix=de, useprefix=false","Ráth, István","Tisi, Massimo"],"ids":["kolovosProceedings2ndWorkshop2014a"],"publisher":["CEUR-WS.org"],"series":["CEUR Workshop Proceedings"],"title":["Proceedings of the 2nd Workshop on Scalability in Model Driven Engineering co-located with the Software Technologies: Applications and Foundations Conference, BigMDE@STAF2014, York, UK, July 24, 2014"],"url":["http://ceur-ws.org/Vol-1206"],"volume":["1206"]},"creators":{"editor":[{"lastName":"Kolovos","firstName":"Dimitris S."},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Matragkas","firstName":"Nicholas Drivalos"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":false},{"lastName":"Ráth","firstName":"István"},{"lastName":"Tisi","firstName":"Massimo"}]},"sentenceCased":true},{"key":"kolovosProceedings3rdWorkshop2015","type":"book","fields":{"date":["2015"],"editor":["Kolovos, Dimitris S.","Ruscio, Davide Di","Matragkas, Nicholas Drivalos","Cuadrado, Jesús Sánchez","Ráth, István","Tisi, Massimo"],"ids":["kolovosProceedings3rdWorkshop2015a,kolovosProceedings3rdWorkshop2016"],"publisher":["CEUR-WS.org"],"series":["CEUR Workshop Proceedings"],"title":["Proceedings of the 3rd Workshop on Scalable Model Driven Engineering part of the Software Technologies: Applications and Foundations (STAF 2015) federation of conferences, L'Aquila, Italy, July 23, 2015"],"url":["http://ceur-ws.org/Vol-1406"],"volume":["1406"]},"creators":{"editor":[{"lastName":"Kolovos","firstName":"Dimitris S."},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Matragkas","firstName":"Nicholas Drivalos"},{"lastName":"Cuadrado","firstName":"Jesús Sánchez"},{"lastName":"Ráth","firstName":"István"},{"lastName":"Tisi","firstName":"Massimo"}]},"sentenceCased":true},{"key":"kolovosProceedings4rdWorkshop2016","type":"book","fields":{"date":["2016"],"editor":["Kolovos, Dimitris S.","Ruscio, Davide Di","Matragkas, Nicholas Drivalos","Cuadrado, Jesús Sánchez","Ráth, István","Tisi, Massimo"],"publisher":["CEUR-WS.org"],"series":["CEUR Workshop Proceedings"],"title":["Proceedings of the 4rd Workshop on Scalable Model Driven Engineering part of the Software Technologies: Applications and Foundations (STAF 2016) federation of conferences, Vienna, Austria, July 8, 2016"],"url":["http://ceur-ws.org/Vol-1652"],"volume":["1652"]},"creators":{"editor":[{"lastName":"Kolovos","firstName":"Dimitris S."},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Matragkas","firstName":"Nicholas Drivalos"},{"lastName":"Cuadrado","firstName":"Jesús Sánchez"},{"lastName":"Ráth","firstName":"István"},{"lastName":"Tisi","firstName":"Massimo"}]},"sentenceCased":true},{"key":"koModelTransformationVerification2013","type":"article","fields":{"author":["Ko, Jong-Won","Chung, Kyung-Yong","Han, Jung-Soo"],"date":["2013"],"doi":["10.1007/s11042-013-1581-y"],"journaltitle":["Multimed. Tools Appl."],"note":["TL;DR \n\nThis study suggests a new verification method by defining the meta-model which has additional structural attributes and property information and the transformation profile, and using graph comparison algorithm which checks whether the information acquired from transformation is correct."],"title":["Model transformation verification using similarity and graph comparison algorithm"]},"creators":{"author":[{"lastName":"Ko","firstName":"Jong-Won"},{"lastName":"Chung","firstName":"Kyung-Yong"},{"lastName":"Han","firstName":"Jung-Soo"}]},"sentenceCased":true},{"key":"Kontolatis2013313","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Int. J. Manuf. Res."],"affiliation":["School of Mechanical Engineering, National Technical University of Athens, Zografou Campus, HeroonPolytechniou 9, 15780 Zografou, Greece"],"author":["Kontolatis, N.","Vosniakos, G.-C.","Gogouvitis, X.V."],"correspondence_address1":["Vosniakos, G.-C.; School of Mechanical Engineering, HeroonPolytechniou 9, 15780 Zografou, Greece; email: vosniak@central.ntua.gr"],"date":["2013"],"document_type":["Article"],"doi":["10.1504/IJMR.2013.055246"],"issn":["17500591"],"journaltitle":["Int. J. Manuf. Res."],"note":["cited By 1"],"number":["3"],"pages":["313–335"],"publisher":["Inderscience Publishers"],"source":["Scopus"],"title":["Image-based part programming with process parameter selection guidance for laser milling"],"volume":["8"]},"creators":{"author":[{"lastName":"Kontolatis","firstName":"N."},{"lastName":"Vosniakos","firstName":"G.-C."},{"lastName":"Gogouvitis","firstName":"X.V."}]},"sentenceCased":true},{"key":"Koseler201915","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["MODELSWARD - Proc. Int. Conf. Model-Driven Eng. Softw. Dev."],"affiliation":["Dept. of Computer Science and Software Engineering, Miami University, 510 East High Street, Oxford Ohio, United States"],"author":["Koseler, K.","McGraw, K.","Stephan, M."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.5220/0007245800150026"],"editor":["Hammoudi S., Pires L.F., Selic B."],"isbn":["978-989-758-358-2"],"note":["cited By 2"],"pages":["15–26"],"publisher":["SciTePress"],"series":["MODELSWARD 2019 - Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development"],"source":["Scopus"],"title":["Realization of a machine learning domain specific modeling language: A baseball analytics case study"]},"creators":{"author":[{"lastName":"Koseler","firstName":"K."},{"lastName":"McGraw","firstName":"K."},{"lastName":"Stephan","firstName":"M."}],"editor":[{"lastName":"Hammoudi S.","suffix":"Pires L.F.","firstName":"Selic B."}]},"sentenceCased":true},{"key":"koshimaReconciliationFrameworkSupport2013","type":"article","fields":{"author":["Koshima, Amanuel Alemayehu","Englebert, Vincent","Thiran, Philippe"],"date":["2013"],"doi":["10.1007/978-3-642-36654-3_10"],"journaltitle":["Domain Eng."],"pages":["239–259"],"title":["A Reconciliation Framework to Support Cooperative Work with DSM"]},"creators":{"author":[{"lastName":"Koshima","firstName":"Amanuel Alemayehu"},{"lastName":"Englebert","firstName":"Vincent"},{"lastName":"Thiran","firstName":"Philippe"}]}},{"key":"kotsiantis2007supervised","type":"article","fields":{"author":["Kotsiantis, Sotiris B","Zaharakis, I","Pintelas, P"],"date":["2007"],"journaltitle":["Emerg. Artif. Intell. Appl. Comput. Eng."],"note":["TL;DR \n\nThis paper describes various supervised machine learning classification techniques, and suggests possible bias combinations that have yet to be explored."],"pages":["3–24"],"title":["Supervised machine learning: A review of classification techniques"],"volume":["160"]},"creators":{"author":[{"lastName":"Kotsiantis","firstName":"Sotiris B"},{"lastName":"Zaharakis","firstName":"I"},{"lastName":"Pintelas","firstName":"P"}]},"sentenceCased":true},{"key":"kounevSelfAwareComputingSystems2017","type":"book","fields":{"langid":["english"],"date":["2017"],"doi":["10.1007/978-3-319-47474-8"],"editor":["Kounev, Samuel","Kephart, Jeffrey O.","Milenkoski, Aleksandar","Zhu, Xiaoyun"],"isbn":["978-3-319-47472-4 978-3-319-47474-8"],"location":["Cham"],"note":["TL;DR \n\nThis book addresses the new notion of computational self-awareness as a fundamental concept for designing and operating computing systems from an engineering perspective, aiming at developing primitives for building systems and applications."],"publisher":["Springer International Publishing"],"title":["Self-Aware Computing Systems"]},"creators":{"editor":[{"lastName":"Kounev","firstName":"Samuel"},{"lastName":"Kephart","firstName":"Jeffrey O."},{"lastName":"Milenkoski","firstName":"Aleksandar"},{"lastName":"Zhu","firstName":"Xiaoyun"}]}},{"key":"Kourouklidis2021160","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Companion Proc. - Int. Conf. Model-Driven Eng. Lang. Syst., MODELS-C"],"affiliation":["University of York, British Telecom, Ipswich, United Kingdom; University of York, York, United Kingdom"],"author":["Kourouklidis, P.","Kolovos, D.","Noppen, J.","Matragkas, N."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/MODELS-C53483.2021.00028"],"isbn":["978-1-66542-484-4"],"note":["cited By 0"],"pages":["160–164"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Companion Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021"],"source":["Scopus"],"title":["A model-driven engineering approach for monitoring machine learning models"]},"creators":{"author":[{"lastName":"Kourouklidis","firstName":"P."},{"lastName":"Kolovos","firstName":"D."},{"lastName":"Noppen","firstName":"J."},{"lastName":"Matragkas","firstName":"N."}]},"sentenceCased":true},{"key":"kowald_popularity_2022","type":"inproceedings","fields":{"langid":["english"],"abstract":["Multimedia recommender systems suggest media items, e.g., songs, (digital) books and movies, to users by utilizing concepts of traditional recommender systems such as collaborative filtering. In this paper, we investigate a potential issue of such collaborative-filtering based multimedia recommender systems, namely popularity bias that leads to the underrepresentation of unpopular items in the recommendation lists. Therefore, we study four multimedia datasets, i.e., Last.fm, MovieLens, BookCrossing and MyAnimeList, that we each split into three user groups differing in their inclination to popularity, i.e., LowPop, MedPop and HighPop. Using these user groups, we evaluate four collaborative filtering-based algorithms with respect to popularity bias on the item and the user level. Our findings are three-fold: firstly, we show that users with little interest into popular items tend to have large user profiles and thus, are important data sources for multimedia recommender systems. Secondly, we find that popular items are recommended more frequently than unpopular ones. Thirdly, we find that users with little interest into popular items receive significantly worse recommendations than users with medium or high interest into popularity."],"author":["Kowald, Dominik","Lacic, Emanuel"],"booktitle":["Adv. Bias Fairness Inf. Retr."],"date":["2022"],"doi":["10.1007/978-3-031-09316-6_1"],"editor":["Boratto, Ludovico","Faralli, Stefano","Marras, Mirko","Stilo, Giovanni"],"isbn":["978-3-031-09316-6"],"keywords":["algorithmic fairness","collaborative filtering","multimedia recommender systems","popularity bias"],"location":["Cham"],"note":["TL;DR \n\nIt is shown that users with little interest into popular items tend to have large user profiles and thus, are important data sources for multimedia recommender systems, and it is found that popular items are recommended more frequently than unpopular ones."],"pages":["1–11"],"publisher":["Springer International Publishing"],"series":["Communications in Computer and Information Science"],"title":["Popularity Bias in Collaborative Filtering-Based Multimedia Recommender Systems"]},"creators":{"author":[{"lastName":"Kowald","firstName":"Dominik"},{"lastName":"Lacic","firstName":"Emanuel"}],"editor":[{"lastName":"Boratto","firstName":"Ludovico"},{"lastName":"Faralli","firstName":"Stefano"},{"lastName":"Marras","firstName":"Mirko"},{"lastName":"Stilo","firstName":"Giovanni"}]}},{"key":"koyanagiExploringEffectMultiple2024","type":"article","fields":{"abstract":["GitHub Copilot is an AI-enabled tool that automates program synthesis. It has gained significant attention since its launch in 2021. Recent studies have extensively examined Copilot's capabilities in various programming tasks, as well as its security issues. However, little is known about the effect of different natural languages on code suggestion. Natural language is considered a social bias in the field of NLP, and this bias could impact the diversity of software engineering. To address this gap, we conducted an empirical study to investigate the effect of three popular natural languages (English, Japanese, and Chinese) on Copilot. We used 756 questions of varying difficulty levels from AtCoder contests for evaluation purposes. The results highlight that the capability varies across natural languages, with Chinese achieving the worst performance. Furthermore, regardless of the type of natural language, the performance decreases significantly as the difficulty of questions increases. Our work represents the initial step in comprehending the significance of natural languages in Copilot's capability and introduces promising opportunities for future endeavors."],"author":["Koyanagi, Kei","Wang, Dong","Noguchi, Kotaro","Kondo, Masanari","Serebrenik, Alexander","Kamei, Yasutaka","Ubayashi, Naoyasu"],"date":["2024-01-13"],"journaltitle":["21st Int. Conf. Min. Softw. Repos."],"note":["TL;DR \n\nAn empirical study is conducted to investigate the effect of three popular natural languages (English, Japanese, and Chinese) on Copilot and highlights that the capability varies across natural languages, with Chinese achieving the worst performance."],"title":["Exploring the Effect of Multiple Natural Languages on Code Suggestion Using GitHub Copilot"]},"creators":{"author":[{"lastName":"Koyanagi","firstName":"Kei"},{"lastName":"Wang","firstName":"Dong"},{"lastName":"Noguchi","firstName":"Kotaro"},{"lastName":"Kondo","firstName":"Masanari"},{"lastName":"Serebrenik","firstName":"Alexander"},{"lastName":"Kamei","firstName":"Yasutaka"},{"lastName":"Ubayashi","firstName":"Naoyasu"}]}},{"key":"kramerSelfManagedSystemsArchitectural2007","type":"inproceedings","fields":{"author":["Kramer, Jeff","Magee, Jeff"],"date":["2007-05"],"doi":["10.1109/FOSE.2007.19"],"isbn":["978-0-7695-2829-8"],"note":["TL;DR \n\nSome of the current promising work in self-management is discussed and an outline three-layer reference model is presented as a context in which to articulate some of the main outstanding research challenges."],"pages":["259–268"],"publisher":["IEEE"],"shorttitle":["Self-Managed Systems"],"title":["Self-Managed Systems: An Architectural Challenge"]},"creators":{"author":[{"lastName":"Kramer","firstName":"Jeff"},{"lastName":"Magee","firstName":"Jeff"}]}},{"key":"krauseMetamodelSpecificCoupledEvolution2013","type":"article","fields":{"author":["Krause, Christian","Dyck, Johannes","Giese, Holger"],"date":["2013"],"doi":["10.1007/978-3-642-38883-5_10"],"journaltitle":["Theory Pract. Model Transform."],"pages":["76–91"],"title":["Metamodel-Specific Coupled Evolution Based on Dynamically Typed Graph Transformations"],"volume":["7909"]},"creators":{"author":[{"lastName":"Krause","firstName":"Christian"},{"lastName":"Dyck","firstName":"Johannes"},{"lastName":"Giese","firstName":"Holger"}]}},{"key":"Krenker11","type":"incollection","fields":{"author":["Krenker, Andrej","Bester, Janez","Kos, Andrej"],"booktitle":["Artificial neural networks"],"chapter":["1"],"date":["2011"],"editor":["Suzuki, Kenji"],"location":["Rijeka"],"nodoi":["10.5772/15751"],"publisher":["IntechOpen"],"title":["Introduction to the artificial neural networks"]},"creators":{"author":[{"lastName":"Krenker","firstName":"Andrej"},{"lastName":"Bester","firstName":"Janez"},{"lastName":"Kos","firstName":"Andrej"}],"editor":[{"lastName":"Suzuki","firstName":"Kenji"}]},"sentenceCased":true},{"key":"Krishnan2017","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Workshop Hum.-Loop Data Anal."],"affiliation":["UC Berkeley, United States; Columbia University, United States"],"art_number":["3077271"],"author":["Krishnan, S.","Wu, E."],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.1145/3077257.3077271"],"isbn":["978-1-4503-5029-7"],"keywords":["GOAL_Debugging","notion"],"note":["cited By 34 \n\nTL;DR \n\nPALM is a tool that learns and summarizes this responsibility structure to aide machine learning debugging, which approximates a complex model using a meta-model that partitions the training data, and a set of sub-models that approximate the patterns within each partition."],"publisher":["Association for Computing Machinery, Inc"],"series":["Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics, HILDA 2017"],"source":["Scopus"],"title":["PALM: Machine learning explanations for iterative debugging"]},"creators":{"author":[{"lastName":"Krishnan","firstName":"S."},{"lastName":"Wu","firstName":"E."}]},"sentenceCased":true},{"key":"Kroetz2017394","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Adv Eng Software"],"affiliation":["Department of Structural Engineering, University of São Paulo, São Carlos, Brazil"],"author":["Kroetz, H.M.","Tessari, R.K.","Beck, A.T."],"coden":["AESOD"],"correspondence_address1":["Kroetz, H.M.; Department of Structural Engineering, Brazil; email: henrique.kroetz@usp.br"],"date":["2017"],"document_type":["Article"],"doi":["10.1016/j.advengsoft.2017.08.001"],"issn":["09659978"],"journaltitle":["Adv. Eng. Softw."],"note":["cited By 25"],"pages":["394–404"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Performance of global metamodeling techniques in solution of structural reliability problems"],"volume":["114"]},"creators":{"author":[{"lastName":"Kroetz","firstName":"H.M."},{"lastName":"Tessari","firstName":"R.K."},{"lastName":"Beck","firstName":"A.T."}]},"sentenceCased":true},{"key":"krupitzerSurveyEngineeringApproaches2015","type":"article","fields":{"langid":["english"],"author":["Krupitzer, Christian","Roth, Felix Maximilian","VanSyckel, Sebastian","Schiele, Gregor","Becker, Christian"],"date":["2015-02"],"doi":["10.1016/j.pmcj.2014.09.009"],"issn":["15741192"],"journaltitle":["Pervasive Mob. Comput."],"pages":["184–206"],"title":["A survey on engineering approaches for self-adaptive systems"],"volume":["17"]},"creators":{"author":[{"lastName":"Krupitzer","firstName":"Christian"},{"lastName":"Roth","firstName":"Felix Maximilian"},{"lastName":"VanSyckel","firstName":"Sebastian"},{"lastName":"Schiele","firstName":"Gregor"},{"lastName":"Becker","firstName":"Christian"}]},"sentenceCased":true},{"key":"kuangNewSearchEngine","type":"article","fields":{"langid":["english"],"abstract":["The original Yahoo! search engine consists of manually organized topic hierarchy of webpages for easy browsing. Modern search engines (such as Google and Bing), on the other hand, return a flat list of webpages based on keywords. It would be ideal if hierarchical browsing and keyword search can be seamlessly combined. The main difficulty in doing so is to automatically (i.e., not manually) classify and rank a massive number of webpages into various hierarchies (such as topics, media types, regions of the world). In this paper we report our attempt towards building this integrated search engine, called SEE (Search Engine with hiErarchy). We implement a hierarchical classification system based on Support Vector Machines, and embed it in SEE. We also design a novel user interface that allows users to dynamically adjust their desire for a higher accuracy vs. more results in any (sub)category of the hierarchy. Though our current search engine is still small (indexing about 1.2 million webpages), the results, including a small user study, have shown a great promise for integrating such techniques in the next-generation search engine."],"author":["Kuang, Da","Li, Xiao","Ling, Charles X"],"pages":["6"],"title":["A New Search Engine Integrating Hierarchical Browsing and Keyword Search"]},"creators":{"author":[{"lastName":"Kuang","firstName":"Da"},{"lastName":"Li","firstName":"Xiao"},{"lastName":"Ling","firstName":"Charles X"}]}},{"key":"kuhn2005enriching","type":"inproceedings","fields":{"author":["Kuhn, Adrian","Ducasse, Stéphane","Girba, Tudor"],"booktitle":["12th Work. Conf. Reverse Eng. WCRE05"],"date":["2005"],"note":["TL;DR \n\nThis paper analyzes how semantics of the source code are spread over the source artifacts using latent semantic indexing, an information retrieval technique that cluster artifacts that use similar terms, and reveals the most relevant terms for the computed clusters."],"organization":["IEEE"],"pages":["10-pp"],"title":["Enriching reverse engineering with semantic clustering"]},"creators":{"author":[{"lastName":"Kuhn","firstName":"Adrian"},{"lastName":"Ducasse","firstName":"Stéphane"},{"lastName":"Girba","firstName":"Tudor"}]},"sentenceCased":true},{"key":"kula_rauximpact--security-advisories--library-migrations_2018","type":"misc","fields":{"abstract":["Contribute to raux/Impact-of-Security-Advisories-on-Library-Migrations development by creating an account on GitHub."],"author":["Kula, R. G."],"date":["2018-06"],"note":["original-date: 2017-02-15T08:36:47Z"],"nourl":["https://github.com/raux/Impact-of-Security-Advisories-on-Library-Migrations"],"title":["Raux/Impact-of-Security-Advisories-on-Library-Migrations"]},"creators":{"author":[{"lastName":"Kula","firstName":"R. G."}]}},{"key":"kulaDevelopersUpdateTheir2018","type":"article","fields":{"langid":["english"],"author":["Kula, Raula Gaikovina","German, Daniel M.","Ouni, Ali","Ishio, Takashi","Inoue, Katsuro"],"date":["2018-02"],"doi":["10.1007/s10664-017-9521-5"],"ids":["kula_developers_2018"],"issn":["1382-3256, 1573-7616"],"journaltitle":["Empir Software Eng"],"nourl":["http://link.springer.com/10.1007/s10664-017-9521-5"],"number":["1"],"pages":["384–417"],"shorttitle":["Do developers update their library dependencies?"],"title":["Do developers update their library dependencies?: An empirical study on the impact of security advisories on library migration"],"volume":["23"]},"creators":{"author":[{"lastName":"Kula","firstName":"Raula Gaikovina"},{"lastName":"German","firstName":"Daniel M."},{"lastName":"Ouni","firstName":"Ali"},{"lastName":"Ishio","firstName":"Takashi"},{"lastName":"Inoue","firstName":"Katsuro"}]},"sentenceCased":true},{"key":"kullbackInformationSufficiency1951","type":"article","fields":{"added-at":["2010-10-31T19:59:47.000+0100"],"author":["Kullback, S.","Leibler, R. A."],"biburl":["https://www.bibsonomy.org/bibtex/2560a5719c537c5c4a496bfebd4a21603/leeₚeck"],"date":["1951"],"description":["Kullback , Leibler : On Information and Sufficiency"],"interhash":["f9d41d76a07383cca4c3a1a94c24d533"],"intrahash":["560a5719c537c5c4a496bfebd4a21603"],"journaltitle":["Ann Math Stat."],"keywords":["51 Kullback Leibler divergence kl"],"number":["1"],"pages":["79–86"],"timestamp":["2010-10-31T19:59:47.000+0100"],"title":["On information and sufficiency"],"volume":["22"]},"creators":{"author":[{"lastName":"Kullback","firstName":"S."},{"lastName":"Leibler","firstName":"R. A."}]},"sentenceCased":true},{"key":"kumarToolRecommenderSystem2021","type":"article","fields":{"langid":["english"],"abstract":["Abstract Background Galaxy is a web-based and open-source scientific data-processing platform. Researchers compose pipelines in Galaxy to analyse scientific data. These pipelines, also known as workflows, can be complex and difficult to create from thousands of tools, especially for researchers new to Galaxy. To help researchers with creating workflows, a system is developed to recommend tools that can facilitate further data analysis. Findings A model is developed to recommend tools using a deep learning approach by analysing workflows composed by researchers on the European Galaxy server. The higher-order dependencies in workflows, represented as directed acyclic graphs, are learned by training a gated recurrent units neural network, a variant of a recurrent neural network. In the neural network training, the weights of tools used are derived from their usage frequencies over time and the sequences of tools are uniformly sampled from training data. Hyperparameters of the neural network are optimized using Bayesian optimization. Mean accuracy of 98% in recommending tools is achieved for the top-1 metric. Conclusions The model is accessed by a Galaxy API to provide researchers with recommended tools in an interactive manner using multiple user interface integrations on the European Galaxy server. High-quality and highly used tools are shown at the top of the recommendations. The scripts and data to create the recommendation system are available under MIT license at https://github.com/anuprulez/galaxy_tool_recommendation."],"author":["Kumar, Anup","Rasche, Helena","Grüning, Björn","Backofen, Rolf"],"date":["2021-01-06"],"doi":["10.1093/gigascience/giaa152"],"issn":["2047-217X"],"journaltitle":["GigaScience"],"note":["TL;DR \n\nA model is created to recommend tools by analysing workflows, composed by researchers on the European Galaxy server, using a deep learning approach to make creating workflows easier, faster and less error-prone."],"number":["1"],"pages":["giaa152"],"title":["Tool recommender system in Galaxy using deep learning"],"volume":["10"]},"creators":{"author":[{"lastName":"Kumar","firstName":"Anup"},{"lastName":"Rasche","firstName":"Helena"},{"lastName":"Grüning","firstName":"Björn"},{"lastName":"Backofen","firstName":"Rolf"}]},"sentenceCased":true},{"key":"kuselRealityCheckModel","type":"article","fields":{"author":["Kusel, A","Schonbock, J","Wimmer, M","Retschitzegger, W","Schwinger, W","Kappel, G"],"note":["TL;DR \n\nThis paper developed a semi-automated process for extracting transformation projects from the ATL Transformation Zoo, which are classified and analyzed with respect to the application frequency of reuse mechanisms."],"title":["Reality Check for Model Transformation Reuse: The ATL Transformation Zoo Case Study"]},"creators":{"author":[{"lastName":"Kusel","firstName":"A"},{"lastName":"Schonbock","firstName":"J"},{"lastName":"Wimmer","firstName":"M"},{"lastName":"Retschitzegger","firstName":"W"},{"lastName":"Schwinger","firstName":"W"},{"lastName":"Kappel","firstName":"G"}]}},{"key":"kuselReuseModeltomodelTransformation2015","type":"article","fields":{"langid":["english"],"author":["Kusel, A.","Schönböck, J.","Wimmer, M.","Kappel, G.","Retschitzegger, W.","Schwinger, W."],"date":["2015-05"],"doi":["10.1007/s10270-013-0343-7"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nAn in-depth comparison of reuse mechanisms in model-to-model transformation languages and categorizes them along their intended scope of application is provided."],"number":["2"],"pages":["537–572"],"shorttitle":["Reuse in model-to-model transformation languages"],"title":["Reuse in model-to-model transformation languages: Are we there yet?"],"volume":["14"]},"creators":{"author":[{"lastName":"Kusel","firstName":"A."},{"lastName":"Schönböck","firstName":"J."},{"lastName":"Wimmer","firstName":"M."},{"lastName":"Kappel","firstName":"G."},{"lastName":"Retschitzegger","firstName":"W."},{"lastName":"Schwinger","firstName":"W."}]},"sentenceCased":true},{"key":"Kusiak201590","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Adv Eng Software"],"affiliation":["Department of Applied Computer Science and Modelling, AGH University of Science and Technology, Kraków, Poland"],"author":["Kusiak, J.","Sztangret, Ł.","Pietrzyk, M."],"coden":["AESOD"],"correspondence_address1":["Kusiak, J.; Department of Applied Computer Science and Modelling, Poland; email: kusiak@agh.edu.pl"],"date":["2015"],"document_type":["Article"],"doi":["10.1016/j.advengsoft.2015.02.002"],"issn":["09659978"],"journaltitle":["Adv. Eng. Softw."],"note":["cited By 17"],"pages":["90–97"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Effective strategies of metamodelling of industrial metallurgical processes"],"volume":["89"]},"creators":{"author":[{"lastName":"Kusiak","firstName":"J."},{"lastName":"Sztangret","firstName":"Ł."},{"lastName":"Pietrzyk","firstName":"M."}]},"sentenceCased":true},{"key":"kutsche2008bizycle","type":"article","fields":{"author":["Kutsche, Ralf","Milanovic, Nikola","Bauhoff, Gregor","Baum, Timo","Cartsburg, Mario","Kumpe, Daniel","Widiker, Jürgen"],"date":["2008"],"journaltitle":["Proc. MDTPI ECMDA"],"title":["Bizycle: Model-based interoperability platform for software and data integration"],"volume":["430"]},"creators":{"author":[{"lastName":"Kutsche","firstName":"Ralf"},{"lastName":"Milanovic","firstName":"Nikola"},{"lastName":"Bauhoff","firstName":"Gregor"},{"lastName":"Baum","firstName":"Timo"},{"lastName":"Cartsburg","firstName":"Mario"},{"lastName":"Kumpe","firstName":"Daniel"},{"lastName":"Widiker","firstName":"Jürgen"}]},"sentenceCased":true},{"key":"kuwaharaAutomatedPlanningSystem2019","type":"inproceedings","fields":{"abstract":["The automation of system management has been expanding, and there has been interest lately in an automated workflow generation that automatically generates the workflows of system updates. However, because these automation technologies operate under the assumption that systems work in accordance with their underlying system model, they are not good at handling unexpected behaviors of target systems.In this paper, we propose a way to incorporate unexpected handling into our declarative system update mechanism by automatically generating a \"recovery workflow\" to roll back a target system in the event of abnormal system stops. We evaluate our tool through a practical three-tier architecture system operating a simple Web service, and found that our method can complete generation of a recovery workflow in one second, and roll back the system from all system states. © 2019 IFIP."],"author":["Kuwahara, T.","Kuroda, T.","Nakanoya, M.","Yakuwa, Y.","Sato, Y.","Matsunaga, Y."],"booktitle":["2019 IFIPIEEE Symp. Integr. Netw. Serv. Manag. IM 2019"],"date":["2019"],"isbn":["978-3-903176-15-7"],"keywords":["AI planning","Automation","Change management","Client server computer systems","Computer system recovery","Declarative","Fault management","Model-driven","System rollback","Web services"],"note":["cited By 1 \n\nTL;DR \n\nThis paper proposes a way to incorporate unexpected handling into the authors' declarative system update mechanism by automatically generating a \"recovery workflow\" to roll back a target system in the event of abnormal system stops."],"pages":["428–434"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Automated planning of system rollback in declarative IT system update"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067009661&partnerID=40&md5=e12df5fd076b85398777e6937d090a82"]},"creators":{"author":[{"lastName":"Kuwahara","firstName":"T."},{"lastName":"Kuroda","firstName":"T."},{"lastName":"Nakanoya","firstName":"M."},{"lastName":"Yakuwa","firstName":"Y."},{"lastName":"Sato","firstName":"Y."},{"lastName":"Matsunaga","firstName":"Y."}]},"sentenceCased":true},{"key":"Kwon202053","type":"inproceedings","fields":{"abstract":["Deep neural networks (DNNs) provide good performance in image recognition, speech recognition and pattern analysis. However, DNNs are vulnerable to backdoor attacks. Backdoor attacks allow attackers to proactively access training data of DNNs to train additional malicious data, including the specific trigger. In normal times, DNNs correctly classify the normal data, but the malicious data with the specific trigger trained by attackers can cause misclassification of DNNs. For example, if an attacker sets up a road sign that includes a specific trigger, an autonomous vehicle equipped with a DNN may misidentify the road sign and cause an accident. Thus, an attacker can use a backdoor attack to threaten the DNN at any time. However, this backdoor attack can be useful in certain situations, such as in military situations. Since there is a mixture of enemy and friendly force in the military situations, it is necessary to cause misclassification of the enemy equipment and classification of the friendly equipment. Therefore, it is necessary to make backdoor attacks that are correctly recognized by friendly equipment and misrecognized by the enemy equipment. In this paper, we propose a friendnet backdoor that is correctly recognized by friendly classifier and misclassified by the enemy classifier. This method additionally trains the friendly and enemy classifier with the proposed data, including the specific trigger that is correctly recognized by friendly classifier and misclassified by enemy classifier. We used MNIST and Fashion-MNIST as experimental datasets and Tensorflow as a machine learning library. Experimental results show that the proposed method in MNIST and Fashion-MNIST has 100% attack success rate of the enemy classifier and the 99.21% and 92.3% accuracy of the friendly classifier, respectively. © 2020 Association for Computing Machinery."],"author":["Kwon, H.","Yoon, H.","Park, K.-W."],"author_keywords":["Adversarial example; Backdoor attack; Deep neural network; Machine learning; Poisoning attack"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3378936.3378938"],"isbn":["978-1-4503-7690-7"],"keywords":["Accidents","Adversarial example","Backdoor attack","Big data","Classification (of information)","Deep learning","Deep neural networks","Highway administration","Image recognition","Indentifying","Information management","Learning systems","Malware","Misclassifications","Neural networks","Pattern analysis","Poisoning attacks","Road signs","Roads and streets","Software engineering","Speech recognition","Training data"],"note":["cited By 2 \n\nTL;DR \n\nA friendnet backdoor that is correctly recognized by friendly classifier and misclassified by the enemy classifier is proposed, which additionally trains the friendly and enemy classifiers with the proposed data, including the specific trigger that is incorrectly recognized byfriendly classifiers and mis classified by enemyclassifier."],"pages":["53–57"],"publisher":["Association for Computing Machinery"],"series":["ACM International Conference Proceeding Series"],"source":["Scopus"],"title":["FriendNet backdoor: Indentifying backdoor attack that is safe for friendly deep neural network"]},"creators":{"author":[{"lastName":"Kwon","firstName":"H."},{"lastName":"Yoon","firstName":"H."},{"lastName":"Park","firstName":"K.-W."}]},"sentenceCased":true},{"key":"Kyriacou2014895","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Eng Optim"],"affiliation":["Parallel CFD and Optimization Unit, National Technical University of Athens, Heroon Polytechniou 9, Athens 15780, Greece; Andritz HYDRO GmbH, Lunzerstrasse 78, 4031 Linz, Austria"],"author":["Kyriacou, S.A.","Asouti, V.G.","Giannakoglou, K.C."],"coden":["EGOPA"],"correspondence_address1":["Giannakoglou, K.C.; Parallel CFD and Optimization Unit, National Technical University of Athens, Heroon Polytechniou 9, Athens 15780, Greece; email: kgianna@central.ntua.gr"],"date":["2014"],"document_type":["Article"],"doi":["10.1080/0305215X.2013.812726"],"issn":["0305215X"],"journaltitle":["Eng. Optim."],"note":["cited By 21"],"number":["7"],"pages":["895–911"],"publisher":["Taylor and Francis Ltd."],"source":["Scopus"],"title":["Efficient PCA-driven EAs and metamodel-assisted EAs, with applications in turbomachinery"],"volume":["46"]},"creators":{"author":[{"lastName":"Kyriacou","firstName":"S.A."},{"lastName":"Asouti","firstName":"V.G."},{"lastName":"Giannakoglou","firstName":"K.C."}]},"sentenceCased":true},{"key":"kyriazisSmartAutonomousReliable2013","type":"article","fields":{"langid":["english"],"author":["Kyriazis, Dimosthenis","Varvarigou, Theodora"],"date":["2013"],"doi":["10.1016/j.procs.2013.09.059"],"issn":["18770509"],"journaltitle":["Procedia Comput. Sci."],"pages":["442–448"],"title":["Smart, Autonomous and Reliable Internet of Things"],"volume":["21"]},"creators":{"author":[{"lastName":"Kyriazis","firstName":"Dimosthenis"},{"lastName":"Varvarigou","firstName":"Theodora"}]}},{"key":"L04","type":"article","fields":{"abstract":["We present the R2D2 redundancy detector. R2D2 identifies redundant code fragments in large software systems written in Lisp. For each pair of code fragments, R2D2 uses a combination of techniques ranging from syntax-based analysis to semantics-based analysis, that detects positive and negative evidences regarding the redundancy of the analyzed code fragments. These evidences are combined according to a well-defined model and sufficiently redundant fragments are reported to the user. R2D2 explores several techniques and heuristics to operate within reasonable time and space bounds and is designed to be extensible."],"author":["Leitão, António Menezes"],"date":["2004-12-01"],"doi":["10.1023/B:SQJO.0000039793.31052.72"],"issn":["1573-1367"],"journaltitle":["Softw. Qual. J."],"note":["TL;DR \n\nR2D2 identifies redundant code fragments in large software systems written in Lisp using a combination of techniques ranging from syntax-based analysis to semantics- based analysis, that detects positive and negative evidences regarding the redundancy of the analyzed code fragments."],"number":["4"],"pages":["361–382"],"title":["Detection of redundant code using R2D2"],"volume":["12"]},"creators":{"author":[{"lastName":"Leitão","firstName":"António Menezes"}]},"sentenceCased":true},{"key":"lacavaEvaluatingRecommenderSystems2021","type":"article","fields":{"langid":["english"],"abstract":["Abstract Motivation Many researchers with domain expertise are unable to easily apply machine learning (ML) to their bioinformatics data due to a lack of ML and/or coding expertise. Methods that have been proposed thus far to automate ML mostly require programming experience as well as expert knowledge to tune and apply the algorithms correctly. Here, we study a method of automating biomedical data science using a web-based AI platform to recommend model choices and conduct experiments. We have two goals in mind: first, to make it easy to construct sophisticated models of biomedical processes; and second, to provide a fully automated AI agent that can choose and conduct promising experiments for the user, based on the user’s experiments as well as prior knowledge. To validate this framework, we conduct an experiment on 165 classification problems, comparing to state-of-the-art, automated approaches. Finally, we use this tool to develop predictive models of septic shock in critical care patients. Results We find that matrix factorization-based recommendation systems outperform metalearning methods for automating ML. This result mirrors the results of earlier recommender systems research in other domains. The proposed AI is competitive with state-of-the-art automated ML methods in terms of choosing optimal algorithm configurations for datasets. In our application to prediction of septic shock, the AI-driven analysis produces a competent ML model (AUROC 0.85±0.02) that performs on par with state-of-the-art deep learning results for this task, with much less computational effort. Availability and implementation PennAI is available free of charge and open-source. It is distributed under the GNU public license (GPL) version 3. Supplementary information Supplementary data are available at Bioinformatics online."],"author":["La Cava, William","Williams, Heather","Fu, Weixuan","Vitale, Steve","Srivatsan, Durga","Moore, Jason H"],"date":["2021-04-19"],"doi":["10.1093/bioinformatics/btaa698"],"editor":["Wren, Jonathan"],"issn":["1367-4803, 1460-2059"],"journaltitle":["Bioinformatics"],"number":["2"],"pages":["250–256"],"title":["Evaluating recommender systems for AI-driven biomedical informatics"],"volume":["37"]},"creators":{"author":[{"lastName":"La Cava","firstName":"William"},{"lastName":"Williams","firstName":"Heather"},{"lastName":"Fu","firstName":"Weixuan"},{"lastName":"Vitale","firstName":"Steve"},{"lastName":"Srivatsan","firstName":"Durga"},{"lastName":"Moore","firstName":"Jason H"}],"editor":[{"lastName":"Wren","firstName":"Jonathan"}]},"sentenceCased":true},{"key":"laiRobustOnlinePath2016","type":"article","fields":{"langid":["english"],"author":["Lai, Shupeng","Wang, Kangli","Qin, Hailong","Cui, Jin Q.","Chen, Ben M."],"date":["2016-02"],"doi":["10.1007/s11768-016-6007-8"],"issn":["2095-6983, 2198-0942"],"journaltitle":["Control Theory Technol."],"note":["TL;DR \n\nA robust online path planning method, which allows a micro rotorcraft drone to fly safely in GPS-denied and obstacle-strewn environments with limited onboard computational power, and has been realized on actual drones platforms and successfully demonstrated in real flight tests."],"number":["1"],"pages":["83–96"],"title":["A robust online path planning approach in cluttered environments for micro rotorcraft drones"],"volume":["14"]},"creators":{"author":[{"lastName":"Lai","firstName":"Shupeng"},{"lastName":"Wang","firstName":"Kangli"},{"lastName":"Qin","firstName":"Hailong"},{"lastName":"Cui","firstName":"Jin Q."},{"lastName":"Chen","firstName":"Ben M."}]},"sentenceCased":true},{"key":"Lakshminarayan20192043","type":"inproceedings","fields":{"abstract":["Big data characterized by variety can be divided into 3 principal categories: numeric structured data, semi-structured data, and unstructured multimedia data involving audio, video, and text. Decision making requires multiple analytical engines suitable for each type of data, programming languages, algorithms, visualization tools, and user interfaces. More often than not, industrial analytics is conducted ad hoc by lashing together analytics components such as distributed data sources, analytics engines, and algorithms. This kind of piecemeal approach ignores scale, security, governance, reliability, model management and fault tolerance that are paramount for industrial strength analytics. A unified, versatile, and robust architecture that combines various components in a single integrated platform is the need of the hour. Teradata Vantage (TD Vantage) is such a platform for delivering production quality enterprise analytics at scale. In this paper, we outline the proposed TD Vantage (available in the market and under continuous development) that unifies data, engines, and algorithms operating in a seamless symphony. We will demonstrate its capabilities through three proofs of concept biz: image data using TensorFlow, text data using Spark, and transaction data using Aster (now renamed Machine Learning Engine or MLE), with Teradata orchestrating interactions among the various components. © 2019 IEEE."],"art_number":["9006321"],"author":["Lakshminarayan, C.","Ramakrishnan, T.","Al-Omari, A.","Bouaziz, K.","Ahmad, F.","Raghavan, S.","Agarwal, P."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/BigData47090.2019.9006321"],"editor":["Baru C., Huan J., Hu X.T., Ak R., Tian Y., Barga R., Zaniolo C., Lee K., Ye Y.F., Khan L."],"isbn":["978-1-72810-858-2"],"note":["cited By 2 \n\nTL;DR \n\nThe proposed TD Vantage is outlined and its capabilities are demonstrated through three proofs of concept biz: image data using TensorFlow, text data using Spark, and transaction data using Aster, with Teradata orchestrating interactions among the various components."],"pages":["2043–2046"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019"],"source":["Scopus"],"title":["Enterprise-wide machine learning using teradata vantage: An integrated analytics platform"]},"creators":{"author":[{"lastName":"Lakshminarayan","firstName":"C."},{"lastName":"Ramakrishnan","firstName":"T."},{"lastName":"Al-Omari","firstName":"A."},{"lastName":"Bouaziz","firstName":"K."},{"lastName":"Ahmad","firstName":"F."},{"lastName":"Raghavan","firstName":"S."},{"lastName":"Agarwal","firstName":"P."}],"editor":[{"lastName":"Baru C.","suffix":"Huan J.","firstName":"Hu X.T., Ak R., Tian Y., Barga R., Zaniolo C., Lee K., Ye Y.F., Khan L."}]},"sentenceCased":true},{"key":"Lakshminarayan20196110","type":"inproceedings","fields":{"abstract":["Ease-of-use analytics at scale is the holy grail of industrial strength machine learning. In order to reap benefits from the mother-lode of business related data; tools, technologies, and analytical functions should operate in perpetual symphony to derive insightful business outcomes. While there have been advances in APIs, algorithms, and user interfaces, building an end to end workflow spanning data ingestion, data preparation, model training, model scoring, visualization and finally continuous improvement and model management received limited investment. In this paper we demonstrate an analytical workflow that integrates multiple analytical tools and techniques for image recognition wrapped in the model management framework. As analytics in industry is maturing, analytics implementations are no longer one-off, but are components of Analytics Operations known as AnalyticsOps. We introduce the notion of Model Quality Index (MQI) to track model performance. The MQI is similar to Process Capability Index (PCI) common in 6 σprograms in manufacturing. Our solution combines relational databases (Teradata DB), Machine Learning (Teradata/Aster), Deep Learning (TensorFlow), Hadoop Distributed File System (HDFS), and user interface tools over a communication fabric (Teradata QueryGrid). In particular, we demonstrate a hand written word recognition use-case for an enterprise customer cast in a model management workflow for repeatable deployments across a range of businesses. © 2019 IEEE."],"art_number":["9005445"],"author":["Lakshminarayan, C.","Ramakrishnan, T.","Al-Omari, A.","Bouaziz, K.","Ahmad, F.","Raghavan, S.","Agarwal, P."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/BigData47090.2019.9005445"],"editor":["Baru C., Huan J., Hu X.T., Ak R., Tian Y., Barga R., Zaniolo C., Lee K., Ye Y.F., Khan L."],"isbn":["978-1-72810-858-2"],"note":["cited By 1 \n\nTL;DR \n\nThis paper demonstrates an analytical workflow that integrates multiple analytical tools and techniques for image recognition wrapped in the model management framework and introduces the notion of Model Quality Index (MQI) to track model performance."],"pages":["6110–6112"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019"],"source":["Scopus"],"title":["Model management and handwritten character recognition: An enterprise solution"]},"creators":{"author":[{"lastName":"Lakshminarayan","firstName":"C."},{"lastName":"Ramakrishnan","firstName":"T."},{"lastName":"Al-Omari","firstName":"A."},{"lastName":"Bouaziz","firstName":"K."},{"lastName":"Ahmad","firstName":"F."},{"lastName":"Raghavan","firstName":"S."},{"lastName":"Agarwal","firstName":"P."}],"editor":[{"lastName":"Baru C.","suffix":"Huan J.","firstName":"Hu X.T., Ak R., Tian Y., Barga R., Zaniolo C., Lee K., Ye Y.F., Khan L."}]},"sentenceCased":true},{"key":"lalandaAutonomicComputing2013","type":"book","fields":{"author":["Lalanda, Philippe","McCann, Julie A.","Diaconescu, Ada"],"date":["2013"],"isbn":["978-1-4471-5006-0 978-1-4471-5007-7"],"location":["London"],"publisher":["Springer London"],"series":["Undergraduate Topics in Computer Science"],"title":["Autonomic Computing"],"url":["http://link.springer.com/10.1007/978-1-4471-5007-7"],"urldate":["2016-09-29"]},"creators":{"author":[{"lastName":"Lalanda","firstName":"Philippe"},{"lastName":"McCann","firstName":"Julie A."},{"lastName":"Diaconescu","firstName":"Ada"}]}},{"key":"lam_shilling_2004","type":"inproceedings","fields":{"langid":["english"],"abstract":["Recommender systems have emerged in the past several years as an effective way to help people cope with the problem of information overload. One application in which they have become particularly common is in e-commerce, where recommendation of items can often help a customer find what she is interested in and, therefore can help drive sales. Unscrupulous producers in the never-ending quest for market penetration may find it profitable to shill recommender systems by lying to the systems in order to have their products recommended more often than those of their competitors. This paper explores four open questions that may affect the effectiveness of such shilling attacks: which recommender algorithm is being used, whether the application is producing recommendations or predictions, how detectable the attacks are by the operator of the system, and what the properties are of the items being attacked. The questions are explored experimentally on a large data set of movie ratings. Taken together, the results of the paper suggest that new ways must be used to evaluate and detect shilling attacks on recommender systems."],"author":["Lam, Shyong K.","Riedl, John"],"booktitle":["Proc. 13th Conf. World Wide Web - WWW 04"],"date":["2004"],"doi":["10.1145/988672.988726"],"isbn":["978-1-58113-844-3"],"location":["New York, NY, USA"],"note":["TL;DR \n\nFour open questions are explored that may affect the effectiveness of shilling attacks on recommender systems: which recommender algorithm is being used, whether the application is producing recommendations or predictions, how detectable the attacks are by the operator of the system, and what the properties are of the items being attacked."],"pages":["393"],"publisher":["ACM Press"],"title":["Shilling recommender systems for fun and profit"]},"creators":{"author":[{"lastName":"Lam","firstName":"Shyong K."},{"lastName":"Riedl","firstName":"John"}]},"sentenceCased":true},{"key":"Landauer1998","type":"article","fields":{"added-at":["2009-11-19T19:28:27.000+0100"],"author":["Landauer, T.K.","Foltz, P.W.","Laham, D."],"biburl":["https://www.bibsonomy.org/bibtex/2d07817c8e498b282f56f8abc53c156d9/georg.oettl"],"date":["1998"],"interhash":["60c2cae5093c82d65be9f2e516da9b29"],"intrahash":["d07817c8e498b282f56f8abc53c156d9"],"journaltitle":["Discourse Process."],"keywords":["Psycho NLP semantic"],"note":["TL;DR \n\nThe adequacy of LSA's reflection of human knowledge has been established in a variety of ways, for example, its scores overlap those of humans on standard vocabulary and subject matter tests; it mimics human word sorting and category judgments; it simulates word‐word and passage‐word lexical priming data."],"pages":["259–284"],"publisher":["ABLEX PUBLISHING CO"],"timestamp":["2009-11-19T19:28:27.000+0100"],"title":["An introduction to latent semantic analysis"],"volume":["25"]},"creators":{"author":[{"lastName":"Landauer","firstName":"T.K."},{"lastName":"Foltz","firstName":"P.W."},{"lastName":"Laham","firstName":"D."}]},"sentenceCased":true},{"key":"landauer2006latent","type":"book","fields":{"author":["Landauer, Thomas K"],"date":["2006"],"publisher":["Wiley Online Library"],"title":["Latent semantic analysis"]},"creators":{"author":[{"lastName":"Landauer","firstName":"Thomas K"}]},"sentenceCased":true},{"key":"langerEMFProfilesLightweight2012","type":"article","fields":{"langid":["english"],"author":["Langer, Philip","Wieland, Konrad","Wimmer, Manuel","Cabot, Jordi"],"date":["2012"],"doi":["10.5381/jot.2012.11.1.a8"],"issn":["1660-1769"],"journaltitle":["J. Object Technol."],"note":["TL;DR \n\nThis paper advocates for the use of EMF Profiles, an adaptation of the UML Profile concept to DSMLs, and proposes reusable profile definition mechanisms whereby profiles are defined independently of any DSML and, later on, coupled with all DS MLs that can benefit from these profiles."],"number":["1"],"pages":["8:1"],"shorttitle":["EMF Profiles"],"title":["EMF Profiles: A Lightweight Extension Approach for EMF Models."],"volume":["11"]},"creators":{"author":[{"lastName":"Langer","firstName":"Philip"},{"lastName":"Wieland","firstName":"Konrad"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Cabot","firstName":"Jordi"}]}},{"key":"langerPosterioriOperationDetection2013","type":"article","fields":{"langid":["english"],"author":["Langer, Philip","Wimmer, Manuel","Brosch, Petra","Herrmannsdörfer, Markus","Seidl, Martina","Wieland, Konrad","Kappel, Gerti"],"date":["2013-02"],"doi":["10.1016/j.jss.2012.09.037"],"issn":["01641212"],"journaltitle":["J. Syst. Softw."],"number":["2"],"pages":["551–566"],"title":["A posteriori operation detection in evolving software models"],"volume":["86"]},"creators":{"author":[{"lastName":"Langer","firstName":"Philip"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Brosch","firstName":"Petra"},{"lastName":"Herrmannsdörfer","firstName":"Markus"},{"lastName":"Seidl","firstName":"Martina"},{"lastName":"Wieland","firstName":"Konrad"},{"lastName":"Kappel","firstName":"Gerti"}]},"sentenceCased":true},{"key":"Lano2020277","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - ACM/IEEE Int. Conf. Model Driven Eng. Lang. Syst., MODELS-C - Companion Proc."],"affiliation":["Dept. of Informatics, King's College London, London, United Kingdom; National Automative Innovation Centre, University of Warwick, United Kingdom"],"author":["Lano, K.","Fang, S.","Umar, M.A.","Yassipour-Tehrani, S."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3417990.3421386"],"isbn":["978-1-4503-8135-2"],"keywords":["GOAL_Model-Transformation-Development","notion","TECHNIQUE_ILP"],"note":["cited By 3"],"pages":["277–286"],"publisher":["Association for Computing Machinery, Inc"],"series":["Proceedings - 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2020 - Companion Proceedings"],"source":["Scopus"],"title":["Enhancing model transformation synthesis using natural language processing"]},"creators":{"author":[{"lastName":"Lano","firstName":"K."},{"lastName":"Fang","firstName":"S."},{"lastName":"Umar","firstName":"M.A."},{"lastName":"Yassipour-Tehrani","firstName":"S."}]},"sentenceCased":true},{"key":"Lano2021173","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Companion Proc. - Int. Conf. Model-Driven Eng. Lang. Syst., MODELS-C"],"affiliation":["Dept. of Informatics, King's College London, London, United Kingdom; Roehampton University, Dept. of Computer Science, London, United Kingdom"],"author":["Lano, K.","Yassipour-Tehrani, S.","Umar, M.A."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/MODELS-C53483.2021.00030"],"isbn":["978-1-66542-484-4"],"keywords":["GOAL_Model-Requirements","notion","TECHNIQUE_DECISION-TREE"],"note":["cited By 0 \n\nTL;DR \n\nTechniques for automating the derivation of software specifications from requirements statements are described, in order to reduce the effort required in creating MDE specifications, and hence to improve the usability and agility of MDE."],"pages":["173–180"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Companion Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021"],"source":["Scopus"],"title":["Automated requirements formalisation for agile MDE"]},"creators":{"author":[{"lastName":"Lano","firstName":"K."},{"lastName":"Yassipour-Tehrani","firstName":"S."},{"lastName":"Umar","firstName":"M.A."}]},"sentenceCased":true},{"key":"Lano2022","type":"article","fields":{"langid":["english"],"abbrev_source_title":["ACM Trans. Software Eng. Methodol."],"affiliation":["Dept. of Informatics, King's College London, Strand, London, WC2R 2LS, United Kingdom; Dept. of Software Engineering, University of Isfahan, Isfahan, Iran"],"art_number":["18"],"author":["Lano, K.","Kolahdouz-Rahimi, S.","Fang, S."],"coden":["ATSME"],"date":["2022"],"document_type":["Article"],"doi":["10.1145/3471907"],"issn":["1049331X"],"journaltitle":["ACM Trans. Softw. Eng. Methodol."],"keywords":["GOAL_Model-Transformation-Development","notion"],"note":["cited By 0"],"number":["2"],"publisher":["Association for Computing Machinery"],"source":["Scopus"],"title":["Model transformation development using automated requirements analysis, metamodel matching, and transformation by example"],"volume":["31"]},"creators":{"author":[{"lastName":"Lano","firstName":"K."},{"lastName":"Kolahdouz-Rahimi","firstName":"S."},{"lastName":"Fang","firstName":"S."}]},"sentenceCased":true},{"key":"Lano2022362","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc Int Conf Software Eng"],"affiliation":["King's College London, Dept. of Informatics, London, United Kingdom"],"author":["Lano, K."],"coden":["PCSED"],"correspondence_address1":["Lano, K.; King's College London, United Kingdom; email: kevin.lano@kcl.ac.uk"],"date":["2022"],"document_type":["Conference Paper"],"doi":["10.1109/ICSE-Companion55297.2022.9793785"],"isbn":["978-1-66549-598-1"],"issn":["02705257"],"note":["cited By 0"],"pages":["362–363"],"publisher":["IEEE Computer Society"],"series":["Proceedings - International Conference on Software Engineering"],"source":["Scopus"],"title":["Program translation using model-driven engineering"]},"creators":{"author":[{"lastName":"Lano","firstName":"K."}]},"sentenceCased":true},{"key":"lanoConstraintbasedSpecificationModel2013","type":"article","fields":{"author":["Lano, K.","Kolahdouz-Rahimi, S."],"date":["2013"],"doi":["10.1016/j.jss.2012.09.006"],"journaltitle":["J. Syst. Softw."],"number":["2"],"pages":["412–436"],"title":["Constraint-based specification of model transformations"],"volume":["86"]},"creators":{"author":[{"lastName":"Lano","firstName":"K."},{"lastName":"Kolahdouz-Rahimi","firstName":"S."}]},"sentenceCased":true},{"key":"LanoX23","type":"article","fields":{"langid":["english"],"author":["Lano, Kevin","Xue, Qiaomu"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2023"],"doi":["10.1007/S42979-022-01573-4"],"journaltitle":["SN Comput, Sci,"],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["2"],"pages":["170"],"timestamp":["Sat, 11 Mar 2023 00:13:04 +0100"],"title":["Code generation by example using symbolic machine learning"],"volume":["4"]},"creators":{"author":[{"lastName":"Lano","firstName":"Kevin"},{"lastName":"Xue","firstName":"Qiaomu"}]},"sentenceCased":true},{"key":"lanzaPolymetricViewsLightweight2003","type":"article","fields":{"author":["Lanza, M.","Ducasse, S."],"date":["2003"],"doi":["10.1109/TSE.2003.1232284"],"journaltitle":["IEEE Trans. Softw. Eng."],"note":["TL;DR \n\nThe concept of a polymetric view is presented, a lightweight software visualization technique enriched with software metrics information that helps to understand the structure and detect problems of a software system in the initial phases of a reverse engineering process."],"number":["9"],"pages":["782–795"],"title":["Polymetric views - A lightweight visual approach to reverse engineering"],"volume":["29"]},"creators":{"author":[{"lastName":"Lanza","firstName":"M."},{"lastName":"Ducasse","firstName":"S."}]},"sentenceCased":true},{"key":"laraAbstractingModellingLanguages2012","type":"article","fields":{"author":["Lara, Juan","Guerra, Esther","Sánchez-Cuadrado, Jesús"],"date":["2012"],"doi":["10.1007/978-3-642-31095-9_9"],"journaltitle":["Adv. Inf. Syst. Eng."],"note":["TL;DR \n\nA catalogue of reusable abstractions that are defined once and can be reused over families of modelling languages sharing certain requirements is presented, together with an implementation in the MetaDepth multi-level meta-modelling tool."],"pages":["127–143"],"title":["Abstracting Modelling Languages: A Reutilization Approach"],"volume":["7328"]},"creators":{"author":[{"lastName":"Lara","firstName":"Juan"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Sánchez-Cuadrado","firstName":"Jesús"}]}},{"key":"laraAutomatedReuseModel2019","type":"article","fields":{"langid":["english"],"author":["Lara, Juan De","Guerra, Esther","Ruscio, Davide Di","Rocco, Juri Di","Cuadrado, Jesus Sanchez","Iovino, Ludovico","Pierantonio, Alfonso"],"date":["2019"],"entrysubtype":["magazine"],"ids":["delaraAutomatedReuseModel2019,delaraAutomatedReuseModel2019a,laraAutomatedReuseModel2019a"],"journaltitle":["ACM Transactions on Software Engineering and Methodology"],"note":["cited By 4 \n\ncited By 4"],"number":["4"],"pages":["21:1–21:62"],"title":["Automated Reuse of Model Transformations through Typing Requirements Models"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071907716&doi=10.1145%2f3340108&partnerID=40&md5=0e7a03a44e78e6bfbd8d83de5326e1f5"],"volume":["28"]},"creators":{"author":[{"lastName":"Lara","firstName":"Juan De"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Cuadrado","firstName":"Jesus Sanchez"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]}},{"key":"laraModeldrivenEngineeringDomainspecific2013","type":"article","fields":{"author":["Lara, Juan","Guerra, Esther","Cuadrado, Jesús Sánchez"],"date":["2013"],"doi":["10.1007/s10270-013-0367-z"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nThis paper applies multi-level meta-modelling for the systematic engineering of DSMM architectures, and provides a flexible approach to define textual concrete syntaxes for DSMM languages, and extends existing model management languages to work in a multi- level setting, thus enabling the practical use ofDSMM in MDE."],"title":["Model-driven engineering with domain-specific meta-modelling languages"]},"creators":{"author":[{"lastName":"Lara","firstName":"Juan"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Cuadrado","firstName":"Jesús Sánchez"}]},"sentenceCased":true},{"key":"laraProceedingsWorkshopExtreme2013","type":"book","fields":{"date":["2013"],"editor":["family=Lara, given=Juan, prefix=de, useprefix=false","Ruscio, Davide Di","Pierantonio, Alfonso"],"ids":["laraProceedingsWorkshopExtreme2013a"],"publisher":["CEUR-WS.org"],"series":["CEUR Workshop Proceedings"],"title":["Proceedings of the Workshop on Extreme Modeling co-located with ACM/IEEE 16th International Conference on Model Driven Engineering Languages & Systems (MoDELS 2013), Miami, Florida, USA, September 29, 2013"],"url":["http://ceur-ws.org/Vol-1089"],"volume":["1089"]},"creators":{"editor":[{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":false},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"laraTypesTypeRequirements2011","type":"article","fields":{"author":["Lara, Juan","Guerra, Esther"],"date":["2011"],"doi":["10.1007/s10270-011-0221-0"],"journaltitle":["Softw. Syst. Model."],"keywords":["software engineering"],"number":["3"],"pages":["453–474"],"title":["From types to type requirements: Genericity for model-driven engineering"],"volume":["12"]},"creators":{"author":[{"lastName":"Lara","firstName":"Juan"},{"lastName":"Guerra","firstName":"Esther"}]},"sentenceCased":true},{"key":"larruceaSoftwareEngineeringInternet2017a","type":"article","fields":{"langid":["english"],"author":["Larrucea, Xabier","Combelles, Annie","Favaro, John","Taneja, Kunal"],"date":["2017-01"],"doi":["10.1109/MS.2017.28"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"number":["1"],"pages":["24–28"],"title":["Software Engineering for the Internet of Things"],"volume":["34"]},"creators":{"author":[{"lastName":"Larrucea","firstName":"Xabier"},{"lastName":"Combelles","firstName":"Annie"},{"lastName":"Favaro","firstName":"John"},{"lastName":"Taneja","firstName":"Kunal"}]}},{"key":"LatexSource","type":"online","fields":{"organization":["Latex source"],"title":["Latex source"],"type":["Latex source"],"url":["https://github.com/MDEGroup/ESEM2020"]},"creators":{},"sentenceCased":true},{"key":"LatexSourcePaper","type":"online","fields":{"title":["Latex source of the paper"],"url":["https://www.overleaf.com/project/5e5fdaa1a7e16e00013cf31f"],"urldate":["2020-03-10"]},"creators":{},"sentenceCased":true},{"key":"Lawrence981","type":"report","fields":{"author":["Lawrence, Page","Sergey, Brin","Motwani, Rajeev","Winograd, Terry"],"date":["1998"],"institution":["Stanford University"],"note":["TL;DR \n\nThis paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them, and shows how to efficiently compute PageRank for large numbers of pages."],"title":["The PageRank citation ranking: Bringing order to the web"],"type":["Technical report"]},"creators":{"author":[{"lastName":"Lawrence","firstName":"Page"},{"lastName":"Sergey","firstName":"Brin"},{"lastName":"Motwani","firstName":"Rajeev"},{"lastName":"Winograd","firstName":"Terry"}]},"sentenceCased":true},{"key":"lebensRiseCitizenDeveloper2021","type":"article","fields":{"langid":["english"],"abstract":["A worldwide shortage of developers has made low- and no-code platforms important and necessary. This paper investigates the use of these platforms in organizations, along with the role of workforce automation tools. A survey was conducted to find out how prevalent low- and no-code platforms and workforce automation tools are within companies. These platforms are used by citizen developers, employees who are working outside of the Information Technology (IT) department and are not professional programmers. With low- and no-code platforms citizen developers can create the applications that are needed by their work units or even their entire organizations. These platforms are seen as key to the demands of digital transformation. The results of this study are that companies both large and small are making use of low- and no-code platforms, as well as workforce automation tools. In addition, the majority of organizations have employees outside of the IT department who are creating technology solutions. The broad implication of this research is that citizen developers using low- and no-code platforms to create technology solutions may be the solution to the current shortage of developers. By using low- and no-code platforms, the citizen developer can create the applications that the manager needs for their team. This increases the technology available to the organization while at the same time reducing the pressure on the IT department."],"author":["Lebens, Mary","J Finnegan, Roger","C Sorsen, Steven","Shah, Jinal"],"date":["2021"],"doi":["10.28945/4885"],"issn":["2640-6373"],"journaltitle":["MBR"],"keywords":["LOGSEQ"],"note":["TL;DR \n\nThe broad implication of this research is that citizen developers using low- and no-code platforms to create technology solutions may be the solution to the current shortage of developers."],"pages":["101–111"],"title":["Rise of the Citizen Developer"],"volume":["5"]},"creators":{"author":[{"lastName":"Lebens","firstName":"Mary"},{"lastName":"J Finnegan","firstName":"Roger"},{"lastName":"C Sorsen","firstName":"Steven"},{"lastName":"Shah","firstName":"Jinal"}]}},{"key":"LeClair2018AdaptingNT","type":"article","fields":{"author":["LeClair, Alexander","Eberhart, Zachary","McMillan, Collin"],"date":["2018"],"journaltitle":["CoRR"],"note":["TL;DR \n\nThis paper proposes a set of adaptations to a state-of-the-art neural classification algorithm and performs two evaluations: one with reference data from Debian end-user programs, and one with aSet of C/C++ libraries that the authors hired professional programmers to annotate."],"title":["Adapting neural text classification for improved software categorization"],"volume":["abs/1806.01742"]},"creators":{"author":[{"lastName":"LeClair","firstName":"Alexander"},{"lastName":"Eberhart","firstName":"Zachary"},{"lastName":"McMillan","firstName":"Collin"}]},"sentenceCased":true},{"key":"LectureIoTData","type":"online","fields":{"keywords":["data processing","internet of things"],"title":["Lecture 6: IoT Data Processing"],"url":["https://www2.slideshare.net/PayamBarnaghi/lecture-6-iot-data-processing?qid=8711baae-0a4e-45df-ba7a-9eb987306850&v=&b=&from_search=14"],"urldate":["2021-01-05"]},"creators":{}},{"key":"LecturesSENG371","type":"online","fields":{"title":["Lectures SENG 371 Software Evolution"],"url":["http://www.engr.uvic.ca/~seng371/lectures.html"],"urldate":["2016-09-19"]},"creators":{}},{"key":"lee_adlib_2019","type":"inproceedings","fields":{"abstract":["Mobile advertising has become a popular advertising approach by taking advantage of various information from mobile devices and rich interaction with users. Mobile advertising platforms show advertisements of nearby restaurants to users using the geographic locations of their mobile devices, and also allow users to make reservations easily using their phone numbers. However, at the same time, they may open the doors for advertisements to steal device information or to perform malicious behaviors. When application developers integrate mobile advertising platform SDKs (AdSDKs) to their applications, they are informed of only the permissions required by the AdSDKs, and they may not be aware of the rich functionalities of the SDKs that are available to advertisements. In this paper, we first report that various AdSDKs provide powerful functionalities to advertisements, which are seriously vulnerable to security threats. We present representative malicious behaviors by advertisements using APIs provided by AdSDKs. To mitigate the security vulnerability, we develop a static analyzer, Adlib, which analyzes Android Java libraries that use hybrid features to enable communication with JavaScript code and detects possible flows from the APIs that are accessible from third-party advertisements to device-specific features like geographic locations. Our evaluation shows that Adlib found genuine security vulnerabilities from real-world AdSDKs."],"author":["Lee, Sungho","Ryu, Sukyoung"],"booktitle":["Proc. 28th ACM SIGSOFT Int. Symp. Softw. Test. Anal."],"date":["2019-07"],"doi":["10.1145/3293882.3330562"],"isbn":["978-1-4503-6224-5"],"keywords":["Advertisement Attacks","Advertising Libraries","Android Hybrid Apps","Malicious Advertisements"],"location":["New York, NY, USA"],"note":["TL;DR \n\nA static analyzer, Adlib, is developed, which analyzes Android Java libraries that use hybrid features to enable communication with JavaScript code and detects possible flows from the APIs that are accessible from third-party advertisements to device-specific features like geographic locations."],"pages":["262–272"],"publisher":["Association for Computing Machinery"],"series":["ISSTA 2019"],"shorttitle":["Adlib"],"title":["Adlib: Analyzer for mobile ad platform libraries"]},"creators":{"author":[{"lastName":"Lee","firstName":"Sungho"},{"lastName":"Ryu","firstName":"Sukyoung"}]},"sentenceCased":true},{"key":"Lee202035","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Comput Intell"],"affiliation":["Department of Mechanical Engineering, Dong-A University, Busan, South Korea"],"author":["Lee, K.-H.","Jeong, G.-I.","Lee, S.-H."],"coden":["COMIE"],"correspondence_address1":["Lee, K.-H.; Department of Mechanical Engineering, South Korea; email: leekh@dau.ac.kr"],"date":["2020"],"document_type":["Article"],"doi":["10.1111/coin.12237"],"issn":["08247935"],"journaltitle":["Comput. Intell."],"note":["cited By 3 \n\nTL;DR \n\nFive mathematical test problems, two‐bar design, spring design, and propeller shaft design problems are solved with the suggested method, verifying its usefulness."],"number":["1"],"pages":["35–54"],"publisher":["Blackwell Publishing Inc."],"source":["Scopus"],"title":["An approximate optimization strategy using refined hybrid metamodel"],"volume":["36"]},"creators":{"author":[{"lastName":"Lee","firstName":"K.-H."},{"lastName":"Jeong","firstName":"G.-I."},{"lastName":"Lee","firstName":"S.-H."}]},"sentenceCased":true},{"key":"leeCyberPhysicalSystems2008","type":"inproceedings","fields":{"author":["Lee, Edward A."],"date":["2008-05"],"doi":["10.1109/ISORC.2008.25"],"isbn":["978-0-7695-3132-8"],"note":["TL;DR \n\nIt is concluded that it will not be sufficient to improve design processes, raise the level of abstraction, or verify designs that are built on today's abstractions to realize the full potential of cyber-Physical Systems."],"pages":["363–369"],"publisher":["IEEE"],"shorttitle":["Cyber Physical Systems"],"title":["Cyber Physical Systems: Design Challenges"]},"creators":{"author":[{"lastName":"Lee","firstName":"Edward A."}]}},{"key":"leeInternetThingsIoT2015","type":"article","fields":{"langid":["english"],"author":["Lee, In","Lee, Kyoochun"],"date":["2015-07"],"doi":["10.1016/j.bushor.2015.03.008"],"issn":["00076813"],"journaltitle":["Bus. Horiz."],"number":["4"],"pages":["431–440"],"shorttitle":["The Internet of Things (IoT)"],"title":["The Internet of Things (IoT): Applications, investments, and challenges for enterprises"],"volume":["58"]},"creators":{"author":[{"lastName":"Lee","firstName":"In"},{"lastName":"Lee","firstName":"Kyoochun"}]},"sentenceCased":true},{"key":"leePresentFutureCyberPhysical2015","type":"article","fields":{"langid":["english"],"author":["Lee, Edward"],"date":["2015-02-26"],"doi":["10.3390/s150304837"],"issn":["1424-8220"],"journaltitle":["Sensors"],"number":["3"],"pages":["4837–4869"],"shorttitle":["The Past, Present and Future of Cyber-Physical Systems"],"title":["The Past, Present and Future of Cyber-Physical Systems: A Focus on Models"],"volume":["15"]},"creators":{"author":[{"lastName":"Lee","firstName":"Edward"}]}},{"key":"leeSelfAdaptiveFrameworkBased2019","type":"article","fields":{"langid":["english"],"abstract":["The Internet of Things (IoT) connects a wide range of objects and the types of environments in which IoT can be deployed dynamically change. Therefore, these environments can be modified dynamically at runtime considering the emergence of other requirements. Self-adaptive software alters its behavior to satisfy the requirements in a dynamic environment. In this context, the concept of self-adaptive software is suitable for some dynamic IoT environments (e.g., smart greenhouses, smart homes, and reality applications). In this study, we propose a self-adaptive framework for decision-making in an IoT environment at runtime. The framework comprises a finite-state machine model design and a game theoretic decision-making method for extracting efficient strategies. The framework was implemented as a prototype and experiments were conducted to evaluate its runtime performance. The results demonstrate that the proposed framework can be applied to IoT environments at runtime. In addition, a smart greenhouse-based use case is included to illustrate the usability of the proposed framework."],"author":["Lee, Euijong","Seo, Young-Duk","Kim, Young-Gab"],"date":["2019-07-07"],"doi":["10.3390/s19132996"],"issn":["1424-8220"],"journaltitle":["Sensors"],"note":["TL;DR \n\nThis study proposes a self-adaptive framework for decision-making in an IoT environment at runtime that comprises a finite-state machine model design and a game theoretic decision- making method for extracting efficient strategies."],"number":["13"],"pages":["2996"],"title":["Self-Adaptive Framework Based on MAPE Loop for Internet of Things"],"volume":["19"]},"creators":{"author":[{"lastName":"Lee","firstName":"Euijong"},{"lastName":"Seo","firstName":"Young-Duk"},{"lastName":"Kim","firstName":"Young-Gab"}]}},{"key":"Lejeune2021","type":"article","fields":{"langid":["english"],"abbrev_source_title":["CAD Comput Aided Des"],"affiliation":["Department of Mechanical Engineering, Boston University, Boston, MA 02215, United States"],"art_number":["102948"],"author":["Lejeune, E."],"coden":["CAIDA"],"date":["2021"],"document_type":["Article"],"doi":["10.1016/j.cad.2020.102948"],"issn":["00104485"],"journaltitle":["CAD Comput. Aided Des."],"keywords":["GOAL_Model-Classification","notion"],"note":["cited By 4"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Geometric stability classification: Datasets, metamodels, and adversarial attacks"],"volume":["131"]},"creators":{"author":[{"lastName":"Lejeune","firstName":"E."}]},"sentenceCased":true},{"key":"leopoldTextCategorizationSupport2002","type":"article","fields":{"author":["Leopold, Edda","Kindermann, Jörg"],"date":["2002"],"journaltitle":["Mach. Learn."],"note":["TL;DR \n\nIt is shown that in the case of text classification, term-frequency transformations have a larger impact on the performance of SVM than the kernel itself."],"number":["1-3"],"pages":["423–444"],"publisher":["Springer"],"title":["Text categorization with support vector machines. How to represent texts in input space?"],"volume":["46"]},"creators":{"author":[{"lastName":"Leopold","firstName":"Edda"},{"lastName":"Kindermann","firstName":"Jörg"}]},"sentenceCased":true},{"key":"lepallecSupportQualityMetrics2013","type":"article","fields":{"author":["Le Pallec, Xavier","Dupuy-Chessa, Sophie"],"date":["2013"],"doi":["10.1145/2489820.2489825"],"journaltitle":["Proc. Second Workshop Graph. Model. Lang. Dev. - GMLD 13"],"note":["TL;DR \n\nThis paper presents functions that are necesary to calculate metrics in a metamodeling environment, and introduces how metrics are integrated in a modeling environment named ModX."],"pages":["23–31"],"title":["Support for quality metrics in metamodelling"]},"creators":{"author":[{"lastName":"Le Pallec","firstName":"Xavier"},{"lastName":"Dupuy-Chessa","firstName":"Sophie"}]},"sentenceCased":true},{"key":"Leppänen2020308","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Comput Commun"],"affiliation":["Center for Ubiquitous Computing, University of Oulu, Finland; Department of Informatics, Modeling, Electronics and Systems, University of Calabria, Italy"],"author":["Leppänen, T.","Savaglio, C.","Fortino, G."],"coden":["COCOD"],"correspondence_address1":["Leppänen, T.P.O.Box 4500, FI-90014 University of Oulu, Finland; email: teemu.leppanen@oulu.fi"],"date":["2020"],"document_type":["Article"],"doi":["10.1016/j.comcom.2020.04.011"],"issn":["01403664"],"journaltitle":["Comput. Commun."],"note":["cited By 10"],"pages":["308–319"],"publisher":["Elsevier B.V."],"source":["Scopus"],"title":["Service modeling for opportunistic edge computing systems with feature engineering"],"volume":["157"]},"creators":{"author":[{"lastName":"Leppänen","firstName":"T."},{"lastName":"Savaglio","firstName":"C."},{"lastName":"Fortino","firstName":"G."}]},"sentenceCased":true},{"key":"lethbridgeLowCodeOftenHighCode2021","type":"incollection","fields":{"langid":["english"],"abstract":["The concept of low-code (and no-code) platforms has been around for decades, even before the term was used. The idea is that applications on these platforms can be built by people with less technical expertise than a professional programmer, yet can leverage powerful technology such as, for example, for databases, financial analysis, web development and machine learning. However, in practice, software written on such platforms often accumulates large volumes of complex code, which can be worse to maintain than in traditional languages because the low-code platforms tend not to properly support good engineering practices such as version control, separation of concerns, automated testing and literate programming. In this paper we discuss experiences with several low-code platforms and provide suggestions for directions forward towards an era where the benefits of low-code can be obtained without accumulation of technical debt. Our recommendations focus on ensuring low-code platforms enable scaling, understandability, documentability, testability, vendor-independence, and the overall user experience for developers those end-users who do some development."],"author":["Lethbridge, Timothy C."],"booktitle":["Leveraging Applications of Formal Methods, Verification and Validation"],"date":["2021"],"doi":["10.1007/978-3-030-89159-6_14"],"editor":["Margaria, Tiziana","Steffen, Bernhard"],"isbn":["978-3-030-89158-9 978-3-030-89159-6"],"keywords":["LOGSEQ"],"location":["Cham"],"pages":["202–212"],"publisher":["Springer International Publishing"],"title":["Low-Code Is Often High-Code, So We Must Design Low-Code Platforms to Enable Proper Software Engineering"],"volume":["13036"]},"creators":{"author":[{"lastName":"Lethbridge","firstName":"Timothy C."}],"editor":[{"lastName":"Margaria","firstName":"Tiziana"},{"lastName":"Steffen","firstName":"Bernhard"}]}},{"key":"LEV4REC-deployment","type":"misc","fields":{"author":["MDEGroup"],"commit":["8868ea67a8f719ce9f9b8c2470793df57fb3d418"],"date":["2023"],"organization":["GitHub"],"title":["LEV4REC-deployment: A deployment module for the LEV4REC recommendation system"],"url":["https://github.com/MDEGroup/LEV4REC-deployment"],"urldate":["2023-11-06"]},"creators":{"author":[{"literal":"MDEGroup"}]},"sentenceCased":true},{"key":"levenshtein1966bcc","type":"article","fields":{"added-at":["2008-03-15T10:37:17.000+0100"],"author":["family=Levenshtein, given=VI, given-i=VI"],"biburl":["https://www.bibsonomy.org/bibtex/21a29b294552edb63828d57f3495e2eb2/brightbyte"],"date":["1966"],"ids":["Levenshtein_SPD66"],"interhash":["55f7ad93fcb9ae3ed999afaa6e24937d"],"intrahash":["1a29b294552edb63828d57f3495e2eb2"],"journaltitle":["Sov. Phys. Dokl."],"keywords":["edit-distance","lexicography similarity"],"note":["Doklady Akademii Nauk SSSR, V163 No4 845-848 1965 \n\nDoklady Akademii Nauk SSSR, V163 No4 845-848 1965 \n\nDoklady Akademii Nauk SSSR, V163 No4 845-848 1965 \n\nDoklady Akademii Nauk SSSR, V163 No4 845-848 1965 \n\nDoklady Akademii Nauk SSSR, V163 No4 845-848 1965"],"pages":["707"],"timestamp":["2009-01-23T09:58:50.000+0100"],"title":["Binary codes capable of correcting deletions, insertions and reversals"],"volume":["10"]},"creators":{"author":[{"lastName":"Levenshtein","firstName":"VI","initial":"VI"}]},"sentenceCased":true},{"key":"lewisRetrievalAugmentedGenerationKnowledgeIntensive2021","type":"online","fields":{"langid":["english"],"abstract":["Large pre-trained language models have been shown to store factual knowledge in their parameters, and achieve state-of-the-art results when fine-tuned on downstream NLP tasks. However, their ability to access and precisely manipulate knowledge is still limited, and hence on knowledge-intensive tasks, their performance lags behind task-specific architectures. Additionally, providing provenance for their decisions and updating their world knowledge remain open research problems. Pretrained models with a differentiable access mechanism to explicit non-parametric memory have so far been only investigated for extractive downstream tasks. We explore a general-purpose fine-tuning recipe for retrieval-augmented generation (RAG) — models which combine pre-trained parametric and non-parametric memory for language generation. We introduce RAG models where the parametric memory is a pre-trained seq2seq model and the non-parametric memory is a dense vector index of Wikipedia, accessed with a pre-trained neural retriever. We compare two RAG formulations, one which conditions on the same retrieved passages across the whole generated sequence, and another which can use different passages per token. We fine-tune and evaluate our models on a wide range of knowledgeintensive NLP tasks and set the state of the art on three open domain QA tasks, outperforming parametric seq2seq models and task-specific retrieve-and-extract architectures. For language generation tasks, we find that RAG models generate more specific, diverse and factual language than a state-of-the-art parametric-only seq2seq baseline."],"author":["Lewis, Patrick","Perez, Ethan","Piktus, Aleksandra","Petroni, Fabio","Karpukhin, Vladimir","Goyal, Naman","Küttler, Heinrich","Lewis, Mike","Yih, Wen-tau","Rocktäschel, Tim","Riedel, Sebastian","Kiela, Douwe"],"date":["2021-04-12"],"eprint":["2005.11401"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Computation and Language","Computer Science - Machine Learning","LOGSEQ"],"note":["Comment: Accepted at NeurIPS 2020 \n\nTL;DR \n\nA general-purpose fine-tuning recipe for retrieval-augmented generation (RAG) – models which combine pre-trained parametric and non-parametric memory for language generation, and finds that RAG models generate more specific, diverse and factual language than a state-of-the-art parametric-only seq2seq baseline."],"pubstate":["preprint"],"title":["Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks"],"url":["http://arxiv.org/abs/2005.11401"],"urldate":["2024-01-18"]},"creators":{"author":[{"lastName":"Lewis","firstName":"Patrick"},{"lastName":"Perez","firstName":"Ethan"},{"lastName":"Piktus","firstName":"Aleksandra"},{"lastName":"Petroni","firstName":"Fabio"},{"lastName":"Karpukhin","firstName":"Vladimir"},{"lastName":"Goyal","firstName":"Naman"},{"lastName":"Küttler","firstName":"Heinrich"},{"lastName":"Lewis","firstName":"Mike"},{"lastName":"Yih","firstName":"Wen-tau"},{"lastName":"Rocktäschel","firstName":"Tim"},{"lastName":"Riedel","firstName":"Sebastian"},{"lastName":"Kiela","firstName":"Douwe"}]}},{"key":"lewisWhatItTrust2022","type":"article","fields":{"abstract":["The trustworthiness (or otherwise) of AI has been much in discussion of late, not least because of the recent publication of the EU Guidelines for Trustworthy AI. Discussions range from how we might make people trust AI to AI being not possible to trust, with many points inbetween. In this article, we question whether or not these discussions somewhat miss the point, which is that people are going ahead and basically doing their own thing anyway, and that we should probably help them. Acknowledging that trust is a heuristic that is widely used by humans in a range of situations, we lean on the literature concerning how humans make trust decisions, to arrive at a general model of how people might consider trust in AI (and other artefacts) for specific purposes in a human world. We then use a series of thought experiments and observations of trust and trustworthiness, to illustrate the use of the model in taking a functionalist perspective on trust decisions, including with machines. Our hope is that this forms a useful basis upon which to develop intelligent systems in a way that considers how and when people may trust them, and in doing so empowers people to make better trust decisions about AI."],"author":["Lewis, Peter R.","Marsh, Stephen"],"date":["2022-03-01"],"doi":["10.1016/j.cogsys.2021.11.001"],"issn":["1389-0417"],"journaltitle":["Cognitive Systems Research"],"keywords":["Artificial intelligence","Trust","Trustworthiness"],"pages":["33–49"],"shorttitle":["What is it like to trust a rock?"],"title":["What is it like to trust a rock? A functionalist perspective on trust and trustworthiness in artificial intelligence"],"volume":["72"]},"creators":{"author":[{"lastName":"Lewis","firstName":"Peter R."},{"lastName":"Marsh","firstName":"Stephen"}]},"sentenceCased":true},{"key":"li_fairgan_2022","type":"inproceedings","fields":{"abstract":["Ranking algorithms in recommender systems influence people to make decisions. Conventional ranking algorithms based on implicit feedback data aim to maximize the utility to users by capturing users’ preferences over items. However, these utility-focused algorithms tend to cause fairness issues that require careful consideration in online platforms. Existing fairness-focused studies does not explicitly consider the problem of lacking negative feedback in implicit feedback data, while previous utility-focused methods ignore the importance of fairness in recommendations. To fill this gap, we propose a Generative Adversarial Networks (GANs) based learning algorithm FairGAN mapping the exposure fairness issue to the problem of negative preferences in implicit feedback data. FairGAN does not explicitly treat unobserved interactions as negative, but instead, adopts a novel fairness-aware learning strategy to dynamically generate fairness signals. This optimizes the search direction to make FairGAN capable of searching the space of the optimal ranking that can fairly allocate exposure to individual items while preserving users’ utilities as high as possible."],"author":["Li, Jie","Ren, Yongli","Deng, Ke"],"booktitle":["Proc. ACM Web Conf. 2022"],"date":["2022-04"],"doi":["10.1145/3485447.3511958"],"isbn":["978-1-4503-9096-5"],"keywords":["Exposure","Fairness","GANs","Ranking","Recommendation"],"location":["New York, NY, USA"],"pages":["297–307"],"publisher":["Association for Computing Machinery"],"series":["WWW '22"],"shorttitle":["FairGAN"],"title":["FairGAN: GANs-based Fairness-aware Learning for Recommendations with Implicit Feedback"]},"creators":{"author":[{"lastName":"Li","firstName":"Jie"},{"lastName":"Ren","firstName":"Yongli"},{"lastName":"Deng","firstName":"Ke"}]}},{"key":"li_fairsr_2022","type":"article","fields":{"abstract":["Sequential recommendation (SR) learns from the temporal dynamics of user-item interactions to predict the next ones. Fairness-aware recommendation mitigates a variety of algorithmic biases in the learning of user preferences. This article aims at bringing a marriage between SR and algorithmic fairness. We propose a novel fairness-aware sequential recommendation task, in which a new metric, interaction fairness, is defined to estimate how recommended items are fairly interacted by users with different protected attribute groups. We propose a multi-task learning-based deep end-to-end model, FairSR, which consists of two parts. One is to learn and distill personalized sequential features from the given user and her item sequence for SR. The other is fairness-aware preference graph embedding (FPGE). The aim of FPGE is two-fold: incorporating the knowledge of users’ and items’ attributes and their correlation into entity representations, and alleviating the unfair distributions of user attributes on items. Extensive experiments conducted on three datasets show FairSR can outperform state-of-the-art SR models in recommendation performance. In addition, the recommended items by FairSR also exhibit promising interaction fairness."],"author":["Li, Cheng-Te","Hsu, Cheng","Zhang, Yang"],"date":["2022-02"],"doi":["10.1145/3495163"],"issn":["2157-6904"],"journaltitle":["ACM Trans. Intell. Syst. Technol."],"keywords":["Fairness-aware models","knowledge graph embedding","multi-task learning","sequential recommendation"],"note":["TL;DR \n\nA novel fairness-aware sequential recommendation task, in which a new metric, interaction fairness, is defined to estimate how recommended items are fairly interacted by users with different protected attribute groups, is proposed."],"number":["1"],"pages":["16:1–16:21"],"shorttitle":["FairSR"],"title":["FairSR: Fairness-aware Sequential Recommendation through Multi-Task Learning with Preference Graph Embeddings"],"volume":["13"]},"creators":{"author":[{"lastName":"Li","firstName":"Cheng-Te"},{"lastName":"Hsu","firstName":"Cheng"},{"lastName":"Zhang","firstName":"Yang"}]}},{"key":"Li2015122","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Int J Modell Simul"],"affiliation":["School of Naval Architecture & Ocean Engineering, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212003, China; Faculty of Engineering and the Environment, University of Southampton, Southampton, SO17 1BJ, United Kingdom"],"author":["Li, D.","Wilson, P.A.","Jiang, Z."],"coden":["IMSIE"],"correspondence_address1":["Li, D.; School of Naval Architecture & Ocean Engineering, China; email: lidq@just.edu.cn"],"date":["2015"],"document_type":["Article"],"doi":["10.1080/02286203.2015.1111055"],"issn":["02286203"],"journaltitle":["Int. J. Model. Simul."],"note":["cited By 7"],"number":["3-4"],"pages":["122–128"],"publisher":["Taylor and Francis Ltd."],"source":["Scopus"],"title":["An improved support vector regression and its modelling of manoeuvring performance in multidisciplinary ship design optimization"],"volume":["35"]},"creators":{"author":[{"lastName":"Li","firstName":"D."},{"lastName":"Wilson","firstName":"P.A."},{"lastName":"Jiang","firstName":"Z."}]},"sentenceCased":true},{"key":"LI2019157","type":"article","fields":{"abstract":["The packaging model of Android apps requires the entire code to be shipped into a single APK file in order to be installed and executed on a device. This model introduces noises to Android app analyses, e.g., detection of repackaged applications, malware classification, as not only the core developer code but also the other assistant code will be visited. Such assistant code is often contributed by common libraries that are used pervasively by all apps. Despite much effort has been put in our community to investigate Android libraries, the momentum of Android research has not yet produced a complete and reliable set of common libraries for supporting thorough analyses of Android apps. In this work, we hence leverage a dataset of about 1.5 million apps from Google Play to identify potential common libraries, including advertisement libraries, and their abstract representations. With several steps of refinements, we finally collect 1113 libraries supporting common functions and 240 libraries for advertisement. For each library, we also collected its various abstract representations that could be leveraged to find new usages, including obfuscated cases. Based on these datasets, we further empirically revisit three popular Android app analyses, namely (1) repackaged app detection, (2) machine learning-based malware detection, and (3) static code analysis, aiming at measuring the impact of common libraries on their analysing performance. Our experimental results demonstrate that common library can indeed impact the performance of Android app analysis approaches. Indeed, common libraries can introduce both false positive and false negative results to repackaged app detection approaches. The existence of common libraries in Android apps may also impact the performance of machine learning-based classifications as well as that of static code analysers. All in all, the aforementioned results suggest that it is essential to harvest a reliable list of common libraries and also important to pay special attention to them when conducting Android-related investigations."],"author":["Li, Li","Riom, Timothée","Bissyandé, Tegawendé F.","Wang, Haoyu","Klein, Jacques","Yves, Le Traon"],"date":["2019"],"doi":["10.1016/j.jss.2019.04.065"],"issn":["0164-1212"],"journaltitle":["J. Syst. Softw."],"pages":["157–175"],"title":["Revisiting the impact of common libraries for android-related investigations"],"volume":["154"]},"creators":{"author":[{"lastName":"Li","firstName":"Li"},{"lastName":"Riom","firstName":"Timothée"},{"lastName":"Bissyandé","firstName":"Tegawendé F."},{"lastName":"Wang","firstName":"Haoyu"},{"lastName":"Klein","firstName":"Jacques"},{"lastName":"Yves","firstName":"Le Traon"}]},"sentenceCased":true},{"key":"Li201928737","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Multimedia Tools Appl"],"affiliation":["School of Mechanical and Electrical Engineering, Xuchang University, Xuchang, 461000, China; National CAD Centre, Huazhong University of Science and Technology, Wuhan, China"],"author":["Li, Y.","Zhang, Q.","Wu, Y.","Wang, S."],"coden":["MTAPF"],"correspondence_address1":["Li, Y.; School of Mechanical and Electrical Engineering, China; email: liyaohui@hust.edu.cn"],"date":["2019"],"document_type":["Article"],"doi":["10.1007/s11042-018-6563-7"],"issn":["13807501"],"journaltitle":["Multimed. Tools Appl."],"note":["cited By 4 \n\nTL;DR \n\nThis work proposes a sequential Kriging method assisted by trust region strategy (SKM-TRS) to solve unconstrained black-box problems and demonstrates the efficiency and robustness of the SKM- TRS in contrast with Efficient Global Optimization (EGO), Trust Region Implementation in Kriged-based optimization with Expected improvement (TRIKE) and an Adaptive Metamodel based Globaloptimization algorithm (AMGO)."],"number":["20"],"pages":["28737–28756"],"publisher":["Springer New York LLC"],"source":["Scopus"],"title":["A sequential Kriging method assisted by trust region strategy for proxy cache size optimization of the streaming media video data due to fragment popularity distribution"],"volume":["78"]},"creators":{"author":[{"lastName":"Li","firstName":"Y."},{"lastName":"Zhang","firstName":"Q."},{"lastName":"Wu","firstName":"Y."},{"lastName":"Wang","firstName":"S."}]},"sentenceCased":true},{"key":"Li2021172","type":"inproceedings","fields":{"abstract":["Recently researches about receiver structures for orthogonal time-frequency space (OTFS) have been received widespread attention. Previous OTFS receiver algorithms are based on model-driven, which would lead to complex structures. Motivated by recent advances in data-driven receivers, this paper proposes a data-driven OTFS receiver with a deep neural network (DNN). We demonstrate that the proposed data-driven receiver for OTFS can be generalized to different high mobility scenarios. Specifically, this scheme combines the power of deep learning (DL), which is widely used in various fields. With DL, the proposed algorithm can achieve excellent robustness and strong generalization ability for channel parameters, which are ubiquitous challenges in the design of receiver algorithms. Through a good deal of numerical experiments, simulation results show that the proposed data-driven receiver based on DNN for OTFS can achieve superior performance than comparison methods. © 2021 IEEE."],"author":["Li, Q.","Gong, Y.","Meng, F.","Xu, Z."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/IC-NIDC54101.2021.9660432"],"isbn":["978-1-66540-582-9"],"note":["cited By 0 \n\nTL;DR \n\nIt is demonstrated that the proposed data-driven receiver for OTFS can be generalized to different high mobility scenarios and can achieve superior performance than comparison methods."],"pages":["172–176"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings of 2021 7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021"],"source":["Scopus"],"title":["Data-driven receiver for OTFS system with deep learning"]},"creators":{"author":[{"lastName":"Li","firstName":"Q."},{"lastName":"Gong","firstName":"Y."},{"lastName":"Meng","firstName":"F."},{"lastName":"Xu","firstName":"Z."}]},"sentenceCased":true},{"key":"liang2003introduction","type":"book","fields":{"author":["Liang, Y Daniel"],"date":["2003"],"isbn":["978-0-13-376131-3"],"publisher":["Pearson Education India"],"title":["Introduction to java programming"]},"creators":{"author":[{"lastName":"Liang","firstName":"Y Daniel"}]},"sentenceCased":true},{"key":"liangModeldrivenClusterResource2022","type":"article","fields":{"langid":["english"],"abstract":["Since emerging edge applications such as Internet of Things (IoT) analytics and augmented reality have tight latency constraints, hardware AI accelerators have been recently proposed to speed up deep neural network (DNN) inference run by these applications. Resource-constrained edge servers and accelerators tend to be multiplexed across multiple IoT applications, introducing the potential for performance interference between latency-sensitive workloads. In this paper, we design analytic models to capture the performance of DNN inference workloads on shared edge accelerators, such as GPU and edgeTPU, under different multiplexing and concurrency behaviors. After validating our models using extensive experiments, we use them to design various cluster resource management algorithms to intelligently manage multiple applications on edge accelerators while respecting their latency constraints. We implement a prototype of our system in Kubernetes and show that our system can host 2.3X more DNN applications in heterogeneous multi-tenant edge clusters with no latency violations when compared to traditional knapsack hosting algorithms."],"author":["Liang, Qianlin","Hanafy, Walid A.","Ali-Eldin, Ahmed","Shenoy, Prashant"],"date":["2022-01-18"],"eprint":["2201.07312"],"eprintclass":["cs, eess"],"eprinttype":["arxiv"],"journaltitle":["ArXiv220107312 Cs Eess"],"keywords":["Computer Science - Distributed, Parallel, and Cluster Computing","Electrical Engineering and Systems Science - Systems and Control"],"title":["Model-driven Cluster Resource Management for AI Workloads in Edge Clouds"],"url":["http://arxiv.org/abs/2201.07312"],"urldate":["2022-01-25"]},"creators":{"author":[{"lastName":"Liang","firstName":"Qianlin"},{"lastName":"Hanafy","firstName":"Walid A."},{"lastName":"Ali-Eldin","firstName":"Ahmed"},{"lastName":"Shenoy","firstName":"Prashant"}]},"sentenceCased":true},{"key":"Liao20201724","type":"article","fields":{"abstract":["In this letter, an efficient massive multiple-input multiple-output (MIMO) detector is proposed by employing a deep neural network (DNN). Specifically, we first unfold an existing iterative detection algorithm into the DNN structure, such that the detection task can be implemented by deep learning (DL) approach. We then introduce two auxiliary parameters at each layer to better cancel multiuser interference (MUI). The first parameter is to generate the residual error vector while the second one is to adjust the relationship among previous layers. We further design the training procedure to optimize the auxiliary parameters with pre-processed inputs. The so derived MIMO detector falls into the category of model-driven DL. The simulation results show that the proposed MIMO detector can achieve preferable detection performance compared to the existing detectors for massive MIMO systems. © 1997-2012 IEEE."],"art_number":["9075976"],"author":["Liao, J.","Zhao, J.","Gao, F.","Li, G.Y."],"coden":["ICLEF"],"date":["2020"],"document_type":["Article"],"doi":["10.1109/LCOMM.2020.2989672"],"issn":["10897798"],"journaltitle":["IEEE Commun. Lett."],"note":["cited By 16"],"number":["8"],"pages":["1724–1728"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["A model-driven deep learning method for massive MIMO detection"],"volume":["24"]},"creators":{"author":[{"lastName":"Liao","firstName":"J."},{"lastName":"Zhao","firstName":"J."},{"lastName":"Gao","firstName":"F."},{"lastName":"Li","firstName":"G.Y."}]},"sentenceCased":true},{"key":"liaoDataAdapterQuerying2016","type":"article","fields":{"langid":["english"],"abstract":["As the growing of applications with big data in cloud computing become popular, many existing systems expect to expand their service to support the explosive increase of data. We propose a data adapter system to support hybrid database architecture including a relational database (RDB) and NoSQL database. It can support query from application and deal with database transformation at the same time. We provide three modes of query approach in data adapter system: blocking transformation mode (BT mode), blocking dump mode (BD mode), and direct access mode (DA mode). We provide a data synchronization mechanism and describe the design and implementation in detail. This paper focuses on velocity with proposed three modes and partly variety with data stored in RDB, NoSQL database and temporary files. With the proposed data adapter system, we can provide a seamless mechanism to use RDB and NoSQL database at the same time."],"author":["Liao, Ying-Ti","Zhou, Jiazheng","Lu, Chia-Hung","Chen, Shih-Chang","Hsu, Ching-Hsien","Chen, Wenguang","Jiang, Mon-Fong","Chung, Yeh-Ching"],"date":["2016-12"],"doi":["10.1016/j.future.2016.02.002"],"issn":["0167739X"],"journaltitle":["Future Gener. Comput. Syst."],"pages":["111–121"],"title":["Data adapter for querying and transformation between SQL and NoSQL database"],"volume":["65"]},"creators":{"author":[{"lastName":"Liao","firstName":"Ying-Ti"},{"lastName":"Zhou","firstName":"Jiazheng"},{"lastName":"Lu","firstName":"Chia-Hung"},{"lastName":"Chen","firstName":"Shih-Chang"},{"lastName":"Hsu","firstName":"Ching-Hsien"},{"lastName":"Chen","firstName":"Wenguang"},{"lastName":"Jiang","firstName":"Mon-Fong"},{"lastName":"Chung","firstName":"Yeh-Ching"}]},"sentenceCased":true},{"key":"Lim2019219","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["GECCO Companion - Proc. Genet. Evolut. Comput. Conf. Companion"],"affiliation":["Yonsei University, Seoul, South Korea"],"author":["Lim, J.","Lee, J."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1145/3319619.3321901"],"isbn":["978-1-4503-6748-6"],"note":["cited By 0 \n\nTL;DR \n\nAn effective optimization approach, which integrated the probabilistic surrogate model, non-dominated sorting genetic algorithm, and reliability index method, is proposed to multi-objective reliability-based design optimization."],"pages":["219–220"],"publisher":["Association for Computing Machinery, Inc"],"series":["GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion"],"source":["Scopus"],"title":["Reliability-based MOGA design optimization using probabilistic response surface method and Bayesian neural network"]},"creators":{"author":[{"lastName":"Lim","firstName":"J."},{"lastName":"Lee","firstName":"J."}]},"sentenceCased":true},{"key":"liMoreAgentsAll2024","type":"online","fields":{"abstract":["We find that, simply via a sampling-and-voting method, the performance of large language models (LLMs) scales with the number of agents instantiated. Also, this method is orthogonal to existing complicated methods to further enhance LLMs, while the degree of enhancement is correlated to the task difficulty. We conduct comprehensive experiments on a wide range of LLM benchmarks to verify the presence of our finding, and to study the properties that can facilitate its occurrence. Our code is publicly available at: \\url{https://anonymous.4open.science/r/more_agent_is_all_you_need}."],"author":["Li, Junyou","Zhang, Qin","Yu, Yangbin","Fu, Qiang","Ye, Deheng"],"date":["2024-02-03"],"eprint":["2402.05120"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Computation and Language","Computer Science - Machine Learning"],"pubstate":["preprint"],"title":["More Agents Is All You Need"],"url":["http://arxiv.org/abs/2402.05120"],"urldate":["2024-02-09"]},"creators":{"author":[{"lastName":"Li","firstName":"Junyou"},{"lastName":"Zhang","firstName":"Qin"},{"lastName":"Yu","firstName":"Yangbin"},{"lastName":"Fu","firstName":"Qiang"},{"lastName":"Ye","firstName":"Deheng"}]}},{"key":"Lin:1998:IDS:645527.657297","type":"inproceedings","fields":{"acmid":["657297"],"author":["Lin, Dekang"],"booktitle":["Proc. Fifteenth Int. Conf. Mach. Learn."],"date":["1998"],"isbn":["1-55860-556-8"],"location":["San Francisco, CA, USA"],"note":["TL;DR \n\nThis work presents an informationtheoretic definition of similarity that is applicable as long as there is a probabilistic model and demonstrates how this definition can be used to measure the similarity in a number of different domains."],"numpages":["9"],"pages":["296–304"],"publisher":["Morgan Kaufmann Publishers Inc."],"series":["ICML '98"],"title":["An information-theoretic definition of similarity"],"url":["http://dl.acm.org/citation.cfm?id=645527.657297"]},"creators":{"author":[{"lastName":"Lin","firstName":"Dekang"}]},"sentenceCased":true},{"key":"Linares-Vasquez:2014:ACT:2597008.2597155","type":"inproceedings","fields":{"acmid":["2597155"],"author":["Linares-Vásquez, Mario","Bavota, Gabriele","Di Penta, Massimiliano","Oliveto, Rocco","Poshyvanyk, Denys"],"booktitle":["Proc. 22Nd Int. Conf. Program Comprehension"],"date":["2014"],"isbn":["978-1-4503-2879-1"],"keywords":["Android","API changes","Social media","StackOverflow"],"location":["New York, NY, USA"],"nodoi":["10.1145/2597008.2597155"],"note":["TL;DR \n\nIt is suggested that Android developers usually have more questions when the behavior of APIs is modified, and deleting public methods from APIs is a trigger for questions that are more discussed and of major interest for the community, and posted by more experienced developers."],"numpages":["12"],"pages":["83–94"],"publisher":["ACM"],"series":["ICPC 2014"],"title":["How do API changes trigger stack overflow discussions? A study on the android SDK"],"url":["http://doi.acm.org/10.1145/2597008.2597155"]},"creators":{"author":[{"lastName":"Linares-Vásquez","firstName":"Mario"},{"lastName":"Bavota","firstName":"Gabriele"},{"lastName":"Di Penta","firstName":"Massimiliano"},{"lastName":"Oliveto","firstName":"Rocco"},{"lastName":"Poshyvanyk","firstName":"Denys"}]},"sentenceCased":true},{"key":"Linares-Vasquez:2014:UML:2617668.2617703","type":"article","fields":{"acmid":["2617703"],"address":["Hingham, MA, USA"],"author":["Linares-Vásquez, Mario","Mcmillan, Collin","Poshyvanyk, Denys","Grechanik, Mark"],"date":["2014-06"],"issn":["1382-3256"],"issue_date":["June 2014"],"journaltitle":["Empir. Softw Engg"],"keywords":["Closed-source","machine learning","Open-source","Software categorization"],"nodoi":["10.1007/s10664-012-9230-z"],"note":["TL;DR \n\nA new approach is proposed that makes it possible to categorize software projects without any source code using a small number of API calls as attributes, and furthermore a comprehensive empirical evaluation of automatic categorization approaches is carried out."],"number":["3"],"numpages":["37"],"pages":["582–618"],"publisher":["Kluwer Academic Publishers"],"title":["On using machine learning to automatically classify software applications into domain categories"],"url":["http://dx.doi.org/10.1007/s10664-012-9230-z"],"volume":["19"]},"creators":{"author":[{"lastName":"Linares-Vásquez","firstName":"Mario"},{"lastName":"Mcmillan","firstName":"Collin"},{"lastName":"Poshyvanyk","firstName":"Denys"},{"lastName":"Grechanik","firstName":"Mark"}]},"sentenceCased":true},{"key":"linares-vasquezAPIChangeFault2013","type":"inproceedings","fields":{"langid":["english"],"abstract":["During the recent years, the market of mobile software applications (apps) has maintained an impressive upward trajectory. Many small and large software development companies invest considerable resources to target available opportunities. As of today, the markets for such devices feature over 850K+ apps for Android and 900K+ for iOS. Availability, cost, functionality, and usability are just some factors that determine the success or lack of success for a given app. Among the other factors, reliability is an important criteria: users easily get frustrated by repeated failures, crashes, and other bugs; hence, abandoning some apps in favor of others. This paper reports a study analyzing how the fault- and change-proneness of APIs used by 7,097 (free) Android apps relates to applications’ lack of success, estimated from user ratings. Results of this study provide important insights into a crucial issue: making heavy use of fault- and change-prone APIs can negatively impact the success of these apps."],"author":["Linares-Vásquez, Mario","Bavota, Gabriele","Bernal-Cárdenas, Carlos","Di Penta, Massimiliano","Oliveto, Rocco","Poshyvanyk, Denys"],"booktitle":["Proc. 2013 9th Jt. Meet. Found. Softw. Eng. - ESECFSE 2013"],"date":["2013"],"doi":["10.1145/2491411.2491428"],"eventtitle":["The 2013 9th Joint Meeting"],"isbn":["978-1-4503-2237-9"],"location":["Saint Petersburg, Russia"],"note":["TL;DR \n\nA study analyzing how the fault- and change-proneness of APIs used by 7,097 (free) Android apps relates to applications' lack of success, estimated from user ratings."],"pages":["477"],"publisher":["ACM Press"],"shorttitle":["API change and fault proneness"],"title":["API change and fault proneness: A threat to the success of Android apps"]},"creators":{"author":[{"lastName":"Linares-Vásquez","firstName":"Mario"},{"lastName":"Bavota","firstName":"Gabriele"},{"lastName":"Bernal-Cárdenas","firstName":"Carlos"},{"lastName":"Di Penta","firstName":"Massimiliano"},{"lastName":"Oliveto","firstName":"Rocco"},{"lastName":"Poshyvanyk","firstName":"Denys"}]},"sentenceCased":true},{"key":"linares-vasquezAutomaticallyDetectingSimilar2016","type":"inproceedings","fields":{"author":["Linares-Vásquez, Mario","Holtzhauer, Andrew","Poshyvanyk, Denys"],"booktitle":["Program Comprehension ICPC 2016 IEEE 24th Int. Conf. On"],"date":["2016"],"note":["TL;DR \n\nThe results show that using Android-specific semantic anchors are useful for detecting similar Android apps across different categories, and the results suggest that there is significant difference in the accuracy when third-party libraries are excluded."],"pages":["1–10"],"publisher":["IEEE"],"title":["On automatically detecting similar android apps"],"url":["http://ieeexplore.ieee.org/abstract/document/7503721/"],"urldate":["2017-09-25"]},"creators":{"author":[{"lastName":"Linares-Vásquez","firstName":"Mario"},{"lastName":"Holtzhauer","firstName":"Andrew"},{"lastName":"Poshyvanyk","firstName":"Denys"}]},"sentenceCased":true},{"key":"Linden:2003:ARI:642462.642471","type":"article","fields":{"acmid":["642471"],"address":["Piscataway, NJ, USA"],"author":["Linden, Greg","Smith, Brent","York, Jeremy"],"date":["2003-01"],"issn":["1089-7801"],"issue_date":["January 2003"],"journaltitle":["IEEE Internet Comput."],"nodoi":["10.1109/MIC.2003.1167344"],"note":["TL;DR \n\nThis work compares three common approaches to solving the recommendation problem: traditional collaborative filtering, cluster models, and search-based methods, and their algorithm, which is called item-to-item collaborative filtering."],"number":["1"],"numpages":["5"],"pages":["76–80"],"publisher":["IEEE Educational Activities Department"],"title":["Amazon.Com recommendations: Item-to-item collaborative filtering"],"url":["http://dx.doi.org/10.1109/MIC.2003.1167344"],"volume":["7"]},"creators":{"author":[{"lastName":"Linden","firstName":"Greg"},{"lastName":"Smith","firstName":"Brent"},{"lastName":"York","firstName":"Jeremy"}]},"sentenceCased":true},{"key":"linModelingUsersMobile","type":"article","fields":{"langid":["english"],"abstract":["In this paper, we investigate the feasibility of identifying a small set of privacy profiles as a way of helping users manage their mobile app privacy preferences. Our analysis does not limit itself to looking at permissions people feel comfortable granting to an app. Instead it relies on static code analysis to determine the purpose for which an app requests each of its permissions, distinguishing for instance between apps relying on particular permissions to deliver their core functionality and apps requesting these permissions to share information with advertising networks or social networks. Using privacy preferences that reflect people’s comfort with the purpose for which different apps request their permissions, we use clustering techniques to identify privacy profiles. A major contribution of this work is to show that, while people’s mobile app privacy preferences are diverse, it is possible to identify a small number of privacy profiles that collectively do a good job at capturing these diverse preferences."],"author":["Lin, Jialiu","Liu, Bin","Sadeh, Norman","Hong, Jason I"],"pages":["14"],"title":["Modeling Users’ Mobile App Privacy Preferences: Restoring Usability in a Sea of Permission Settings"]},"creators":{"author":[{"lastName":"Lin","firstName":"Jialiu"},{"lastName":"Liu","firstName":"Bin"},{"lastName":"Sadeh","firstName":"Norman"},{"lastName":"Hong","firstName":"Jason I"}]}},{"key":"linSentimentAnalysisSoftware2018","type":"article","fields":{"langid":["english"],"abstract":["Sentiment analysis has been applied to various software engineering (SE) tasks, such as evaluating app reviews or analyzing developers’ emotions in commit messages. Studies indicate that sentiment analysis tools provide unreliable results when used out-of-the-box, since they are not designed to process SE datasets. The silver bullet for a successful application of sentiment analysis tools to SE datasets might be their customization to the specific usage context. We describe our experience in building a software library recommender exploiting developers’ opinions mined from Stack Overflow. To reach our goal, we retrained—on a set of 40k manually labeled sentences/words extracted from Stack Overflow—a state-of-the-art sentiment analysis tool exploiting deep learning. Despite such an effort- and time-consuming training process, the results were negative. We changed our focus and performed a thorough investigation of the accuracy of commonly used tools to identify the sentiment of SE related texts. Meanwhile, we also studied the impact of different datasets on tool performance. Our results should warn the research community about the strong limitations of current sentiment analysis tools."],"author":["Lin, Bin","Zampetti, Fiorella","Bavota, Gabriele","Penta, Massimiliano Di","Lanza, Michele","Oliveto, Rocco"],"date":["2018"],"note":["TL;DR \n\nThis work retrained—on a set of 40k manually labeled sentences/words extracted from Stack Overflow—a state-of-the-art sentiment analysis tool exploiting deep learning, and found the results were negative."],"pages":["11"],"title":["Sentiment Analysis for Software Engineering: How Far Can We Go?"]},"creators":{"author":[{"lastName":"Lin","firstName":"Bin"},{"lastName":"Zampetti","firstName":"Fiorella"},{"lastName":"Bavota","firstName":"Gabriele"},{"lastName":"Penta","firstName":"Massimiliano Di"},{"lastName":"Lanza","firstName":"Michele"},{"lastName":"Oliveto","firstName":"Rocco"}]}},{"key":"linsteadSourcererMiningSearching2009","type":"article","fields":{"langid":["english"],"author":["Linstead, Erik","Bajracharya, Sushil","Ngo, Trung","Rigor, Paul","Lopes, Cristina","Baldi, Pierre"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/journals/datamine/LinsteadBNRLB09"],"date":["2009-04"],"ids":["DBLP:journals/datamine/LinsteadBNRLB09"],"issn":["1384-5810, 1573-756X"],"journaltitle":["Data Min. Knowl. Discov."],"nodoi":["10.1007/s10618-008-0118-x"],"number":["2"],"pages":["300–336"],"shorttitle":["Sourcerer"],"timestamp":["Sat, 20 May 2017 00:25:07 +0200"],"title":["Sourcerer: Mining and searching internet-scale software repositories"],"url":["http://link.springer.com/10.1007/s10618-008-0118-x"],"urldate":["2019-09-04"],"volume":["18"]},"creators":{"author":[{"lastName":"Linstead","firstName":"Erik"},{"lastName":"Bajracharya","firstName":"Sushil"},{"lastName":"Ngo","firstName":"Trung"},{"lastName":"Rigor","firstName":"Paul"},{"lastName":"Lopes","firstName":"Cristina"},{"lastName":"Baldi","firstName":"Pierre"}]},"sentenceCased":true},{"key":"liPreprocessingMethodsPipelines","type":"article","fields":{"abstract":["0"],"author":["Li, Canchen"],"journaltitle":["0"],"keywords":["Computer Science - Databases","Computer Science - Machine Learning","DONE","STARRED","Statistics - Machine Learning"],"note":["Comment: 7 pages, 3 figures, IEEE conference format \n\nComment: 7 pages, 3 figures, IEEE conference format"],"shorttitle":["0"],"title":["Preprocessing Methods and Pipelines of Data Mining"],"url":["0"],"urldate":["2021-03-18"]},"creators":{"author":[{"lastName":"Li","firstName":"Canchen"}]}},{"key":"liSystematicMappingStudy2015","type":"article","fields":{"langid":["english"],"author":["Li, Zengyang","Avgeriou, Paris","Liang, Peng"],"date":["2015-03"],"doi":["10.1016/j.jss.2014.12.027"],"issn":["01641212"],"journaltitle":["Journal of Systems and Software"],"pages":["193–220"],"title":["A systematic mapping study on technical debt and its management"],"volume":["101"]},"creators":{"author":[{"lastName":"Li","firstName":"Zengyang"},{"lastName":"Avgeriou","firstName":"Paris"},{"lastName":"Liang","firstName":"Peng"}]},"sentenceCased":true},{"key":"liu_searching_2018","type":"inproceedings","fields":{"langid":["english"],"abstract":["StackOverflow provides answers for a huge number of software development questions that are frequently encountered by developers. However, searching relevant questions in StackOverflow is not always easy using the keyword based search engine provided by StackOverflow. A software development question can be characterized by multiple attributes, such as, its concern (e.g.,configuration problem, error handling, sample code, etc.), programming language, operating system, and involved middleware, framework, library and software technology. We propose a multi-faceted and interactive approach for searching StackOverflow questions (called MFISSO), which leverages these attributes of the questions. Our approach starts with an initial keyword-based query and extracts a multifaceted categorization from all the candidate questions using natural language processing and data mining. It then allows developers to iteratively refine the search results through an interactive process. We evaluated an implementation of MFISSO in a controlled experiments with 20 computing students, solving ten software development tasks using StackOverflow. The experiment shows that MFISSO can help developers find relevant questions faster and with higher accuracy."],"author":["Liu, Mingwei","Peng, Xin","Jiang, Qingtao","Marcus, Andrian","Yang, Junwen","Zhao, Wenyun"],"booktitle":["Proc. Tenth Asia-Pac. Symp. Internetware - Internetware 18"],"date":["2018"],"doi":["10.1145/3275219.3275227"],"isbn":["978-1-4503-6590-1"],"location":["Beijing, China"],"note":["TL;DR \n\nThis work proposes a multi-faceted and interactive approach for searching StackOverflow questions (called MFISSO), which extracts a multifaceted categorization from all the candidate questions using natural language processing and data mining, and allows developers to iteratively refine the search results through an interactive process."],"pages":["1–10"],"publisher":["ACM Press"],"title":["Searching StackOverflow Questions with Multi-Faceted Categorization"]},"creators":{"author":[{"lastName":"Liu","firstName":"Mingwei"},{"lastName":"Peng","firstName":"Xin"},{"lastName":"Jiang","firstName":"Qingtao"},{"lastName":"Marcus","firstName":"Andrian"},{"lastName":"Yang","firstName":"Junwen"},{"lastName":"Zhao","firstName":"Wenyun"}]}},{"key":"Liu:2006:GDS:1150402.1150522","type":"inproceedings","fields":{"acmid":["1150522"],"author":["Liu, Chao","Chen, Chen","Han, Jiawei","Yu, Philip S."],"booktitle":["Proc. 12th ACM SIGKDD Int. Conf. Knowl. Discov. Data Min."],"date":["2006"],"isbn":["1-59593-339-5"],"keywords":["graph mining","program dependence graph","software plagiarism detection"],"location":["New York, NY, USA"],"nodoi":["10.1145/1150402.1150522"],"note":["TL;DR \n\nA new plagiarism detection tool, called GPLAG, is developed, which detects plagiarism by mining program dependence graphs (PDGs) and is more effective than state-of-the-art tools for plagiarism Detection."],"numpages":["10"],"pages":["872–881"],"publisher":["ACM"],"series":["KDD '06"],"title":["GPLAG: Detection of software plagiarism by program dependence graph analysis"],"url":["http://doi.acm.org/10.1145/1150402.1150522"]},"creators":{"author":[{"lastName":"Liu","firstName":"Chao"},{"lastName":"Chen","firstName":"Chen"},{"lastName":"Han","firstName":"Jiawei"},{"lastName":"Yu","firstName":"Philip S."}]},"sentenceCased":true},{"key":"Liu2015","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Des. Eng. Tech. Conf."],"affiliation":["School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, United States; Dept. of Mechanical Engineering, Indiana Univ.-Purdue Univ. Indpls, Indianapolis, IN 46202, United States; Honda R and D Americas, Raymond, OH 43067, United States"],"author":["Liu, K.","Tovar, A.","Nutwell, E.","Detwiler, D."],"correspondence_address1":["Tovar, A.; Dept. of Mechanical Engineering, United States; email: tovara@iupui.edu"],"date":["2015"],"document_type":["Conference Paper"],"doi":["10.1115/DETC201546534"],"isbn":["978-0-7918-5708-3"],"note":["cited By 7 \n\nTL;DR \n\nThis work introduces a multimaterial density-based topology optimization method suitable for nonlinear structural problems and is demonstrated with the design of multimaterial stiff structures, compliant mechanisms, and a thin-walled S-rail structure for crashworthiness."],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the ASME Design Engineering Technical Conference"],"source":["Scopus"],"title":["Towards nonlinear multimaterial topology optimization using unsupervised machine learning and metamodel-based optimization"],"volume":["2B-2015"]},"creators":{"author":[{"lastName":"Liu","firstName":"K."},{"lastName":"Tovar","firstName":"A."},{"lastName":"Nutwell","firstName":"E."},{"lastName":"Detwiler","firstName":"D."}]},"sentenceCased":true},{"key":"Liu2016","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Des. Eng. Tech. Conf."],"affiliation":["School of Mechanical Engr., Purdue University, West Lafayette, IN, United States; Honda R and D Americas, Inc., Raymond, OH, United States; Dept. of Mechanical Engr., Indiana U - Purdue U Indianapolis, Indianapolis, IN, United States"],"author":["Liu, K.","Detwiler, D.","Tovar, A."],"correspondence_address1":["Tovar, A.; Dept. of Mechanical Engr., United States; email: tovara@iupui.edu"],"date":["2016"],"document_type":["Conference Paper"],"doi":["10.1115/DETC2016-60471"],"isbn":["978-0-7918-5011-4"],"note":["cited By 0"],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the ASME Design Engineering Technical Conference"],"source":["Scopus"],"title":["Machine learning and metamodel-based design optimization of nonlinear multimaterial structures"],"volume":["2B-2016"]},"creators":{"author":[{"lastName":"Liu","firstName":"K."},{"lastName":"Detwiler","firstName":"D."},{"lastName":"Tovar","firstName":"A."}]},"sentenceCased":true},{"key":"Liu2017","type":"article","fields":{"langid":["english"],"abbrev_source_title":["J Mech Des, Trans ASME"],"affiliation":["School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, United States; Honda RandD Americas, Inc., Raymond, OH 43067, United States; Department of Mechanical Engineering, Indiana University-Purdue, University Indianapolis, Indianapolis, IN 46202, United States"],"art_number":["101401"],"author":["Liu, K.","Detwiler, D.","Tovar, A."],"coden":["JMDEE"],"correspondence_address1":["Tovar, A.; Department of Mechanical Engineering, United States; email: tovara@iupui.edu"],"date":["2017"],"document_type":["Article"],"doi":["10.1115/1.4037620"],"issn":["10500472"],"journaltitle":["J. Mech. Des. Trans. ASME"],"note":["cited By 10"],"number":["10"],"publisher":["American Society of Mechanical Engineers (ASME)"],"source":["Scopus"],"title":["Optimal design of nonlinear multimaterial structures for crashworthiness using cluster analysis"],"volume":["139"]},"creators":{"author":[{"lastName":"Liu","firstName":"K."},{"lastName":"Detwiler","firstName":"D."},{"lastName":"Tovar","firstName":"A."}]},"sentenceCased":true},{"key":"Liu2019","type":"inproceedings","fields":{"abstract":["The existing spectrum sensing methods mostly make decisions using model-driven test statistics, such as energy and eigenvalues. A weakness of these model-driven methods is the difficulty in accurately modeling for practical environment. In contrast to the model-driven approach, in this paper, we use a deep neural network to automatically learn features from data itself, and develop a data-driven detection approach. Inspired by the powerful capability of convolutional neural network (CNN) in extracting features of matrix-shaped data, we use the sample covariance matrix as the input of CNN, proposing a novel covariance matrix-aware CNN-based detection scheme, which consists of offline training and online detection. Different from the existing deep learning-based detection methods which replace the whole detection system by an end-to-end neural network, in this work, we use CNN for offline test statistic design and develop a practical threshold-based online detection mechanism. Specially, according to the maximum a posteriori probability (MAP) criterion, we derive the cost function for offline training in the spectrum sensing model, which guarantees the optimality of the designed test statistic. Simulation results have shown that whether the PU signals are independent or correlated, the detection performance of the proposed method is close to the optimal bound of estimator-correlator detector. Particularly, when the PU signals are correlated with a correlation coefficient 0.7, the probability of detection of the proposed method outperforms the conventional maximum eigenvalue detection method by nearly 7.5 times at SNR = -14dB. © 2019 IEEE."],"art_number":["8761360"],"author":["Liu, C.","Liu, X.","Liang, Y.-C."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/ICC.2019.8761360"],"isbn":["978-1-5386-8088-9"],"issn":["15503607"],"keywords":["EXCLUDED"],"note":["cited By 13 \n\nTL;DR \n\nThis paper uses a deep neural network to automatically learn features from data itself, and develops a data-driven detection approach, which outperforms the conventional maximum eigenvalue detection method and derives the cost function for offline training in the spectrum sensing model, which guarantees the optimality of the designed test statistic."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["IEEE International Conference on Communications"],"source":["Scopus"],"title":["Deep CNN for spectrum sensing in cognitive radio"],"volume":["2019-May"]},"creators":{"author":[{"lastName":"Liu","firstName":"C."},{"lastName":"Liu","firstName":"X."},{"lastName":"Liang","firstName":"Y.-C."}]},"sentenceCased":true},{"key":"Liu20223","type":"article","fields":{"abstract":["The application of machine learning and deep learning is widely used in the business of the power grid. However, the business of the power grid is complicated, and the online service of deep learning faces greater performance challenges. In order to solve this problem, this paper proposes an online service EOSP based on go-tensorflow. EOSP service is divided into 3 modules, namely model configuration module, execution engine module and model management module. The model configuration module mainly includes functions such as online model configuration and model configuration information synchronization. The execution engine can execute graphical model calls, and has optimized performance based on the characteristics of golang language coroutines. The model management module is responsible for model registration, update, uninstallation and version management. Experiments show that the EOSP service is highly stable, which greatly reduces the time consumption of online services. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG."],"author":["Liu, P.","Lu, Y.","Wang, G.","Zhou, W."],"date":["2022"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-97774-0_1"],"editor":["Qiu M., Gai K., Qiu H."],"isbn":["9783030977733"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 0"],"pages":["3–13"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Efficient online service based on go-tensorflow in the middle-station scenario of grid service"],"volume":["13202 LNCS"]},"creators":{"author":[{"lastName":"Liu","firstName":"P."},{"lastName":"Lu","firstName":"Y."},{"lastName":"Wang","firstName":"G."},{"lastName":"Zhou","firstName":"W."}],"editor":[{"lastName":"Qiu M.","suffix":"Gai K.","firstName":"Qiu H."}]},"sentenceCased":true},{"key":"liuFollowMyRecommendations","type":"article","fields":{"langid":["english"],"abstract":["Modern smartphone platforms have millions of apps, many of which request permissions to access private data and resources, like user accounts or location. While these smartphone platforms provide varying degrees of control over these permissions, the sheer number of decisions that users are expected to manage has been shown to be unrealistically high. Prior research has shown that users are often unaware of, if not uncomfortable with, many of their permission settings. Prior work also suggests that it is theoretically possible to predict many of the privacy settings a user would want by asking the user a small number of questions. However, this approach has neither been operationalized nor evaluated with actual users before. We report on a field study (n=72) in which we implemented and evaluated a Personalized Privacy Assistant (PPA) with participants using their own Android devices. The results of our study are encouraging. We find that 78.7% of the recommendations made by the PPA were adopted by users. Following initial recommendations on permission settings, participants were motivated to further review and modify their settings with daily “privacy nudges.” Despite showing substantial engagement with these nudges, participants only changed 5.1% of the settings previously adopted based on the PPA’s recommendations. The PPA and its recommendations were perceived as useful and usable. We discuss the implications of our results for mobile permission management and the design of personalized privacy assistant solutions."],"author":["Liu, Bin","Andersen, Mads Schaarup","Schaub, Florian","Almuhimedi, Hazim","Zhang, Shikun","Sadeh, Norman","Acquisti, Alessandro","Agarwal, Yuvraj"],"note":["TL;DR \n\nA field study in which a Personalized Privacy Assistant (PPA) was implemented and evaluated with participants using their own Android devices, and it is found that 78.7% of the recommendations made by the PPA were adopted by users."],"pages":["16"],"title":["Follow My Recommendations: A Personalized Privacy Assistant for Mobile App Permissions"]},"creators":{"author":[{"lastName":"Liu","firstName":"Bin"},{"lastName":"Andersen","firstName":"Mads Schaarup"},{"lastName":"Schaub","firstName":"Florian"},{"lastName":"Almuhimedi","firstName":"Hazim"},{"lastName":"Zhang","firstName":"Shikun"},{"lastName":"Sadeh","firstName":"Norman"},{"lastName":"Acquisti","firstName":"Alessandro"},{"lastName":"Agarwal","firstName":"Yuvraj"}]}},{"key":"liuJointProceedingsMODELS2014","type":"book","fields":{"date":["2014"],"editor":["Liu, Yan","Zschaler, Steffen","Baudry, Benoit","Ghosh, Sudipto","Ruscio, Davide Di","Jackson, Ethan K.","Wimmer, Manuel"],"ids":["liuJointProceedingsMODELS2014a"],"publisher":["CEUR-WS.org"],"series":["CEUR Workshop Proceedings"],"title":["Joint Proceedings of MODELS'13 Invited Talks, Demonstration Session, Poster Session, and ACM Student Research Competition co-located with the 16th International Conference on Model Driven Engineering Languages and Systems (MODELS 2013), Miami, USA, September 29 - October 4, 2013"],"url":["http://ceur-ws.org/Vol-1115"],"volume":["1115"]},"creators":{"editor":[{"lastName":"Liu","firstName":"Yan"},{"lastName":"Zschaler","firstName":"Steffen"},{"lastName":"Baudry","firstName":"Benoit"},{"lastName":"Ghosh","firstName":"Sudipto"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Jackson","firstName":"Ethan K."},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"liuRefiningChatGPTGeneratedCode2023","type":"online","fields":{"abstract":["In this paper, we systematically study the quality of 4,066 ChatGPT-generated code implemented in two popular programming languages, i.e., Java and Python, for 2,033 programming tasks. The goal of this work is three folds. First, we analyze the correctness of ChatGPT on code generation tasks and uncover the factors that influence its effectiveness, including task difficulty, programming language, time that tasks are introduced, and program size. Second, we identify and characterize potential issues with the quality of ChatGPT-generated code. Last, we provide insights into how these issues can be mitigated. Experiments highlight that out of 4,066 programs generated by ChatGPT, 2,757 programs are deemed correct, 1,081 programs provide wrong outputs, and 177 programs contain compilation or runtime errors. Additionally, we further analyze other characteristics of the generated code through static analysis tools, such as code style and maintainability, and find that 1,933 ChatGPT-generated code snippets suffer from maintainability issues. Subsequently, we investigate ChatGPT's self-debugging ability and its interaction with static analysis tools to fix the errors uncovered in the previous step. Experiments suggest that ChatGPT can partially address these challenges, improving code quality by more than 20%, but there are still limitations and opportunities for improvement. Overall, our study provides valuable insights into the current limitations of ChatGPT and offers a roadmap for future research and development efforts to enhance the code generation capabilities of AI models like ChatGPT."],"author":["Liu, Yue","Le-Cong, Thanh","Widyasari, Ratnadira","Tantithamthavorn, Chakkrit","Li, Li","Le, Xuan-Bach D.","Lo, David"],"date":["2023-07-24"],"eprint":["2307.12596"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Software Engineering"],"pubstate":["preprint"],"shorttitle":["Refining ChatGPT-Generated Code"],"title":["Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues"],"url":["http://arxiv.org/abs/2307.12596"],"urldate":["2023-07-28"]},"creators":{"author":[{"lastName":"Liu","firstName":"Yue"},{"lastName":"Le-Cong","firstName":"Thanh"},{"lastName":"Widyasari","firstName":"Ratnadira"},{"lastName":"Tantithamthavorn","firstName":"Chakkrit"},{"lastName":"Li","firstName":"Li"},{"lastName":"Le","firstName":"Xuan-Bach D."},{"lastName":"Lo","firstName":"David"}]}},{"key":"liuSyntaxDomainAware2023","type":"online","fields":{"abstract":["There is growing interest in software migration as the development of software and society. Manually migrating projects between languages is error-prone and expensive. In recent years, researchers have begun to explore automatic program translation using supervised deep learning techniques by learning from large-scale parallel code corpus. However, parallel resources are scarce in the programming language domain, and it is costly to collect bilingual data manually. To address this issue, several unsupervised programming translation systems are proposed. However, these systems still rely on huge monolingual source code to train, which is very expensive. Besides, these models cannot perform well for translating the languages that are not seen during the pre-training procedure. In this paper, we propose SDA-Trans, a syntax and domain-aware model for program translation, which leverages the syntax structure and domain knowledge to enhance the cross-lingual transfer ability. SDA-Trans adopts unsupervised training on a smaller-scale corpus, including Python and Java monolingual programs. The experimental results on function translation tasks between Python, Java, and C++ show that SDA-Trans outperforms many large-scale pre-trained models, especially for unseen language translation."],"author":["Liu, Fang","Li, Jia","Zhang, Li"],"date":["2023-03-09"],"eprint":["2302.03908"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Software Engineering"],"note":["Comment: Accepted by International Conference on Software Engineering (ICSE-2023) \n\nTL;DR \n\nSDA-Trans is proposed, a syntax and domain-aware model for program translation, which leverages the syntax structure and domain knowledge to enhance the cross-lingual transfer ability and outperforms many large-scale pre-trained models, especially for unseen language translation."],"pubstate":["preprint"],"title":["Syntax and Domain Aware Model for Unsupervised Program Translation"],"url":["http://arxiv.org/abs/2302.03908"],"urldate":["2023-04-25"]},"creators":{"author":[{"lastName":"Liu","firstName":"Fang"},{"lastName":"Li","firstName":"Jia"},{"lastName":"Zhang","firstName":"Li"}]}},{"key":"Lo2022","type":"article","fields":{"abstract":["Federated learning has received fast-growing interests from academia and industry to tackle the challenges of data hungriness and privacy in machine learning. A federated learning system can be viewed as a large-scale distributed system with different components and stakeholders as numerous client devices participate in federated learning. Designing a federated learning system requires software system design thinking apart from the machine learning knowledge. Although much effort has been put into federated learning from the machine learning technique aspects, the software architecture design concerns in building federated learning systems have been largely ignored. Therefore, in this paper, we present a collection of architectural patterns to deal with the design challenges of federated learning systems. Architectural patterns present reusable solutions to a commonly occurring problem within a given context during software architecture design. The presented patterns are based on the results of a systematic literature review and include three client management patterns, four model management patterns, three model training patterns, four model aggregation patterns, and one configuration pattern. The patterns are associated to the particular state transitions in a federated learning model lifecycle, serving as a guidance for effective use of the patterns in the design of federated learning systems. © 2022 Elsevier Inc."],"art_number":["111357"],"author":["Lo, S.K.","Lu, Q.","Zhu, L.","Paik, H.-Y.","Xu, X.","Wang, C."],"coden":["JSSOD"],"date":["2022"],"document_type":["Article"],"doi":["10.1016/j.jss.2022.111357"],"issn":["01641212"],"journaltitle":["J. Syst. Softw."],"note":["cited By 0"],"publisher":["Elsevier Inc."],"source":["Scopus"],"title":["Architectural patterns for the design of federated learning systems"],"volume":["191"]},"creators":{"author":[{"lastName":"Lo","firstName":"S.K."},{"lastName":"Lu","firstName":"Q."},{"lastName":"Zhu","firstName":"L."},{"lastName":"Paik","firstName":"H.-Y."},{"lastName":"Xu","firstName":"X."},{"lastName":"Wang","firstName":"C."}]},"sentenceCased":true},{"key":"LondonbasedGyanaRaises","type":"online","fields":{"title":["London-based Gyana raises $3.9M for a no-code approach to data science – TechCrunch"],"url":["https://techcrunch.com/2020/02/27/london-based-gyana-raises-3-9m-for-a-no-code-approach-to-data-science/amp/?guce_referrer=aHR0cHM6Ly90LmNvL0p4U1pmVFJ4dms_YW1wPTE&guce_referrer_sig=AQAAAK7PsQ7LRtmCbJPzeDGcZKBNQWYD7Kx1bOzyc7RPk9m25HkGQKbBfxKc&guccounter=2"],"urldate":["2020-03-02"]},"creators":{},"sentenceCased":true},{"key":"lonettiDesigningTestingSystems2022","type":"article","fields":{"langid":["english"],"abstract":["In the early stages of a system of systems (SoS) conception, several constituent systems could be available that provide similar functionalities. An SoS design methodology should provide adequate means to model variability in order to support the opportunistic selection of the most desirable SoS configuration. We propose the VANTESS approach that (i) supports SoS modeling taking into account the variation points implied by the considered constituent systems; (ii) includes a heuristics to weight benefits and costs of potential architectural choices (called as SoS variants) for the selection of the constituent systems; and finally (iii) also helps test planning for the selected SoS variant by deriving a simulation model on which test objectives and scenarios can be devised. We illustrate an application example of VANTESS to the “educational” SoS and discuss its pros and cons within a focus group."],"author":["Lonetti, Francesca","Oliveira Neves, Vânia","Bertolino, Antonia"],"date":["2022-01-17"],"doi":["10.1002/smr.2427"],"ids":["lonetti_designing_2022"],"issn":["2047-7473, 2047-7481"],"journaltitle":["J Software Evolu Process"],"keywords":["LOGSEQ"],"note":["TL;DR \n\nThe VANTESS approach is proposed that supports SoS modeling taking into account the variation points implied by the considered constituent systems, and includes a heuristics to weight benefits and costs of potential architectural choices for the selection of the constituent systems."],"shorttitle":["Designing and testing systems of systems"],"title":["Designing and testing systems of systems: From variability models to test cases passing through desirability assessment"]},"creators":{"author":[{"lastName":"Lonetti","firstName":"Francesca"},{"lastName":"Oliveira Neves","firstName":"Vânia"},{"lastName":"Bertolino","firstName":"Antonia"}]},"sentenceCased":true},{"key":"lopez-fernandezAssessingQualityMetamodels2014","type":"inproceedings","fields":{"author":["López-Fernández, Jesús J.","Guerra, Esther","family=Lara, given=Juan, prefix=de, useprefix=true"],"booktitle":["11th Workshop Model Driven Eng. Verification Valid. MoDeVVa 2014"],"date":["2014"],"note":["TL;DR \n\nA language and tool are presented to specify and check properties on meta-models and visualise the problematic elements and draw recommendations for both MDE practitioners and meta-model tool builders."],"pages":["3"],"title":["Assessing the Quality of Meta-models"],"url":["http://ceur-ws.org/Vol-1235/MoDeVVa2014-complete.pdf#page=9"],"urldate":["2015-09-15"]},"creators":{"author":[{"lastName":"López-Fernández","firstName":"Jesús J."},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true}]}},{"key":"lopez-fernandezExampledrivenMetamodelDevelopment2015","type":"article","fields":{"langid":["english"],"author":["López-Fernández, Jesús J.","Cuadrado, Jesús Sánchez","Guerra, Esther","family=Lara, given=Juan, prefix=de, useprefix=true"],"date":["2015-10"],"doi":["10.1007/s10270-013-0392-y"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"number":["4"],"pages":["1323–1347"],"title":["Example-driven meta-model development"],"volume":["14"]},"creators":{"author":[{"lastName":"López-Fernández","firstName":"Jesús J."},{"lastName":"Cuadrado","firstName":"Jesús Sánchez"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true}]},"sentenceCased":true},{"key":"López-Quintero20181845","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Soft Comput."],"affiliation":["Universidad de Oviedo, Oviedo, Spain; Departamento de Informática, Universidad de Oviedo, Oviedo, Spain; Escuela Superior de Ingeniería y Tecnología, Universidad Internacional de La Rioja (UNIR), Logroño, Spain"],"author":["López-Quintero, J.F.","Cueva Lovelle, J.M.","González Crespo, R.","García-Díaz, V."],"correspondence_address1":["González Crespo, R.; Escuela Superior de Ingeniería y Tecnología, Spain; email: ruben.gonzalez@unir.net"],"date":["2018"],"document_type":["Article"],"doi":["10.1007/s00500-016-2437-y"],"issn":["14327643"],"journaltitle":["Soft Comput."],"keywords":["notion"],"note":["cited By 12 \n\nTL;DR \n\nThe result is the design of a functional architecture that permits integrating the Web 2.0 application and a semantic analysis algorithm from unstructured information by applying machine learning techniques."],"number":["6"],"pages":["1845–1854"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["A personal knowledge management metamodel based on semantic analysis and social information"],"volume":["22"]},"creators":{"author":[{"lastName":"López-Quintero","firstName":"J.F."},{"lastName":"Cueva Lovelle","firstName":"J.M."},{"lastName":"González Crespo","firstName":"R."},{"lastName":"García-Díaz","firstName":"V."}]},"sentenceCased":true},{"key":"López2022967","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Softw. Syst. Model."],"affiliation":["Facultad de Informática, Universidad de Murcia, Murcia, Spain; UOC - IN3, Castelldefels, Spain"],"author":["López, J.A.H.","Cánovas Izquierdo, J.L.","Cuadrado, J.S."],"correspondence_address1":["López, J.A.H.; Facultad de Informática, Spain; email: joseantonio.hernandez6@um.es"],"date":["2022"],"document_type":["Article"],"doi":["10.1007/s10270-021-00929-3"],"issn":["16191366"],"journaltitle":["Softw. Syst. Model."],"keywords":["EXCLUDED_NO-AI-ML"],"note":["cited By 0 \n\nTL;DR \n\nTo create ModelSet, a labelled dataset of software models intended to enable the application of ML to address software modelling problems, a method designed to facilitate the exploration and labelling of model datasets by interactively grouping similar models using off-the-shelf technologies like a search engine is devised."],"number":["3"],"pages":["967–986"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["ModelSet: A dataset for machine learning in model-driven engineering"],"volume":["21"]},"creators":{"author":[{"lastName":"López","firstName":"J.A.H."},{"lastName":"Cánovas Izquierdo","firstName":"J.L."},{"lastName":"Cuadrado","firstName":"J.S."}]},"sentenceCased":true},{"key":"lopez2022efficient","type":"article","fields":{"langid":["english"],"author":["López, José Antonio Hernández","Cuadrado, Jesús Sánchez"],"date":["2022"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["5"],"pages":["1715–1737"],"title":["An efficient and scalable search engine for models"],"volume":["21"]},"creators":{"author":[{"lastName":"López","firstName":"José Antonio Hernández"},{"lastName":"Cuadrado","firstName":"Jesús Sánchez"}]},"sentenceCased":true},{"key":"LOPEZ2024103009","type":"article","fields":{"langid":["english"],"abstract":["Curated collections of models are essential for the success of Machine Learning (ML) and Data Analytics in Model-Driven Engineering (MDE). However, current datasets are either too small or not properly curated. In this paper, we present ModelSet, a dataset composed of 5,466 Ecore models and 5,120 UML models which have been manually labelled to support ML tasks. We describe the structure of the dataset and explain how to use the associated library to develop ML applications in Python. Finally, we present some applications which can be addressed using ModelSet. Tool Website: https://github.com/modelset"],"author":["López, José Antonio Hernández","Cánovas Izquierdo, Javier Luis","Cuadrado, Jesús Sánchez"],"date":["2024"],"doi":["10.1016/j.scico.2023.103009"],"ids":["Izquierdo_Cuadrado_2024"],"issn":["0167-6423"],"journaltitle":["Sci. Comput. Program."],"keywords":["/unread","⛔ No INSPIRE recid found","Dataset","Machine learning","Model-driven engineering","Software models"],"pages":["103009"],"title":["ModelSet: A labelled dataset of software models for machine learning"],"volume":["231"]},"creators":{"author":[{"lastName":"López","firstName":"José Antonio Hernández"},{"lastName":"Cánovas Izquierdo","firstName":"Javier Luis"},{"lastName":"Cuadrado","firstName":"Jesús Sánchez"}]},"sentenceCased":true},{"key":"LopezC23","type":"article","fields":{"langid":["english"],"author":["López, José Antonio Hernández","Cuadrado, Jesús Sánchez"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2023"],"doi":["10.1109/TSE.2022.3228630"],"ids":["lopez2022generating"],"journaltitle":["IEEE Trans, Softw. Eng,"],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["4"],"pages":["2661–2676"],"timestamp":["Sat, 29 Apr 2023 19:26:32 +0200"],"title":["Generating structurally realistic models with deep autoregressive networks"],"volume":["49"]},"creators":{"author":[{"lastName":"López","firstName":"José Antonio Hernández"},{"lastName":"Cuadrado","firstName":"Jesús Sánchez"}]},"sentenceCased":true},{"key":"lopezInterdatasetCodeDuplication2024","type":"online","fields":{"abstract":["Motivation. Large language models (LLMs) have exhibited remarkable proficiency in diverse software engineering (SE) tasks. Handling such tasks typically involves acquiring foundational coding knowledge on large, general-purpose datasets during a pre-training phase, and subsequently refining on smaller, task-specific datasets as part of a fine-tuning phase. Problem statement. Data leakage is a well-known issue in training of machine learning models. A manifestation of this issue is the intersection of the training and testing splits. While intra-dataset code duplication examines this intersection within a given dataset and has been addressed in prior research, inter-dataset code duplication, which gauges the overlap between different datasets, remains largely unexplored. If this phenomenon exists, it could compromise the integrity of LLM evaluations because of the inclusion of fine-tuning test samples that were already encountered during pre-training, resulting in inflated performance metrics. Contribution. This paper explores the phenomenon of inter-dataset code duplication and its impact on evaluating LLMs across diverse SE tasks. Study design. We conduct an empirical study using the CSN dataset, a widely adopted pre-training dataset, and five fine-tuning datasets used for various SE tasks. We first identify the intersection between the pre-training and fine-tuning datasets using a deduplication process. Then, we fine-tune four models pre-trained on CSN to evaluate their performance on samples encountered during pre-training and those unseen during that phase. Results. Our findings reveal a potential threat to the evaluation of various LLMs across multiple SE tasks, stemming from the inter-dataset code duplication phenomenon. Moreover, we demonstrate that this threat is accentuated by factors like the LLM's size and the chosen fine-tuning technique."],"author":["López, José Antonio Hernández","Chen, Boqi","Sharma, Tushar","Varró, Dániel"],"date":["2024-01-15"],"eprint":["2401.07930"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Software Engineering"],"pubstate":["preprint"],"title":["On Inter-dataset Code Duplication and Data Leakage in Large Language Models"],"url":["http://arxiv.org/abs/2401.07930"],"urldate":["2024-01-20"]},"creators":{"author":[{"lastName":"López","firstName":"José Antonio Hernández"},{"lastName":"Chen","firstName":"Boqi"},{"lastName":"Sharma","firstName":"Tushar"},{"lastName":"Varró","firstName":"Dániel"}]}},{"key":"lopezLowcodeEngineeringInternet2020","type":"article","fields":{"langid":["english"],"abstract":["The availability of shared software models provides opportunities for reusing, adapting and learning from them. Public models are typically stored in a variety of locations, including model repositories, regular source code repositories, web pages, etc. To profit from them developers need effective search mechanisms to locate the models relevant for their tasks. However, to date, there has been little success in creating a generic and efficient search engine specially tailored to the modelling domain. In this paper we present MAR, a search engine for models. MAR is generic in the sense that it can index any type of model if its meta-model is known. MAR uses a query-by-example approach, that is, it uses example models as queries. The search takes the model structure into account using the notion of bag of paths, which encodes the structure of a model using paths between model elements and is a representation amenable for indexing. MAR is built over HBase using a specific design to deal with large repositories. Our benchmarks show that the engine is efficient and has fast response times in most cases. We have also evaluated the precision of the search engine by creating model mutants which simulate user queries. A REST API is available to perform queries and an Eclipse plug-in allows end users to connect to the search engine from model editors. We have currently indexed more than 50.000 models of different kinds, including Ecore meta-models, BPMN diagrams and UML models. MAR is available at http://mar-search.org."],"author":["López, José Antonio Hernández","Cuadrado, Jesús Sánchez"],"date":["2020-08-26"],"doi":["10.1145/3365438.3410947"],"eprint":["2008.11858"],"eprinttype":["arxiv"],"eventtitle":["MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems"],"ids":["lopezMARStructurebasedSearch2020,lopezMARStructurebasedSearch2020a"],"isbn":["978-1-4503-7019-6"],"journaltitle":["Proc. 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst."],"keywords":["IoT","Low-code engineering","Model driven engineering (MDE)","notion"],"location":["Virtual Event Canada"],"pages":["57–67"],"publisher":["ACM"],"shorttitle":["MAR"],"title":["Low-code engineering for internet of things: A state of research"],"volume":["abs/2009.01876"]},"creators":{"author":[{"lastName":"López","firstName":"José Antonio Hernández"},{"lastName":"Cuadrado","firstName":"Jesús Sánchez"}]},"sentenceCased":true},{"key":"lopezMachineLearningMethods2022","type":"article","fields":{"langid":["english"],"abstract":["In the quest to reuse modeling artifacts, academics and industry have proposed several model repositories over the last decade. Different storage and indexing techniques have been conceived to facilitate searching capabilities to help users find reusable artifacts that might fit the situation at hand. In this respect, machine learning (ML) techniques have been proposed to categorize and group large sets of modeling artifacts automatically. This paper reports the results of a comparative study of different ML classification techniques employed to automatically label models stored in model repositories. We have built a framework to systematically compare different ML models (feed-forward neural networks, graph neural networks, k-nearest neighbors, support version machines, etc.) with varying model encodings (TF-IDF, word embeddings, graphs and paths). We apply this framework to two datasets of about 5,000 Ecore and 5,000 UML models. We show that specific ML models and encodings perform better than others depending on the characteristics of the available datasets (e.g., the presence of duplicates) and on the goals to be achieved. © 2022 ACM."],"author":["López, J.A.H.","Rubei, R.","Cuadrado, J.S.","Di Ruscio, D."],"date":["2022"],"doi":["10.1145/3550355.3552461"],"ids":["lopez2022machine,lopezMachineLearningMethods2022a,lopezMachineLearningMethods2022b,lopezMachineLearningMethods2022c"],"isbn":["978-1-4503-9466-6"],"journaltitle":["Proc. - 25th ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS 2022"],"keywords":["/unread","⛔ No INSPIRE recid found","Comparatives studies","Encoding (symbols)","Encodings","Feedforward neural networks","Learning systems","Machine learning","Machine learning methods","Machine learning models","Machine-learning","Model classification","Model repositories","Model-driven Engineering","Nearest neighbor search","Reuse model","Storage technique"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0"],"pages":["165–175"],"publisher":["Association for Computing Machinery, Inc"],"title":["Machine Learning Methods for Model Classification: A Comparative Study"]},"creators":{"author":[{"lastName":"López","firstName":"J.A.H."},{"lastName":"Rubei","firstName":"R."},{"lastName":"Cuadrado","firstName":"J.S."},{"lastName":"Di Ruscio","firstName":"D."}]}},{"key":"lopezWordEmbeddingsModelDriven","type":"article","fields":{"langid":["english"],"abstract":["Model-Driven Engineering practitioners have to deal with the construction of modelling evironments by devising metamodels, grammars, editors, etc. One of the goals of the application of Machine Learning to MDE is to use ML algorithms to assist the MDE expert in these tasks. These algorithms cannot directly receive raw models or meta-models as input, but they typically have to be transformed into a numeric representation, i.e., a vector. In this context, a common approach is to use pre-trained Word Embeddings, which define mapping functions that associate words to semantic vectors. However, current word embeddings are trained with general texts and lack the technical words which typically arise in the modelling domain. To tackle this issue, we have collected a corpus of modelling texts from well-known modelling venues, and we have trained two types of word embedding models. The resulting embeddings (named WordE4MDE) are specialised to address ML tasks in the MDE domain. We have performed an extensive evaluation using the Ecore models of the ModelSet dataset and two state-of-the-art word embeddings (GloVe and Word2Vec) as baselines. We show that WordE4MDE outperforms these two baselines in three meta-modelling tasks, namely meta-model classification, meta-model clustering, and meta-model concept recommendation. WordE4MDE embeddings are available at https://github.com/models-lab/worde4mde and can be loaded using standard Python libraries for their use in ML pipelines."],"author":["Lopez, Jose Antonio Hernandez","Dura, Carlos","Cuadrado, Jesus Sanchez"],"title":["Word Embeddings for Model-Driven Engineering"]},"creators":{"author":[{"lastName":"Lopez","firstName":"Jose Antonio Hernandez"},{"lastName":"Dura","firstName":"Carlos"},{"lastName":"Cuadrado","firstName":"Jesus Sanchez"}]}},{"key":"LopsCB","type":"incollection","fields":{"author":["Lops, Pasquale","family=Gemmis, given=Marco, prefix=de, useprefix=true","Semeraro, Giovanni"],"booktitle":["Recommender systems handbook"],"date":["2011"],"editor":["Ricci, Francesco","Rokach, Lior","Shapira, Bracha","Kantor, Paul B."],"isbn":["978-0-387-85819-7"],"keywords":["dblp"],"note":["TL;DR \n\nThe role of User Generated Content is described as a way for taking into account evolving vocabularies, and the challenge of feeding users with serendipitous recommendations, that is to say surprisingly interesting items that they might not have otherwise discovered."],"pages":["73–105"],"publisher":["Springer"],"title":["Content-based recommender systems: State of the art and trends."],"url":["http://dblp.uni-trier.de/db/reference/rsh/rsh2011.html#LopsGS11"]},"creators":{"author":[{"lastName":"Lops","firstName":"Pasquale"},{"lastName":"Gemmis","firstName":"Marco","prefix":"de","useprefix":true},{"lastName":"Semeraro","firstName":"Giovanni"}],"editor":[{"lastName":"Ricci","firstName":"Francesco"},{"lastName":"Rokach","firstName":"Lior"},{"lastName":"Shapira","firstName":"Bracha"},{"lastName":"Kantor","firstName":"Paul B."}]},"sentenceCased":true},{"key":"lorenzoniMachineLearningModel2021","type":"article","fields":{"abstract":["Data scientists often develop machine learning models to solve a variety of problems in the industry and academy but not without facing several challenges in terms of Model Development. The problems regarding Machine Learning Development involves the fact that such professionals do not realize that they usually perform ad-hoc practices that could be improved by the adoption of activities presented in the Software Engineering Development Lifecycle. Of course, since machine learning systems are different from traditional Software systems, some differences in their respective development processes are to be expected. In this context, this paper is an effort to investigate the challenges and practices that emerge during the development of ML models from the software engineering perspective by focusing on understanding how software developers could benefit from applying or adapting the traditional software engineering process to the Machine Learning workflow."],"author":["Lorenzoni, Giuliano","Alencar, Paulo","Nascimento, Nathalia","Cowan, Donald"],"date":["2021-02-15"],"eprint":["2102.07574"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv210207574 Cs"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Machine Learning","Computer Science - Software Engineering"],"note":["Comment: 9 pages, 2 columns. Under review \n\nTL;DR \n\nThis paper is an effort to investigate the challenges and practices that emerge during the development of ML models from the software engineering perspective by focusing on understanding how software developers could benefit from applying or adapting the traditional software engineering process to the Machine Learning workflow."],"shorttitle":["Machine Learning Model Development from a Software Engineering Perspective"],"title":["Machine Learning Model Development from a Software Engineering Perspective: A Systematic Literature Review"],"url":["http://arxiv.org/abs/2102.07574"],"urldate":["2021-03-25"]},"creators":{"author":[{"lastName":"Lorenzoni","firstName":"Giuliano"},{"lastName":"Alencar","firstName":"Paulo"},{"lastName":"Nascimento","firstName":"Nathalia"},{"lastName":"Cowan","firstName":"Donald"}]}},{"key":"lourencoChoosingRightNoSQL2015","type":"article","fields":{"langid":["english"],"author":["Lourenço, João Ricardo","Cabral, Bruno","Carreiro, Paulo","Vieira, Marco","Bernardino, Jorge"],"date":["2015-12"],"doi":["10.1186/s40537-015-0025-0"],"issn":["2196-1115"],"journaltitle":["Journal of Big Data"],"keywords":["LOGSEQ","TYPHONML"],"number":["1"],"pages":["18"],"shorttitle":["Choosing the right NoSQL database for the job"],"title":["Choosing the right NoSQL database for the job: A quality attribute evaluation"],"volume":["2"]},"creators":{"author":[{"lastName":"Lourenço","firstName":"João Ricardo"},{"lastName":"Cabral","firstName":"Bruno"},{"lastName":"Carreiro","firstName":"Paulo"},{"lastName":"Vieira","firstName":"Marco"},{"lastName":"Bernardino","firstName":"Jorge"}]},"sentenceCased":true},{"key":"lowcode","type":"misc","fields":{"author":["Richardson, C.","Rymer, J. R."],"date":["2016-04"],"note":["Technical report, Forrester Research"],"title":["The forrester wave: Low-code development platforms, Q2 2016"]},"creators":{"author":[{"lastName":"Richardson","firstName":"C."},{"lastName":"Rymer","firstName":"J. R."}]},"sentenceCased":true},{"key":"LowcodeAbstractionLevels","type":"online","fields":{"keywords":["lowcode"],"title":["Low-code and abstraction levels - Stefan Dreverman - Medium"],"url":["https://medium.com/@stefan.dreverman/low-code-and-abstraction-levels-e9412e9e5329"],"urldate":["2020-04-08"]},"creators":{},"sentenceCased":true},{"key":"LowCodeDevelopment","type":"online","fields":{"keywords":["lowcode"],"title":["Low Code Development Platforms: A Complete Guide | QuickBase"],"url":["https://www.quickbase.com/resources/articles/low-code-development-platforms"],"urldate":["2020-04-08"]},"creators":{}},{"key":"LowcodeDevelopmentModeldriven","type":"online","fields":{"title":["Low-code development and model-driven engineering: Two sides of the same coin? | SpringerLink"],"url":["https://link.springer.com/article/10.1007/s10270-021-00970-2"],"urldate":["2023-05-17"]},"creators":{},"sentenceCased":true},{"key":"LowCodeDevelopmentPlatform","type":"online","fields":{"langid":["british"],"abstract":["Low-Code Development Platform Economic (Free) Survey Unlimited free version Free Trial Period OutSystems 60 days 30 days 15 days Visual LANSA Appian Kissflow (14 days) Mendix FileMaker (45 days) Microsoft PowerApps Zoho Creator (15 days) Kony Heroku (verifies accoun..."],"keywords":["lowcode"],"organization":["Google Docs"],"title":["Low-Code Development Platform Economic (Free) Survey"],"url":["https://docs.google.com/document/d/1F1pLpNudMnth3bxYd1RyfjkxxUYeTbi-qa3BTJmat_8/edit?ts=5e3d9277&usp=embed_facebook"],"urldate":["2020-02-11"]},"creators":{}},{"key":"LowcodeNocodeDevelopment","type":"online","fields":{"ids":["LowcodeNocodeDevelopmenta"],"keywords":["lowcode"],"title":["Low-code and no-code development platforms"],"url":["https://www.computerweekly.com/feature/Low-code-and-no-code-development-platforms"],"urldate":["2020-03-29"]},"creators":{},"sentenceCased":true},{"key":"LowcodePlatformsFuture2020","type":"online","fields":{"langid":["american"],"abstract":["The future of low-code platforms is improving which eliminates the progression of the hard side of coding. The trend of low coding is now evolving towards data sciences and analytics."],"date":["2020-07-15T12:53:47+00:00"],"organization":["Big Data Analytics News"],"shorttitle":["Low-code platforms"],"title":["Low-code platforms: The Future of Data Analytics"],"url":["https://bigdataanalyticsnews.com/low-code-platforms-future-of-data-analytics/"],"urldate":["2021-03-18"]},"creators":{},"sentenceCased":true},{"key":"LowCodePlatformsSurvey","type":"online","fields":{"langid":["english"],"abstract":["An online LaTeX editor that's easy to use. No installation, real-time collaboration, version control, hundreds of LaTeX templates, and more."],"keywords":["lowcode"],"title":["Low-Code Platforms Survey_MoDELS Conference_v2"],"url":["https://www.overleaf.com/4361461464kxwpjrzcvszz"],"urldate":["2020-02-11"]},"creators":{}},{"key":"LowcodeWillDigital2020","type":"article","fields":{"langid":["english"],"abstract":["In recent years, recommender systems have gained an increasingly crucial role in software engineering. Such systems allow developers to exploit a plethora of reusable artifacts, including source code and documentation, which can support the development activities. However, recommender systems are complex tools that are difficult to personalize or fine-tune if developers want to improve them for increasing the relevance of the retrievable recommendations."],"date":["2020-10-16"],"ids":["LowcodeWillDigitala"],"journaltitle":["MODELS 20 ACMIEEE 23rd Int. Conf. Model Driven Eng. Lang. Syst. Virtual Event Can. 18-23 Oct. 2020 Companion Proc."],"keywords":["lowcode"],"pages":["68:1–68:9"],"title":["Low-code will save the Digital Transformation"]},"creators":{},"sentenceCased":true},{"key":"loza14recsys","type":"incollection","fields":{"abstract":["In this paper, we discuss the development of a hybrid multi-strategy book recommendation system using Linked Open Data. Our approach builds on training individual base recommenders and using global popularity scores as generic recommenders. The results of the individual recommenders are combined using stacking regression and rank aggregation. We show that this approach delivers very good results in different recommendation settings and also allows for incorporating diversity of recommendations."],"author":["Ristoski, Petar","Loza Mencía, Eneldo","Paulheim, Heiko"],"booktitle":["Semantic web evaluation challenge, proceedings (ESWC 2014)"],"date":["2014-05"],"isbn":["978-3-319-12023-2"],"nodoi":["10.1007/978-3-319-12024-9₁9"],"pages":["150–156"],"publisher":["Springer"],"series":["Communications in computer and information science"],"title":["A hybrid multi-strategy recommender system using linked open data"],"url":["http://2014.eswc-conferences.org/sites/default/files/eswc2014-challenges_rs_submission_12.pdf"],"volume":["475"]},"creators":{"author":[{"lastName":"Ristoski","firstName":"Petar"},{"lastName":"Loza Mencía","firstName":"Eneldo"},{"lastName":"Paulheim","firstName":"Heiko"}]},"sentenceCased":true},{"key":"Lu2007","type":"article","fields":{"abstract":["Published scientific articles are linked together into a graph, the citation graph, through their citations. This paper explores the notion of similarity based on connectivity alone, and proposes several algorithms to quantify it. Our metrics take advantage of the local neighborhoods of the nodes in the citation graph. Two variants of link-based similarity estimation between two nodes are described, one based on the separate local neighborhoods of the nodes, and another based on the joint local neighborhood expanded from both nodes at the same time. The algorithms are implemented and evaluated on a subgraph of the citation graph of computer science in a retrieval context. The results are compared with text-based similarity, and demonstrate the complementarity of link-based and text-based retrieval."],"author":["Lu, Wangzhong","Janssen, J.","Milios, E.","Japkowicz, N.","Zhang, Yongzheng"],"date":["2007-01-01"],"doi":["10.1007/s10115-006-0023-9"],"issn":["0219-3116"],"journaltitle":["Knowl. Inf. Syst."],"number":["1"],"pages":["105–129"],"title":["Node similarity in the citation graph"],"volume":["11"]},"creators":{"author":[{"lastName":"Lu","firstName":"Wangzhong"},{"lastName":"Janssen","firstName":"J."},{"lastName":"Milios","firstName":"E."},{"lastName":"Japkowicz","firstName":"N."},{"lastName":"Zhang","firstName":"Yongzheng"}]},"sentenceCased":true},{"key":"lucasCollabRDLLanguageCoordinate2017","type":"article","fields":{"langid":["english"],"author":["Lucas, Edson M.","Oliveira, Toacy C.","Farias, Kleinner","Alencar, Paulo S.C."],"date":["2017-02"],"doi":["10.1016/j.jss.2017.01.031"],"issn":["01641212"],"journaltitle":["J. Syst. Softw."],"keywords":["collavorative modeling"],"shorttitle":["CollabRDL"],"title":["CollabRDL: A language to coordinate collaborative reuse"]},"creators":{"author":[{"lastName":"Lucas","firstName":"Edson M."},{"lastName":"Oliveira","firstName":"Toacy C."},{"lastName":"Farias","firstName":"Kleinner"},{"lastName":"Alencar","firstName":"Paulo S.C."}]},"sentenceCased":true},{"key":"lucene","type":"article","fields":{"note":["last access 26.04.2019 \n\nlast access 26.04.2019 \n\nlast access 26.04.2019 \n\nlast access 26.04.2019 \n\nlast access 26.04.2019"],"title":["Apache lucene core"],"url":["https://lucene.apache.org/core/"]},"creators":{},"sentenceCased":true},{"key":"LucioADLSSSW16","type":"article","fields":{"langid":["english"],"author":["Lúcio, Levi","Amrani, Moussa","Dingel, Juergen","Lambers, Leen","Salay, Rick","Selim, Gehan M. K.","Syriani, Eugene","Wimmer, Manuel"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2016"],"doi":["10.1007/S10270-014-0429-X"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nA framework for the description of model transformation intents is defined, which includes a description of properties a model transformation has to satisfy to qualify as a suitable realization of an intent."],"number":["3"],"pages":["647–684"],"timestamp":["Fri, 18 Sep 2020 11:19:42 +0200"],"title":["Model transformation intents and their properties"],"volume":["15"]},"creators":{"author":[{"lastName":"Lúcio","firstName":"Levi"},{"lastName":"Amrani","firstName":"Moussa"},{"lastName":"Dingel","firstName":"Juergen"},{"lastName":"Lambers","firstName":"Leen"},{"lastName":"Salay","firstName":"Rick"},{"lastName":"Selim","firstName":"Gehan M. K."},{"lastName":"Syriani","firstName":"Eugene"},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"lucioFTGPMIntegrated2013","type":"incollection","fields":{"langid":["english"],"abstract":["In this paper, we describe our ongoing work on model transformation chains. Model transformation chains refer to the sequences of model transformations in Model Driven Engineering (MDE). The transformations represent and formalise typical model/software engineering activities, and their chaining is the natural composition of such activities. Model transformation chains found in industrial practice vary widely, depending on the specific domain they are used in. By explicitly modelling development activities, these activities can be analysed and the MDE process may be improved. As a step towards such analyses, we propose an integrated framework to describe all the artifacts involved in model transformation chains, as well as the means to execute “enact” those chains. We describe the Formalism Transformation Graph + Process Model (FTG+PM) which is at the heart of our framework in detail."],"author":["Lúcio, Levi","Mustafiz, Sadaf","Denil, Joachim","Vangheluwe, Hans","Jukss, Maris"],"booktitle":["SDL 2013: Model-Driven Dependability Engineering"],"date":["2013"],"editor":["Khendek, Ferhat","Toeroe, Maria","Gherbi, Abdelouahed","Reed, Rick"],"isbn":["978-3-642-38910-8 978-3-642-38911-5"],"keywords":["software engineering"],"note":["TL;DR \n\nAn integrated framework to describe all the artifacts involved in model transformation chains, as well as the means to execute “enact” those chains is proposed and the Formalism Transformation Graph + Process Model (FTG+PM) is described which is at the heart of the framework in detail."],"number":["7916"],"pages":["182–202"],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture Notes in Computer Science"],"shorttitle":["FTG+PM"],"title":["FTG+PM: An Integrated Framework for Investigating Model Transformation Chains"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-38911-5_11"],"urldate":["2015-03-24"]},"creators":{"author":[{"lastName":"Lúcio","firstName":"Levi"},{"lastName":"Mustafiz","firstName":"Sadaf"},{"lastName":"Denil","firstName":"Joachim"},{"lastName":"Vangheluwe","firstName":"Hans"},{"lastName":"Jukss","firstName":"Maris"}],"editor":[{"lastName":"Khendek","firstName":"Ferhat"},{"lastName":"Toeroe","firstName":"Maria"},{"lastName":"Gherbi","firstName":"Abdelouahed"},{"lastName":"Reed","firstName":"Rick"}]}},{"key":"lucioModelTransformationIntents2014","type":"article","fields":{"author":["Lúcio, Levi","Amrani, Moussa","Dingel, Jürgen","Lambers, Leen","Salay, Rick","Selim, Gehan MK","Syriani, Eugene","Wimmer, Manuel"],"date":["2014"],"journaltitle":["Softw. Syst. Model."],"pages":["1–38"],"title":["Model transformation intents and their properties"],"url":["http://link.springer.com/article/10.1007/s10270-014-0429-x"],"urldate":["2015-03-20"]},"creators":{"author":[{"lastName":"Lúcio","firstName":"Levi"},{"lastName":"Amrani","firstName":"Moussa"},{"lastName":"Dingel","firstName":"Jürgen"},{"lastName":"Lambers","firstName":"Leen"},{"lastName":"Salay","firstName":"Rick"},{"lastName":"Selim","firstName":"Gehan MK"},{"lastName":"Syriani","firstName":"Eugene"},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"lucioTechniqueAutomaticValidation2010","type":"article","fields":{"author":["Lúcio, Levi","Barroca, Bruno","Amaral, Vasco"],"date":["2010"],"doi":["10.1007/978-3-642-16145-2_10"],"journaltitle":["Model Driven Eng. Lang. Syst."],"pages":["136–150"],"title":["A Technique for Automatic Validation of Model Transformations"],"volume":["6394"]},"creators":{"author":[{"lastName":"Lúcio","firstName":"Levi"},{"lastName":"Barroca","firstName":"Bruno"},{"lastName":"Amaral","firstName":"Vasco"}]}},{"key":"luckeyHighqualitySpecificationSelfadaptive2013","type":"inproceedings","fields":{"author":["Luckey, Markus","Engels, Gregor"],"booktitle":["Proc. 8th Int. Symp. Softw. Eng. Adapt. Self-Manag. Syst."],"date":["2013"],"pages":["143–152"],"publisher":["IEEE Press"],"title":["High-quality specification of self-adaptive software systems"],"url":["http://dl.acm.org/citation.cfm?id=2487359"],"urldate":["2016-09-21"]},"creators":{"author":[{"lastName":"Luckey","firstName":"Markus"},{"lastName":"Engels","firstName":"Gregor"}]},"sentenceCased":true},{"key":"lucredioMOOGLEMetamodelbasedModel2010","type":"article","fields":{"author":["Lucrédio, Daniel","M. Fortes, Renata P.","Whittle, Jon"],"date":["2010"],"doi":["10.1007/s10270-010-0167-7"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nMoogle is presented, a model search engine that uses metamodeling information to create richer search indexes and to allow more complex queries to be performed and to improve the accuracy of the search."],"number":["2"],"pages":["183–208"],"title":["MOOGLE: A metamodel-based model search engine"],"volume":["11"]},"creators":{"author":[{"lastName":"Lucrédio","firstName":"Daniel"},{"lastName":"M. Fortes","firstName":"Renata P."},{"lastName":"Whittle","firstName":"Jon"}]},"sentenceCased":true},{"key":"LUNG2004227","type":"article","fields":{"abstract":["The artifacts constituting a software system are sometimes unnecessarily coupled with one another or may drift over time. As a result, support of software partitioning, recovery, and restructuring is often necessary. This paper presents studies on applying the numerical taxonomy clustering technique to software applications. The objective is to facilitate those activities just mentioned and to improve design, evaluation and evolution. Numerical taxonomy is mathematically simple and yet it is a useful mechanism for component clustering and software partitioning. The technique can be applied at various levels of abstraction or to different software life-cycle phases. We have applied the technique to: (1) software partitioning at the software architecture design phase; (2) grouping of components based on the source code to recover the software architecture in the reverse engineering process; (3) restructuring of a software to support evolution in the maintenance stage; and (4) improving cohesion and reducing coupling for source code. In this paper, we provide an introduction to the numerical taxonomy, discuss our experiences in applying the approach to various areas, and relate the technique to the context of similar work."],"author":["Lung, Chung-Horng","Zaman, Marzia","Nandi, Amit"],"date":["2004"],"issn":["0164-1212"],"journaltitle":["J. Syst. Softw."],"keywords":["Clustering","Cohesion and coupling","Design recovery","Evolution","Restructuring","Reverse engineering","Software partitioning"],"nodoi":["https://doi.org/10.1016/S0164-1212(03)00234-6"],"note":["Applications of statistics in software engineering \n\nApplications of statistics in software engineering \n\nApplications of statistics in software engineering \n\nApplications of statistics in software engineering \n\nApplications of statistics in software engineering"],"number":["2"],"pages":["227–244"],"title":["Applications of clustering techniques to software partitioning, recovery and restructuring"],"url":["http://www.sciencedirect.com/science/article/pii/S0164121203002346"],"volume":["73"]},"creators":{"author":[{"lastName":"Lung","firstName":"Chung-Horng"},{"lastName":"Zaman","firstName":"Marzia"},{"lastName":"Nandi","firstName":"Amit"}]},"sentenceCased":true},{"key":"Luo2019504","type":"article","fields":{"abstract":["Accurate and automatic analysis of breast MRI plays a vital role in early diagnosis and successful treatment planning for breast cancer. Due to the heterogeneity nature, precise diagnosis of tumors remains a challenging task. In this paper, we propose to identify breast tumor in MRI by Cosine Margin Sigmoid Loss (CMSL) with deep learning (DL) and localize possible cancer lesion by COrrelation Attention Map (COAM) based on the learned features. The CMSL embeds tumor features onto a hyper-sphere and imposes a decision margin through cosine constraints. In this way, the DL model could learn more separable inter-class features and more compact intra-class features in the angular space. Furthermore, we utilize the correlations among feature vectors to generate attention maps that could accurately localize cancer candidates with only image-level labels. We build the largest breast cancer dataset involving 10,290 DCE-MRI scan volumes for developing and evaluating the proposed methods. The model driven by CMSL achieved a classification accuracy of 0.855 and AUC of 0.902 on the testing set, with sensitivity and specificity of 0.857 and 0.852, respectively, outperforming competitive methods overall. In addition, the proposed COAM accomplished more accurate localization of the cancer center compared with other state-of-the-art weakly supervised localization method. © Springer Nature Switzerland AG 2019."],"author":["Luo, L.","Chen, H.","Wang, X.","Dou, Q.","Lin, H.","Zhou, J.","Li, G.","Heng, P.-A."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-32251-9_55"],"editor":["Shen D., Yap P.-T., Peters T.M., Khan A., Staib L.H., Essert C., Zhou S., Liu T."],"isbn":["9783030322502"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 9"],"pages":["504–512"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Deep angular embedding and feature correlation attention for breast MRI cancer analysis"],"volume":["11767 LNCS"]},"creators":{"author":[{"lastName":"Luo","firstName":"L."},{"lastName":"Chen","firstName":"H."},{"lastName":"Wang","firstName":"X."},{"lastName":"Dou","firstName":"Q."},{"lastName":"Lin","firstName":"H."},{"lastName":"Zhou","firstName":"J."},{"lastName":"Li","firstName":"G."},{"lastName":"Heng","firstName":"P.-A."}],"editor":[{"lastName":"Shen D.","suffix":"Yap P.-T.","firstName":"Peters T.M., Khan A., Staib L.H., Essert C., Zhou S., Liu T."}]},"sentenceCased":true},{"key":"luoCharacteristicsChallengesLowCode2021","type":"inproceedings","fields":{"langid":["english"],"author":["Luo, Yajing","Liang, Peng","Wang, Chong","Shahin, Mojtaba","Zhan, Jing"],"booktitle":["Proc. 15th ACM IEEE Int. Symp. Empir. Softw. Eng. Meas. ESEM"],"date":["2021-10-11"],"doi":["10.1145/3475716.3475782"],"eventtitle":["ESEM '21: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement"],"isbn":["978-1-4503-8665-4"],"keywords":["LOGSEQ"],"location":["Bari Italy"],"note":["TL;DR \n\nThe findings suggest that researchers should clearly define the terms when they refer to LCD, and developers should consider whether the characteristics of LCD are appropriate for their projects."],"pages":["1–11"],"publisher":["ACM"],"shorttitle":["Characteristics and Challenges of Low-Code Development"],"title":["Characteristics and Challenges of Low-Code Development: The Practitioners' Perspective"]},"creators":{"author":[{"lastName":"Luo","firstName":"Yajing"},{"lastName":"Liang","firstName":"Peng"},{"lastName":"Wang","firstName":"Chong"},{"lastName":"Shahin","firstName":"Mojtaba"},{"lastName":"Zhan","firstName":"Jing"}]}},{"key":"luongFACOSFindingAPI2021","type":"article","fields":{"langid":["english"],"abstract":["Collecting API examples, usages, and mentions relevant to a specific API method over discussions on venues such as Stack Overflow is not a trivial problem. It requires efforts to correctly recognize whether the discussion refers to the API method that developers/tools are searching for. The content of the thread, which consists of both text paragraphs describing the involvement of the API method in the discussion and the code snippets containing the API invocation, may refer to the given API method. Leveraging this observation, we develop FACOS, a context-specific algorithm to capture the semantic and syntactic information of the paragraphs and code snippets in a discussion. FACOS combines a syntactic word-based score with a score from a predictive model fine-tuned from CodeBERT. FACOS beats the state-of-the-art approach by 13.9% in terms of F1-score."],"author":["Luong, Kien","Hadi, Mohammad","Thung, Ferdian","Fard, Fatemeh","Lo, David"],"date":["2021-11-13"],"eprint":["2111.07238"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv211107238 Cs"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Programming Languages","Computer Science - Software Engineering"],"note":["TL;DR \n\nFACOS is a context-specific algorithm to capture the semantic and syntactic information of the paragraphs and code snippets in a discussion that beats the state-of-the-art approach by 13.9% in terms of F1-score."],"shorttitle":["FACOS"],"title":["FACOS: Finding API Relevant Contents on Stack Overflow with Semantic and Syntactic Analysis"],"url":["http://arxiv.org/abs/2111.07238"],"urldate":["2021-11-21"]},"creators":{"author":[{"lastName":"Luong","firstName":"Kien"},{"lastName":"Hadi","firstName":"Mohammad"},{"lastName":"Thung","firstName":"Ferdian"},{"lastName":"Fard","firstName":"Fatemeh"},{"lastName":"Lo","firstName":"David"}]}},{"key":"luoOnlineAdaptationAutonomous2022","type":"article","fields":{"langid":["english"],"abstract":["Autonomous unmanned systems (AUSs) emerge to replace human operators for achieving better safety, efficiency, and effectiveness in harsh and difficult missions. They usually run in a highly open and dynamic operating environment, in which some unexpected situations may occur, leading to violations of predefined requirements. In order to maintain stable performance, the AUS control software needs to predict in advance whether the requirements will be violated and then make adaptations to maximize requirements satisfaction. We propose Captain, a model-driven and control-based online adaptation approach, for the AUS control software. At the modeling phase, apart from the system behavior model and the operating environment model, we construct a requirements satisfaction model. At runtime, based on the requirements satisfaction model, Captain first predicts whether the requirements will be violated in the upcoming situation; then identifies the unsatisfiable requirements that need to be accommodated; and finally, finds an optimal adaptation for the upcoming situation. We evaluate Captain in both simulated scenarios and the real world. For the former, we use two cases of UAV Delivery and UUV Ocean Surveillance, whose results demonstrate the Captain’s robustness, scalability, and real-time performance. For the latter, we have successfully implemented Captain in the DJI Matrice 100 UAV with real-world workloads."],"author":["Luo, Yixing","Zhou, Yuan","Zhao, Haiyan","Jin, Zhi","Zhang, Tianwei","Liu, Yang","Barthaud, Danny","Yu, Yijun"],"date":["2022-08"],"doi":["10.1007/s10270-022-00981-7"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"note":["TL;DR \n\nThis work proposes Captain, a model-driven and control-based online adaptation approach, for the AUS control software that predicts whether the requirements will be violated in the upcoming situation; identifies the unsatisfiable requirements that need to be accommodated; and finally, finds an optimal adaptation for the forthcoming situation."],"number":["4"],"pages":["1295–1319"],"title":["Online adaptation for autonomous unmanned systems driven by requirements satisfaction model"],"volume":["21"]},"creators":{"author":[{"lastName":"Luo","firstName":"Yixing"},{"lastName":"Zhou","firstName":"Yuan"},{"lastName":"Zhao","firstName":"Haiyan"},{"lastName":"Jin","firstName":"Zhi"},{"lastName":"Zhang","firstName":"Tianwei"},{"lastName":"Liu","firstName":"Yang"},{"lastName":"Barthaud","firstName":"Danny"},{"lastName":"Yu","firstName":"Yijun"}]},"sentenceCased":true},{"key":"luResponsibleAIEra2023","type":"online","fields":{"abstract":["The release of ChatGPT, Bard, and other large language model (LLM)-based chatbots has drawn huge attention on foundations models worldwide. There is a growing trend that foundation models will serve as the fundamental building blocks for most of the future AI systems. However, incorporating foundation models in AI systems raises significant concerns about responsible AI due to their black box nature and rapidly advancing super-intelligence. Additionally, the foundation model's growing capabilities can eventually absorb the other components of AI systems, introducing the moving boundary and interface evolution challenges in architecture design. To address these challenges, this paper proposes a pattern-oriented responsible-AI-by-design reference architecture for designing foundation model-based AI systems. Specially, the paper first presents an architecture evolution of AI systems in the era of foundation models, from \"foundation-model-as-a-connector\" to \"foundation-model-as-a-monolithic architecture\". The paper then identifies the key design decision points and proposes a pattern-oriented reference architecture to provide reusable responsible-AI-by-design architectural solutions to address the new architecture evolution and responsible AI challenges. The patterns can be embedded as product features of foundation model-based AI systems and can enable organisations to capitalise on the potential of foundation models while minimising associated risks."],"author":["Lu, Qinghua","Zhu, Liming","Xu, Xiwei","Xing, Zhenchang","Whittle, Jon"],"date":["2023-04-13"],"eprint":["2304.11090"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Computation and Language","Computer Science - Software Engineering","LOGSEQ"],"note":["TL;DR \n\nThe paper identifies key design decisions and proposes a pattern-oriented reference architecture for designing responsible foundation-model-based systems, which can enable the potential of foundation models while minimising associated risks."],"pubstate":["preprint"],"shorttitle":["Towards Responsible AI in the Era of ChatGPT"],"title":["Towards Responsible AI in the Era of ChatGPT: A Reference Architecture for Designing Foundation Model-based AI Systems"],"url":["http://arxiv.org/abs/2304.11090"],"urldate":["2023-05-18"]},"creators":{"author":[{"lastName":"Lu","firstName":"Qinghua"},{"lastName":"Zhu","firstName":"Liming"},{"lastName":"Xu","firstName":"Xiwei"},{"lastName":"Xing","firstName":"Zhenchang"},{"lastName":"Whittle","firstName":"Jon"}]}},{"key":"Lutz2021583","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Simul. Ser."],"affiliation":["Dept. of Computer Science and Software Engineering, Miami University, 205 Benton Hall, 510 E. High Street, Oxford, OH, United States; Dept. of Computer Science, Lakehead University, FB 1009B, 955 Oliver Rd, Thunder Bay, ON, Canada"],"author":["Lutz, C.B.","Giabbanelli, P.J.","Fisher, A.","Mago, V.K."],"date":["2021"],"document_type":["Conference Paper"],"editor":["Martin C.R., Blas M.J., Psijas A.I."],"issn":["07359276"],"note":["cited By 0"],"number":["2"],"pages":["583–594"],"publisher":["The Society for Modeling and Simulation International"],"series":["Simulation Series"],"source":["Scopus"],"title":["How many costly simulations do we need to create accurate metamodels? A case study on predicting hiv viral load in response to clinically relevant intervention scenarios"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118574816&partnerID=40&md5=9eea6773e6551052e5a35c095cf09935"],"volume":["53"]},"creators":{"author":[{"lastName":"Lutz","firstName":"C.B."},{"lastName":"Giabbanelli","firstName":"P.J."},{"lastName":"Fisher","firstName":"A."},{"lastName":"Mago","firstName":"V.K."}],"editor":[{"lastName":"Martin C.R.","suffix":"Blas M.J.","firstName":"Psijas A.I."}]},"sentenceCased":true},{"key":"lv_codehow:_2015","type":"inproceedings","fields":{"langid":["english"],"abstract":["Over the years of software development, a vast amount of source code has been accumulated. Many code search tools were proposed to help programmers reuse previouslywritten code by performing free-text queries over a large-scale codebase. Our experience shows that the accuracy of these code search tools are often unsatisfactory. One major reason is that existing tools lack of query understanding ability. In this paper, we propose CodeHow, a code search technique that can recognize potential APIs a user query refers to. Having understood the potentially relevant APIs, CodeHow expands the query with the APIs and performs code retrieval by applying the Extended Boolean model, which considers the impact of both text similarity and potential APIs on code search. We deploy the backend of CodeHow as a Microsoft Azure service and implement the frontend as a Visual Studio extension. We evaluate CodeHow on a large-scale codebase consisting of 26K C# projects downloaded from GitHub. The experimental results show that when the top 1 results are inspected, CodeHow achieves a precision score of 0.794 (i.e., 79.4% of the first returned results are relevant code snippets). The results also show that CodeHow outperforms conventional code search tools. Furthermore, we perform a controlled experiment and a survey of Microsoft developers. The results confirm the usefulness and effectiveness of CodeHow in programming practices."],"author":["Lv, Fei","Zhang, Hongyu","Lou, Jian-guang","Wang, Shaowei","Zhang, Dongmei","Zhao, Jianjun"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/conf/kbse/LvZLWZZ15"],"booktitle":["2015 30th IEEEACM Int. Conf. Autom. Softw. Eng. ASE"],"date":["2015-11"],"ids":["DBLP:conf/kbse/LvZLWZZ15"],"isbn":["978-1-5090-0025-8"],"location":["Lincoln, NE, USA"],"nodoi":["10.1109/ASE.2015.42"],"note":["TL;DR \n\nThis paper proposes CodeHow, a code search technique that can recognize potential APIs a user query refers to and performs code retrieval by applying the Extended Boolean model, which considers the impact of both text similarity and potential APIs on code search."],"pages":["260–270"],"publisher":["IEEE"],"shorttitle":["CodeHow"],"timestamp":["Fri, 01 Mar 2019 13:05:18 +0100"],"title":["CodeHow: Effective Code Search Based on API Understanding and Extended Boolean Model (E)"],"url":["http://ieeexplore.ieee.org/document/7372014/"],"urldate":["2019-09-11"]},"creators":{"author":[{"lastName":"Lv","firstName":"Fei"},{"lastName":"Zhang","firstName":"Hongyu"},{"lastName":"Lou","firstName":"Jian-guang"},{"lastName":"Wang","firstName":"Shaowei"},{"lastName":"Zhang","firstName":"Dongmei"},{"lastName":"Zhao","firstName":"Jianjun"}]}},{"key":"Ma20212388","type":"article","fields":{"abstract":["This paper proposes a model-driven deep learning (MDDL)-based channel estimation and feedback scheme for wideband millimeter-wave (mmWave) massive hybrid multiple-input multiple-output (MIMO) systems, where the angle-delay domain channels' sparsity is exploited for reducing the overhead. First, we consider the uplink channel estimation for time-division duplexing systems. To reduce the uplink pilot overhead for estimating high-dimensional channels from a limited number of radio frequency (RF) chains at the base station (BS), we propose to jointly train the phase shift network and the channel estimator as an auto-encoder. Particularly, by exploiting the channels' structured sparsity from an a priori model and learning the integrated trainable parameters from the data samples, the proposed multiple-measurement-vectors learned approximate message passing (MMV-LAMP) network with the devised redundant dictionary can jointly recover multiple subcarriers' channels with significantly enhanced performance. Moreover, we consider the downlink channel estimation and feedback for frequency-division duplexing systems. Similarly, the pilots at the BS and channel estimator at the users can be jointly trained as an encoder and a decoder, respectively. Besides, to further reduce the channel feedback overhead, only the received pilots on part of the subcarriers are fed back to the BS, which can exploit the MMV-LAMP network to reconstruct the spatial-frequency channel matrix. Numerical results show that the proposed MDDL-based channel estimation and feedback scheme outperforms state-of-the-art approaches. © 1983-2012 IEEE."],"art_number":["9452036"],"author":["Ma, X.","Gao, Z.","Gao, F.","DI Renzo, M."],"coden":["ISACE"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/JSAC.2021.3087269"],"issn":["07338716"],"journaltitle":["IEEE J. Sel. Areas Commun."],"note":["cited By 8 \n\nTL;DR \n\nA model-driven deep learning (MDDL)-based channel estimation and feedback scheme for wideband millimeter-wave (mmWave) massive hybrid multiple-input multiple-output (MIMO) systems, where the angle-delay domain channels’ sparsity is exploited for reducing the overhead."],"number":["8"],"pages":["2388–2406"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Model-driven deep learning based channel estimation and feedback for millimeter-wave massive hybrid MIMO systems"],"volume":["39"]},"creators":{"author":[{"lastName":"Ma","firstName":"X."},{"lastName":"Gao","firstName":"Z."},{"lastName":"Gao","firstName":"F."},{"lastName":"DI Renzo","firstName":"M."}]},"sentenceCased":true},{"key":"Maarek:1991:IRA:126244.126254","type":"article","fields":{"acmid":["126254"],"address":["Piscataway, NJ, USA"],"author":["Maarek, Yoëlle S.","Berry, Daniel M.","Kaiser, Gail E."],"date":["1991-08"],"issn":["0098-5589"],"issue_date":["August 1991"],"journaltitle":["IEEE Trans. Softw. Eng."],"keywords":["attributes","automatic programming","browsing","clustering technique","free-style natural language queries","free-text indexing scheme","indexing scheme","information retrieval approach","information retrieval systems","large software libraries","lexical affinities","natural language documentation","natural languages","software reusability","software reuse","subroutines"],"nodoi":["10.1109/32.83915"],"note":["TL;DR \n\nA technology for automatically assembling large software libraries which promote software reuse by helping the user locate the components closest to her/his needs is described."],"number":["8"],"numpages":["14"],"pages":["800–813"],"publisher":["IEEE Press"],"title":["An information retrieval approach for automatically constructing software libraries"],"url":["http://dx.doi.org/10.1109/32.83915"],"volume":["17"]},"creators":{"author":[{"lastName":"Maarek","firstName":"Yoëlle S."},{"lastName":"Berry","firstName":"Daniel M."},{"lastName":"Kaiser","firstName":"Gail E."}]},"sentenceCased":true},{"key":"maAssessingQualityMetamodels2013","type":"article","fields":{"langid":["english"],"author":["Ma, Zhiyi","He, Xiao","Liu, Chao"],"date":["2013-08"],"doi":["10.1007/s11704-013-1151-5"],"ids":["maAssessingQualityMetamodels2013a"],"issn":["2095-2228, 2095-2236"],"journaltitle":["Front. Comput. Sci."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nA quality model, which systematically characterizes and classifies quality attributes, and an operable measuring mechanism for effectively assessing the quality of metamodels based on the quality model are presented, using UML as the main example."],"number":["4"],"pages":["558–570"],"title":["Assessing the quality of metamodels"],"volume":["7"]},"creators":{"author":[{"lastName":"Ma","firstName":"Zhiyi"},{"lastName":"He","firstName":"Xiao"},{"lastName":"Liu","firstName":"Chao"}]},"sentenceCased":true},{"key":"maccioniQUEPAQUeryingExploring2016","type":"inproceedings","fields":{"langid":["english"],"abstract":["Polystore systems (or simply polystores) have been recently proposed to support a common scenario in which enterprise data are stored in a variety of database technologies relying on different data models and languages. Polystores provide a loosely coupled integration of data sources and support the direct access, with the local language, to each specific storage engine to exploit its distinctive features. Given the absence of a global schema, new challenges for accessing data arise in these environments. In fact, it is usually hard to know in advance if a query to a specific data store can be satisfied with data stored elsewhere in the polystore."],"author":["Maccioni, Antonio","Basili, Edoardo","Torlone, Riccardo"],"date":["2016"],"doi":["10.1145/2882903.2899393"],"isbn":["978-1-4503-3531-7"],"keywords":["TYPHONML"],"note":["TL;DR \n\nQUEPA implements in this way a lightweight mechanism for data integration in the polystore and operates in a plug-and-play mode, thus reducing the need for ad-hoc configurations and for middleware layers involving standard APIs, unified query languages or shared data models."],"pages":["2133–2136"],"publisher":["ACM Press"],"shorttitle":["QUEPA"],"title":["QUEPA: QUerying and Exploring a Polystore by Augmentation"]},"creators":{"author":[{"lastName":"Maccioni","firstName":"Antonio"},{"lastName":"Basili","firstName":"Edoardo"},{"lastName":"Torlone","firstName":"Riccardo"}]}},{"key":"Macdonald2012","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Winter Simul. Conf."],"affiliation":["Dalhousie University, PO Box 15000, Halifax, NS B3H 4R2, Canada"],"art_number":["6464998"],"author":["Macdonald, C.","Gunn, E.A."],"coden":["WSCPD"],"correspondence_address1":["Macdonald, C.; Dalhousie University, PO Box 15000, Halifax, NS B3H 4R2, Canada; email: corinne.macdonald@dal.ca"],"date":["2012"],"document_type":["Conference Paper"],"doi":["10.1109/WSC.2012.6464998"],"isbn":["978-1-4673-4779-2"],"issn":["08917736"],"keywords":["notion"],"note":["cited By 1 \n\nTL;DR \n\nIt is shown that a distribution of simulation effort over a larger sample of input points may result in better neural network metamodels; this conclusion differs from other studies involving regression metAModels."],"series":["Proceedings - Winter Simulation Conference"],"source":["Scopus"],"title":["Allocation of simulation effort for neural network vs. Regression metamodels"]},"creators":{"author":[{"lastName":"Macdonald","firstName":"C."},{"lastName":"Gunn","firstName":"E.A."}]},"sentenceCased":true},{"key":"MacDonellSKM10","type":"article","fields":{"author":["MacDonell, Stephen G.","Shepperd, Martin J.","Kitchenham, Barbara A.","Mendes, Emilia"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/journals/tse/MacDonellSKM10.bib"],"date":["2010"],"doi":["10.1109/TSE.2010.28"],"journaltitle":["IEEE Trans Softw. Eng"],"number":["5"],"pages":["676–687"],"timestamp":["Fri, 27 Mar 2020 08:44:36 +0100"],"title":["How reliable are systematic reviews in empirical software engineering?"],"volume":["36"]},"creators":{"author":[{"lastName":"MacDonell","firstName":"Stephen G."},{"lastName":"Shepperd","firstName":"Martin J."},{"lastName":"Kitchenham","firstName":"Barbara A."},{"lastName":"Mendes","firstName":"Emilia"}]},"sentenceCased":true},{"key":"MachineLearningAutomation","type":"online","fields":{"title":["Machine Learning Automation - Run:AI"],"url":["https://www.run.ai/guides/machine-learning-operations/machine-learning-automation/"],"urldate":["2021-04-21"]},"creators":{}},{"key":"MachineLearningPipelines","type":"online","fields":{"langid":["english"],"abstract":["ResearchGate is a network dedicated to science and research. Connect, collaborate and discover scientific publications, jobs and conferences. All for free."],"keywords":["DONE"],"organization":["ResearchGate"],"shorttitle":["(17) (PDF) Machine Learning Pipelines"],"title":["Machine Learning Pipelines: Provenance, Reproducibility and FAIR Data Principles"],"url":["https://www.researchgate.net/publication/342377391_Machine_Learning_Pipelines_Provenance_Reproducibility_and_FAIR_Data_Principles"],"urldate":["2021-03-18"]},"creators":{}},{"key":"macias-escrivaSelfadaptiveSystemsSurvey2013","type":"article","fields":{"langid":["english"],"author":["Macías-Escrivá, Frank D.","Haber, Rodolfo","family=Toro, given=Raul, prefix=del, useprefix=true","Hernandez, Vicente"],"date":["2013-12"],"doi":["10.1016/j.eswa.2013.07.033"],"issn":["09574174"],"journaltitle":["Expert Syst. Appl."],"number":["18"],"pages":["7267–7279"],"shorttitle":["Self-adaptive systems"],"title":["Self-adaptive systems: A survey of current approaches, research challenges and applications"],"volume":["40"]},"creators":{"author":[{"lastName":"Macías-Escrivá","firstName":"Frank D."},{"lastName":"Haber","firstName":"Rodolfo"},{"lastName":"Toro","firstName":"Raul","prefix":"del","useprefix":true},{"lastName":"Hernandez","firstName":"Vicente"}]},"sentenceCased":true},{"key":"mahdavinejadMachineLearningInternet2018","type":"article","fields":{"langid":["english"],"abstract":["Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things (IoT), continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the IoT generates big data characterized by its velocity in terms of time and location dependency, with a variety of multiple modalities and varying data quality. Intelligent processing and analysis of this big data are the key to developing smart IoT applications. This article assesses the various machine learning methods that deal with the challenges presented by IoT data by considering smart cities as the main use case. The key contribution of this study is the presentation of a taxonomy of machine learning algorithms explaining how different techniques are applied to the data in order to extract higher level information. The potential and challenges of machine learning for IoT data analytics will also be discussed. A use case of applying a Support Vector Machine (SVM) to Aarhus smart city traffic data is presented for a more detailed exploration."],"author":["Mahdavinejad, Mohammad Saeid","Rezvan, Mohammadreza","Barekatain, Mohammadamin","Adibi, Peyman","Barnaghi, Payam","Sheth, Amit P."],"date":["2018-08"],"doi":["10.1016/j.dcan.2017.10.002"],"issn":["23528648"],"journaltitle":["Digital Communications and Networks"],"number":["3"],"pages":["161–175"],"shorttitle":["Machine learning for internet of things data analysis"],"title":["Machine learning for internet of things data analysis: A survey"],"volume":["4"]},"creators":{"author":[{"lastName":"Mahdavinejad","firstName":"Mohammad Saeid"},{"lastName":"Rezvan","firstName":"Mohammadreza"},{"lastName":"Barekatain","firstName":"Mohammadamin"},{"lastName":"Adibi","firstName":"Peyman"},{"lastName":"Barnaghi","firstName":"Payam"},{"lastName":"Sheth","firstName":"Amit P."}]},"sentenceCased":true},{"key":"Mahmoudi20161","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Finite Elem Anal Des"],"affiliation":["FEMTO-ST Institute, UMR 6174, Department of Applied Mechanics, University of Franche-Comté, UBFC, 24 rue de lÉpitaphe, Besançon, 25000, France"],"author":["Mahmoudi, S.","Trivaudey, F.","Bouhaddi, N."],"coden":["FEADE"],"correspondence_address1":["Mahmoudi, S.; FEMTO-ST Institute, 24 rue de lÉpitaphe, France; email: saber.mahmoudi@femto-st.fr"],"date":["2016"],"document_type":["Article"],"doi":["10.1016/j.finel.2016.05.001"],"issn":["0168874X"],"journaltitle":["Finite Elem. Anal. Des."],"note":["cited By 6"],"pages":["1–14"],"publisher":["Elsevier B.V."],"source":["Scopus"],"title":["Benefits of metamodel-reduction for nonlinear dynamic response analysis of damaged composite structures"],"volume":["119"]},"creators":{"author":[{"lastName":"Mahmoudi","firstName":"S."},{"lastName":"Trivaudey","firstName":"F."},{"lastName":"Bouhaddi","firstName":"N."}]},"sentenceCased":true},{"key":"maiaDragonflyToolSimulating2019","type":"inproceedings","fields":{"langid":["english"],"abstract":["Drone simulators can provide an abstraction of different applications of drones and facilitate reasoning about distinct situations, in order to evaluate the effectiveness of these applications. In this paper we describe Dragonfly, a simulator of the behaviours of individual and collection of drones in various environments, involving random contextual variables and different environmental settings. Dragonfly supports the use of several drones in applications and evaluates the satisfaction of requirements under normal and exceptional situations. It simulates adaptive behaviours of drones due to exceptional situations. The adaption of drones is based on the use of wrappers implemented using aspect-oriented programming."],"author":["Maia, Paulo Henrique","Vieira, Lucas","Chagas, Matheus","Yu, Yijun","Zisman, Andrea","Nuseibeh, Bashar"],"booktitle":["2019 IEEEACM 14th Int. Symp. Softw. Eng. Adapt. Self-Manag. Syst. SEAMS"],"date":["2019-05"],"doi":["10.1109/SEAMS.2019.00022"],"eventtitle":["2019 IEEE/ACM 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)"],"isbn":["978-1-72813-368-3"],"location":["Montreal, QC, Canada"],"note":["TL;DR \n\nDragonfly is described, a simulator of the behaviours of individual and collection of drones in various environments, involving random contextual variables and different environmental settings, which simulates adaptive behaviours of drones due to exceptional situations."],"pages":["107–113"],"publisher":["IEEE"],"shorttitle":["Dragonfly"],"title":["Dragonfly: A Tool for Simulating Self-Adaptive Drone Behaviours"]},"creators":{"author":[{"lastName":"Maia","firstName":"Paulo Henrique"},{"lastName":"Vieira","firstName":"Lucas"},{"lastName":"Chagas","firstName":"Matheus"},{"lastName":"Yu","firstName":"Yijun"},{"lastName":"Zisman","firstName":"Andrea"},{"lastName":"Nuseibeh","firstName":"Bashar"}]}},{"key":"maiwaldWhatAreReal2019","type":"incollection","fields":{"langid":["english"],"author":["Maiwald, Benjamin","Riedle, Benjamin","Scherzinger, Stefanie"],"booktitle":["Advances in Conceptual Modeling"],"date":["2019"],"doi":["10.1007/978-3-030-34146-6_9"],"editor":["Guizzardi, Giancarlo","Gailly, Frederik","Suzana Pitangueira Maciel, Rita"],"isbn":["978-3-030-34145-9 978-3-030-34146-6"],"location":["Cham"],"note":["TL;DR \n\nA first empirical analysis of a curated collection of real-world JSON Schemas is presented, which helps practitioners and researchers in making realistic assumptions when building tools for JSON Schema processing."],"pages":["95–105"],"publisher":["Springer International Publishing"],"shorttitle":["What Are Real JSON Schemas Like?"],"title":["What Are Real JSON Schemas Like?: An Empirical Analysis of Structural Properties"],"volume":["11787"]},"creators":{"author":[{"lastName":"Maiwald","firstName":"Benjamin"},{"lastName":"Riedle","firstName":"Benjamin"},{"lastName":"Scherzinger","firstName":"Stefanie"}],"editor":[{"lastName":"Guizzardi","firstName":"Giancarlo"},{"lastName":"Gailly","firstName":"Frederik"},{"lastName":"Suzana Pitangueira Maciel","firstName":"Rita"}]}},{"key":"maiya_ktrain_2020","type":"article","fields":{"abstract":["We present ktrain, a low-code Python library that makes machine learning more accessible and easier to apply. As a wrapper to TensorFlow and many other libraries (e.g., transformers, scikit-learn, stellargraph), it is designed to make sophisticated, state-of-the-art machine learning models simple to build, train, inspect, and apply by both beginners and experienced practitioners. Featuring modules that support text data (e.g., text classification, sequence tagging, open-domain question-answering), vision data (e.g., image classification), graph data (e.g., node classification, link prediction), and tabular data, ktrain presents a simple unified interface enabling one to quickly solve a wide range of tasks in as little as three or four \"commands\" or lines of code."],"author":["Maiya, Arun S."],"date":["2020-07"],"eprint":["2004.10703"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv200410703 Cs"],"keywords":["Computer Science - Computation and Language","Computer Science - Computer Vision and Pattern Recognition","Computer Science - Machine Learning","Computer Science - Social and Information Networks"],"note":["arXiv: 2004.10703 \n\nComment: 9 pages"],"shorttitle":["Ktrain"],"title":["Ktrain: A Low-Code Library for Augmented Machine Learning"]},"creators":{"author":[{"lastName":"Maiya","firstName":"Arun S."}]}},{"key":"maki_context","type":"article","fields":{"langid":["english"],"abstract":["Recommendation System in Software Engineering (RSSE) represents a new promising research area, whose goal is to help software developers in their tasks by providing them with contextdependent insights extracted from their current project or taken from best practices. A key challenge here is to retrieve the context from the programming task in order to provide useful recommendations. In this paper, we conduct a survey of RSSEs with a particular focus on different approaches used to extract the context. We propose a feature model to represent some important characteristics of such extraction and identify some open issues."],"author":["Maki, Sana","Kpodjedo, Sègla","Boussaidi, Ghizlane El"],"date":["2015"],"note":["TL;DR \n\nA survey of RSSEs is conducted with a particular focus on different approaches used to extract the context, and a feature model is proposed to represent some important characteristics of such extraction and identify some open issues."],"pages":["10"],"title":["Context Extraction in Recommendation Systems in Software Engineering: A Preliminary Survey"]},"creators":{"author":[{"lastName":"Maki","firstName":"Sana"},{"lastName":"Kpodjedo","firstName":"Sègla"},{"lastName":"Boussaidi","firstName":"Ghizlane El"}]}},{"key":"maLibRadarFastAccurate2016","type":"inproceedings","fields":{"langid":["english"],"author":["Ma, Ziang","Wang, Haoyu","Guo, Yao","Chen, Xiangqun"],"date":["2016"],"doi":["10.1145/2889160.2889178"],"ids":["7883363"],"isbn":["978-1-4503-4205-6"],"pages":["653–656"],"publisher":["ACM Press"],"shorttitle":["LibRadar"],"title":["LibRadar: Fast and accurate detection of third-party libraries in Android apps"]},"creators":{"author":[{"lastName":"Ma","firstName":"Ziang"},{"lastName":"Wang","firstName":"Haoyu"},{"lastName":"Guo","firstName":"Yao"},{"lastName":"Chen","firstName":"Xiangqun"}]},"sentenceCased":true},{"key":"mangharamThreeChallengesCyberphysical2016","type":"inproceedings","fields":{"author":["Mangharam, Rahul","Abbas, Houssam","Behl, Madhur","Jang, Kuk","Pajic, Miroslav","Jiang, Zhihao"],"booktitle":["2016 8th Int. Conf. Commun. Syst. Netw. COMSNETS"],"date":["2016"],"note":["TL;DR \n\nThis work discusses five challenges which require creative insights and application of model-based design, control systems, scheduling theory, formal methods, statistical machine learning and domain-specific experimentation."],"pages":["1–8"],"publisher":["IEEE"],"title":["Three challenges in cyber-physical systems"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7440015"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Mangharam","firstName":"Rahul"},{"lastName":"Abbas","firstName":"Houssam"},{"lastName":"Behl","firstName":"Madhur"},{"lastName":"Jang","firstName":"Kuk"},{"lastName":"Pajic","firstName":"Miroslav"},{"lastName":"Jiang","firstName":"Zhihao"}]},"sentenceCased":true},{"key":"Manning:2008:IIR:1394399","type":"book","fields":{"author":["Manning, Christopher D.","Raghavan, Prabhakar","Schütze, Hinrich"],"date":["2008"],"ids":["10.5555/1394399"],"isbn":["0-521-86571-9 978-0-521-86571-5"],"location":["New York, NY, USA"],"note":["TL;DR \n\nThis textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science."],"publisher":["Cambridge University Press"],"title":["Introduction to information retrieval"]},"creators":{"author":[{"lastName":"Manning","firstName":"Christopher D."},{"lastName":"Raghavan","firstName":"Prabhakar"},{"lastName":"Schütze","firstName":"Hinrich"}]},"sentenceCased":true},{"key":"mansoNoredundantMetricsUML2003","type":"article","fields":{"author":["Manso, Ma Esperanza","Genero, Marcela","Piattini, Mario"],"date":["2003"],"doi":["10.1007/3-540-45017-3_11"],"journaltitle":["Adv. Inf. Syst. Eng."],"note":["TL;DR \n\nThe obtained results show that the metrics related to associations, aggregations, generalizations and dependencies, are the most relevant whilst those related to size seem to be redundant."],"pages":["127–142"],"title":["No-redundant Metrics for UML Class Diagram Structural Complexity"],"volume":["2681"]},"creators":{"author":[{"lastName":"Manso","firstName":"Ma Esperanza"},{"lastName":"Genero","firstName":"Marcela"},{"lastName":"Piattini","firstName":"Mario"}]},"sentenceCased":true},{"key":"MansoorKLWBD15","type":"article","fields":{"langid":["english"],"author":["Mansoor, Usman","Kessentini, Marouane","Langer, Philip","Wimmer, Manuel","Bechikh, Slim","Deb, Kalyanmoy"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2015-05"],"doi":["10.1016/j.jss.2014.11.043"],"issn":["01641212"],"journaltitle":["J. Syst. Softw."],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["423–439"],"shorttitle":["MOMM"],"timestamp":["Mon, 24 Feb 2020 15:58:20 +0100"],"title":["MOMM: Multi-objective model merging"],"volume":["103"]},"creators":{"author":[{"lastName":"Mansoor","firstName":"Usman"},{"lastName":"Kessentini","firstName":"Marouane"},{"lastName":"Langer","firstName":"Philip"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Bechikh","firstName":"Slim"},{"lastName":"Deb","firstName":"Kalyanmoy"}]},"sentenceCased":true},{"key":"mansouryFeedbackLoopBias2020","type":"article","fields":{"abstract":["Recommendation algorithms are known to suffer from popularity bias; a few popular items are recommended frequently while the majority of other items are ignored. These recommendations are then consumed by the users, their reaction will be logged and added to the system: what is generally known as a feedback loop. In this paper, we propose a method for simulating the users interaction with the recommenders in an offline setting and study the impact of feedback loop on the popularity bias amplification of several recommendation algorithms. We then show how this bias amplification leads to several other problems such as declining the aggregate diversity, shifting the representation of users' taste over time and also homogenization of the users experience. In particular, we show that the impact of feedback loop is generally stronger for the users who belong to the minority group."],"author":["Mansoury, Masoud","Abdollahpouri, Himan","Pechenizkiy, Mykola","Mobasher, Bamshad","Burke, Robin"],"date":["2020-07-25"],"eprint":["2007.13019"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv200713019 Cs"],"keywords":["Computer Science - Information Retrieval"],"note":["TL;DR \n\nA method for simulating the users interaction with the recommenders in an offline setting is proposed and the impact of feedback loop on the popularity bias amplification of several recommendation algorithms is studied."],"title":["Feedback Loop and Bias Amplification in Recommender Systems"],"url":["http://arxiv.org/abs/2007.13019"],"urldate":["2022-03-24"]},"creators":{"author":[{"lastName":"Mansoury","firstName":"Masoud"},{"lastName":"Abdollahpouri","firstName":"Himan"},{"lastName":"Pechenizkiy","firstName":"Mykola"},{"lastName":"Mobasher","firstName":"Bamshad"},{"lastName":"Burke","firstName":"Robin"}]}},{"key":"mantzCoevolvingMetamodelsTheir2015","type":"article","fields":{"langid":["english"],"author":["Mantz, Florian","Taentzer, Gabriele","Lamo, Yngve","Wolter, Uwe"],"date":["2015-06"],"doi":["10.1016/j.scico.2015.01.002"],"issn":["01676423"],"journaltitle":["Sci. Comput. Program."],"pages":["2–43"],"shorttitle":["Co-evolving meta-models and their instance models"],"title":["Co-evolving meta-models and their instance models: A formal approach based on graph transformation"],"volume":["104"]},"creators":{"author":[{"lastName":"Mantz","firstName":"Florian"},{"lastName":"Taentzer","firstName":"Gabriele"},{"lastName":"Lamo","firstName":"Yngve"},{"lastName":"Wolter","firstName":"Uwe"}]},"sentenceCased":true},{"key":"mantzCustomizingModelMigrations2013","type":"article","fields":{"author":["Mantz, Florian","Taentzer, Gabriele","Lamo, Yngve"],"date":["2013"],"doi":["10.1145/2501543.2501545"],"journaltitle":["Proc. 2013 Int. Workshop Princ. Softw. Evol. - IWPSE 2013"],"pages":["1"],"title":["Customizing model migrations by rule schemes"]},"creators":{"author":[{"lastName":"Mantz","firstName":"Florian"},{"lastName":"Taentzer","firstName":"Gabriele"},{"lastName":"Lamo","firstName":"Yngve"}]},"sentenceCased":true},{"key":"ManuallyConfigureTelegraf","type":"online","fields":{"title":["Manually configure Telegraf for InfluxDB v2.0 | InfluxDB OSS 2.0 Documentation"],"url":["https://docs.influxdata.com/influxdb/v2.0/write-data/no-code/use-telegraf/manual-config/"],"urldate":["2021-01-11"]},"creators":{},"sentenceCased":true},{"key":"MAO201757","type":"article","fields":{"author":["Mao, Ke","Capra, Licia","Harman, Mark","Jia, Yue"],"date":["2017"],"issn":["0164-1212"],"journaltitle":["J. Syst. Softw."],"nodoi":["https://doi.org/10.1016/j.jss.2016.09.015"],"pages":["57–84"],"title":["A survey of the use of crowdsourcing in software engineering"],"url":["http://www.sciencedirect.com/science/article/pii/S0164121216301832"],"volume":["126"]},"creators":{"author":[{"lastName":"Mao","firstName":"Ke"},{"lastName":"Capra","firstName":"Licia"},{"lastName":"Harman","firstName":"Mark"},{"lastName":"Jia","firstName":"Yue"}]},"sentenceCased":true},{"key":"Mao20222870","type":"article","fields":{"abstract":["For conventional signaling, the length of the orthogonal pilot is required at least equal to the total number of user antennas. However, it is not recommended in the Internet of Things (IoT) due to the expensive cost paid in massive connectivities. Thanks to the sporadic nature of the massive connected users where a considerable fraction of users are inactive within a coherence time, the nonorthogonal pilot can be utilized with the joint channel estimation and active-user detection being modeled as a compressive sensing problem. According to the different antenna configuration methods employed by the base station, the constructed problems in this work are formulated into the single measurement vector and the multiple measurement vectors recovery problems. Also, we develop a model-driven deep learning algorithm to solve the problems based on the traditional alternative direction method of multipliers (ADMM) algorithm, where the iteration operation is unfolded into the network layer. The network parameters are learned with the help of the stochastic gradient descent algorithm. Simulation results show that the proposed approach can achieve better performance than an ADMM algorithm under the same computational complexity. © 2014 IEEE."],"author":["Mao, Z.","Liu, X.","Peng, M.","Chen, Z.","Wei, G."],"date":["2022"],"document_type":["Article"],"doi":["10.1109/JIOT.2021.3097133"],"issn":["23274662"],"journaltitle":["IEEE Internet Things J."],"note":["cited By 0 \n\nTL;DR \n\nA model-driven deep learning algorithm is developed to solve the problems based on the traditional alternative direction method of multipliers algorithm, where the iteration operation is unfolded into the network layer and the network parameters are learned with the help of the stochastic gradient descent algorithm."],"number":["4"],"pages":["2870–2881"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Joint channel estimation and active-user detection for massive access in internet of things-A deep learning approach"],"volume":["9"]},"creators":{"author":[{"lastName":"Mao","firstName":"Z."},{"lastName":"Liu","firstName":"X."},{"lastName":"Peng","firstName":"M."},{"lastName":"Chen","firstName":"Z."},{"lastName":"Wei","firstName":"G."}]},"sentenceCased":true},{"key":"maozFrameworkRelatingSyntactic","type":"article","fields":{"author":["Maoz, Shahar","Ringert, Jan Oliver"],"note":["TL;DR \n\nThe Diffuse framework provides a novel foundation for combining syntactic and semantic differencing, a language-independent, abstract framework which relates syntactic change operations and semantic difference witnesses."],"title":["A Framework for Relating Syntactic and Semantic Model Differences"],"url":["http://www.cs.tau.ac.il/~ringert/publications/MR15synsemdiff.pdf"],"urldate":["2015-09-10"]},"creators":{"author":[{"lastName":"Maoz","firstName":"Shahar"},{"lastName":"Ringert","firstName":"Jan Oliver"}]}},{"key":"maqbool2007hierarchical","type":"article","fields":{"author":["Maqbool, Onaiza","Babri, Haroon"],"date":["2007"],"journaltitle":["IEEE Trans. Softw. Eng."],"note":["TL;DR \n\nThis paper provides a detailed analysis of the behavior of various similarity and distance measures that may be employed for software clustering, and analyzes the clustering process of various well-known clustering algorithms by using multiple criteria."],"number":["11"],"pages":["759–780"],"publisher":["IEEE"],"title":["Hierarchical clustering for software architecture recovery"],"volume":["33"]},"creators":{"author":[{"lastName":"Maqbool","firstName":"Onaiza"},{"lastName":"Babri","firstName":"Haroon"}]},"sentenceCased":true},{"key":"marcusDeepLearningCritical2018","type":"online","fields":{"abstract":["Although deep learning has historical roots going back decades, neither the term \"deep learning\" nor the approach was popular just over five years ago, when the field was reignited by papers such as Krizhevsky, Sutskever and Hinton's now classic (2012) deep network model of Imagenet. What has the field discovered in the five subsequent years? Against a background of considerable progress in areas such as speech recognition, image recognition, and game playing, and considerable enthusiasm in the popular press, I present ten concerns for deep learning, and suggest that deep learning must be supplemented by other techniques if we are to reach artificial general intelligence."],"author":["Marcus, Gary"],"date":["2018-01-02"],"eprint":["1801.00631"],"eprintclass":["cs, stat"],"eprinttype":["arxiv"],"keywords":["97R40","Computer Science - Artificial Intelligence","Computer Science - Machine Learning","I.2.0","I.2.6","Statistics - Machine Learning"],"pubstate":["preprint"],"shorttitle":["Deep Learning"],"title":["Deep Learning: A Critical Appraisal"],"url":["http://arxiv.org/abs/1801.00631"],"urldate":["2023-03-17"]},"creators":{"author":[{"lastName":"Marcus","firstName":"Gary"}]}},{"key":"margariaLeveragingApplicationsFormal2021","type":"book","fields":{"langid":["english"],"date":["2021"],"doi":["10.1007/978-3-030-89159-6"],"editor":["Margaria, Tiziana","Steffen, Bernhard"],"isbn":["978-3-030-89158-9 978-3-030-89159-6"],"location":["Cham"],"publisher":["Springer International Publishing"],"series":["Lecture Notes in Computer Science"],"shorttitle":["Leveraging Applications of Formal Methods, Verification and Validation"],"title":["Leveraging Applications of Formal Methods, Verification and Validation: 10th International Symposium on Leveraging Applications of Formal Methods, ISoLA 2021, Rhodes, Greece, October 17–29, 2021, Proceedings"],"volume":["13036"]},"creators":{"editor":[{"lastName":"Margaria","firstName":"Tiziana"},{"lastName":"Steffen","firstName":"Bernhard"}]}},{"key":"marozzoWorkflowManagementSystem2018","type":"article","fields":{"langid":["english"],"abstract":["The extraction of useful information from data is often a complex process that can be conveniently modeled as a data analysis workflow. When very large data sets must be analyzed and/or complex data mining algorithms must be executed, data analysis workflows may take very long times to complete their execution. Therefore, efficient systems are required for the scalable execution of data analysis workflows, by exploiting the computing services of the Cloud platforms where data is increasingly being stored. The objective of the paper is to demonstrate how Cloud software technologies can be integrated to implement an effective environment for designing and executing scalable data analysis workflows. We describe the design and implementation of the Data Mining Cloud Framework (DMCF), a data analysis system that integrates a visual workflow language and a parallel runtime with the Software-as-aService (SaaS) model. DMCF was designed taking into account the needs of real data mining applications, with the goal of simplifying the development of data mining applications compared to generic workflow management systems that are not specifically designed for this domain. The result is a high-level environment that, through an integrated visual workflow language, minimizes the programming effort, making easier to domain experts the use of common patterns specifically designed for the development and the parallel execution of data mining applications. The DMCF’s visual workflow language, system architecture and runtime mechanisms are presented. We also discuss several data mining workflows developed with DMCF and the scalability obtained executing such workflows on a public Cloud."],"author":["Marozzo, Fabrizio","Talia, Domenico","Trunfio, Paolo"],"date":["2018-05-01"],"doi":["10.1109/TSC.2016.2589243"],"issn":["1939-1374"],"journaltitle":["IEEE Trans. Serv. Comput."],"keywords":["STARRED"],"note":["<b>Blue Annotations (3/2/2022, 15:37:35)</b> \n\n\"Several systems have been proposed to design and execute workflow-based applications [10], [11], [12], but only some of them currently work on the Cloud and support visual workflow programming. In the following we discuss representative visual workflow management systems that can be used in Cloud environments.\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=2\">Marozzo et al 2018:481</a>) \n\n\"Galaxy\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=2\">Marozzo et al 2018:481</a>) \n\n\"averna [15] is a workflow management system mostly used in the life sciences community\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=2\">Marozzo et al 2018:481</a>) \n\n\"Orange4WS [17] is a service-oriented workflow system that extends Orange, a data mining toolbox and a visual programming environment for the visual composition of data mining workflows.\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=2\">Marozzo et al 2018:481</a>) \n\n\"Kepler [18] is a visual workflow management system that provides a graphical user interface for designing scientific\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=2\">Marozzo et al 2018:481</a>) \n\n\"workflows\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=3\">Marozzo et al 2018:482</a>) \n\n\"E-Science Central (e-SC) [19] allows scientists to store,\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=3\">Marozzo et al 2018:482</a>) \n\n\"analyze and share data in the Cloud.\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=3\">Marozzo et al 2018:482</a>) \n\n\"ClowdFlows [20] is a Cloud-based platform for the composition, execution, and sharing of interactive data mining workflows.\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=3\">Marozzo et al 2018:482</a>) \n\n\"set of technologies to execute workflow-based applications over clusters and Grid\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=3\">Marozzo et al 2018:482</a>) \n\n\"RapidMiner1 is a powerful commercial platform through which users can exploit many analytics tools to visually create predictive analytics workflows.\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=3\">Marozzo et al 2018:482</a>) \n\n\"each tool node of a workflow can be a Hadoop program, and therefore it can exploit the Hadoop parallelism\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=3\">Marozzo et al 2018:482</a>) \n\n\"DMCF workflow, task Yes PaaS Yes\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=3\">Marozzo et al 2018:482</a>) \n\n\"RapidMiner\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=3\">Marozzo et al 2018:482</a>) \n\nTL;DR \n\nThe design and implementation of the Data Mining Cloud Framework (DMCF), a data analysis system that integrates a visual workflow language and a parallel runtime with the Software-as-a-Service (SaaS) model is described. \n\n<b>Yellow Annotations (3/2/2022, 15:37:35)</b> \n\n\"The extraction of useful information from data is often a complex process that can be conveniently modeled as a data analysis workflow\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"data analysis workflows may take very long times to complete their execution\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"efficient systems are required for the scalable execution of data analysis workflows, by exploiting the computing services of the Cloud platforms where data is increasingly being stored.\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"Cloud software technologies can be integrated to implement an effective environment for designing and executing scalable data analysis workflows\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"Data Mining Cloud Framework (DMCF), a data analysis system that integrates a visual workflow language and a parallel runtime with the Software-as-aService (SaaS) model\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"eal data mining applications\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"simplifying the development of data mining applications compared to generic workflow management systems that are not specifically designed for this domain\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"minimizes the programming effort, making easier to domain experts the use of common patterns specifically designed for the development and the parallel execution of data mining applications.\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"DMCF's visual workflow language, system architecture and runtime mechanisms are presented. We also discuss several data mining workflows developed with DMCF and the scalability obtained executing such workflows on a public Cloud\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"distributed datasets, preprocessing tools, data mining algorithms and knowledge models\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"Workflows provide a declarative way of specifying the high-level logic of an application, hiding the low-level details that are not fundamental for application design\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"DMCF minimizes the programming effort,\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=1\">Marozzo et al 2018:480</a>) \n\n\"use of common patterns specifically designed for the development and the parallel execution of data mining applications\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=2\">Marozzo et al 2018:481</a>) \n\n<i>DEFINITION OF COMMONG PATTERNS FOR THE PARALLEL EXECUTION OF DATA MINING APPLICATINS (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=2\">note on p.481</a>)</i> \n\n\"isual patterns useful in real data mining applications, in particular: data pre-processing (data partitioning and filtering); parameter sweeping (the concurrent execution of many instances of the same tool with different parameters to find the best result); input sweeping (the concurrent execution of many instances of the same tool with different input data); tool sweeping (the concurrent execution of different tools on same data); combinations of parameter, input, and tool sweeping patterns for the highest flexibility; data and models aggregation (e.g., models evaluations, voting operations, models aggregation).\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=2\">Marozzo et al 2018:481</a>) \n\n\"design of parallel data analysis workflows.\" (<a href=\"zotero://open-pdf/library/items/XTEYZECW?page=2\">Marozzo et al 2018:481</a>)"],"number":["3"],"pages":["480–492"],"title":["A Workflow Management System for Scalable Data Mining on Clouds"],"volume":["11"]},"creators":{"author":[{"lastName":"Marozzo","firstName":"Fabrizio"},{"lastName":"Talia","firstName":"Domenico"},{"lastName":"Trunfio","firstName":"Paolo"}]}},{"key":"martinez-lasacaDandelionScalableCloudbased2023","type":"article","fields":{"langid":["english"],"abstract":["There is an increasing demand nowadays for low-code development platforms (LCDPs). As they rely heavily on graphical languages rather than writing code, these platforms enable citizen developers to participate in software development. However, creating new LCDPs is very costly, since it requires building support for graphical modelling and its integration with services like model validation, recommendation systems, or code generation. While Model-driven Engineering (MDE) has developed technologies to create these components, most of them are not cloud-based, as required by LCDPs. In particular, a cloud-based graphical workbench capable of providing the scalability required by industrial applications and adequately supporting technological heterogeneity is currently missing."],"author":["Martínez-Lasaca, Francisco","Díez, Pablo","Guerra, Esther","De Lara, Juan"],"date":["2023-05"],"doi":["10.1016/j.cola.2023.101217"],"issn":["25901184"],"journaltitle":["Journal of Computer Languages"],"keywords":["LOGSEQ"],"pages":["101217"],"shorttitle":["Dandelion"],"title":["Dandelion: A scalable, cloud-based graphical language workbench for industrial low-code development"]},"creators":{"author":[{"lastName":"Martínez-Lasaca","firstName":"Francisco"},{"lastName":"Díez","firstName":"Pablo"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"De Lara","firstName":"Juan"}]},"sentenceCased":true},{"key":"martinezAutomatingExtractionModelBased2015","type":"inproceedings","fields":{"author":["Martinez, Jabier","Ziadi, Tewfik","Bissyande, Tegawende F.","Klein, Jacques","family=Traon, given=Yves, prefix=le, useprefix=false"],"date":["2015-11"],"doi":["10.1109/ASE.2015.44"],"isbn":["978-1-5090-0025-8"],"pages":["396–406"],"publisher":["IEEE"],"title":["Automating the Extraction of Model-Based Software Product Lines from Model Variants (T)"]},"creators":{"author":[{"lastName":"Martinez","firstName":"Jabier"},{"lastName":"Ziadi","firstName":"Tewfik"},{"lastName":"Bissyande","firstName":"Tegawende F."},{"lastName":"Klein","firstName":"Jacques"},{"lastName":"Traon","firstName":"Yves","prefix":"le","useprefix":false}]}},{"key":"marussySpecificationLanguageConsistent2020","type":"article","fields":{"langid":["english"],"author":["Marussy, Kristóf","Semeráth, Oszkár","A. Babikian, Aren","Varró, Dániel"],"date":["2020"],"doi":["10.5381/jot.2020.19.3.a12"],"issn":["1660-1769"],"journaltitle":["JOT"],"note":["TL;DR \n\nA novel specification language for partial models used in consistent graph model generation by combining partial models, graph predicates and model metrics with mutual dependencies between them is proposed."],"number":["3"],"pages":["3:1"],"title":["A Specification Language for Consistent Model Generation based on Partial Models."],"volume":["19"]},"creators":{"author":[{"lastName":"Marussy","firstName":"Kristóf"},{"lastName":"Semeráth","firstName":"Oszkár"},{"lastName":"A. Babikian","firstName":"Aren"},{"lastName":"Varró","firstName":"Dániel"}]},"sentenceCased":true},{"key":"Masthead2017","type":"article","fields":{"langid":["english"],"date":["2017-01"],"doi":["10.1109/MS.2017.5"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"number":["1"],"pages":["8–8"],"title":["Masthead"],"volume":["34"]},"creators":{}},{"key":"Masthead2018","type":"article","fields":{"abstract":["Describes the above-named upcoming conference event. May include topics to be covered or calls for papers."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571248"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"number":["5"],"pages":["c2-c2"],"title":["Masthead"],"volume":["35"]},"creators":{}},{"key":"Masthead2020","type":"article","fields":{"langid":["english"],"date":["2020-07"],"doi":["10.1109/MS.2020.2972660"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"number":["4"],"pages":["C2-C2"],"title":["Masthead"],"volume":["37"]},"creators":{}},{"key":"Masthead2020a","type":"article","fields":{"langid":["english"],"date":["2020-09"],"doi":["10.1109/MS.2020.2972672"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"number":["5"],"pages":["C2-C2"],"title":["Masthead"],"volume":["37"]},"creators":{}},{"key":"mastropaolo2023robustness","type":"misc","fields":{"author":["Mastropaolo, Antonio","Pascarella, Luca","Guglielmi, Emanuela","Ciniselli, Matteo","Scalabrino, Simone","Oliveto, Rocco","Bavota, Gabriele"],"date":["2023"],"journaltitle":["International conference on software engineering (ICSE 2023), may 17-19 2023, melbourne, australia"],"note":["TL;DR \n\nThis paper presents an empirical study in which it is aimed at understanding whether different but semantically equivalent natural language descriptions result in the same recommended function in the generated code function."],"title":["On the robustness of code generation techniques: An empirical study on GitHub copilot"]},"creators":{"author":[{"lastName":"Mastropaolo","firstName":"Antonio"},{"lastName":"Pascarella","firstName":"Luca"},{"lastName":"Guglielmi","firstName":"Emanuela"},{"lastName":"Ciniselli","firstName":"Matteo"},{"lastName":"Scalabrino","firstName":"Simone"},{"lastName":"Oliveto","firstName":"Rocco"},{"lastName":"Bavota","firstName":"Gabriele"}]},"sentenceCased":true},{"key":"mastropaoloAutomaticallyCompletingGitHub2023","type":"online","fields":{"abstract":["Continuous integration and delivery (CI/CD) are nowadays at the core of software development. Their benefits come at the cost of setting up and maintaining the CI/CD pipeline, which requires knowledge and skills often orthogonal to those entailed in other software-related tasks. While several recommender systems have been proposed to support developers across a variety of tasks, little automated support is available when it comes to setting up and maintaining CI/CD pipelines. We present GH-WCOM (GitHub Workflow COMpletion), a Transformer-based approach supporting developers in writing a specific type of CI/CD pipelines, namely GitHub workflows. To deal with such a task, we designed an abstraction process to help the learning of the transformer while still making GH-WCOM able to recommend very peculiar workflow elements such as tool options and scripting elements. Our empirical study shows that GH-WCOM provides up to 34.23% correct predictions, and the model's confidence is a reliable proxy for the recommendations' correctness likelihood."],"author":["Mastropaolo, Antonio","Zampetti, Fiorella","Di Penta, Massimiliano","Bavota, Gabriele"],"date":["2023-08-31"],"eprint":["2308.16774"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Software Engineering","LOGSEQ"],"pubstate":["preprint"],"title":["Toward Automatically Completing GitHub Workflows"],"url":["http://arxiv.org/abs/2308.16774"],"urldate":["2023-09-05"]},"creators":{"author":[{"lastName":"Mastropaolo","firstName":"Antonio"},{"lastName":"Zampetti","firstName":"Fiorella"},{"lastName":"Di Penta","firstName":"Massimiliano"},{"lastName":"Bavota","firstName":"Gabriele"}]}},{"key":"mastropaoloEvaluatingCodeSummarization2023","type":"online","fields":{"langid":["english"],"abstract":["Several code summarization techniques have been proposed in the literature to automatically document a code snippet or a function. Ideally, software developers should be involved in assessing the quality of the generated summaries. However, in most cases, researchers rely on automatic evaluation metrics such as BLEU, ROUGE, and METEOR. These metrics are all based on the same assumption: The higher the textual similarity between the generated summary and a reference summary written by developers, the higher its quality. However, there are two reasons for which this assumption falls short: (i) reference summaries, e.g., code comments collected by mining software repositories, may be of low quality or even outdated; (ii) generated summaries, while using a different wording than a reference one, could be semantically equivalent to it, thus still being suitable to document the code snippet. In this paper, we perform a thorough empirical investigation on the complementarity of different types of metrics in capturing the quality of a generated summary. Also, we propose to address the limitations of existing metrics by considering a new dimension, capturing the extent to which the generated summary aligns with the semantics of the documented code snippet, independently from the reference summary. To this end, we present a new metric based on contrastive learning to capture said aspect. We empirically show that the inclusion of this novel dimension enables a more effective representation of developers’ evaluations regarding the quality of automatically generated summaries."],"author":["Mastropaolo, Antonio","Ciniselli, Matteo","Di Penta, Massimiliano","Bavota, Gabriele"],"date":["2023-12-24"],"eprint":["2312.15475"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Software Engineering","LOGSEQ"],"note":["<h1>Annotazioni\n (19/1/2024, 11:16:08)</h1> \n\n“Evaluating Code Summarization Techniques: A New Metric and an Empirical Characterization” (Mastropaolo et al., 2023, p. 1) #5fb236 \n <i>This is related to project [[PROJECTS/MOSAICO]]</i> \n\n“Several code summarization techniques have been proposed in the literature to document a code snippet or a function automatically.” (Mastropaolo et al., 2023, p. 1) #ffd400 \n <i>This is a comment for a yellow highlight [[P1]] [[STAR]]</i> \n\n“oftware developers should be involved in assessing the quality of the generated summaries. However, in most cases, researchers rely on a” (Mastropaolo et al., 2023, p. 1) #ff6666 \n <i>This is not good [[people/phuong]]</i> \n\n“falls short: (i) reference summaries, e.g., code comments collected by mining software repositories, may be of low quality or even outdated; (ii)” (Mastropaolo et al., 2023, p. 1) #5fb236 \n\n“m a thorough empirical investigation on the complementarity of different types of metrics in capturing the quality of a generated summary. Also, we propose to address the limitations of existing metrics by consid” (Mastropaolo et al., 2023, p. 1) #ffd400 \n\nTL;DR \n\nA thorough empirical investigation on the complementarity of different types of metrics in capturing the quality of a generated summary is performed, and a new metric based on contrastive learning to capture said aspect is presented."],"pubstate":["preprint"],"shorttitle":["Evaluating Code Summarization Techniques"],"title":["Evaluating Code Summarization Techniques: A New Metric and an Empirical Characterization"],"url":["http://arxiv.org/abs/2312.15475"],"urldate":["2024-01-18"]},"creators":{"author":[{"lastName":"Mastropaolo","firstName":"Antonio"},{"lastName":"Ciniselli","firstName":"Matteo"},{"lastName":"Di Penta","firstName":"Massimiliano"},{"lastName":"Bavota","firstName":"Gabriele"}]}},{"key":"mastropaoloStudyingUsageTextToText2021","type":"inproceedings","fields":{"author":["Mastropaolo, Antonio","Scalabrino, Simone","Cooper, Nathan","Nader Palacio, David","Poshyvanyk, Denys","Oliveto, Rocco","Bavota, Gabriele"],"booktitle":["2021 IEEEACM 43rd Int. Conf. Softw. Eng. ICSE"],"date":["2021-05"],"doi":["10.1109/ICSE43902.2021.00041"],"eventtitle":["2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)"],"ids":["T5_Oliveto_Bavota_2021"],"isbn":["978-1-66540-296-5"],"location":["Madrid, ES"],"pages":["336–347"],"publisher":["IEEE"],"title":["Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks"]},"creators":{"author":[{"lastName":"Mastropaolo","firstName":"Antonio"},{"lastName":"Scalabrino","firstName":"Simone"},{"lastName":"Cooper","firstName":"Nathan"},{"lastName":"Nader Palacio","firstName":"David"},{"lastName":"Poshyvanyk","firstName":"Denys"},{"lastName":"Oliveto","firstName":"Rocco"},{"lastName":"Bavota","firstName":"Gabriele"}]}},{"key":"mathewSoftwareEngineeringTop2018","type":"article","fields":{"abstract":["For this theme issue on the 50th anniversary of software engineering (SE), Redirections offers an overview of the twists, turns, and numerous redirections seen over the years in the SE research literature. Nearly a dozen topics have dominated the past few decades of SE research—and these have been redirected many times. Some are gaining popularity, whereas others are becoming increasingly rare. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Mathew, G.","Menzies, T."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571230"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"note":["TL;DR \n\nThis theme issue on the 50th anniversary of software engineering (SE) offers an overview of the twists, turns, and numerous redirections seen over the years in the SE research literature."],"number":["5"],"pages":["88–93"],"title":["Software Engineering’s Top Topics, Trends, and Researchers"],"volume":["35"]},"creators":{"author":[{"lastName":"Mathew","firstName":"G."},{"lastName":"Menzies","firstName":"T."}]}},{"key":"Matic2021","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Electronics (Switzerland)"],"affiliation":["Department for Information Systems and Technologies, Belgrade Academy for Business and Arts Applied Studies, Kraljice Marije 73, Belgrade, 11000, Serbia; Faculty of Informatics and Computing, Singidunum University, Danijelova 32, Belgrade, 11000, Serbia; School of Electrical Engineering, University of Belgrade, Bulevar Kralja Aleksandra 73, Belgrade, 11000, Serbia"],"art_number":["2300"],"author":["Matic, R.","Kabiljo, M.","Zivkovic, M.","Cabarkapa, M."],"correspondence_address1":["Zivkovic, M.; Faculty of Informatics and Computing, Danijelova 32, Serbia; email: mzivkovic@singidunum.ac.rs; Cabarkapa, M.; School of Electrical Engineering, Bulevar Kralja Aleksandra 73, Serbia; email: cabmilan@etf.bg.ac.rs"],"date":["2021"],"document_type":["Article"],"doi":["10.3390/electronics10182300"],"issn":["20799292"],"journaltitle":["Electron. Switz."],"keywords":["GOAL_Model-Assistance","notion"],"note":["cited By 1 \n\nTL;DR \n\nThe paper describes overall chatbot architecture and provides corresponding metamodels as well as rules for mapping between the proposed and two commonly used NLU metAModels and could be easily extended with new NLU services and communication channels. \n\nto be excluded"],"number":["18"],"publisher":["MDPI"],"source":["Scopus"],"title":["Extensible chatbot architecture using metamodels of natural language understanding"],"volume":["10"]},"creators":{"author":[{"lastName":"Matic","firstName":"R."},{"lastName":"Kabiljo","firstName":"M."},{"lastName":"Zivkovic","firstName":"M."},{"lastName":"Cabarkapa","firstName":"M."}]},"sentenceCased":true},{"key":"mattihalliPlantLeafDiseases2018","type":"article","fields":{"langid":["english"],"abstract":["Leaf diseases in plants cause major production and economic losses as well as reduction in both quality and quantity of agricultural crop. It’s better to detect the leaf diseases in early on leaf health and disease detection can facilitate the control of diseases through proper management strategies."],"author":["Mattihalli, Channamallikarjuna","Gedefaye, Edemialem","Endalamaw, Fasil","Necho, Adugna"],"date":["2018-09"],"doi":["10.1016/j.iot.2018.08.007"],"issn":["25426605"],"journaltitle":["Internet Things"],"pages":["67–73"],"title":["Plant leaf diseases detection and auto-medicine"],"volume":["1–2"]},"creators":{"author":[{"lastName":"Mattihalli","firstName":"Channamallikarjuna"},{"lastName":"Gedefaye","firstName":"Edemialem"},{"lastName":"Endalamaw","firstName":"Fasil"},{"lastName":"Necho","firstName":"Adugna"}]},"sentenceCased":true},{"key":"mattsonDemonstratingBigDAWGPolystore","type":"article","fields":{"langid":["english"],"abstract":["In most Big Data applications, the data is heterogeneous. As we have been arguing in a series of papers, storage engines should be well suited to the data they hold. Therefore, a system supporting Big Data applications should be able to expose multiple storage engines through a single interface. We call such systems, polystore systems. Our reference implementation of the polystore concept is called BigDAWG (short for the Big Data Analytics Working Group). In this demonstration, we will show the BigDAWG system and a number of polystore applications built to help ocean metagenomics researchers handle their heterogenous Big Data."],"author":["Mattson, Tim","Gadepally, Vijay","She, Zuohao","Dziedzic, Adam","Parkhurst, Jeff"],"note":["TL;DR \n\nThis demonstration will show the BigDAWG system and a number of polystore applications built to help ocean metage-nomics researchers handle their heterogenous Big Data."],"pages":["9"],"title":["Demonstrating the BigDAWG Polystore System for Ocean Metagenomic Analysis"]},"creators":{"author":[{"lastName":"Mattson","firstName":"Tim"},{"lastName":"Gadepally","firstName":"Vijay"},{"lastName":"She","firstName":"Zuohao"},{"lastName":"Dziedzic","firstName":"Adam"},{"lastName":"Parkhurst","firstName":"Jeff"}]}},{"key":"MayerhoferLWK13","type":"inproceedings","fields":{"langid":["english"],"author":["Mayerhofer, Tanja","Langer, Philip","Wimmer, Manuel","Kappel, Gerti"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Softw. Lang. Eng. - 6th Int. Conf. SLE 2013 Indianap. USA Oct. 26-28 2013 Proc."],"date":["2013"],"doi":["10.1007/978-3-319-02654-1\\_4"],"editor":["Erwig, Martin","Paige, Richard F.","Wyk, Eric Van"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper integrates fUML, a standardized executable subset of UML, with MOF leading to a new metamodeling language xMOF, and proposes a methodology for developing executable DSMLs fostering the separation of abstract syntax and behavioral semantics."],"pages":["56–75"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Tue, 14 May 2019 10:00:40 +0200"],"title":["xMOF: Executable DSMLs based on fUML"],"volume":["8225"]},"creators":{"author":[{"lastName":"Mayerhofer","firstName":"Tanja"},{"lastName":"Langer","firstName":"Philip"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Kappel","firstName":"Gerti"}],"editor":[{"lastName":"Erwig","firstName":"Martin"},{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Wyk","firstName":"Eric Van"}]},"sentenceCased":true},{"key":"mazaheriRecommenderSystemScientific2021","type":"article","fields":{"langid":["english"],"abstract":["Scientific datasets and analysis pipelines are increasingly being shared publicly in the interest of open science. However, mechanisms are lacking to reliably identify which pipelines and datasets can appropriately be used together. Given the increasing number of high-quality public datasets and pipelines, this lack of clear compatibility threatens the findability and reusability of these resources. We investigate the feasibility of a collaborative filtering system to recommend pipelines and datasets based on provenance records from previous executions. We evaluate our system using datasets and pipelines extracted from the Canadian Open Neuroscience Platform, a national initiative for open neuroscience. The recommendations provided by our system (AUC$=0.83$) are significantly better than chance and outperform recommendations made by domain experts using their previous knowledge as well as pipeline and dataset descriptions (AUC$=0.63$). In particular, domain experts often neglect low-level technical aspects of a pipeline-dataset interaction, such as the level of pre-processing, which are captured by a provenance-based system. We conclude that provenance-based pipeline and dataset recommenders are feasible and beneficial to the sharing and usage of open-science resources. Future work will focus on the collection of more comprehensive provenance traces, and on deploying the system in production."],"author":["Mazaheri, Mandana","Kiar, Gregory","Glatard, Tristan"],"date":["2021-08-20"],"doi":["10.1109/WORKS54523.2021.00006"],"journaltitle":["2021 IEEE Workshop Work. Support Large-Scale Sci. WORKS"],"keywords":["Computer Science - Information Retrieval","Computer Science - Machine Learning"],"pages":["62011–62021"],"title":["A Recommender System for Scientific Datasets and Analysis Pipelines"],"volume":["7"]},"creators":{"author":[{"lastName":"Mazaheri","firstName":"Mandana"},{"lastName":"Kiar","firstName":"Gregory"},{"lastName":"Glatard","firstName":"Tristan"}]}},{"key":"mazanekToolDemonstrationTransformation2011","type":"incollection","fields":{"author":["Mazanek, Steffen","Rutetzki, Christian","Minas, Mark"],"booktitle":["Applications of Graph Transformations with Industrial Relevance"],"date":["2011"],"note":["TL;DR \n\nThe transformation judge is a novel system for the automatic evaluation and comparison of graph and model transformations that have been submitted as solutions for common transformation tasks such as those accepted as case studies for the transformation tool contest."],"pages":["97–104"],"publisher":["Springer"],"title":["Tool demonstration of the transformation judge"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-34176-2_10"],"urldate":["2016-02-09"]},"creators":{"author":[{"lastName":"Mazanek","firstName":"Steffen"},{"lastName":"Rutetzki","firstName":"Christian"},{"lastName":"Minas","firstName":"Mark"}]},"sentenceCased":true},{"key":"mccallumBuildingDomainSpecificSearch","type":"article","fields":{"langid":["english"],"abstract":["Domain-speci c search engines are growing in popularity because they o er increased accuracy and extra functionality not possible with the general, Web-wide search engines. For example, www.campsearch.com allows complex queries by age-group, size, location and cost over summer camps. Unfortunately these domain-speci c search engines are di cult and timeconsuming to maintain. This paper proposes the use of machine learning techniques to greatly automate the creation and maintenance of domain-speci c search engines. We describe new research in reinforcement learning, information extraction and text classi cation that enables e cient spidering, identifying informative text segments, and populating topic hierarchies. Using these techniques, we have built a demonstration system: a search engine for computer science research papers. It already contains over 50,000 papers and is publicly available at www.cora.justresearch.com."],"author":["McCallum, Andrew","Nigam, Kamal","Rennie, Jason","Seymore, Kristie"],"keywords":["GOAL-Model_Search","notion","TECHNIQUE_ReinforcementLearning"],"note":["TL;DR \n\nNew research in reinforcement learning, information extraction and text classification that enables efficient spidering, identifying informative text segments, and populating topic hierarchies is described. \n\nTOO OLD, 1999 \n\n<a href=\"https://www.ri.cmu.edu/pub_files/pub1/mccallum_andrew_1999_2/mccallum_andrew_1999_2.pdf\">cora.dvi (cmu.edu)</a>"],"pages":["12"],"title":["Building Domain-Specific Search Engines with Machine Learning Techniques"]},"creators":{"author":[{"lastName":"McCallum","firstName":"Andrew"},{"lastName":"Nigam","firstName":"Kamal"},{"lastName":"Rennie","firstName":"Jason"},{"lastName":"Seymore","firstName":"Kristie"}]}},{"key":"mcdonnell_empirical_2013","type":"inproceedings","fields":{"abstract":["When APIs evolve, clients make corresponding changes to their applications to utilize new or updated APIs. Despite the benefits of new or updated APIs, developers are often slow to adopt the new APIs. As a first step toward understanding the impact of API evolution on software ecosystems, we conduct an in-depth case study of the co-evolution behavior of Android API and dependent applications using the version history data found in github. Our study confirms that Android is evolving fast at a rate of 115 API updates per month on average. Client adoption, however, is not catching up with the pace of API evolution. About 28% of API references in client applications are outdated with a median lagging time of 16 months. 22% of outdated API usages eventually upgrade to use newer API versions, but the propagation time is about 14 months, much slower than the average API release interval (3 months). Fast evolving APIs are used more by clients than slow evolving APIs but the average time taken to adopt new versions is longer for fast evolving APIs. Further, API usage adaptation code is more defect prone than the one without API usage adaptation. This may indicate that developers avoid API instability."],"author":["McDonnell, Tyler","Ray, Baishakhi","Kim, Miryung"],"booktitle":["2013 IEEE Int Conf Softw. Maint."],"date":["2013-09"],"doi":["10.1109/ICSM.2013.18"],"keywords":["Android API coevolution behavior","Android ecosystem","Androids","API evolution","API stability","API usage adaptation code","application program interfaces","github","Google","History","Humanoid robots","Mobile communication","mobile computing","operating systems (computers)","Smart phones","Software","software ecosystems","software maintenance","version history data"],"note":["TL;DR \n\nAn in-depth case study of the co-evolution behavior of Android API and dependent applications using the version history data found in github confirms that Android is evolving fast at a rate of 115 API updates per month on average, but client adoption, however, is not catching up with the pace of API evolution."],"pages":["70–79"],"title":["An Empirical Study of API Stability and Adoption in the Android Ecosystem"]},"creators":{"author":[{"lastName":"McDonnell","firstName":"Tyler"},{"lastName":"Ray","firstName":"Baishakhi"},{"lastName":"Kim","firstName":"Miryung"}]}},{"key":"mcewenDesigningInternetThings2014","type":"book","fields":{"langid":["english"],"author":["McEwen, Adrian","Cassimally, Hakim"],"date":["2014"],"edition":["Reprinted with corrections"],"isbn":["978-1-118-43062-0 978-1-118-43063-7 978-1-118-43065-1"],"location":["Chichester"],"note":["TL;DR \n\nDesigning the Internet of Things helps software engineers, web designers, product designers, and electronics engineers start designing products using the Internet-of-Things approach and explains how to combine sensors, servos, robotics, Arduino chips, and more with various networks or the Internet to create interactive, cutting-edge devices."],"pagetotal":["324"],"publisher":["Wiley"],"title":["Designing the Internet of things"]},"creators":{"author":[{"lastName":"McEwen","firstName":"Adrian"},{"lastName":"Cassimally","firstName":"Hakim"}]},"sentenceCased":true},{"key":"mckinney2011pandas","type":"article","fields":{"author":["McKinney, Wes","others"],"date":["2011"],"journaltitle":["Python High Perform. Sci. Comput."],"number":["9"],"pages":["1–9"],"publisher":["Seattle"],"title":["Pandas: A foundational Python library for data analysis and statistics"],"volume":["14"]},"creators":{"author":[{"lastName":"McKinney","firstName":"Wes"},{"lastName":"others"}]},"sentenceCased":true},{"key":"McMillan:2011:CSA:2117694.2119646","type":"inproceedings","fields":{"acmid":["2119646"],"author":["McMillan, Collin","Linares-Vasquez, Mario","Poshyvanyk, Denys","Grechanik, Mark"],"booktitle":["Proc. 2011 27th IEEE Int. Conf. Softw. Maint."],"date":["2011"],"ids":["6080801"],"isbn":["978-1-4577-0663-9"],"issn":["1063-6773"],"keywords":["API calls","application program interfaces","application programming interface","automatic categorization","binary executables","byte-code","categorizing software applications","closed source repository","closed-source","closed-source repository","Companies","Entropy","Java","Java repository","learning (artificial intelligence)","legal reasons","Libraries","machine learning","maintenance tasks","open-source","open-source repository","organizational reasons","predict maintenance problems","project management","public domain software","Software","software categorization","software maintenance","software management","software projects","software repository","source code","Support vector machines","third-party library"],"location":["Washington, DC, USA"],"nodoi":["10.1109/ICSM.2011.6080801"],"numpages":["10"],"pages":["343–352"],"publisher":["IEEE Computer Society"],"series":["ICSM '11"],"title":["Categorizing software applications for maintenance"],"url":["https://doi.org/10.1109/ICSM.2011.6080801"]},"creators":{"author":[{"lastName":"McMillan","firstName":"Collin"},{"lastName":"Linares-Vasquez","firstName":"Mario"},{"lastName":"Poshyvanyk","firstName":"Denys"},{"lastName":"Grechanik","firstName":"Mark"}]},"sentenceCased":true},{"key":"mcmillanDetectingSimilarSoftware2012","type":"inproceedings","fields":{"acmid":["2337267"],"author":["McMillan, Collin","Grechanik, Mark","Poshyvanyk, Denys"],"booktitle":["Softw. Eng. ICSE 2012 34th Int. Conf. On"],"date":["2012"],"ids":["McMillan:2012:DSS:2337223.2337267"],"location":["Zurich, Switzerland"],"note":["TL;DR \n\nThe results show with strong statistical significance that CLAN automatically detects similar applications from a large repository of 8,310 Java applications with a higher precision than MUDABlue."],"numpages":["11"],"pages":["364–374"],"publisher":["IEEE"],"title":["Detecting similar software applications"],"url":["http://ieeexplore.ieee.org/abstract/document/6227178/"],"urldate":["2017-03-14"]},"creators":{"author":[{"lastName":"McMillan","firstName":"Collin"},{"lastName":"Grechanik","firstName":"Mark"},{"lastName":"Poshyvanyk","firstName":"Denys"}]},"sentenceCased":true},{"key":"mcmillanRecommendingSourceCode2010","type":"inproceedings","fields":{"acmid":["1808925"],"author":["McMillan, Collin","Poshyvanyk, Denys","Grechanik, Mark"],"booktitle":["Proc. 2Nd Int. Workshop Recomm. Syst. Softw. Eng."],"date":["2010"],"isbn":["978-1-60558-974-9"],"location":["New York, NY, USA"],"nodoi":["10.1145/1808920.1808925"],"numpages":["5"],"pages":["21–25"],"publisher":["ACM"],"series":["RSSE '10"],"title":["Recommending source code examples via API call usages and documentation"],"url":["http://doi.acm.org/10.1145/1808920.1808925"]},"creators":{"author":[{"lastName":"McMillan","firstName":"Collin"},{"lastName":"Poshyvanyk","firstName":"Denys"},{"lastName":"Grechanik","firstName":"Mark"}]},"sentenceCased":true},{"key":"mcnemar","type":"article","fields":{"author":["McNemar, Quinn"],"date":["1947"],"journaltitle":["Psychometrika"],"note":["TL;DR \n\nTwo formulas are presented for judging the significance of the difference between correlated proportions and the chi square equivalent of one of the developed formulas."],"number":["2"],"pages":["153–157"],"title":["Note on the sampling error of the difference between correlated proportions or percentages"],"volume":["12"]},"creators":{"author":[{"lastName":"McNemar","firstName":"Quinn"}]},"sentenceCased":true},{"key":"MDD4DRESProgram","type":"online","fields":{"title":["MDD4DRES Program"],"url":["http://www.mdd4dres.org/program/#JM"],"urldate":["2016-03-10"]},"creators":{}},{"key":"MDE","type":"article","fields":{"langid":["english"],"author":["Schmidt, D. C."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2006-02"],"doi":["10.1109/MC.2006.58"],"ids":["Schmidt06"],"issn":["1558-0814"],"journaltitle":["Computer"],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["2"],"pages":["25–31"],"timestamp":["Wed, 12 Aug 2020 10:30:10 +0200"],"title":["Guest editor's introduction: Model-driven engineering"],"volume":["39"]},"creators":{"author":[{"lastName":"Schmidt","firstName":"D. C."}]},"sentenceCased":true},{"key":"meadHalfCenturySoftware2018","type":"article","fields":{"abstract":["From the aspirational title of the 1968 NATO conference, software engineering has evolved to a well-defined engineering discipline with strong educational underpinnings. The supporting educational foundation has grown from a few courses in programming languages and data structures, evolving through structured programming, correctness formalisms, and state machine abstractions to full curricula and degree programs. With this context in mind, the authors discuss the evolution of software engineering education and pedagogy, software engineering principles, and future needs, drawing specifically on their experience at Carnegie Mellon University. Reflecting on the software development profession today, they believe that formal software engineering education is needed at least as much as it was in earlier decades. However, it must address the increasing diversity of the developer community, and it must be an education based on the enduring principles that will last a lifetime. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Mead, N. R.","Garlan, D.","Shaw, M."],"date":["2018-09"],"doi":["10.1109/MS.2018.290110743"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"note":["TL;DR \n\nReflecting on the software development profession today, the authors believe that formal software engineering education is needed at least as much as it was in earlier decades, but it must address the increasing diversity of the developer community, and it must be an education based on the enduring principles that will last a lifetime."],"number":["5"],"pages":["25–31"],"shorttitle":["Half a Century of Software Engineering Education"],"title":["Half a Century of Software Engineering Education: The CMU Exemplar"],"volume":["35"]},"creators":{"author":[{"lastName":"Mead","firstName":"N. R."},{"lastName":"Garlan","firstName":"D."},{"lastName":"Shaw","firstName":"M."}]}},{"key":"mehrabiSurveyBiasFairness2022","type":"article","fields":{"langid":["english"],"abstract":["With the widespread use of artificial intelligence (AI) systems and applications in our everyday lives, accounting for fairness has gained significant importance in designing and engineering of such systems. AI systems can be used in many sensitive environments to make important and life-changing decisions; thus, it is crucial to ensure that these decisions do not reflect discriminatory behavior toward certain groups or populations. More recently some work has been developed in traditional machine learning and deep learning that address such challenges in different subdomains. With the commercialization of these systems, researchers are becoming more aware of the biases that these applications can contain and are attempting to address them. In this survey, we investigated different real-world applications that have shown biases in various ways, and we listed different sources of biases that can affect AI applications. We then created a taxonomy for fairness definitions that machine learning researchers have defined to avoid the existing bias in AI systems. In addition to that, we examined different domains and subdomains in AI showing what researchers have observed with regard to unfair outcomes in the state-of-the-art methods and ways they have tried to address them. There are still many future directions and solutions that can be taken to mitigate the problem of bias in AI systems. We are hoping that this survey will motivate researchers to tackle these issues in the near future by observing existing work in their respective fields."],"author":["Mehrabi, Ninareh","Morstatter, Fred","Saxena, Nripsuta","Lerman, Kristina","Galstyan, Aram"],"date":["2022-07-31"],"doi":["10.1145/3457607"],"issn":["0360-0300, 1557-7341"],"journaltitle":["ACM Comput. Surv."],"keywords":["LOGSEQ"],"note":["TL;DR \n\nThis survey investigated different real-world applications that have shown biases in various ways, and created a taxonomy for fairness definitions that machine learning researchers have defined to avoid the existing bias in AI systems."],"number":["6"],"pages":["1–35"],"title":["A Survey on Bias and Fairness in Machine Learning"],"volume":["54"]},"creators":{"author":[{"lastName":"Mehrabi","firstName":"Ninareh"},{"lastName":"Morstatter","firstName":"Fred"},{"lastName":"Saxena","firstName":"Nripsuta"},{"lastName":"Lerman","firstName":"Kristina"},{"lastName":"Galstyan","firstName":"Aram"}]}},{"key":"meijerCorelationalModelData2011","type":"article","fields":{"langid":["english"],"author":["Meijer, Erik","Bierman, Gavin"],"date":["2011-04-01"],"doi":["10.1145/1924421.1924436"],"issn":["00010782"],"journaltitle":["Commun. ACM"],"note":["TL;DR \n\nA model based on n-ary relations, a normal form for data base relations, and the concept of a universal data sublanguage are introduced and certain operations on relations are discussed and applied to the problems of redundancy and consistency in the user's model."],"number":["4"],"pages":["49"],"title":["A co-relational model of data for large shared data banks"],"volume":["54"]},"creators":{"author":[{"lastName":"Meijer","firstName":"Erik"},{"lastName":"Bierman","firstName":"Gavin"}]},"sentenceCased":true},{"key":"Mekala2020410","type":"inproceedings","fields":{"abstract":["Adversarial examples pose a serious threat to the robustness of machine learning models in general and of deep learning models in particular. These carefully designed perturbations of input images can cause targeted misclassifications to a label of the attacker's choice, without being detectable to the naked eye. A particular class of adversarial attacks called black box attacks can be used to fool a target model despite not having access to the model parameters or to the input data used to train the model. In this paper, we first build a black box attack against robust multi-model face recognition pipelines and then test it against Google's FaceNet. We then present a novel metamorphic defense pipeline relying on nonlinear image transformations to detect adversarial attacks with a high degree of accuracy. We further use the results to create probabilistic metamorphic relations that define efficient decision boundaries between the safe and adversarial examples; achieving adversarial classification accuracy of up to 96%. © 2020 ACM."],"author":["Mekala, R.R.","Porter, A.","Lindvall, M."],"author_keywords":["adversarial attacks; computer vision; deep learning; machine learning"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3387940.3391483"],"isbn":["978-1-4503-7963-2"],"keywords":["Adversarial classifications","Decision boundary","Deep learning","Face recognition","High degree of accuracy","Image transformations","Machine learning models","Mathematical transformations","Metamorphic relations","Misclassifications","Pipelines","Recognition models","Software engineering","Technical presentations"],"note":["cited By 2 \n\nTL;DR \n\nThis paper builds a black box attack against robust multi-model face recognition pipelines and then presents a novel metamorphic defense pipeline relying on nonlinear image transformations to detect adversarial attacks with a high degree of accuracy."],"pages":["410–417"],"publisher":["Association for Computing Machinery, Inc"],"series":["Proceedings - 2020 IEEE/ACM 42nd International Conference on Software Engineering Workshops, ICSEW 2020"],"source":["Scopus"],"title":["Metamorphic filtering of black-box adversarial attacks on multi-network face recognition models"]},"creators":{"author":[{"lastName":"Mekala","firstName":"R.R."},{"lastName":"Porter","firstName":"A."},{"lastName":"Lindvall","firstName":"M."}]},"sentenceCased":true},{"key":"melanconReusableSemanticsImplementation","type":"article","fields":{"langid":["french"],"author":["Melançon, Olivier"],"keywords":["LOGSEQ"],"title":["Reusable Semantics for Implementation of Python Optimizing Compilers"]},"creators":{"author":[{"lastName":"Melançon","firstName":"Olivier"}]}},{"key":"meloContextAugmentedSoftwareDevelopment2019","type":"inproceedings","fields":{"author":["Melo, Glaucia","Alencar, Paulo","Cowan, Don"],"booktitle":["2019 IEEE Int. Conf. Big Data Big Data"],"date":["2019-12"],"doi":["10.1109/BigData47090.2019.9006245"],"eventtitle":["2019 IEEE International Conference on Big Data (Big Data)"],"isbn":["978-1-72810-858-2"],"location":["Los Angeles, CA, USA"],"note":["TL;DR \n\nIt is believed supporting contextual knowledge through its representation and mining for recommendation and real-time provision can significantly improve traditional and big data software project development."],"pages":["3449–3457"],"publisher":["IEEE"],"shorttitle":["Context-Augmented Software Development in Traditional and Big Data Projects"],"title":["Context-Augmented Software Development in Traditional and Big Data Projects: Literature Review and Preliminary Framework"]},"creators":{"author":[{"lastName":"Melo","firstName":"Glaucia"},{"lastName":"Alencar","firstName":"Paulo"},{"lastName":"Cowan","firstName":"Don"}]}},{"key":"melvilleRecommenderSystems2010","type":"incollection","fields":{"added-at":["2011-11-25T00:00:00.000+0100"],"author":["Melville, Prem","Sindhwani, Vikas"],"biburl":["https://www.bibsonomy.org/bibtex/226b0f0d297e0d3302c28cbf58efad665/dblp"],"booktitle":["Encyclopedia of machine learning"],"date":["2010"],"editor":["Sammut, Claude","Webb, Geoffrey I."],"ee":["http://dx.doi.org/10.1007/978-0-387-30164-8₇05"],"ids":["melville_recommender_2010"],"interhash":["50b623dcfae0cd344f966cb9e9d7b9c0"],"intrahash":["26b0f0d297e0d3302c28cbf58efad665"],"isbn":["978-0-387-30768-8"],"keywords":["dblp"],"note":["TL;DR \n\nAn overview of recommender system, types of RS, problems in RS and future scope of RS are presented, and the future of Recommender System is envisions which may open up new research directions in this domain."],"pages":["829–838"],"publisher":["Springer"],"timestamp":["2011-11-26T11:38:23.000+0100"],"title":["Recommender systems."],"url":["http://dblp.uni-trier.de/db/reference/ml/ml2010.html#MelvilleS10"]},"creators":{"author":[{"lastName":"Melville","firstName":"Prem"},{"lastName":"Sindhwani","firstName":"Vikas"}],"editor":[{"lastName":"Sammut","firstName":"Claude"},{"lastName":"Webb","firstName":"Geoffrey I."}]},"sentenceCased":true},{"key":"mendoncaDevelopingSelfAdaptiveMicroservice2021","type":"article","fields":{"langid":["english"],"author":["Mendonca, Nabor C.","Jamshidi, Pooyan","Garlan, David","Pahl, Claus"],"date":["2021-03"],"doi":["10.1109/MS.2019.2955937"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"keywords":["LOGSEQ"],"note":["TL;DR \n\nKey challenges for the development of microservice applications as self-adaptive systems are identified, using a cloud-based intelligent video-surveillance application as a motivating example and potential new directions for addressing most of the identified challenges are suggested."],"number":["2"],"pages":["70–79"],"shorttitle":["Developing Self-Adaptive Microservice Systems"],"title":["Developing Self-Adaptive Microservice Systems: Challenges and Directions"],"volume":["38"]},"creators":{"author":[{"lastName":"Mendonca","firstName":"Nabor C."},{"lastName":"Jamshidi","firstName":"Pooyan"},{"lastName":"Garlan","firstName":"David"},{"lastName":"Pahl","firstName":"Claus"}]}},{"key":"Meng2019","type":"inproceedings","fields":{"abstract":["The model-driven power allocation (PA) algorithms in the wireless cellular networks with interfering multiple-access channel (IMAC) have been investigated for decades. Nowadays, the data-driven model-free machine learning-based approaches are rapidly developing in this field, and among them the deep reinforcement learning (DRL) is proved to be of great potential. Different from supervised learning, the DRL takes advantages of exploration and exploitation to maximize the objective function under certain constraints. In our paper, we propose a two-step training framework. First, with the off-line learning in simulated environment, a deep Q network (DQN) is trained with deep Q learning (DQL) algorithm, which is well-designed to be in consistent with this PA issue. Second, the DQN will be further fine-tuned with real data in on-line training procedure. The simulation results show that the proposed DQN achieves the highest averaged sum-rate, comparing to the ones with present standard DQL training. With different user densities, our DQN outperforms benchmark algorithms and thus a good generalization ability is verified. © 2019 IEEE."],"art_number":["8761431"],"author":["Meng, F.","Chen, P.","Wu, L."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/ICC.2019.8761431"],"isbn":["978-1-5386-8088-9"],"issn":["15503607"],"note":["cited By 33 \n\nTL;DR \n\nA deep Q network (DQN) is trained with deep Q learning (DQL) algorithm, which is well-designed to be in consistent with this PA issue, and results show that the proposed DQN achieves the highest averaged sum-rate, comparing to the ones with present standard DQL training."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["IEEE International Conference on Communications"],"source":["Scopus"],"title":["Power allocation in multi-user cellular networks with deep Q learning approach"],"volume":["2019-May"]},"creators":{"author":[{"lastName":"Meng","firstName":"F."},{"lastName":"Chen","firstName":"P."},{"lastName":"Wu","firstName":"L."}]},"sentenceCased":true},{"key":"Mens06","type":"inproceedings","fields":{"langid":["english"],"author":["Mens, Tom"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Gener. Transform. Tech. Softw. Eng. Int. Summer Sch. GTTSE 2005 Braga Port. July 4-8 2005 Revis. Pap."],"date":["2005"],"doi":["10.1007/11877028\\_7"],"editor":["Lämmel, Ralf","Saraiva, João","Visser, Joost"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis work focuses on the activity of model refactoring, and shows how graph transformation theory can provide formal support for this activity, and how such support can be implemented in state-of-the-art graph transformation tools such as AGG and Fujaba."],"pages":["219–257"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Sun, 26 Apr 2020 17:09:18 +0200"],"title":["On the use of graph transformations for model refactoring"],"volume":["4143"]},"creators":{"author":[{"lastName":"Mens","firstName":"Tom"}],"editor":[{"lastName":"Lämmel","firstName":"Ralf"},{"lastName":"Saraiva","firstName":"João"},{"lastName":"Visser","firstName":"Joost"}]},"sentenceCased":true},{"key":"MenziesBCMLSTZ13","type":"article","fields":{"author":["Menzies, Tim","Butcher, Andrew","Cok, David R.","Marcus, Andrian","Layman, Lucas","Shull, Forrest","Turhan, Burak","Zimmermann, Thomas"],"date":["2013"],"journaltitle":["IEEE Trans Softw. Eng"],"note":["TL;DR \n\nIt is concluded that when researchers attempt to draw lessons from some historical data source, they should ignore any existing local divisions into multiple sources, cluster across all available data, then restrict the learning of lessons to the clusters from other sources that are nearest to the test data."],"number":["6"],"pages":["822–834"],"title":["Local versus global lessons for defect prediction and effort estimation"],"volume":["39"]},"creators":{"author":[{"lastName":"Menzies","firstName":"Tim"},{"lastName":"Butcher","firstName":"Andrew"},{"lastName":"Cok","firstName":"David R."},{"lastName":"Marcus","firstName":"Andrian"},{"lastName":"Layman","firstName":"Lucas"},{"lastName":"Shull","firstName":"Forrest"},{"lastName":"Turhan","firstName":"Burak"},{"lastName":"Zimmermann","firstName":"Thomas"}]},"sentenceCased":true},{"key":"menziesFiveLawsSE2020","type":"article","fields":{"langid":["english"],"author":["Menzies, Tim"],"date":["2020-01"],"doi":["10.1109/MS.2019.2954841"],"ids":["menziesFiveLawsSE2020a,menziesFiveLawsSE2020b"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"keywords":["DONE"],"note":["TL;DR \n\nIt is time to talk about software engineering (SE) for artificial intelligence (AI) as industry is becoming increasingly dependent on AI software."],"number":["1"],"pages":["81–85"],"title":["The Five Laws of SE for AI"],"volume":["37"]},"creators":{"author":[{"lastName":"Menzies","firstName":"Tim"}]}},{"key":"menziesShockinglySimpleKEYS2021","type":"article","fields":{"langid":["english"],"author":["Menzies, Tim"],"date":["2021-03"],"doi":["10.1109/MS.2020.3043014"],"ids":["menziesShockinglySimpleKEYS2021a"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nAs 2020 drew to a close, I was thinking about what lessons the authors have learned about software engineering (SE) for artificial intelligence (AI)-things that they can believe now but, in the last century, would have seemed somewhat shocking."],"number":["2"],"pages":["114–118"],"shorttitle":["Shockingly Simple"],"title":["Shockingly Simple:\"KEYS\" for Better AI for SE"],"volume":["38"]},"creators":{"author":[{"lastName":"Menzies","firstName":"Tim"}]}},{"key":"menziesSoftwareAnalyticsWhat2018","type":"article","fields":{"abstract":["Knowing what factors control software projects is very useful because humans might not understand those factors. Developers sometimes develop their own ideas about good and bad software, on the basis of just a few past projects. Using software analytics, we can correct those misconceptions. Software analytics lets software engineers learn about AI techniques. Once they learn those techniques, they can build and ship innovative AI tools. That is, software analytics is the training ground for the next generation of AI-literate software engineers. This article is part of a special issue on software engineering’s 50th anniversary."],"author":["Menzies, T.","Zimmermann, T."],"date":["2018-09"],"doi":["10.1109/MS.2018.290111035"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["artificial intelligence","software engineering"],"note":["TL;DR \n\nSoftware analytics lets software engineers learn about AI techniques, and once they learn those techniques, they can build and ship innovative AI tools."],"number":["5"],"pages":["64–70"],"shorttitle":["Software Analytics"],"title":["Software Analytics: What’s Next?"],"volume":["35"]},"creators":{"author":[{"lastName":"Menzies","firstName":"T."},{"lastName":"Zimmermann","firstName":"T."}]}},{"key":"merilinnaStateArtPractice2006","type":"inproceedings","fields":{"author":["Merilinna, Janne","Matinlassi, Mari"],"booktitle":["Softw. Eng. Adv. Appl. 2006 SEAA06 32nd EUROMICRO Conf. On"],"date":["2006"],"note":["TL;DR \n\nThe main observations are that the lack of documentation and heterogeneity of platforms are problems that neither the state of the art or practice could solve and both techniques and methods for predicting and solving both architecture and component level integration problems were not used in practice."],"pages":["170–177"],"publisher":["IEEE"],"title":["State of the art and practice of opensource component integration"],"url":["http://ieeexplore.ieee.org/abstract/document/1690138/"],"urldate":["2017-02-25"]},"creators":{"author":[{"lastName":"Merilinna","firstName":"Janne"},{"lastName":"Matinlassi","firstName":"Mari"}]},"sentenceCased":true},{"key":"MessageRoSE20182018","type":"book","fields":{"date":["2018"],"ids":["MessageRoSE20182018a"],"journaltitle":["Proceedings - International Conference on Software Engineering"],"publisher":["IEEE Computer Society"],"title":["Message from the RoSE 2018 Co-Organizers"],"volume":["137815"]},"creators":{}},{"key":"meyerSoftwareEngineering2015","type":"book","fields":{"date":["2015"],"doi":["10.1007/978-3-319-28406-4"],"editor":["Meyer, Bertrand","Nordio, Martin"],"ids":["laser_software_2015"],"isbn":["978-3-319-28405-7 978-3-319-28406-4"],"location":["Cham"],"note":["OCLC: 944106474 \n\nOCLC: 944106474 \n\nTL;DR \n\nThe need for automation of software development is discussed in the context of next-generation computing and the lag in the use of available tools is pointed out."],"publisher":["Springer International Publishing"],"series":["Lecture Notes in Computer Science"],"title":["Software Engineering"],"volume":["8987"]},"creators":{"editor":[{"lastName":"Meyer","firstName":"Bertrand"},{"lastName":"Nordio","firstName":"Martin"}]}},{"key":"miEmpiricalCharacterizationIFTTT2017","type":"inproceedings","fields":{"langid":["english"],"abstract":["IFTTT is a popular trigger-action programming platform whose applets can automate more than 400 services of IoT devices and web applications. We conduct an empirical study of IFTTT using a combined approach of analyzing data collected for 6 months and performing controlled experiments using a custom testbed. We profile the interactions among different entities, measure how applets are used by end users, and test the performance of applet execution. Overall we observe the fast growth of the IFTTT ecosystem and its increasing usage for automating IoT-related tasks, which correspond to 52% of all services and 16% of the applet usage. We also observe several performance inefficiencies and identify their causes."],"author":["Mi, Xianghang","Qian, Feng","Zhang, Ying","Wang, XiaoFeng"],"booktitle":["Proc. 2017 Internet Meas. Conf. - IMC 17"],"date":["2017"],"doi":["10.1145/3131365.3131369"],"eventtitle":["The 2017 Internet Measurement Conference"],"isbn":["978-1-4503-5118-8"],"location":["London, United Kingdom"],"pages":["398–404"],"publisher":["ACM Press"],"shorttitle":["An empirical characterization of IFTTT"],"title":["An empirical characterization of IFTTT: Ecosystem, usage, and performance"]},"creators":{"author":[{"lastName":"Mi","firstName":"Xianghang"},{"lastName":"Qian","firstName":"Feng"},{"lastName":"Zhang","firstName":"Ying"},{"lastName":"Wang","firstName":"XiaoFeng"}]},"sentenceCased":true},{"key":"Mihalcea:2006:CKM:1597538.1597662","type":"inproceedings","fields":{"acmid":["1597662"],"author":["Mihalcea, Rada","Corley, Courtney","Strapparava, Carlo"],"booktitle":["Proc. 21st Natl. Conf. Artif. Intell. - Vol. 1"],"date":["2006"],"isbn":["978-1-57735-281-5"],"location":["Boston, Massachusetts"],"numpages":["6"],"pages":["775–780"],"publisher":["AAAI Press"],"series":["AAAI'06"],"title":["Corpus-based and knowledge-based measures of text semantic similarity"],"url":["http://dl.acm.org/citation.cfm?id=1597538.1597662"]},"creators":{"author":[{"lastName":"Mihalcea","firstName":"Rada"},{"lastName":"Corley","firstName":"Courtney"},{"lastName":"Strapparava","firstName":"Carlo"}]},"sentenceCased":true},{"key":"millerMDAGuideVersion2003","type":"report","fields":{"author":["Miller, J.","Mukerji, J."],"date":["2003"],"institution":["Object Management Group (OMG)"],"keywords":["architecture model-driven"],"note":["TL;DR \n\nEvery organization on the planet consisting of more than one person has already realized that their information technology infrastructure is effectively a distributed computing system, which means that CPUs must be intimately linked to the networks of the world and be capable of freely passing and receiving information."],"title":["MDA Guide Version 1.0.1"]},"creators":{"author":[{"lastName":"Miller","firstName":"J."},{"lastName":"Mukerji","firstName":"J."}]}},{"key":"millerWordNetLexicalDatabase1995","type":"article","fields":{"acmid":["219748"],"address":["New York, NY, USA"],"author":["Miller, George A."],"date":["1995-11"],"issn":["0001-0782"],"issue_date":["Nov. 1995"],"journaltitle":["Commun. ACM"],"nodoi":["10.1145/219717.219748"],"note":["TL;DR \n\nWordNet1 provides a more effective combination of traditional lexicographic information and modern computing, and is an online lexical database designed for use under program control."],"number":["11"],"numpages":["3"],"pages":["39–41"],"publisher":["ACM"],"title":["WordNet: A lexical database for english"],"url":["http://doi.acm.org/10.1145/219717.219748"],"volume":["38"]},"creators":{"author":[{"lastName":"Miller","firstName":"George A."}]},"sentenceCased":true},{"key":"minoliBlockchainMechanismsIoT2018","type":"article","fields":{"langid":["english"],"abstract":["The deployment of Internet of Things (IoT) results in an enlarged attack surface that requires end-to-end security mitigation. IoT applications range from mission-critical predicaments (e.g., Smart Grid, Intelligent Transportation Systems, video surveillance, e-health) to business-oriented applications (e.g., banking, logistics, insurance, and contract law). There is a need for comprehensive support of security in the IoT, especially for mission-critical applications, but also for the down-stream business applications. A number of security techniques and approaches have been proposed and/or utilized. Blockchain mechanisms (BCMs) play a role in securing many IoT-oriented applications by becoming part of a security mosaic, in the context of a defenses-in-depth/Castle Approach. A blockchain is a database that stores all processed transactions – or data – in chronological order, in a set of computer memories that are tamperproof to adversaries. These transactions are then shared by all participating users. Information is stored and/or published as a public ledger that is infeasible to modify; every user or node in the system retains the same ledger as all other users or nodes in the network. This paper highlights some IoT environments where BCMs play an important role, while at the same time pointing out that BCMs are only part of the IoT Security (IoTSec) solution."],"author":["Minoli, Daniel","Occhiogrosso, Benedict"],"date":["2018-09"],"doi":["10.1016/j.iot.2018.05.002"],"issn":["25426605"],"journaltitle":["Internet Things"],"pages":["1–13"],"title":["Blockchain mechanisms for IoT security"],"volume":["1–2"]},"creators":{"author":[{"lastName":"Minoli","firstName":"Daniel"},{"lastName":"Occhiogrosso","firstName":"Benedict"}]},"sentenceCased":true},{"key":"miorandiInternetThingsVision2012","type":"article","fields":{"langid":["english"],"abstract":["The term ‘‘Internet-of-Things’’ is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. Internet-of-Things envisions a future in which digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a whole new class of applications and services. In this article, we present a survey of technologies, applications and research challenges for Internetof-Things."],"author":["Miorandi, Daniele","Sicari, Sabrina","De Pellegrini, Francesco","Chlamtac, Imrich"],"date":["2012-09"],"doi":["10.1016/j.adhoc.2012.02.016"],"issn":["15708705"],"journaltitle":["Ad Hoc Networks"],"keywords":["relevant"],"number":["7"],"pages":["1497–1516"],"shorttitle":["Internet of things"],"title":["Internet of things: Vision, applications and research challenges"],"volume":["10"]},"creators":{"author":[{"lastName":"Miorandi","firstName":"Daniele"},{"lastName":"Sicari","firstName":"Sabrina"},{"lastName":"De Pellegrini","firstName":"Francesco"},{"lastName":"Chlamtac","firstName":"Imrich"}]},"sentenceCased":true},{"key":"miorNoSESchemaDesign2016","type":"inproceedings","fields":{"author":["Mior, Michael J.","Salem, Kenneth","Aboulnaga, Ashraf","Liu, Rui"],"booktitle":["2016 IEEE 32nd Int. Conf. Data Eng. ICDE"],"date":["2016-05"],"doi":["10.1109/ICDE.2016.7498239"],"eventtitle":["2016 IEEE 32nd International Conference on Data Engineering (ICDE)"],"isbn":["978-1-5090-2020-1"],"location":["Helsinki, Finland"],"note":["TL;DR \n\nThis work presents a system for recommending database schemas for NoSQL applications that is able to capture rules of thumb used by expert designers without explicitly encoding the rules, and implemented a prototype of this approach for the Cassandra extensible record store."],"pages":["181–192"],"publisher":["IEEE"],"shorttitle":["NoSE"],"title":["NoSE: Schema design for NoSQL applications"]},"creators":{"author":[{"lastName":"Mior","firstName":"Michael J."},{"lastName":"Salem","firstName":"Kenneth"},{"lastName":"Aboulnaga","firstName":"Ashraf"},{"lastName":"Liu","firstName":"Rui"}]},"sentenceCased":true},{"key":"Miranda:2008:ICF:1486927.1487083","type":"inproceedings","fields":{"acmid":["1487083"],"author":["Miranda, Catarina","Jorge, Alípio M."],"booktitle":["Proc. 2008 IEEEWICACM Int. Conf. Web Intell. Intell. Agent Technol. - Vol. 01"],"date":["2008"],"isbn":["978-0-7695-3496-1"],"keywords":["Incremental Collaborative Filtering","Web Recommender Systems"],"location":["Washington, DC, USA"],"nodoi":["10.1109/WIIAT.2008.263"],"note":["TL;DR \n\nAn incremental version of item-based CF for implicit binary ratings is proposed, and it is observed that recall and precision tend to improve when the authors continuously add information to the recommender model, and that the time spent for recommendation does not degrade."],"numpages":["4"],"pages":["389–392"],"publisher":["IEEE Computer Society"],"series":["WI-IAT '08"],"title":["Incremental collaborative filtering for binary ratings"],"url":["http://dx.doi.org/10.1109/WIIAT.2008.263"]},"creators":{"author":[{"lastName":"Miranda","firstName":"Catarina"},{"lastName":"Jorge","firstName":"Alípio M."}]},"sentenceCased":true},{"key":"MiSE2017ProgramPreparatory","type":"online","fields":{"abstract":["Program 1 Registrants (33) 3 Preparatory emails 5 To presenters 6 To attendees 6 Program Sunday 21 May 2017 09:00 - 09:05 Welcome from the organizers 09:05 - 10:30 Keynote 1: Empirical Studies into UML in Practice: Pitfalls and Prospects, Michel Chaudron [abstract] [Session chair: Davide] ..."],"organization":["Google Docs"],"title":["MiSE2017 - Program and preparatory emails"],"url":["https://docs.google.com/document/d/1FVBtlKZzdkNVYqea-9nB2YCpicTohzntjEcx2ZKcqjA/edit?usp=sharing&usp=embed_facebook"],"urldate":["2017-05-08"]},"creators":{},"sentenceCased":true},{"key":"misraSoftwareClusteringUnifying2012","type":"inproceedings","fields":{"author":["Misra, J.","Annervaz, K. M.","Kaulgud, V.","Sengupta, S.","Titus, G."],"booktitle":["2012 19th Work. Conf. Reverse Eng."],"date":["2012-10"],"doi":["10.1109/WCRE.2012.21"],"issn":["2375-5369"],"keywords":["application portfolios","architectural recovery","automated component labeling","cluster selection","component discovery","distance estimation","feature extraction","feature location problem","graph theory","high level component architecture extraction","information quality enhancement","inter-component interaction generation","latent semantic indexing","lexical analysis","multiobjective global modularity criterion","multiple hierarchical levels","noise reduction","object-oriented programming","pattern clustering","program comprehension","program diagnostics","Reverse engineering","semantic features","software architecture","software clustering","source code elements","syntactic features","vector space model","weighted graph partitioning"],"pages":["113–122"],"title":["Software clustering: Unifying syntactic and semantic features"]},"creators":{"author":[{"lastName":"Misra","firstName":"J."},{"lastName":"Annervaz","firstName":"K. M."},{"lastName":"Kaulgud","firstName":"V."},{"lastName":"Sengupta","firstName":"S."},{"lastName":"Titus","firstName":"G."}]},"sentenceCased":true},{"key":"MisurazioneDiGas","type":"online","fields":{"title":["Misurazione di gas o di ulteriore protocollo di studio Vaillant e di E-Bus di controllo / Riscaldamento / Casa intelligente 1-Wire con le proprie mani / Ab-Log.Ru"],"url":["http://www.ab-log.ru/smart-house/heating-automation/gaz_meter"],"urldate":["2015-04-04"]},"creators":{},"sentenceCased":true},{"key":"mitchellFAIRDataPipeline2021","type":"article","fields":{"abstract":["Modern epidemiological analyses to understand and combat the spread of disease depend critically on access to, and use of, data. Rapidly evolving data, such as data streams changing during a disease outbreak, are particularly challenging. Data management is further complicated by data being imprecisely identified when used. Public trust in policy decisions resulting from such analyses is easily damaged and is often low, with cynicism arising where claims of \"following the science\" are made without accompanying evidence. Tracing the provenance of such decisions back through open software to primary data would clarify this evidence, enhancing the transparency of the decision-making process. Here, we demonstrate a Findable, Accessible, Interoperable and Reusable (FAIR) data pipeline developed during the COVID-19 pandemic that allows easy annotation of data as they are consumed by analyses, while tracing the provenance of scientific outputs back through the analytical source code to data sources. Such a tool provides a mechanism for the public, and fellow scientists, to better assess the trust that should be placed in scientific evidence, while allowing scientists to support policy-makers in openly justifying their decisions. We believe that tools such as this should be promoted for use across all areas of policy-facing research."],"author":["Mitchell, Sonia Natalie","Lahiff, Andrew","Cummings, Nathan","Hollocombe, Jonathan","Boskamp, Bram","Reddyhoff, Dennis","Field, Ryan","Zarebski, Kristian","Wilson, Antony","Burke, Martin","Archibald, Blair","Bessell, Paul","Blackwell, Richard","Boden, Lisa A.","Brett, Alys","Brett, Sam","Dundas, Ruth","Enright, Jessica","Gonzalez-Beltran, Alejandra N.","Harris, Claire","Hinder, Ian","Hughes, Christopher David","Knight, Martin","Mano, Vino","McMonagle, Ciaran","Mellor, Dominic","Mohr, Sibylle","Marion, Glenn","Matthews, Louise","McKendrick, Iain J.","Pooley, Christopher Mark","Porphyre, Thibaud","Reeves, Aaron","Townsend, Edward","Turner, Robert","Walton, Jeremy","Reeve, Richard"],"date":["2021-10-13"],"eprint":["2110.07117"],"eprintclass":["cs, q-bio"],"eprinttype":["arxiv"],"journaltitle":["ArXiv211007117 Cs Q-Bio"],"keywords":["Computer Science - Digital Libraries","Quantitative Biology - Quantitative Methods"],"shorttitle":["FAIR Data Pipeline"],"title":["FAIR Data Pipeline: Provenance-driven data management for traceable scientific workflows"],"url":["http://arxiv.org/abs/2110.07117"],"urldate":["2022-02-24"]},"creators":{"author":[{"lastName":"Mitchell","firstName":"Sonia Natalie"},{"lastName":"Lahiff","firstName":"Andrew"},{"lastName":"Cummings","firstName":"Nathan"},{"lastName":"Hollocombe","firstName":"Jonathan"},{"lastName":"Boskamp","firstName":"Bram"},{"lastName":"Reddyhoff","firstName":"Dennis"},{"lastName":"Field","firstName":"Ryan"},{"lastName":"Zarebski","firstName":"Kristian"},{"lastName":"Wilson","firstName":"Antony"},{"lastName":"Burke","firstName":"Martin"},{"lastName":"Archibald","firstName":"Blair"},{"lastName":"Bessell","firstName":"Paul"},{"lastName":"Blackwell","firstName":"Richard"},{"lastName":"Boden","firstName":"Lisa A."},{"lastName":"Brett","firstName":"Alys"},{"lastName":"Brett","firstName":"Sam"},{"lastName":"Dundas","firstName":"Ruth"},{"lastName":"Enright","firstName":"Jessica"},{"lastName":"Gonzalez-Beltran","firstName":"Alejandra N."},{"lastName":"Harris","firstName":"Claire"},{"lastName":"Hinder","firstName":"Ian"},{"lastName":"Hughes","firstName":"Christopher David"},{"lastName":"Knight","firstName":"Martin"},{"lastName":"Mano","firstName":"Vino"},{"lastName":"McMonagle","firstName":"Ciaran"},{"lastName":"Mellor","firstName":"Dominic"},{"lastName":"Mohr","firstName":"Sibylle"},{"lastName":"Marion","firstName":"Glenn"},{"lastName":"Matthews","firstName":"Louise"},{"lastName":"McKendrick","firstName":"Iain J."},{"lastName":"Pooley","firstName":"Christopher Mark"},{"lastName":"Porphyre","firstName":"Thibaud"},{"lastName":"Reeves","firstName":"Aaron"},{"lastName":"Townsend","firstName":"Edward"},{"lastName":"Turner","firstName":"Robert"},{"lastName":"Walton","firstName":"Jeremy"},{"lastName":"Reeve","firstName":"Richard"}]},"sentenceCased":true},{"key":"mittelmannPersonalKnowledgeManagement2016","type":"article","fields":{"langid":["english"],"author":["Mittelmann, Angelika"],"date":["2016"],"doi":["10.1016/j.procs.2016.09.105"],"issn":["18770509"],"journaltitle":["Procedia Computer Science"],"pages":["117–124"],"title":["Personal Knowledge Management as Basis for Successful Organizational Knowledge Management in the Digital Age"],"volume":["99"]},"creators":{"author":[{"lastName":"Mittelmann","firstName":"Angelika"}]}},{"key":"MMR02","type":"inproceedings","fields":{"author":["Melnik, S.","Garcia-Molina, H.","Rahm, E."],"booktitle":["Proc. 18th Int. Conf. Data Eng. 2002"],"date":["2002"],"doi":["10.1109/ICDE.2002.994702"],"issn":["1063-6382"],"keywords":["accuracy metric","biochemical applications","Biochemistry","Bioinformatics","Catalogs","data handling","data schemas","data structures","Data structures","data warehouses","data warehousing","e-business","filters","fixpoint computation","Floods","graph matching algorithm","high-level operators","Humans","Information management","information models","mappings","Matched filters","pattern matching","schema matching","similarity flooding","Testing","user labor savings","Warehousing"],"note":["TL;DR \n\nThis paper presents a matching algorithm based on a fixpoint computation that is usable across different scenarios and conducts a user study, in which the accuracy metric was used to estimate the labor savings that the users could obtain by utilizing the algorithm to obtain an initial matching."],"pages":["117–128"],"title":["Similarity flooding: A versatile graph matching algorithm and its application to schema matching"]},"creators":{"author":[{"lastName":"Melnik","firstName":"S."},{"lastName":"Garcia-Molina","firstName":"H."},{"lastName":"Rahm","firstName":"E."}]},"sentenceCased":true},{"key":"mmsim2","type":"incollection","fields":{"author":["Falleri, Jean-Rémy","Huchard, Marianne","Lafourcade, Mathieu","Nebut, Clémentine"],"booktitle":["Model driven engineering languages and systems"],"date":["2008"],"doi":["10.1007/978-3-540-87875-9_24"],"editor":["Czarnecki, Krzysztof","Ober, Ileana","Bruel, Jean-Michel","Uhl, Axel","Völter, Markus"],"isbn":["978-3-540-87874-2"],"note":["TL;DR \n\nThis paper proposes an approach that automatically detects mappings between two metamodels and uses them to generate an alignment between those metAModels, built on the Similarity Flooding algorithm used in the fields of schema matching and ontology alignment."],"pages":["326–340"],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture notes in computer science"],"title":["Metamodel matching for automatic model transformation generation"],"volume":["5301"]},"creators":{"author":[{"lastName":"Falleri","firstName":"Jean-Rémy"},{"lastName":"Huchard","firstName":"Marianne"},{"lastName":"Lafourcade","firstName":"Mathieu"},{"lastName":"Nebut","firstName":"Clémentine"}],"editor":[{"lastName":"Czarnecki","firstName":"Krzysztof"},{"lastName":"Ober","firstName":"Ileana"},{"lastName":"Bruel","firstName":"Jean-Michel"},{"lastName":"Uhl","firstName":"Axel"},{"lastName":"Völter","firstName":"Markus"}]},"sentenceCased":true},{"key":"mobasherAttacksRemediesCollaborative2007","type":"article","fields":{"langid":["english"],"author":["Mobasher, Bamshad","Burke, Robin","Bhaumik, Runa","Sandvig, J.J."],"date":["2007-05"],"doi":["10.1109/MIS.2007.45"],"ids":["4216981,mobasher_attacks_2007"],"issn":["1541-1672"],"journaltitle":["IEEE Intell. Syst."],"number":["3"],"pages":["56–63"],"title":["Attacks and Remedies in Collaborative Recommendation"],"volume":["22"]},"creators":{"author":[{"lastName":"Mobasher","firstName":"Bamshad"},{"lastName":"Burke","firstName":"Robin"},{"lastName":"Bhaumik","firstName":"Runa"},{"lastName":"Sandvig","firstName":"J.J."}]}},{"key":"MobileAutonomousSystems","type":"online","fields":{"title":["Mobile Autonomous Systems Laboratory | Electrical Engineering and Computer Science | MIT OpenCourseWare"],"url":["http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-186-mobile-autonomous-systems-laboratory-january-iap-2005/index.htm"],"urldate":["2016-01-23"]},"creators":{}},{"key":"mocriiIoTbasedSmartHomes2018","type":"article","fields":{"langid":["english"],"abstract":["This article presents a review of major technologies of IoT-based smart homes. It starts with definition of the smart home that sets the perspective adopted in the review. In addition to describing the complementary user and system functions of the smart home, it introduces its general, IoT-based architecture and sets smart homes within the larger context of the smart grid. The following sections concentrate on software solutions and components of smart home management systems, related communication technologies, and issues of privacy and security associated with the connected nature of modern smart homes. A separate section presents current challenges of smart home technologies and their dispersion, and points to some interesting solutions and future trends."],"author":["Mocrii, Dragos","Chen, Yuxiang","Musilek, Petr"],"date":["2018-09"],"doi":["10.1016/j.iot.2018.08.009"],"issn":["25426605"],"journaltitle":["Internet Things"],"pages":["81–98"],"shorttitle":["IoT-based smart homes"],"title":["IoT-based smart homes: A review of system architecture, software, communications, privacy and security"],"volume":["1–2"]},"creators":{"author":[{"lastName":"Mocrii","firstName":"Dragos"},{"lastName":"Chen","firstName":"Yuxiang"},{"lastName":"Musilek","firstName":"Petr"}]},"sentenceCased":true},{"key":"ModeldrivenEngineeringScientific","type":"online","fields":{"title":["Model-driven Engineering of Scientific Applications - Mohamed Almorsy Abdelrazek"],"url":["https://sites.google.com/site/mohamedalmorsy/home/research/model-driven-engineering-of-scientific-applications"],"urldate":["2017-02-23"]},"creators":{},"sentenceCased":true},{"key":"ModelDrivenSustainabilityEvaluation2020","type":"online","fields":{"langid":["american"],"date":["2020-03-01"],"title":["Toward Model-Driven Sustainability Evaluation – Communications of the ACM"],"url":["https://cacm.acm.org/research/toward-model-driven-sustainability-evaluation/"],"urldate":["2024-04-02"]},"creators":{}},{"key":"MODELS20","type":"online","fields":{"langid":["english"],"abstract":["An online LaTeX editor that's easy to use. No installation, real-time collaboration, version control, hundreds of LaTeX templates, and more."],"title":["MODELS20"],"url":["https://www.overleaf.com/8979411763njfrwbxdyfcg"],"urldate":["2020-02-13"]},"creators":{}},{"key":"MODELS24_paper_2827Pdf","type":"misc","fields":{"title":["MODELS24_paper_2827.Pdf"]},"creators":{}},{"key":"MODELS24_paper_2991Pdf","type":"misc","fields":{"title":["MODELS24_paper_2991.Pdf"]},"creators":{}},{"key":"MODELS24_paper_8050Pdf","type":"misc","fields":{"title":["MODELS24_paper_8050.Pdf"]},"creators":{}},{"key":"ModelTypingSpringer","type":"online","fields":{"title":["On model typing - Springer"],"url":["http://link.springer.com/article/10.1007%2Fs10270-006-0036-6"],"urldate":["2015-04-01"]},"creators":{},"sentenceCased":true},{"key":"MoDeS3","type":"online","fields":{"title":["MoDeS3"],"url":["http://modes3.tumblr.com/"],"urldate":["2016-08-21"]},"creators":{}},{"key":"MohagheghiD07","type":"inproceedings","fields":{"langid":["english"],"author":["Mohagheghi, Parastoo","Dehlen, Vegard"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Models Softw. Eng. Workshop Symp. MoDELS 2007 Nashv. TN USA Sept. 30 - Oct. 5 2007 Rep. Revis. Sel. Pap."],"date":["2007"],"doi":["10.1007/978-3-540-69073-3\\_29"],"editor":["Giese, Holger"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["275–286"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Wed, 23 Feb 2022 12:58:02 +0100"],"title":["Developing a quality framework for model-driven engineering"],"volume":["5002"]},"creators":{"author":[{"lastName":"Mohagheghi","firstName":"Parastoo"},{"lastName":"Dehlen","firstName":"Vegard"}],"editor":[{"lastName":"Giese","firstName":"Holger"}]},"sentenceCased":true},{"key":"mohagheghiMetamodelSpecifyingQuality2008","type":"inproceedings","fields":{"author":["Mohagheghi, Parastoo","Dehlen, Vegard"],"booktitle":["Proc Nord. Workshop Model Driven Eng."],"date":["2008"],"pages":["51–65"],"title":["A metamodel for specifying quality models in model-driven engineering"],"url":["http://www.sintef-group.com/globalassets/upload/ikt/9012/qualitymetamodel_final.pdf"],"urldate":["2015-12-02"]},"creators":{"author":[{"lastName":"Mohagheghi","firstName":"Parastoo"},{"lastName":"Dehlen","firstName":"Vegard"}]},"sentenceCased":true},{"key":"Mohanty2015239","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - Int. Symp. Qual. Electron. Des., ISQED"],"affiliation":["NanoSystem Design Laboratory (NSDL), Department of Computer Science and Engineering, University of North Texas, Denton, TX 76207, United States; NanoSystem Design Laboratory (NSDL), Department of Electrical Engineering Technology, University of North Texas, Denton, TX 76207, United States"],"art_number":["7085432"],"author":["Mohanty, S.P.","Kougianos, E.","Yanambaka, V.P."],"date":["2015"],"document_type":["Conference Paper"],"doi":["10.1109/ISQED.2015.7085432"],"isbn":["978-1-4799-7581-5"],"issn":["19483287"],"note":["cited By 1 \n\nTL;DR \n\nA process-variation aware design flow for ultra-fast variability-aware optimization of nano-CMOS based physical design of analog circuits and combines Kriging bootstrapped Neural Network metamodels with a Particle Swarm Optimization (PSO) algorithm in the design optimization flow."],"pages":["239–242"],"publisher":["IEEE Computer Society"],"series":["Proceedings - International Symposium on Quality Electronic Design, ISQED"],"source":["Scopus"],"title":["Ultra-fast variability-aware optimization of mixed-signal designs using bootstrapped kriging"],"volume":["2015-April"]},"creators":{"author":[{"lastName":"Mohanty","firstName":"S.P."},{"lastName":"Kougianos","firstName":"E."},{"lastName":"Yanambaka","firstName":"V.P."}]},"sentenceCased":true},{"key":"Moin2022144","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc Int Conf Software Eng"],"affiliation":["Technical Univ. of Munich (TUM), Dept. of Informatics, Germany; DriotData Ug, Munich, Germany; Univ. of Antwerp & Flanders Make, Dept. of Computer Science, Belgium; Univ. of Reading, Dept. of Computer Science, United Kingdom; Tum, Science Institute, Dept. of Informatics & Munich Data, Germany"],"author":["Moin, A.","Mituca, A.","Challenger, M.","Badii, A.","Gunnemann, S."],"coden":["PCSED"],"date":["2022"],"document_type":["Conference Paper"],"doi":["10.1109/ICSE-Companion55297.2022.9793752"],"isbn":["978-1-66549-598-1"],"issn":["02705257"],"note":["cited By 0"],"pages":["144–148"],"publisher":["IEEE Computer Society"],"series":["Proceedings - International Conference on Software Engineering"],"source":["Scopus"],"title":["ML-Quadrat & DriotData: A model-driven engineering tool and a low-code platform for smart IoT services"]},"creators":{"author":[{"lastName":"Moin","firstName":"A."},{"lastName":"Mituca","firstName":"A."},{"lastName":"Challenger","firstName":"M."},{"lastName":"Badii","firstName":"A."},{"lastName":"Gunnemann","firstName":"S."}]},"sentenceCased":true},{"key":"moinINVALID_SCITE_VALUEINVALID_SCITE_VALUE","type":"article","fields":{"langid":["INVALID_SCITE_VALUE"],"abstract":["INVALID_SCITE_VALUE"],"author":["Moin, Armin","Challenger, Moharram","Badii, Atta","Günnemann, Stephan"],"doi":["INVALID_SCITE_VALUE"],"issn":["INVALID_SCITE_VALUE"],"journaltitle":["INVALID_SCITE_VALUE"],"shorttitle":["INVALID_SCITE_VALUE"],"title":["INVALID_SCITE_VALUE"],"year":["INVALID_SCITE_VALUE"]},"creators":{"author":[{"lastName":"Moin","firstName":"Armin"},{"lastName":"Challenger","firstName":"Moharram"},{"lastName":"Badii","firstName":"Atta"},{"lastName":"Günnemann","firstName":"Stephan"}]}},{"key":"moinMDE4QAIModelDrivenEngineering2021","type":"article","fields":{"abstract":["Over the past decade, Artificial Intelligence (AI) has provided enormous new possibilities and opportunities, but also new demands and requirements for software systems. In particular, Machine Learning (ML) has proven useful in almost every vertical application domain. Although other sub-disciplines of AI, such as intelligent agents and Multi-Agent Systems (MAS) did not become promoted to the same extent, they still possess the potential to be integrated into the mainstream technology stacks and ecosystems, for example, due to the ongoing prevalence of the Internet of Things (IoT) and smart Cyber-Physical Systems (CPS). However, in the decade ahead, an unprecedented paradigm shift from classical computing towards Quantum Computing (QC) is expected, with perhaps a quantum-classical hybrid model. We expect the Model-Driven Engineering (MDE) paradigm to be an enabler and a facilitator, when it comes to the quantum and the quantum-classical hybrid applications as it has already proven beneficial in the highly complex domains of IoT, smart CPS and AI with inherently heterogeneous hardware and software platforms, and APIs. This includes not only automated code generation, but also automated model checking and verification, as well as model analysis in the early design phases, and model-to-model transformations both at the design-time and at the runtime. In this paper, the vision is focused on MDE for Quantum AI, and a holistic approach integrating all of the above."],"author":["Moin, Armin","Challenger, Moharram","Badii, Atta","Günnemann, Stephan"],"date":["2021"],"doi":["10.48550/ARXIV.2107.06708"],"keywords":["notion"],"note":["<h2>Other</h2> Preliminary Version - Vision Paper"],"publisher":["arXiv"],"shorttitle":["MDE4QAI"],"title":["MDE4QAI: Towards Model-Driven Engineering for Quantum Artificial Intelligence"],"version":["1"]},"creators":{"author":[{"lastName":"Moin","firstName":"Armin"},{"lastName":"Challenger","firstName":"Moharram"},{"lastName":"Badii","firstName":"Atta"},{"lastName":"Günnemann","firstName":"Stephan"}]}},{"key":"mokaddem2018recommending","type":"inproceedings","fields":{"langid":["english"],"author":["family=Mokaddem, given=Chihab, prefix=eddine, useprefix=false","Sahraoui, Houari","Syriani, Eugene"],"booktitle":["Proc. 21th ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst."],"date":["2018"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper proposes an approach to recommend refactoring rules that lean automatically fromRefactoring examples, and shows that, in general, the learned rules are accurate."],"pages":["257–266"],"title":["Recommending model refactoring rules from refactoring examples"]},"creators":{"author":[{"lastName":"Mokaddem","firstName":"Chihab","prefix":"eddine","useprefix":false},{"lastName":"Sahraoui","firstName":"Houari"},{"lastName":"Syriani","firstName":"Eugene"}]},"sentenceCased":true},{"key":"mokos2010ontology","type":"inproceedings","fields":{"langid":["english"],"author":["Mokos, Konstantinos","Meditskos, George","Katsaros, Panagiotis","Bassiliades, Nick","Vasiliades, Vangelis"],"booktitle":["2010 36th EUROMICRO Conf. Softw. Eng. Adv. Appl."],"date":["2010"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["47–54"],"title":["Ontology-based model driven engineering for safety verification"]},"creators":{"author":[{"lastName":"Mokos","firstName":"Konstantinos"},{"lastName":"Meditskos","firstName":"George"},{"lastName":"Katsaros","firstName":"Panagiotis"},{"lastName":"Bassiliades","firstName":"Nick"},{"lastName":"Vasiliades","firstName":"Vangelis"}]},"sentenceCased":true},{"key":"molino_ludwig_2019","type":"article","fields":{"abstract":["In this work we present Ludwig, a flexible, extensible and easy to use toolbox which allows users to train deep learning models and use them for obtaining predictions without writing code. Ludwig implements a novel approach to deep learning model building based on two main abstractions: data types and declarative configuration files. The data type abstraction allows for easier code and sub-model reuse, and the standardized interfaces imposed by this abstraction allow for encapsulation and make the code easy to extend. Declarative model definition configuration files enable inexperienced users to obtain effective models and increase the productivity of expert users. Alongside these two innovations, Ludwig introduces a general modularized deep learning architecture called Encoder-Combiner-Decoder that can be instantiated to perform a vast amount of machine learning tasks. These innovations make it possible for engineers, scientists from other fields and, in general, a much broader audience to adopt deep learning models for their tasks, concretely helping in its democratization."],"author":["Molino, Piero","Dudin, Yaroslav","Miryala, Sai Sumanth"],"date":["2019-09"],"eprint":["1909.07930"],"eprintclass":["cs, stat"],"eprinttype":["arxiv"],"journaltitle":["ArXiv190907930 Cs Stat"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Computation and Language","Computer Science - Computer Vision and Pattern Recognition","Computer Science - Machine Learning","Computer Science - Software Engineering","Statistics - Machine Learning"],"note":["arXiv: 1909.07930"],"shorttitle":["Ludwig"],"title":["Ludwig: A type-based declarative deep learning toolbox"]},"creators":{"author":[{"lastName":"Molino","firstName":"Piero"},{"lastName":"Dudin","firstName":"Yaroslav"},{"lastName":"Miryala","firstName":"Sai Sumanth"}]},"sentenceCased":true},{"key":"mongodbSchemaDesignExample10:25:57UTC","type":"unpublished","fields":{"abstract":["One of the challenges that comes with moving to MongoDB is figuring how to"],"author":["MongoDB"],"title":["Schema Design By Example"],"url":["https://www.slideshare.net/mongodb/schema-design-by-example"],"urldate":["2018-04-30"],"year":["10:25:57 UTC"]},"creators":{"author":[{"lastName":"MongoDB"}]}},{"key":"mongodbTransitioningSQLMongoDB10:56:52UTC","type":"unpublished","fields":{"abstract":["Learn how to transition from SQL to MongoDB with this presentation."],"author":["MongoDB"],"title":["Transitioning from SQL to MongoDB"],"type":["Technology"],"url":["https://www.slideshare.net/mongodb/transition-sql2mongo-1?next_slideshow=1"],"urldate":["2018-04-30"],"year":["10:56:52 UTC"]},"creators":{"author":[{"lastName":"MongoDB"}]}},{"key":"MonitoringYourHome","type":"online","fields":{"title":["Monitoring your home network with InfluxDB on Raspberry Pi with Docker | by Pete Shima | Medium"],"url":["https://medium.com/@petey5000/monitoring-your-home-network-with-influxdb-on-raspberry-pi-with-docker-78a23559ffea"],"urldate":["2021-01-07"]},"creators":{},"sentenceCased":true},{"key":"monperrusMeasuringModels","type":"article","fields":{"author":["Monperrus, Martin","Jezequel, Jean-Marc","Champeau, Joel","Hoeltzener, Brigitte"],"title":["Measuring models"]},"creators":{"author":[{"lastName":"Monperrus","firstName":"Martin"},{"lastName":"Jezequel","firstName":"Jean-Marc"},{"lastName":"Champeau","firstName":"Joel"},{"lastName":"Hoeltzener","firstName":"Brigitte"}]},"sentenceCased":true},{"key":"mora_segura_extremo_2019","type":"article","fields":{"langid":["english"],"abstract":["Modelling is a core activity in software development paradigms like Model-driven Engineering (MDE). Therefore, the quality of (meta-)models is crucial for the success of software projects. However, many times, modelling becomes a purely manual activity, which does not take advantage of information embedded in heterogeneous information sources, such as XML documents, ontologies, or other models and meta-models. In order to improve this situation, we present Extremo, an Eclipse plugin aimed at gathering the information stored in heterogeneous sources in a common data model, to facilitate the reuse of information chunks in the model being built. The tool covers the steps needed to incorporate this knowledge within an external modelling tool, supporting the uniform query of the heterogeneous sources and the evaluation of constraints. Flexibility of the main features (e.g., supported data formats, queries) is achieved by means of extensible mechanisms. To illustrate the usefulness of Extremo, we describe a practical case study in the financial domain and evaluate its performance and scalability."],"author":["Mora Segura, Àngel","family=Lara, given=Juan, prefix=de, useprefix=true"],"date":["2019"],"doi":["10.1016/j.scico.2019.05.003"],"issn":["0167-6423"],"journaltitle":["Sci. Comput. Program."],"pages":["71–80"],"shorttitle":["Extremo"],"title":["Extremo: An Eclipse plugin for modelling and meta-modelling assistance"],"volume":["180"]},"creators":{"author":[{"lastName":"Mora Segura","firstName":"Àngel"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true}]},"sentenceCased":true},{"key":"MoralEducationSelfManagement","type":"online","fields":{"title":["E M C I: Moral Education: Self-Management - Lecture 5"],"url":["http://spu.edu/depts/iccs/emci/courses/lectures/self_management_lec5.htm"],"urldate":["2016-09-21"]},"creators":{}},{"key":"morales_repor_2020","type":"article","fields":{"langid":["english"],"abstract":["Refactoring is a maintenance activity that aims to improve design quality while preserving the behavior of a system. Several (semi)automated approaches have been proposed to support developers in this maintenance activity, based on the correction of anti-patterns, which are “poor” solutions to recurring design problems. However, little quantitative evidence exists about the impact of automatically refactored code on program comprehension, and in which context automated refactoring can be as effective as manual refactoring. Leveraging RePOR, an automated refactoring approach based on partial order reduction techniques, we performed an empirical study to investigate whether automated refactoring code structure affects the understandability of systems during comprehension tasks. (1) We surveyed 80 developers, asking them to identify from a set of 20 refactoring changes if they were generated by developers or by a tool, and to rate the refactoring changes according to their design quality; (2) we asked 30 developers to complete code comprehension tasks on 10 systems that were refactored by either a freelancer or an automated refactoring tool. To make comparison fair, for a subset of refactoring actions that introduce new code entities, only synthetic identifiers were presented to practitioners. We measured developers’ performance using the NASA task load index for their effort, the time that they spent performing the tasks, and their percentages of correct answers. Our findings, despite current technology limitations, show that it is reasonable to expect a refactoring tools to match developer code. Indeed, results show that for 3 out of the 5 anti-pattern types studied, developers could not recognize the origin of the refactoring (i.e., whether it was performed by a human or an automatic tool). We also observed that developers do not prefer human refactorings over automated refactorings, except when refactoring Blob classes; and that there is no statistically significant difference between the impact on code understandability of human refactorings and automated refactorings. We conclude that automated refactorings can be as effective as manual refactorings. However, for complex anti-patterns types like the Blob, the perceived quality achieved by developers is slightly higher."],"author":["Morales, Rodrigo","Khomh, Foutse","Antoniol, Giuliano"],"date":["2020-07"],"doi":["10.1007/s10664-020-09826-7"],"issn":["1573-7616"],"journaltitle":["Empir. Softw. Eng."],"keywords":["Anti-patterns","Empirical software engineering studies","Program Comprehension","Refactoring","Software maintenance"],"note":["TL;DR \n\nAn empirical study to investigate whether automated refactoring code structure affects the understandability of systems during comprehension tasks concludes that automated refactorings can be as effective as manualRefactoring, except for complex anti-patterns types like the Blob."],"number":["4"],"pages":["2960–2996"],"shorttitle":["RePOR"],"title":["RePOR: Mimicking humans on refactoring tasks. Are we there yet?"],"volume":["25"]},"creators":{"author":[{"lastName":"Morales","firstName":"Rodrigo"},{"lastName":"Khomh","firstName":"Foutse"},{"lastName":"Antoniol","firstName":"Giuliano"}]},"sentenceCased":true},{"key":"moralesDSLAIEngineering2022","type":"incollection","fields":{"langid":["english"],"author":["Morales, Sergio","Clarisó, Robert","Cabot, Jordi"],"booktitle":["Product-Focused Software Process Improvement"],"date":["2022"],"doi":["10.1007/978-3-031-21388-5_4"],"editor":["Taibi, Davide","Kuhrmann, Marco","Mikkonen, Tommi","Klünder, Jil","Abrahamsson, Pekka"],"isbn":["978-3-031-21387-8 978-3-031-21388-5"],"location":["Cham"],"pages":["53–60"],"publisher":["Springer International Publishing"],"title":["Towards a DSL for AI Engineering Process Modeling"],"volume":["13709"]},"creators":{"author":[{"lastName":"Morales","firstName":"Sergio"},{"lastName":"Clarisó","firstName":"Robert"},{"lastName":"Cabot","firstName":"Jordi"}],"editor":[{"lastName":"Taibi","firstName":"Davide"},{"lastName":"Kuhrmann","firstName":"Marco"},{"lastName":"Mikkonen","firstName":"Tommi"},{"lastName":"Klünder","firstName":"Jil"},{"lastName":"Abrahamsson","firstName":"Pekka"}]}},{"key":"moreno-llorenaFunctionalCharacterizationCollaborative2011","type":"incollection","fields":{"author":["Moreno-Llorena, Jaime","Claros, Iván","Martín, Rafael","Cobos, Ruth","family=Lara, given=Juan, prefix=de, useprefix=true","Guerra, Esther"],"booktitle":["Cooperative Design, Visualization, and Engineering"],"date":["2011"],"pages":["182–185"],"publisher":["Springer"],"title":["Towards a functional characterization of collaborative systems"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-23734-8_30"],"urldate":["2015-04-01"]},"creators":{"author":[{"lastName":"Moreno-Llorena","firstName":"Jaime"},{"lastName":"Claros","firstName":"Iván"},{"lastName":"Martín","firstName":"Rafael"},{"lastName":"Cobos","firstName":"Ruth"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true},{"lastName":"Guerra","firstName":"Esther"}]},"sentenceCased":true},{"key":"Moreno:2015:IUT:2818754.2818860","type":"inproceedings","fields":{"acmid":["2818860"],"author":["Moreno, Laura","Bavota, Gabriele","Di Penta, Massimiliano","Oliveto, Rocco","Marcus, Andrian"],"booktitle":["37th Int. Conf. Softw. Eng."],"date":["2015"],"isbn":["978-1-4799-1934-5"],"location":["Piscataway"],"nodoi":["10.1109/ICSE.2015.98"],"numpages":["11"],"pages":["880–890"],"publisher":["IEEE"],"title":["How can I use this method?"]},"creators":{"author":[{"lastName":"Moreno","firstName":"Laura"},{"lastName":"Bavota","firstName":"Gabriele"},{"lastName":"Di Penta","firstName":"Massimiliano"},{"lastName":"Oliveto","firstName":"Rocco"},{"lastName":"Marcus","firstName":"Andrian"}]},"sentenceCased":true},{"key":"Morin20162160","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Winter Simul. Conf."],"affiliation":["FORAC Research Consortium, Department of Computer Science, Software Engineering, 1065, avodela Medecine, Quebec, QC G1VOA6, Canada"],"art_number":["7408329"],"author":["Morin, M.","Paradis, F.","Rolland, A.","Wery, J.","Gaudreault, J.","Laviolette, F."],"coden":["WSCPD"],"date":["2016"],"document_type":["Conference Paper"],"doi":["10.1109/WSC.2015.7408329"],"isbn":["978-1-4673-9743-8"],"issn":["08917736"],"note":["cited By 10"],"pages":["2160–2171"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - Winter Simulation Conference"],"source":["Scopus"],"title":["Machine learning-based metamodels for sawing simulation"],"volume":["2016-February"]},"creators":{"author":[{"lastName":"Morin","firstName":"M."},{"lastName":"Paradis","firstName":"F."},{"lastName":"Rolland","firstName":"A."},{"lastName":"Wery","firstName":"J."},{"lastName":"Gaudreault","firstName":"J."},{"lastName":"Laviolette","firstName":"F."}]},"sentenceCased":true},{"key":"morinModelBasedSoftwareEngineering2017","type":"article","fields":{"langid":["english"],"author":["Morin, Brice","Harrand, Nicolas","Fleurey, Franck"],"date":["2017-01"],"doi":["10.1109/MS.2017.11"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nThe ThingML (Internet of Things Modeling Language) approach, which was inspired by UML, integrates concepts targeted at the IoT in a model-driven, generative approach."],"number":["1"],"pages":["30–36"],"title":["Model-Based Software Engineering to Tame the IoT Jungle"],"volume":["34"]},"creators":{"author":[{"lastName":"Morin","firstName":"Brice"},{"lastName":"Harrand","firstName":"Nicolas"},{"lastName":"Fleurey","firstName":"Franck"}]}},{"key":"morrisonSoftwareArchitecture2nd2005","type":"book","fields":{"date":["2005"],"doi":["10.1007/b136986"],"editor":["Morrison, Ronald","Oquendo, Flávio"],"isbn":["3-540-26275-X"],"note":["TL;DR \n\nThe ArchWare Tower: the Implementation of an Active Software Engineering Environment using a ?"],"publisher":["Springer"],"series":["Lecture Notes in Computer Science"],"title":["Software Architecture, 2nd European Workshop, EWSA 2005, Pisa, Italy, June 13-14, 2005, Proceedings"],"volume":["3527"]},"creators":{"editor":[{"lastName":"Morrison","firstName":"Ronald"},{"lastName":"Oquendo","firstName":"Flávio"}]}},{"key":"mostermanCyberphysicalSystemsChallenges2016","type":"article","fields":{"langid":["english"],"author":["Mosterman, Pieter J.","Zander, Justyna"],"date":["2016-02"],"doi":["10.1007/s10270-015-0469-x"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"number":["1"],"pages":["5–16"],"shorttitle":["Cyber-physical systems challenges"],"title":["Cyber-physical systems challenges: A needs analysis for collaborating embedded software systems"],"volume":["15"]},"creators":{"author":[{"lastName":"Mosterman","firstName":"Pieter J."},{"lastName":"Zander","firstName":"Justyna"}]},"sentenceCased":true},{"key":"mostermanIndustryCyberPhysicalSystem2016","type":"article","fields":{"langid":["english"],"author":["Mosterman, Pieter J.","Zander, Justyna"],"date":["2016-02"],"doi":["10.1007/s10270-015-0493-x"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nThis work focuses on the collaborative function dimension and presents a set of concrete examples of CPS challenges based on a pick and place machine that solves a distributed version of the Towers of Hanoi puzzle."],"number":["1"],"pages":["17–29"],"title":["Industry 4.0 as a Cyber-Physical System study"],"volume":["15"]},"creators":{"author":[{"lastName":"Mosterman","firstName":"Pieter J."},{"lastName":"Zander","firstName":"Justyna"}]},"sentenceCased":true},{"key":"Mozejko201819","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Schedae Informaticae"],"affiliation":["TensorCell; Faculty of Mathematics and Computer Science, Jagiellonian University, Poland; Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Poland"],"author":["Mozejko, M.","Brzeski, M.","Madry, L.","Skowronek, L.","Gora, P."],"date":["2018"],"document_type":["Article"],"doi":["10.4467/20838476SI.18.002.10407"],"issn":["17323916"],"journaltitle":["Schedae Informaticae"],"note":["cited By 2"],"pages":["19–30"],"publisher":["Jagiellonian University"],"source":["Scopus"],"title":["Traffic signal settings optimization using gradient descent"],"volume":["27"]},"creators":{"author":[{"lastName":"Mozejko","firstName":"M."},{"lastName":"Brzeski","firstName":"M."},{"lastName":"Madry","firstName":"L."},{"lastName":"Skowronek","firstName":"L."},{"lastName":"Gora","firstName":"P."}]},"sentenceCased":true},{"key":"MSCAITN2016","type":"online","fields":{"title":["MSCA-ITN-2016"],"url":["https://ec.europa.eu/research/participants/portal/desktop/en/opportunities/h2020/topics/2056-msca-itn-2016.html"],"urldate":["2015-11-19"]},"creators":{}},{"key":"mucciniSelfadaptationCyberphysicalSystems2016","type":"inproceedings","fields":{"langid":["english"],"author":["Muccini, Henry","Sharaf, Mohammad","Weyns, Danny"],"date":["2016"],"doi":["10.1145/2897053.2897069"],"isbn":["978-1-4503-4187-5"],"pages":["75–81"],"publisher":["ACM Press"],"shorttitle":["Self-adaptation for cyber-physical systems"],"title":["Self-adaptation for cyber-physical systems: A systematic literature review"]},"creators":{"author":[{"lastName":"Muccini","firstName":"Henry"},{"lastName":"Sharaf","firstName":"Mohammad"},{"lastName":"Weyns","firstName":"Danny"}]},"sentenceCased":true},{"key":"mullerAutonomicComputingNow2009","type":"incollection","fields":{"author":["Müller, Hausi A.","Kienle, Holger M.","Stege, Ulrike"],"booktitle":["Software Engineering"],"date":["2009"],"editor":["De Lucia, Andrea","Ferrucci, Filomena"],"editorb":["Hutchison, David","Kanade, Takeo","Kittler, Josef","Kleinberg, Jon M.","Mattern, Friedemann","Mitchell, John C.","Naor, Moni","Nierstrasz, Oscar","Pandu Rangan, C.","Steffen, Bernhard","Sudan, Madhu","Terzopoulos, Demetri","Tygar, Doug","Vardi, Moshe Y.","Weikum, Gerhard"],"editorbtype":["redactor"],"isbn":["978-3-540-95887-1 978-3-540-95888-8"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nIn this article, it is argued that both design perspectives are needed and necessary for autonomic system design."],"pages":["32–54"],"publisher":["Springer Berlin Heidelberg"],"title":["Autonomic Computing Now You See It, Now You Don’t"],"url":["http://link.springer.com/10.1007/978-3-540-95888-8_2"],"urldate":["2016-09-29"],"volume":["5413"]},"creators":{"author":[{"lastName":"Müller","firstName":"Hausi A."},{"lastName":"Kienle","firstName":"Holger M."},{"lastName":"Stege","firstName":"Ulrike"}],"editor":[{"lastName":"De Lucia","firstName":"Andrea"},{"lastName":"Ferrucci","firstName":"Filomena"}],"editorb":[{"lastName":"Hutchison","firstName":"David"},{"lastName":"Kanade","firstName":"Takeo"},{"lastName":"Kittler","firstName":"Josef"},{"lastName":"Kleinberg","firstName":"Jon M."},{"lastName":"Mattern","firstName":"Friedemann"},{"lastName":"Mitchell","firstName":"John C."},{"lastName":"Naor","firstName":"Moni"},{"lastName":"Nierstrasz","firstName":"Oscar"},{"lastName":"Pandu Rangan","firstName":"C."},{"lastName":"Steffen","firstName":"Bernhard"},{"lastName":"Sudan","firstName":"Madhu"},{"lastName":"Terzopoulos","firstName":"Demetri"},{"lastName":"Tygar","firstName":"Doug"},{"lastName":"Vardi","firstName":"Moshe Y."},{"lastName":"Weikum","firstName":"Gerhard"}]}},{"key":"Mumuni2022191","type":"article","fields":{"abstract":["Monocular depth estimation (MDE) provides information (from a single image) about overall scene layout, and is useful in robotics for autonomous navigation and vision-aided guidance. Advancements in deep learning, particularly self-supervised convolutional neural networks (CNNs), have led to the development of MDE models capable of providing highly accurate per-pixel depth maps. However, these models are typically tuned for specific datasets, leading to sharp performance degradation in real-world scenarios, particularly in robot vision tasks—where the natural environments are too varied and complex to be sufficiently described by standard datasets. Motivated by the approach of biological vision, whose immense success relies on optimal combination of multiple depth cues and knowledge about the underlying environments, we exploit structure from motion (SfM) through optical flow as an additional depth cue and prior knowledge about depth distribution in the environment to improve monocular depth prediction. Meanwhile, there is a general incompatibility between the outputs of these models—whereas SfM measures absolute distances, MDE is scale ambiguous, returning only depth ratios. Consequently, we show how it is possible to promote MDE cue from ordinal scale to the same metric scale as SfM, thus, enabling their optimal integration in a Bayesian optimal manner. Additionally, we generalize the relationship between camera tilt angles and resulting MDE distortions, and show how this can be used to further improve depth perception robustness and accuracy (up to 6.2%) for a mobile robot whose heading is subject to arbitrary angular inclinations. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd."],"author":["Mumuni, F.","Mumuni, A."],"date":["2022"],"document_type":["Article"],"doi":["10.1007/s41315-022-00226-2"],"issn":["23665971"],"journaltitle":["Int. J. Intell. Robot. Appl."],"note":["cited By 0 \n\nTL;DR \n\nThis work shows how it is possible to promote MDE cue from ordinal scale to the same metric scale as SfM, thus, enabling their optimal integration in a Bayesian optimal manner, and generalizes the relationship between camera tilt angles and resulting MDE distortions."],"number":["2"],"pages":["191–206"],"publisher":["Springer"],"source":["Scopus"],"title":["Bayesian cue integration of structure from motion and CNN-based monocular depth estimation for autonomous robot navigation"],"volume":["6"]},"creators":{"author":[{"lastName":"Mumuni","firstName":"F."},{"lastName":"Mumuni","firstName":"A."}]},"sentenceCased":true},{"key":"munappyDataPipelineManagement2020","type":"incollection","fields":{"langid":["english"],"abstract":["Data pipelines involve a complex chain of interconnected activities that starts with a data source and ends in a data sink. Data pipelines are important for data-driven organizations since a data pipeline can process data in multiple formats from distributed data sources with minimal human intervention, accelerate data life cycle activities, and enhance productivity in data-driven enterprises. However, there are challenges and opportunities in implementing data pipelines but practical industry experiences are seldom reported. The findings of this study are derived by conducting a qualitative multiple-case study and interviews with the representatives of three companies. The challenges include data quality issues, infrastructure maintenance problems, and organizational barriers. On the other hand, data pipelines are implemented to enable traceability, fault-tolerance, and reduce human errors through maximizing automation thereby producing high-quality data. Based on multiplecase study research with five use cases from three case companies, this paper identifies the key challenges and benefits associated with the implementation and use of data pipelines."],"author":["Munappy, Aiswarya Raj","Bosch, Jan","Olsson, Helena Homström"],"booktitle":["Product-Focused Software Process Improvement"],"date":["2020"],"doi":["10.1007/978-3-030-64148-1_11"],"editor":["Morisio, Maurizio","Torchiano, Marco","Jedlitschka, Andreas"],"isbn":["978-3-030-64147-4 978-3-030-64148-1"],"keywords":["STARRED"],"location":["Cham"],"note":["<b>Blue Annotations (24/2/2022, 11:01:03)</b> \n\n\"Most of the organizations have already realized that big data is an essential factor for success and consequently, they use big data for business decisions [9] [13]. However, high-quality data is critical for excellent data products [3].\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"Companies relying on data for making decisions should be able to collect, store, and process high-quality data.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"it automates the operations involved in the selection, extraction, transformation, aggregation, validation, and loading of data for further analysis and visualization [11]. It oers end to end speed by removing errors and resisting bottlenecks or delay. Data pipelines can process multiple streams of data simultaneously [14].\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=3\">Munappy et al 2020:170</a>) \n\n\"It can route data through a dierent application like visualization or machine learning or deep learning model.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=3\">Munappy et al 2020:170</a>) \n\n\"Data pipelines in production should run iteratively for a longer duration due to which it has to manage process and performance monitoring, validation, fault detection, and mitigation.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=3\">Munappy et al 2020:170</a>) \n\n\"Data Collection Pipeline\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=6\">Munappy et al 2020:173</a>) \n\n\"Data Governance Pipeline\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=7\">Munappy et al 2020:174</a>) \n\n\"Data Pipeline for Machine learning Applications\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=8\">Munappy et al 2020:175</a>) \n\n\"Data for this pipeline is obtained from the devices that are sent to the repair center. Data pipelines for machine learning applications has four main steps namely ingest, store, transform and aggregate.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=8\">Munappy et al 2020:175</a>) \n\n\"These new les are then loaded into the archive directory of the data cluster.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=8\">Munappy et al 2020:175</a>) \n\n\"Data transformation checks for the new les in the archive directory of the data cluster and when found, it is fetched, uncompressed and processed to convert it to an appropriate format\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=8\">Munappy et al 2020:175</a>) \n\n\"Data Collection Pipeline\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=8\">Munappy et al 2020:175</a>) \n\n\"Data Quality analysis Pipeline\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=9\">Munappy et al 2020:176</a>) \n\n\"Integrating new data sources:\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=10\">Munappy et al 2020:177</a>) \n\n\"nodes can have more than one capability.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=10\">Munappy et al 2020:177</a>) \n\n<b>Red Annotations (24/2/2022, 11:01:03)</b> \n\n\"Collecting data from multiple assorted sources to producing useful insights is challenging [1].\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"Moreover, big data is dicult to congure, deploy, and manage due to its volume, velocity, and variety [12].\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"Data ow can be precarious, because there are several things that can go wrong during the transportation of data from one node to another: data can become corrupted, it can cause latency, or data sources may overlap and/or generate duplicates [5]. These problems increase in scale and impact as the number of data sources multiplies and complexity of the requirements grows.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=3\">Munappy et al 2020:170</a>) \n\n\"data pipeline creation, management, and maintenance is a complicated task which demands a considerable amount of time and eort.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=3\">Munappy et al 2020:170</a>) \n\n\"Most of the companies do this maintenance manually by appointing a dedicated person to guard the data ow through the pipeline.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=3\">Munappy et al 2020:170</a>) \n\n\"data pipeline challenges including infrastructural, organizational, and technical ones.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=3\">Munappy et al 2020:170</a>) \n\n\"Data errors and their impact on machine learning models are described in [6] by Caveness et. al. They also propose a data validation framework that validates the data owing through the machine learning pipeline\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=4\">Munappy et al 2020:171</a>) \n\n\"The collected data can have sensitive information like use details which needs responsible attention\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=6\">Munappy et al 2020:173</a>) \n\n\"data generated by sources can be of dierent formats and frequencies\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=6\">Munappy et al 2020:173</a>) \n\n\"data collection pipeline that collects data from distributed devices.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=6\">Munappy et al 2020:173</a>) \n\n\"Data pipeline scalability:\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=10\">Munappy et al 2020:177</a>) \n\n\"ability of a data pipeline to scale with the increased amount of ingested data, while keeping the cost low is a real challenge experienced by the data pipeline developers\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=10\">Munappy et al 2020:177</a>) \n\n\"Increased number of nodes and connectors in upstream:\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=10\">Munappy et al 2020:177</a>) \n\n\"the easy detection of faults, each of the nodes should be preferably assigned a single capability. Thus\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=10\">Munappy et al 2020:177</a>) \n\n\"number of nodes and connectors increases in the upstream in relation to the data product yielded from the pipeline.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=10\">Munappy et al 2020:177</a>) \n\n\"\"With the increased number of components in the data pipeline which in turn makes it dicult to understand and maintain. It is dicult to\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=10\">Munappy et al 2020:177</a>) \n\n\"10 Aiswarya et al. attain the right balance between robustness and complexity\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=11\">Munappy et al 2020:178</a>) \n\n\"Trade-o between data pipeline complexity and robustness:\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=11\">Munappy et al 2020:178</a>) \n\n\"Repeated alarms:\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=11\">Munappy et al 2020:178</a>) \n\n\"Data Quality Challenges\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=12\">Munappy et al 2020:179</a>) \n\n\"Missing data les:\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=12\">Munappy et al 2020:179</a>) \n\n\"\"Data quality is a challenge that is being discussed over years. But, at industry level we still struggle to achieve desired level of data quality\" - Senior Data Scientist(R1)\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=12\">Munappy et al 2020:179</a>) \n\n\"Operational errors:\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=13\">Munappy et al 2020:180</a>) \n\n\"Logical changes:\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=13\">Munappy et al 2020:180</a>) \n\n\"Solve data accessibility challenges\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=13\">Munappy et al 2020:180</a>) \n\n\"Save time and eort of human resources\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=13\">Munappy et al 2020:180</a>) \n\n\"inbuilt monitoring capability\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=13\">Munappy et al 2020:180</a>) \n\n\"Improves traceability of data work ow\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=14\">Munappy et al 2020:181</a>) \n\n\"Supports heterogeneous data sources\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=14\">Munappy et al 2020:181</a>) \n\n\"Accelerates Data life cycle activities\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=15\">Munappy et al 2020:182</a>) \n\n\"Standardize the Data Work ow\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=15\">Munappy et al 2020:182</a>) \n\n\"Improved Data Analytics and Machine Learning Models\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=15\">Munappy et al 2020:182</a>) \n\n\"Data pipelines are traceable since the stages are predened yielding better quality data for the models.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=15\">Munappy et al 2020:182</a>) \n\n\"data pipelines ensure a smooth ow of data unless it fails in one of the steps.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=15\">Munappy et al 2020:182</a>) \n\nTL;DR \n\nThe challenges include data quality issues, infrastructure maintenance problems, and organizational barriers, which are implemented to enable traceability, fault-tolerance, and reduce human errors through maximizing automation thereby producing high-quality data. \n\n<b>Yellow Annotations (24/2/2022, 11:01:03)</b> \n\n\"Data pipelines involve a complex chain of interconnected activities that starts with a data source and ends in a data sink.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"process data in multiple formats\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"minimal human intervention,\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"distributed data sources\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"data life cycle activities\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"enhance productivity in data-driven enterprises\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"data quality issues\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"infrastructure maintenance problems\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"organizational barriers\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"automation thereby producing high-quality data\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"Data is being increasingly used by industries for decision making, training machine learning(ML)/deep learning(DL) models, creating reports, and generating insights.\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=2\">Munappy et al 2020:169</a>) \n\n\"In other words, data pipelines are the connected chain of processes where the output of one or more processes becomes an input for another [19]\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=3\">Munappy et al 2020:170</a>) \n\n\"large scale companies like Google, Amazon, LinkedIn, and Facebook have recognized the importance of pipelines for their daily activities\" (<a href=\"zotero://open-pdf/library/items/BL2NMPE3?page=4\">Munappy et al 2020:171</a>)"],"pages":["168–184"],"publisher":["Springer International Publishing"],"shorttitle":["Data Pipeline Management in Practice"],"title":["Data Pipeline Management in Practice: Challenges and Opportunities"],"volume":["12562"]},"creators":{"author":[{"lastName":"Munappy","firstName":"Aiswarya Raj"},{"lastName":"Bosch","firstName":"Jan"},{"lastName":"Olsson","firstName":"Helena Homström"}],"editor":[{"lastName":"Morisio","firstName":"Maurizio"},{"lastName":"Torchiano","firstName":"Marco"},{"lastName":"Jedlitschka","firstName":"Andreas"}]}},{"key":"murLineeGuidaIniziative","type":"article","fields":{"langid":["italian"],"author":["Mur, Pnrr"],"pages":["47"],"title":["Linee Guida per le iniziative di sistema Missione 4: Istruzione e ricerca Componente 2: Dalla ricerca all’impresa"]},"creators":{"author":[{"lastName":"Mur","firstName":"Pnrr"}]}},{"key":"Murphy-HillMG10","type":"inproceedings","fields":{"author":["Murphy-Hill, Emerson R.","Murphy, Gail C.","Griswold, William G."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/conf/sigsoft/Murphy-HillMG10.bib"],"booktitle":["Proc. FoSER 2010 FSE 2010 St. Fe NM USA Novemb. 7-11 2010"],"date":["2010"],"pages":["255–258"],"timestamp":["Tue, 06 Nov 2018 16:59:23 +0100"],"title":["Understanding context: Creating a lasting impact in experimental software engineering research"]},"creators":{"author":[{"lastName":"Murphy-Hill","firstName":"Emerson R."},{"lastName":"Murphy","firstName":"Gail C."},{"lastName":"Griswold","firstName":"William G."}]},"sentenceCased":true},{"key":"Murphy09","type":"inproceedings","fields":{"author":["Murphy, Gail C."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/conf/vl/Murphy09.bib"],"booktitle":["IEEE Symp. Vis. Lang. Hum.-Centric Comput. VLHCC 2009 Corvallis USA 20-24 Sept. 2009 Proc."],"date":["2009"],"note":["TL;DR \n\nThe overload faced by programmers today is described and several approaches to attack the problem are discussed, some of which may also pertain beyond the domain of software development."],"pages":["4"],"timestamp":["Wed, 16 Oct 2019 14:14:55 +0200"],"title":["Attacking information overload in software development"]},"creators":{"author":[{"lastName":"Murphy","firstName":"Gail C."}]},"sentenceCased":true},{"key":"Murtagh2012","type":"article","fields":{"author":["Murtagh, Fionn","Contreras, Pedro"],"date":["2012-01"],"journaltitle":["Wiley Interdisc Rew Data Min. Knowl. Discov."],"nodoi":["10.1002/widm.53"],"note":["TL;DR \n\nA recently developed very efficient (linear time) hierarchical clustering algorithm is described, which can also be viewed as a hierarchical grid‐based algorithm."],"pages":["86–97"],"title":["Algorithms for hierarchical clustering: An overview"],"volume":["2"]},"creators":{"author":[{"lastName":"Murtagh","firstName":"Fionn"},{"lastName":"Contreras","firstName":"Pedro"}]},"sentenceCased":true},{"key":"MussbacherABBCCCFHHKSSSW14","type":"inproceedings","fields":{"langid":["english"],"author":["Mussbacher, Gunter","Amyot, Daniel","Breu, Ruth","Bruel, Jean-Michel","Cheng, Betty H. C.","Collet, Philippe","Combemale, Benoît","France, Robert B.","Heldal, Rogardt","Hill, James H.","Kienzle, Jörg","Schöttle, Matthias","Steimann, Friedrich","Stikkolorum, Dave R.","Whittle, Jon"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Model-Driven Eng. Lang. Syst. - 17th Int. Conf. MODELS 2014 Valencia Spain Sept. 28 - Oct. 3 2014 Proc."],"date":["2014"],"doi":["10.1007/978-3-319-11653-2\\_12"],"editor":["Dingel, Jürgen","Schulte, Wolfram","Ramos, Isidro","Abrahão, Silvia","Insfrán, Emilio"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["183–200"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Tue, 24 May 2022 15:28:49 +0200"],"title":["The relevance of model-driven engineering thirty years from now"],"volume":["8767"]},"creators":{"author":[{"lastName":"Mussbacher","firstName":"Gunter"},{"lastName":"Amyot","firstName":"Daniel"},{"lastName":"Breu","firstName":"Ruth"},{"lastName":"Bruel","firstName":"Jean-Michel"},{"lastName":"Cheng","firstName":"Betty H. C."},{"lastName":"Collet","firstName":"Philippe"},{"lastName":"Combemale","firstName":"Benoît"},{"lastName":"France","firstName":"Robert B."},{"lastName":"Heldal","firstName":"Rogardt"},{"lastName":"Hill","firstName":"James H."},{"lastName":"Kienzle","firstName":"Jörg"},{"lastName":"Schöttle","firstName":"Matthias"},{"lastName":"Steimann","firstName":"Friedrich"},{"lastName":"Stikkolorum","firstName":"Dave R."},{"lastName":"Whittle","firstName":"Jon"}],"editor":[{"lastName":"Dingel","firstName":"Jürgen"},{"lastName":"Schulte","firstName":"Wolfram"},{"lastName":"Ramos","firstName":"Isidro"},{"lastName":"Abrahão","firstName":"Silvia"},{"lastName":"Insfrán","firstName":"Emilio"}]},"sentenceCased":true},{"key":"mussbacherAssessmentGridIntelligent2020","type":"inproceedings","fields":{"langid":["english"],"author":["Mussbacher, Gunter","Combemale, Benoit","Abrahão, Silvia","Bencomo, Nelly","Burgueño, Loli","Engels, Gregor","Kienzle, Jörg","Kühn, Thomas","Mosser, Sébastien","Sahraoui, Houari","Weyssow, Martin"],"booktitle":["Proc. 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion Proc."],"date":["2020-10-16"],"doi":["10.1145/3417990.3421396"],"eventtitle":["MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems"],"isbn":["978-1-4503-8135-2"],"keywords":["GOAL_Model-Assistance","notion"],"location":["Virtual Event Canada"],"note":["THIS IS A “META” PAPER"],"pages":["1–10"],"publisher":["ACM"],"title":["Towards an assessment grid for intelligent modeling assistance"]},"creators":{"author":[{"lastName":"Mussbacher","firstName":"Gunter"},{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Abrahão","firstName":"Silvia"},{"lastName":"Bencomo","firstName":"Nelly"},{"lastName":"Burgueño","firstName":"Loli"},{"lastName":"Engels","firstName":"Gregor"},{"lastName":"Kienzle","firstName":"Jörg"},{"lastName":"Kühn","firstName":"Thomas"},{"lastName":"Mosser","firstName":"Sébastien"},{"lastName":"Sahraoui","firstName":"Houari"},{"lastName":"Weyssow","firstName":"Martin"}]},"sentenceCased":true},{"key":"mylyn","type":"misc","fields":{"title":["Eclipse Mylyn"],"url":["https://projects.eclipse.org/projects/tools.mylyn"]},"creators":{}},{"key":"naghiaei_cpfair_2022","type":"inproceedings","fields":{"langid":["english"],"abstract":["Recently, there has been a rising awareness that when machine learning (ML) algorithms are used to automate choices, they may treat/affect individuals unfairly, with legal, ethical, or economic consequences. Recommender systems are prominent examples of such ML systems that assist users in making high-stakes judgments. A common trend in the previous literature research on fairness in recommender systems is that the majority of works treat user and item fairness concerns separately, ignoring the fact that recommender systems operate in a two-sided marketplace. In this work, we present an optimization-based re-ranking approach that seamlessly integrates fairness constraints from both the consumer and producer-side in a joint objective framework. We demonstrate through large-scale experiments on 8 datasets that our proposed method is capable of improving both consumer and producer fairness without reducing overall recommendation quality, demonstrating the role algorithms may play in minimizing data biases."],"author":["Naghiaei, Mohammadmehdi","Rahmani, Hossein A.","Deldjoo, Yashar"],"booktitle":["Proc. 45th Int. ACM SIGIR Conf. Res. Dev. Inf. Retr."],"date":["2022-07"],"doi":["10.1145/3477495.3531959"],"isbn":["978-1-4503-8732-3"],"location":["Madrid Spain"],"pages":["770–779"],"publisher":["ACM"],"shorttitle":["CPFair"],"title":["CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems"]},"creators":{"author":[{"lastName":"Naghiaei","firstName":"Mohammadmehdi"},{"lastName":"Rahmani","firstName":"Hossein A."},{"lastName":"Deldjoo","firstName":"Yashar"}]}},{"key":"nagnathpaiMapItsImpact2023","type":"article","fields":{"langid":["english"],"abstract":["The increasing progress of Automated Driving (AD) technologies emphasises the significance of maps in ensuring the safety of these AD systems. While research has been conducted on the safety of AD systems themselves, the role of maps has not been thoroughly explored. In this article, we aim to address this gap by conducting an analysis to quantify the..."],"author":["Nagnath Pai, Vishwanath","Barosan, Ion","Khabbaz Saberi, Arash"],"date":["2023-09-25"],"doi":["10.55060/j.jseas.230925.001"],"issn":["2949-9372"],"journaltitle":["J. Softw. Eng. Auton. Syst."],"keywords":["LOGSEQ"],"note":["TL;DR \n\nThis research successfully identified unsafe scenarios along with their corresponding map features and showcased the admissible error margins in the map for the selected map feature, ensuring the secure operation of an AD system."],"publisher":["Athena Publishing"],"title":["Map and Its Impact on the Functional Safety of Automated Driving Vehicles"]},"creators":{"author":[{"lastName":"Nagnath Pai","firstName":"Vishwanath"},{"lastName":"Barosan","firstName":"Ion"},{"lastName":"Khabbaz Saberi","firstName":"Arash"}]}},{"key":"nagornyBigDataAnalysis","type":"article","fields":{"langid":["english"],"abstract":["The technological evolution emerges a unified (Industrial) Internet of Things network, where loosely coupled smart manufacturing devices build smart manufacturing systems and enable comprehensive collaboration possibilities that increase the dynamic and volatility of their ecosystems. On the one hand, this evolution generates a huge field for exploitation, but on the other hand also increases complexity including new challenges and requirements demanding for new approaches in several issues. One challenge is the analysis of such systems that generate huge amounts of (continuously generated) data, potentially containing valuable information useful for several use cases, such as knowledge generation, key performance indicator (KPI) optimization, diagnosis, predication, feedback to design or decision support. This work presents a review of Big Data analysis in smart manufacturing systems. It includes the status quo in research, innovation and development, next challenges, and a comprehensive list of potential use cases and exploitation possibilities."],"author":["Nagorny, Kevin","Lima-Monteiro, Pedro","Barata, Jose","Colombo, Armando Walter"],"keywords":["big data","DONE","smart manufacturing"],"pages":["29"],"title":["Big Data Analysis in Smart Manufacturing: A Review"]},"creators":{"author":[{"lastName":"Nagorny","firstName":"Kevin"},{"lastName":"Lima-Monteiro","firstName":"Pedro"},{"lastName":"Barata","firstName":"Jose"},{"lastName":"Colombo","firstName":"Armando Walter"}]}},{"key":"nairFindingFasterConfigurations","type":"article","fields":{"langid":["english"],"abstract":["Finding good configurations of a software system is often challenging since the number of configuration options can be large. Software engineers often make poor choices about configuration or, even worse, they usually use a sub-optimal configuration in production, which leads to inadequate performance. To assist engineers in finding the better configuration, this article introduces FLASH, a sequential model-based method that sequentially explores the configuration space by reflecting on the configurations evaluated so far to determine the next best configuration to explore. FLASH scales up to software systems that defeat the prior state-of-the-art model-based methods in this area. FLASH runs much faster than existing methods and can solve both single-objective and multi-objective optimization problems. The central insight of this article is to use the prior knowledge of the configuration space (gained from prior runs) to choose the next promising configuration. This strategy reduces the effort (i.e., number of measurements) required to find the better configuration. We evaluate FLASH using 30 scenarios based on 7 software systems to demonstrate that FLASH saves effort in 100% and 80% of cases in single-objective and multi-objective problems respectively by up to several orders of magnitude compared to state-of-the-art techniques."],"author":["Nair, Vivek","Yu, Zhe","Menzies, Tim","Siegmund, Norbert","Apel, Sven"],"pages":["17"],"title":["Finding Faster Configurations using FLASH"]},"creators":{"author":[{"lastName":"Nair","firstName":"Vivek"},{"lastName":"Yu","firstName":"Zhe"},{"lastName":"Menzies","firstName":"Tim"},{"lastName":"Siegmund","firstName":"Norbert"},{"lastName":"Apel","firstName":"Sven"}]},"sentenceCased":true},{"key":"najdataeiEfficientDataStreaming","type":"article","fields":{"langid":["english"],"abstract":["Today, ubiquitously sensing technologies enable inter-connection of physical objects, as part of Internet of Things (IoT), and provide massive amounts of data streams. In such scenarios, the demand for timely analysis has resulted in a shift of data processing paradigms towards continuous, parallel, and multitier computing. However, these paradigms are followed by several challenges especially regarding analysis speed, precision, costs, and deterministic execution. This thesis studies a number of such challenges to enable efficient continuous processing of streams of data in a decentralized and timely manner. In the first part of the thesis, we investigate techniques aiming at speeding up the processing without a loss in precision. The focus is on continuous machine learning/data mining types of problems, appearing commonly in IoT applications, and in particular continuous clustering and monitoring, for which we present novel algorithms; (i) Lisco, a sequential algorithm to cluster data points collected by LiDAR (a distance sensor that creates a 3D mapping of the environment), (ii) p-Lisco, the parallel version of Lisco to enhance pipeline- and data-parallelism of the latter, (iii) pi-Lisco, the parallel and incremental version to reuse the information and prevent redundant computations, (iv) g-Lisco, a generalized version of Lisco to cluster any data with spatio-temporal locality by leveraging the implicit ordering of the data, and (v) Amble, a continuous monitoring solution in an industrial process."],"author":["Najdataei, Hannaneh"],"keywords":["LOGSEQ"],"title":["Efficient Data Streaming Analytic Designs for Parallel and Distributed Processing"]},"creators":{"author":[{"lastName":"Najdataei","firstName":"Hannaneh"}]}},{"key":"nanayakkaraSurveyFindingTrends2021","type":"article","fields":{"langid":["english"],"abstract":["Social media have become very popular in the last few decades. Users rely on social network sites like Twitter, Facebook, YouTube, and LinkedIn for both information and entertainment needs. Social media analytics with data mining technology could be an analysis axis centered on extracting trends, patterns, and rules from the social media pool, to serve the people and organizations to have optimum choices concerning many disciplines. The traditional media analytical techniques appear obsolete and inadequate to gratify this immense array of unstructured social media knowledge characterized by three key problems namely; size, noise, and dynamism, predominantly shifting from the batch scale to the streaming one. The objective of this study is to investigate the data mining techniques that were used by social media networks during the years 2010 and 2020. The effort is a systematic review of content analysis in studies within the field of social media analytics that was published in principal databases. 125 articles were reviewed in this paper. Content analysis was implemented based on their approach, tools utilized, language, the dataset used, country, year, and nature of the experiment. The review discovered that 22 data mining techniques were employed with social media data while frequently used in Artificial Neural Network (ANN), Bayesian networks (BN) and Support Vector Machine (SVM), K-means Clustering, and Neuro-Fuzzy Logic Approach. The study has focused to assist the involved analyzers and educators to capture the research trends and problems associated with the Social media analytics process with future research initiatives."],"author":["Nanayakkara, A. C.","Kumara, B. T. G. S.","Rathnayaka, R. M. K. T."],"date":["2021-08-01"],"doi":["10.4038/sljssh.v1i2.36"],"issn":["2773-692X, 2773-6911"],"journaltitle":["SL J. Soc. Sci. Hum."],"note":["TL;DR \n\nThe review discovered that 22 data mining techniques were employed with social media data while frequently used in Artificial Neural Network, Bayesian networks, and Support Vector Machine, K-means Clustering, and Neuro-Fuzzy Logic Approach."],"number":["2"],"pages":["37"],"title":["A Survey of Finding Trends in Data Mining Techniques for Social Media Analysis"],"volume":["1"]},"creators":{"author":[{"lastName":"Nanayakkara","firstName":"A. C."},{"lastName":"Kumara","firstName":"B. T. G. S."},{"lastName":"Rathnayaka","firstName":"R. M. K. T."}]}},{"key":"narayanan_multi-view_2018","type":"article","fields":{"langid":["english"],"abstract":["Many existing Machine Learning (ML) based Android malware detection approaches use a variety of features such as security-sensitive APIs, system calls, control-flow structures and information flows in conjunction with ML classifiers to achieve accurate detection. Each of these feature sets provides a unique semantic perspective (or view) of apps’ behaviors with inherent strengths and limitations. Meaning, some views are more amenable to detect certain attacks but may not be suitable to characterize several other attacks. Most of the existing malware detection approaches use only one (or a selected few) of the aforementioned feature sets which prevents them from detecting a vast majority of attacks. Addressing this limitation, we propose MKLDroid, a unified framework that systematically integrates multiple views of apps for performing comprehensive malware detection and malicious code localization. The rationale is that, while a malware app can disguise itself in some views, disguising in every view while maintaining malicious intent will be much harder. MKLDroid uses a graph kernel to capture structural and contextual information from apps’ dependency graphs and identify malice code patterns in each view. Subsequently, it employs Multiple Kernel Learning (MKL) to find a weighted combination of the views which yields the best detection accuracy. Besides multi-view learning, MKLDroid’s unique and salient trait is its ability to locate fine-grained malice code portions in dependency graphs (e.g., methods/classes). Malicious code localization caters several important applications such as supporting human analysts studying malware behaviors, engineering malware signatures, and other counter-measures. Through our large-scale experiments on several datasets (incl. wild apps), we demonstrate that MKLDroid outperforms three state-of-the-art techniques consistently, in terms of accuracy while maintaining comparable efficiency. In our malicious code localization experiments on a dataset of repackaged malware, MKLDroid was able to identify all the malice classes with 94% average recall. Our work opens up two new avenues in malware research: (i) enables the research community to elegantly look at Android malware behaviors in multiple perspectives simultaneously, and (ii) performing precise and scalable malicious code localization."],"author":["Narayanan, Annamalai","Chandramohan, Mahinthan","Chen, Lihui","Liu, Yang"],"date":["2018-06"],"doi":["10.1007/s10664-017-9539-8"],"issn":["1573-7616"],"journaltitle":["Empir. Softw. Eng."],"number":["3"],"pages":["1222–1274"],"title":["A multi-view context-aware approach to Android malware detection and malicious code localization"],"volume":["23"]},"creators":{"author":[{"lastName":"Narayanan","firstName":"Annamalai"},{"lastName":"Chandramohan","firstName":"Mahinthan"},{"lastName":"Chen","firstName":"Lihui"},{"lastName":"Liu","firstName":"Yang"}]},"sentenceCased":true},{"key":"Narayanankutty202192","type":"inproceedings","fields":{"abstract":["IoT networks today face a myriad of security vulnerabilities in their infrastructure due to its wide attack surface. Large-scale networks are increasingly adopting a Software-Defined Networking approach, it allows for simplified network control and management through network virtualization. Since traditional security mechanisms are incapable of handling virtualized environments, SDSec or Software-Defined Security is introduced as a solution to support virtualized infrastructure, specifically aimed at providing security solutions to SDN frameworks. To further aid large scale design and development of SDN frameworks, Model-Driven Engineering (MDE) has been proposed to be used at the design phase, since abstraction, automation and analysis are inherently key aspects of MDE. This provides an efficient approach to reducing large problems through models that abstract away the complex technicality of the total system. Making adaptations to these models to address security issues faced in IoT networks, largely reduces cost and improves efficiency. These models can be simulated, analysed and supports architecture model adaptation; model changes are then reflected back to the real system. We propose a model-driven security approach for SDSec networks that can self-Adapt using machine learning to mitigate security threats. The overall design time changes can be monitored at run time through machine learning techniques (e.g. deep, reinforcement learning) for real time analysis. This approach can be tested in IoT simulation environments, for instance using the CAPS IoT modeling and simulation framework. Using self-Adaptation of models and advanced machine learning for data analysis would ensure that the SDSec architecture adapts and improves over time. This largely reduces the overall attack surface to achieve improved end-To-end security in IoT environments. © 2021 IEEE."],"art_number":["9425853"],"author":["Narayanankutty, H."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/ICSA-C52384.2021.00023"],"isbn":["978-1-66543-910-7"],"note":["cited By 0 \n\nTL;DR \n\nA model-driven security approach for SDSec networks that can self-adapt using machine learning to mitigate security threats is proposed, which largely reduces the overall attack surface to achieve improved end-to-end security in IoT environments."],"pages":["92–93"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2021 IEEE 18th International Conference on Software Architecture Companion, ICSA-C 2021"],"source":["Scopus"],"title":["Self-adapting model-based SDSec for IoT networks using machine learning"]},"creators":{"author":[{"lastName":"Narayanankutty","firstName":"H."}]},"sentenceCased":true},{"key":"nassifAutomaticallyCategorizingSoftware2018","type":"article","fields":{"langid":["english"],"abstract":["Informal language and the absence of a standard taxonomy for software technologies make it difficult to reliably analyze technology trends on discussion forums and other on-line venues. We propose an automated approach called Witt for the categorization of software technology (an expanded version of the hypernym discovery problem). Witt takes as input a phrase describing a software technology or concept and returns a general category that describes it (e.g., integrated development environment), along with attributes that further qualify it (commercial, php, etc.). By extension, the approach enables the dynamic creation of lists of all technologies of a given type (e.g., web application frameworks). Our approach relies on Stack Overflow and Wikipedia, and involves numerous original domain adaptations and a new solution to the problem of normalizing automatically-detected hypernyms. We compared Witt with six independent taxonomy tools and found that, when applied to software terms, Witt demonstrated better coverage than all evaluated alternate solutions, without a corresponding degradation in false positive rate."],"author":["Nassif, Mathieu","Treude, Christoph","Robillard, Martin"],"date":["2018"],"doi":["10.1109/TSE.2018.2836450"],"issn":["0098-5589, 1939-3520"],"journaltitle":["IEEE Trans. Softw. Eng."],"note":["TL;DR \n\nThis work proposes an automated approach to the categorization of software technologies that relies on Stack Overflow and Wikipedia, and involves numerous original domain adaptations and a new solution to the problem of normalizing automatically-detected hypernyms."],"pages":["1–1"],"title":["Automatically Categorizing Software Technologies"]},"creators":{"author":[{"lastName":"Nassif","firstName":"Mathieu"},{"lastName":"Treude","firstName":"Christoph"},{"lastName":"Robillard","firstName":"Martin"}]}},{"key":"nasticPatRICIANovelProgramming2013","type":"inproceedings","fields":{"author":["Nastic, Stefan","Sehic, Sanjin","Vogler, Michael","Truong, Hong-Linh","Dustdar, Schahram"],"date":["2013-12"],"doi":["10.1109/SOCA.2013.48"],"isbn":["978-1-4799-2702-9 978-1-4799-2701-2"],"note":["TL;DR \n\nPatRICIA is outlined, which aims at providing an end-to-end solution for high-level programming and provisioning of IoT applications on cloud platforms, and presents a novel programming model, based on the concept of intent and intent scope, for dealing with the complexity, diversity and scale of IoT systems in the cloud."],"pages":["53–60"],"publisher":["IEEE"],"title":["PatRICIA – A Novel Programming Model for IoT Applications on Cloud Platforms"]},"creators":{"author":[{"lastName":"Nastic","firstName":"Stefan"},{"lastName":"Sehic","firstName":"Sanjin"},{"lastName":"Vogler","firstName":"Michael"},{"lastName":"Truong","firstName":"Hong-Linh"},{"lastName":"Dustdar","firstName":"Schahram"}]}},{"key":"nasticProvisioningSoftwareDefinedIoT2014","type":"inproceedings","fields":{"author":["Nastic, Stefan","Sehic, Sanjin","Le, Duc-Hung","Truong, Hong-Linh","Dustdar, Schahram"],"date":["2014-08"],"doi":["10.1109/FiCloud.2014.52"],"isbn":["978-1-4799-4357-9"],"note":["TL;DR \n\nThis paper introduces the concept of software-defined IoT units - a novel approach to IoT cloud computing that encapsulates fine-grained IoT resources and IoT capabilities in well-defined APIs in order to provide a unified view on accessing, configuring and operating IoT cloud systems."],"pages":["288–295"],"publisher":["IEEE"],"title":["Provisioning Software-Defined IoT Cloud Systems"]},"creators":{"author":[{"lastName":"Nastic","firstName":"Stefan"},{"lastName":"Sehic","firstName":"Sanjin"},{"lastName":"Le","firstName":"Duc-Hung"},{"lastName":"Truong","firstName":"Hong-Linh"},{"lastName":"Dustdar","firstName":"Schahram"}]}},{"key":"naumovDeepLearningRecommendation2019","type":"article","fields":{"langid":["english"],"abstract":["With the advent of deep learning, neural network-based recommendation models have emerged as an important tool for tackling personalization and recommendation tasks. These networks differ significantly from other deep learning networks due to their need to handle categorical features and are not well studied or understood. In this paper, we develop a state-of-the-art deep learning recommendation model (DLRM) and provide its implementation in both PyTorch and Caffe2 frameworks. In addition, we design a specialized parallelization scheme utilizing model parallelism on the embedding tables to mitigate memory constraints while exploiting data parallelism to scale-out compute from the fully-connected layers. We compare DLRM against existing recommendation models and characterize its performance on the Big Basin AI platform, demonstrating its usefulness as a benchmark for future algorithmic experimentation and system co-design."],"author":["Naumov, Maxim","Mudigere, Dheevatsa","Shi, Hao-Jun Michael","Huang, Jianyu","Sundaraman, Narayanan","Park, Jongsoo","Wang, Xiaodong","Gupta, Udit","Wu, Carole-Jean","Azzolini, Alisson G.","Dzhulgakov, Dmytro","Mallevich, Andrey","Cherniavskii, Ilia","Lu, Yinghai","Krishnamoorthi, Raghuraman","Yu, Ansha","Kondratenko, Volodymyr","Pereira, Stephanie","Chen, Xianjie","Chen, Wenlin","Rao, Vijay","Jia, Bill","Xiong, Liang","Smelyanskiy, Misha"],"date":["2019-05-31"],"eprint":["1906.00091"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv190600091 Cs"],"keywords":["68T05","Computer Science - Information Retrieval","Computer Science - Machine Learning","H.3.3","H.3.4","I.2.6","I.5.0"],"note":["Comment: 10 pages, 6 figures"],"title":["Deep Learning Recommendation Model for Personalization and Recommendation Systems"],"url":["http://arxiv.org/abs/1906.00091"],"urldate":["2021-06-07"]},"creators":{"author":[{"lastName":"Naumov","firstName":"Maxim"},{"lastName":"Mudigere","firstName":"Dheevatsa"},{"lastName":"Shi","firstName":"Hao-Jun Michael"},{"lastName":"Huang","firstName":"Jianyu"},{"lastName":"Sundaraman","firstName":"Narayanan"},{"lastName":"Park","firstName":"Jongsoo"},{"lastName":"Wang","firstName":"Xiaodong"},{"lastName":"Gupta","firstName":"Udit"},{"lastName":"Wu","firstName":"Carole-Jean"},{"lastName":"Azzolini","firstName":"Alisson G."},{"lastName":"Dzhulgakov","firstName":"Dmytro"},{"lastName":"Mallevich","firstName":"Andrey"},{"lastName":"Cherniavskii","firstName":"Ilia"},{"lastName":"Lu","firstName":"Yinghai"},{"lastName":"Krishnamoorthi","firstName":"Raghuraman"},{"lastName":"Yu","firstName":"Ansha"},{"lastName":"Kondratenko","firstName":"Volodymyr"},{"lastName":"Pereira","firstName":"Stephanie"},{"lastName":"Chen","firstName":"Xianjie"},{"lastName":"Chen","firstName":"Wenlin"},{"lastName":"Rao","firstName":"Vijay"},{"lastName":"Jia","firstName":"Bill"},{"lastName":"Xiong","firstName":"Liang"},{"lastName":"Smelyanskiy","firstName":"Misha"}]}},{"key":"navarreteIntroducingSubjectiveKnowledge","type":"article","fields":{"langid":["english"],"abstract":["Knowledge-based applications that deal with uncertainty usually represent it by means of a confidence score that expresses the probability that a given fact is true. However, different users may have distinct opinions about the same fact, something that is not considered in existing proposals. This is critical in a number of areas where individual opinions need to be taken into account when making informed decisions, particularly when these are to be made by consensus. This paper introduces Subjective Knowledge Graphs (SKG), an extension to Probabilistic Knowledge Graphs that considers the individual opinions of separate users about the same facts, and allows reasoning about them. We show how SKGs can be implemented using standard graph databases and how the results of the queries can be enriched with the associated degrees of uncertainty."],"author":["Navarrete, Francisco J","Vallecillo, Antonio"],"pages":["10"],"title":["Introducing Subjective Knowledge Graphs"]},"creators":{"author":[{"lastName":"Navarrete","firstName":"Francisco J"},{"lastName":"Vallecillo","firstName":"Antonio"}]}},{"key":"nazabalDataEngineeringData2020","type":"article","fields":{"langid":["english"],"abstract":["Consider the situation where a data analyst wishes to carry out an analysis on a given dataset. It is widely recognized that most of the analyst’s time will be taken up with data engineering tasks such as acquiring, understanding, cleaning and preparing the data. In this paper we provide a description and classification of such tasks into high-levels groups, namely data organization, data quality and feature engineering. We also make available four datasets and example analyses that exhibit a wide variety of these problems, to help encourage the development of tools and techniques to help reduce this burden and push forward research towards the automation or semi-automation of the data engineering process."],"author":["Nazabal, Alfredo","Williams, Christopher K. I.","Colavizza, Giovanni","Smith, Camila Rangel","Williams, Angus"],"date":["2020-04-27"],"eprint":["2004.12929"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv200412929 Cs"],"note":["Comment: 24 pages, 1 figure, submitted to IEEE Transactions on Knowledge and Data Engineering"],"shorttitle":["Data Engineering for Data Analytics"],"title":["Data Engineering for Data Analytics: A Classification of the Issues, and Case Studies"],"url":["http://arxiv.org/abs/2004.12929"],"urldate":["2020-07-21"]},"creators":{"author":[{"lastName":"Nazabal","firstName":"Alfredo"},{"lastName":"Williams","firstName":"Christopher K. I."},{"lastName":"Colavizza","firstName":"Giovanni"},{"lastName":"Smith","firstName":"Camila Rangel"},{"lastName":"Williams","firstName":"Angus"}]}},{"key":"nejatiNextGenerationSoftwareVerification2021","type":"article","fields":{"langid":["english"],"abstract":["In recent years, automated software verification has progressed significantly. We can now effectively explore complex software structures through automated testing or to prove properties of complex programs, such as compilers using formal methods. But, for the most part, software testing and formal software verification techniques have advanced independently with relatively few insights on how their research thrusts compare or can be combined."],"author":["Nejati, Shiva"],"date":["2021-05-01"],"doi":["10.1109/MS.2021.3049322"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nThis paper presents a meta-modelling framework that automates the very labor-intensive and therefore time-heavy and expensive process of manually verifying the properties of complex programs, such as compilers using formal methods."],"number":["03"],"pages":["126–130"],"publisher":["IEEE Computer Society"],"shorttitle":["Next-Generation Software Verification"],"title":["Next-Generation Software Verification: An AI Perspective"],"volume":["38"]},"creators":{"author":[{"lastName":"Nejati","firstName":"Shiva"}]}},{"key":"neo4j_942_2020","type":"misc","fields":{"author":["Neo4j"],"date":["2020-06"],"nourl":["https://neo4j.com/docs/graph-algorithms/current/labs-algorithms/shortest-path/"],"title":["9.4.2. The Shortest Path algorithm - 9.4. Path finding algorithms"]},"creators":{"author":[{"literal":"Neo4j"}]},"sentenceCased":true},{"key":"Neto2017293","type":"article","fields":{"abstract":["The preprocessing stage in knowledge discovery projects is costly, normally taking between 50% and 80% of the total project time. It is in this stage that data in a relational database are transformed for applying a data mining technique. This stage is a complex task that demands from database designers a strong interaction with experts having a broad knowledge about the application domain. Frameworks aiming to systemize this stage have significant limitations when applied to Credit Behavioral Scoring solutions. This paper proposes a framework based on the Model Driven Development approach to systemize the mentioned stage. This work has three main contributions: 1) improving the discriminant power of data mining techniques by means of the construction of new input variables which embed temporal knowledge for the technique; 2) reducing the time of data transformation using automatic code generation, and 3) allowing artificial intelligence and statistics modelers to perform the data transformation without the help of database experts. In order to validate the proposed framework, two comparative studies were conducted. Experiments showed that the proposed framework delivers a performance equivalent or superior to those of existing frameworks and reduces the time of data transformation with a confidence level of 95%. © 2016"],"author":["Neto, R.","Jorge Adeodato, P.","Carolina Salgado, A."],"coden":["ESAPE"],"date":["2017"],"document_type":["Article"],"doi":["10.1016/j.eswa.2016.10.059"],"issn":["09574174"],"journaltitle":["Expert Syst. Appl."],"note":["cited By 11"],"pages":["293–305"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["A framework for data transformation in Credit Behavioral Scoring applications based on Model Driven Development"],"volume":["72"]},"creators":{"author":[{"lastName":"Neto","firstName":"R."},{"lastName":"Jorge Adeodato","firstName":"P."},{"lastName":"Carolina Salgado","firstName":"A."}]},"sentenceCased":true},{"key":"neumannHowMightWe2019","type":"article","fields":{"langid":["english"],"abstract":["Summarizing some of the changes that seem increasingly necessary to address known system and network deficiencies and anticipate currently unknown vulnerabilities."],"author":["Neumann, Peter G."],"date":["2019-09-24"],"doi":["10.1145/3357225"],"issn":["0001-0782, 1557-7317"],"journaltitle":["Commun. ACM"],"number":["10"],"pages":["23–25"],"title":["How might we increase system trustworthiness?"],"volume":["62"]},"creators":{"author":[{"lastName":"Neumann","firstName":"Peter G."}]},"sentenceCased":true},{"key":"NewSimilarityMeasure","type":"online","fields":{"title":["A New Similarity Measure for an Ontology Matching System - Springer"],"url":["http://link.springer.com/chapter/10.1007/978-3-319-25840-9_17?wt_mc=alerts.TOCseries"],"urldate":["2015-11-02"]},"creators":{}},{"key":"NewSoftRobot","type":"online","fields":{"title":["New Soft Robot is Completely Autonomous and Has No Electronics!"],"url":["http://sciencenewsjournal.com/new-soft-robot-completely-autonomous-no-electronics/"],"urldate":["2016-08-29"]},"creators":{},"sentenceCased":true},{"key":"Ng:2002:CMC:627342.628263","type":"article","fields":{"acmid":["628263"],"address":["Piscataway, NJ, USA"],"author":["Ng, Raymond T.","Han, Jiawei"],"date":["2002-09"],"issn":["1041-4347"],"issue_date":["September 2002"],"journaltitle":["IEEE Trans Knowl Data Eng"],"keywords":["clustering algorithms","computational geometry.","randomized search","Spatial data mining"],"nodoi":["10.1109/TKDE.2002.1033770"],"note":["TL;DR \n\nA new clustering method is proposed, called CLARANS, whose aim is to identify spatial structures that may be present in the data, and two spatial data mining algorithms that aim to discover relationships between spatial and nonspatial attributes are developed."],"number":["5"],"numpages":["14"],"pages":["1003–1016"],"publisher":["IEEE Educational Activities Department"],"title":["CLARANS: A method for clustering objects for spatial data mining"],"url":["http://dx.doi.org/10.1109/TKDE.2002.1033770"],"volume":["14"]},"creators":{"author":[{"lastName":"Ng","firstName":"Raymond T."},{"lastName":"Han","firstName":"Jiawei"}]},"sentenceCased":true},{"key":"Nguyen:2015:CRV:2942298.2942305","type":"inproceedings","fields":{"acmid":["2942305"],"author":["Nguyen, Phuong T.","Tomeo, Paolo","Di Noia, Tommaso","Di Sciascio, Eugenio"],"booktitle":["Proc. 14th Int. Conf. Semantic Web - ISWC 2015 - Vol. 9366"],"date":["2015"],"isbn":["978-3-319-25006-9"],"keywords":["Content-based recommender systems","Linked open data","Quality assessment","Semantic similarity"],"location":["New York, NY, USA"],"nodoi":["10.1007/978-3-319-25007-6₃5"],"note":["TL;DR \n\nThis paper investigates how the choice of one of the two datasets may influence the performance of a recommendation engine not only in terms of precision of the results but also in termsof their diversity and novelty."],"numpages":["17"],"pages":["605–621"],"publisher":["Springer-Verlag New York, Inc."],"title":["Content-based recommendations via DBpedia and freebase: A case study in the music domain"],"url":["http://dx.doi.org/10.1007/978-3-319-25007-6_35"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Tomeo","firstName":"Paolo"},{"lastName":"Di Noia","firstName":"Tommaso"},{"lastName":"Di Sciascio","firstName":"Eugenio"}]},"sentenceCased":true},{"key":"Nguyen:2015:ESP:2740908.2742141","type":"inproceedings","fields":{"acmid":["2742141"],"author":["Nguyen, Phuong T.","Tomeo, Paolo","Di Noia, Tommaso","Di Sciascio, Eugenio"],"booktitle":["Proc. 24th Int. Conf. World Wide Web"],"date":["2015"],"isbn":["978-1-4503-3473-0"],"keywords":["personalized pagerank","recommender systems","simrank","web of data"],"location":["New York, NY, USA"],"nodoi":["10.1145/2740908.2742141"],"note":["TL;DR \n\nTwo existing metrics, SimRank and PageRank, are reviewed and investigated and their suitability and performance for computing similarity between resources in RDF graphs and their usage to feed a content-based recommender system are investigated."],"numpages":["6"],"pages":["1477–1482"],"publisher":["ACM"],"series":["WWW '15 companion"],"title":["An evaluation of SimRank and personalized PageRank to build a recommender system for the web of data"],"url":["http://doi.acm.org/10.1145/2740908.2742141"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Tomeo","firstName":"Paolo"},{"lastName":"Di Noia","firstName":"Tommaso"},{"lastName":"Di Sciascio","firstName":"Eugenio"}]},"sentenceCased":true},{"key":"Nguyen:2016:ACR:2950290.2950333","type":"inproceedings","fields":{"acmid":["2950333"],"author":["Nguyen, Anh Tuan","Hilton, Michael","Codoban, Mihai","Nguyen, Hoan Anh","Mast, Lily","Rademacher, Eli","Nguyen, Tien N.","Dig, Danny"],"booktitle":["Proc. 2016 24th ACM SIGSOFT Int. Symp. Found. Softw. Eng."],"date":["2016"],"isbn":["978-1-4503-4218-6"],"keywords":["API Recommendation","Fine-grained Code Changes","Statistical Learning"],"location":["New York, NY, USA"],"nodoi":["10.1145/2950290.2950333"],"note":["TL;DR \n\nA novel API recommendation approach that taps into the predictive power of repetitive code changes to provide relevant API recommendations for developers based on statistical learning from fine-grained code changes and from the context in which those changes were made."],"numpages":["12"],"pages":["511–522"],"publisher":["ACM"],"series":["FSE 2016"],"title":["API code recommendation using statistical learning from fine-grained changes"],"url":["http://doi.acm.org/10.1145/2950290.2950333"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Anh Tuan"},{"lastName":"Hilton","firstName":"Michael"},{"lastName":"Codoban","firstName":"Mihai"},{"lastName":"Nguyen","firstName":"Hoan Anh"},{"lastName":"Mast","firstName":"Lily"},{"lastName":"Rademacher","firstName":"Eli"},{"lastName":"Nguyen","firstName":"Tien N."},{"lastName":"Dig","firstName":"Danny"}]},"sentenceCased":true},{"key":"Nguyen:2017:ACD:3098344.3098399","type":"inproceedings","fields":{"acmid":["3098399"],"author":["Nguyen, Anh Tuan","Nguyen, Tien N."],"booktitle":["Proc. 39th Int. Conf. Softw. Eng. Companion"],"date":["2017"],"isbn":["978-1-5386-1589-8"],"location":["Piscataway, NJ, USA"],"nodoi":["10.1109/ICSE-C.2017.118"],"numpages":["3"],"pages":["164–166"],"publisher":["IEEE Press"],"series":["ICSE-C '17"],"title":["Automatic categorization with deep neural network for open-source java projects"],"url":["https://doi.org/10.1109/ICSE-C.2017.118"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Anh Tuan"},{"lastName":"Nguyen","firstName":"Tien N."}]},"sentenceCased":true},{"key":"Nguyen:2019:FRS:3339505.3339636","type":"article","fields":{"acmid":["3339636"],"author":["Nguyen, P.T.","Di Rocco, J.","Di Ruscio, D.","Ochoa, L.","Degueule, T.","Di Penta, M."],"date":["2019"],"doi":["10.1109/ICSE.2019.00109"],"ids":["nguyenFOCUSRecommenderSystem2019,nguyenFOCUSRecommenderSystem2019a,nguyenFOCUSRecommenderSystem2019b"],"journaltitle":["Proc. - Int. Conf. Softw. Eng."],"location":["Piscataway, NJ, USA"],"note":["cited By 52 \n\ncited By 52 \n\nTL;DR \n\nA new tool is presented, FOCUS, which mines open-source project repositories to recommend API method invocations and usage patterns by analyzing how APIs are used in projects similar to the current project, and results indicate the suitability of context-aware collaborative-filtering recommender systems to provide API usage patterns."],"pages":["1050–1060"],"pagetotal":["11"],"publisher":["IEEE Press"],"series":["ICSE '19"],"title":["FOCUS: A Recommender System for Mining API Function Calls and Usage Patterns"],"volume":["2019-May"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Ochoa","firstName":"L."},{"lastName":"Degueule","firstName":"T."},{"lastName":"Di Penta","firstName":"M."}]}},{"key":"Nguyen:2019:JSS:CrossRec","type":"article","fields":{"author":["Nguyen, Phuong T.","Di Rocco, Juri","Di Ruscio, Davide","Di Penta, Massimiliano"],"date":["2019"],"journaltitle":["J. Syst. Softw."],"title":["CrossRec: Recommending highly relevant third-party libraries - manuscript under review"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Di Penta","firstName":"Massimiliano"}]},"sentenceCased":true},{"key":"Nguyen:2019:JSS:CrossSim","type":"article","fields":{"author":["Nguyen, Phuong T.","Di Rocco, Juri","Rubei, Riccardo","Di Ruscio, Davide"],"date":["2019"],"journaltitle":["Softw. Qual. J."],"title":["An automated approach to assess the similarity of GitHub repositories - manuscript under revision"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Rubei","firstName":"Riccardo"},{"lastName":"Di Ruscio","firstName":"Davide"}]},"sentenceCased":true},{"key":"Nguyen20211797","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Softw. Syst. Model."],"affiliation":["Università degli studi dell’Aquila, L’Aquila, Italy; Gran Sasso Science Institute, L’Aquila, Italy"],"author":["Nguyen, P.T.","Di Rocco, J.","Iovino, L.","Di Ruscio, D.","Pierantonio, A."],"correspondence_address1":["Di Ruscio, D.; Università degli studi dell’AquilaItaly; email: davide.diruscio@univaq.it"],"date":["2021"],"document_type":["Article"],"doi":["10.1007/s10270-021-00913-x"],"ids":["nguyenEvaluationMachineLearning2021,nguyenEvaluationMachineLearning2021a,nguyenEvaluationMachineLearning2021b,nguyenEvaluationMachineLearning2021d"],"issn":["16191366"],"journaltitle":["Softw. Syst. Model."],"keywords":["Boosted decision trees","Clustering algorithms","Decision trees","Error prone tasks","Evaluation metrics","GOAL_Model-Classification","Knowledge management","Learning systems","Machinery","Manual classification","Misclassifications","Model repositories","notion","Personalized search","Petroleum reservoir evaluation","Quality metrics","Reusability","Software design","Support vector machines","TECHNIQUE_NLP","TECHNIQUE_SVM","Turing machines"],"note":["cited By 1 \n\ncited By 1 \n\ncited By 2 \n\ncited By 4 \n\nTL;DR \n\nA thorough evaluation of AURORA as a machine learning classifier for metamodel repositories is presented by taking into consideration different settings as well as evaluation metrics, and it is seen that AurORA outperforms the baselines with respect to various quality metrics."],"number":["6"],"pages":["1797–1821"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Evaluation of a machine learning classifier for metamodels"],"volume":["20"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Iovino","firstName":"L."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"Nguyen20217333","type":"article","fields":{"abstract":["The use of one-bit analog-to-digital converters (ADCs) is a practical solution for reducing cost and power consumption in massive Multiple-Input-Multiple-Output (MIMO) systems. However, the distortion caused by one-bit ADCs makes the data detection task much more challenging. In this paper, we propose a two-stage detection method for massive MIMO systems with one-bit ADCs. In the first stage, we present several linear receivers based on the Bussgang decomposition that show significant performance gains over conventional linear receivers. Next, we reformulate the maximum-likelihood (ML) detection problem to address its non-robustness. Based on the reformulated ML detection problem, we propose a model-driven deep neural network-based detector, namely OBMNet, whose performance is comparable with an existing support vector machine-based receiver, albeit with a much lower computational complexity. A nearest-neighbor search method is then proposed for the second stage to refine the first stage solution. Unlike existing search methods that typically perform the search over a large candidate set, the proposed search method generates a limited number of most likely candidates and thus limits the search complexity. Numerical results confirm the low complexity, efficiency, and robustness of the proposed two-stage detection method. © 2002-2012 IEEE."],"author":["Nguyen, L.V.","Swindlehurst, A.L.","Nguyen, D.H.N."],"date":["2021"],"document_type":["Article"],"doi":["10.1109/TWC.2021.3082844"],"issn":["15361276"],"journaltitle":["IEEE Trans. Wirel. Commun."],"note":["cited By 2 \n\nTL;DR \n\nA model-driven deep neural network-based detector, namely OBMNet, is proposed whose performance is comparable with an existing support vector machine-based receiver, albeit with a much lower computational complexity."],"number":["11"],"pages":["7333–7345"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Linear and deep neural network-based receivers for massive MIMO systems with one-bit ADCs"],"volume":["20"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"L.V."},{"lastName":"Swindlehurst","firstName":"A.L."},{"lastName":"Nguyen","firstName":"D.H.N."}]},"sentenceCased":true},{"key":"nguyenAdversarialAttacksAPI","type":"article","fields":{"langid":["english"],"abstract":["Recommender systems in software engineering provide developers with a wide range of valuable items to help them complete their tasks. Among others, API recommender systems have gained momentum in recent years as they became more successful at suggesting API calls or code snippets. While these systems have proven to be effective in terms of prediction accuracy, there has been less attention for what concerns such recommenders’ resilience against adversarial attempts. In fact, by crafting the recommenders’ learning material, e.g., data from large open-source software (OSS) repositories, hostile users may succeed in injecting malicious data, putting at risk the software clients adopting API recommender systems. In this paper, we present an empirical investigation of adversarial machine learning techniques and their possible influence on recommender systems. The evaluation performed on three state-of-the-art API recommender systems reveals a worrying outcome: all of them are not immune to malicious data. The obtained result triggers the need for effective countermeasures to protect recommender systems against hostile attacks disguised in training data."],"author":["Nguyen, Phuong T","Sipio, Claudio Di","Rocco, Juri Di","Ruscio, Davide Di"],"pages":["13"],"title":["Adversarial Attacks to API Recommender Systems: Time to Wake Up and Smell the Coffee?"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T"},{"lastName":"Sipio","firstName":"Claudio Di"},{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Ruscio","firstName":"Davide Di"}]}},{"key":"nguyenAdversarialAttacksAPI2021","type":"inproceedings","fields":{"langid":["english"],"author":["Nguyen, Phuong","Di Sipio, C.","Di Rocco, J.","Di Penta, M.","Di Ruscio, D."],"author_keywords":["Adversarial Attacks; Adversarial Machine Learning; API Mining; Recommender systems"],"booktitle":["36th IEEEACM Int. Conf. Autom. Softw. Eng. ASE 2021 Melb. Aust. Novemb. 15-19 2021"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/ASE51524.2021.9678946"],"ids":["Nguyen2021253,nguyenAdversarialAttacksAPI2021a,nguyenAdversarialAttacksAPI2021b,nguyenAdversarialAttacksAPI2021c,nguyenAdversarialAttacksAPI2021d"],"isbn":["978-1-66540-337-5"],"keywords":["Adversarial attack","Adversarial Attacks","Adversarial machine learning","Adversarial Machine Learning","API calls","API mining","API Mining","Application programming interfaces (API)","Empirical investigation","Learning materials","Machine learning","Machine learning techniques","Machine-learning","Open source software","Open systems","Prediction accuracy","Recommender systems","Wake up"],"note":["cited By 1 \n\ncited By 1 \n\ncited By 1 \n\ncited By 4 \n\ncited By 4"],"pages":["253–265"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Adversarial Attacks to API Recommender Systems: Time to Wake Up and Smell the Coffee\\(F\\)"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong"},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Penta","firstName":"M."},{"lastName":"Di Ruscio","firstName":"D."}]}},{"key":"nguyenAdversarialMachineLearning2021","type":"inproceedings","fields":{"langid":["english"],"author":["Nguyen, Phuong","Di Ruscio, D.","Di Rocco, J.","Di Sipio, C.","Di Penta, Massimiliano"],"author_keywords":["Adversarial Machine Learning; Recommender systems"],"booktitle":["EASE 2021 Eval. Assess. Softw. Eng. Trondheim Nor. June 21-24 2021"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1145/3463274.3463809"],"ids":["10.1145/3463274.3463809,Nguyen2021247,nguyenAdversarialMachineLearning2021a,nguyenAdversarialMachineLearning2021b,nguyenAdversarialMachineLearning2021c,nguyenAdversarialMachineLearning2021d"],"isbn":["978-1-4503-9053-8"],"keywords":["Adversarial Machine Learning","Application programs","Engineering community","Learning algorithms","Machine learning","Open source software","Open systems","Proof of concept","Recommendation accuracy","Recommender systems","Third parties","Training sets","Two-state"],"location":["Trondheim, Norway"],"note":["cited By 1 \n\ncited By 1 \n\ncited By 1 \n\ncited By 1 \n\ncited By 1 \n\nTL;DR \n\nThe extent to which the presence of manipulated data can have a negative impact on the outcomes of two state-of-the-art recommender systems which suggest third-party libraries to developers is shown."],"pages":["247–253"],"pagetotal":["7"],"publisher":["Association for Computing Machinery"],"source":["Scopus"],"title":["Adversarial machine learning: On the resilience of third-party library recommender systems"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong"},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Di Penta","firstName":"Massimiliano"}]},"sentenceCased":true},{"key":"nguyenAutomatedClassificationMetamodel2019","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - ACM/IEEE Int. Conf. Model Driven Eng. Lang. Syst., MODELS"],"affiliation":["Università degli Studi dell'Aquila, L'Aquila, Italy; Gran Sasso Science Institute, L'Aquila, Italy"],"art_number":["8906979"],"author":["Nguyen, Phuong T.","DI ROCCO, Juri","DI RUSCIO, Davide","Pierantonio, Alfonso","Iovino, Ludovico"],"booktitle":["IEEE ACM 22nd Int. Conf. Model Driven Eng. Lang. Syst. MODELS"],"date":["2019"],"document_type":["Conference Paper"],"ids":["Nguyen2019272,nguyen2019automated,nguyenAutomatedClassificationMetamodel2019a,nguyenAutomatedClassificationMetamodel2019b,nguyenAutomatedClassificationMetamodel2019c"],"keywords":["/unread","⛔ No INSPIRE recid found","GOAL_Model-Classification","notion","TECHNIQUE_FFNN"],"note":["cited By 27 \n\ncited By 29 \n\ncited By 29 \n\nTL;DR \n\nAn experimental evaluation over a dataset of 555 metamodels demonstrates that the technique permits to learn from manually classified data and effectively categorize incoming unlabeled data with a considerably high prediction rate."],"pages":["272–282"],"publisher":["Springer"],"source":["Scopus"],"title":["Automated Classification of Metamodel Repositories: A Machine Learning Approach"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"DI ROCCO","firstName":"Juri"},{"lastName":"DI RUSCIO","firstName":"Davide"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Iovino","firstName":"Ludovico"}]}},{"key":"nguyenBuildingInformationSystems2019","type":"inproceedings","fields":{"author":["Nguyen, Phuong T","Di Rocco, Juri","Di Ruscio, Davide"],"booktitle":["2nd Workshop Flex. Adv. Inf. Syst. FAiSE CAiSE 2019"],"date":["2019"],"eventtitle":["2nd Workshop on Flexible Advanced Information Systems (FAiSE) at CAiSE 2019"],"location":["Rome (Italy)"],"title":["Building information systems by means of collaborative-filtering recommendation techniques"],"url":["http://vps.diruscio.org/nc/s/C6eS5s74DyZtSnH"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"}]},"sentenceCased":true},{"key":"nguyenConvolutionalNeuralNetworks2021","type":"article","fields":{"abbrev_source_title":["J Syst Software"],"affiliation":["Università degli studi dell'Aquila, L'Aquila, 67100, Italy; Gran Sasso Science Institute, Italy"],"art_number":["110860"],"author":["Nguyen, Thanh Phuong","Di Ruscio, D.","Pierantonio, A.","Di Rocco, J.","Iovino, L."],"coden":["JSSOD"],"correspondence_address1":["Di Ruscio, D.; Università degli studi dell'AquilaItaly; email: davide.diruscio@univaq.it"],"date":["2021"],"document_type":["Article"],"doi":["10.1016/j.jss.2020.110860"],"ids":["Nguyen2021,nguyenConvolutionalNeuralNetworks2021a,nguyenConvolutionalNeuralNetworks2021b,nguyenConvolutionalNeuralNetworks2021c,nguyenConvolutionalNeuralNetworks2021e"],"journaltitle":["J. Syst. Softw."],"keywords":["Classification mechanism","Classification procedure","Convolution","Convolutional neural networks","Experimental evaluation","GOAL_Model-Classification","Manual classification","Model-driven Engineering","Modeling environments","notion","Software repositories","Subjectivity of human perception","Supervised learning","TECHNIQUE_CNN"],"note":["cited By 13 \n\ncited By 14 \n\ncited By 15 \n\ncited By 19"],"publisher":["Elsevier Inc."],"source":["Scopus"],"title":["Convolutional neural networks for enhanced classification mechanisms of metamodels"],"volume":["172"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Thanh Phuong"},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Pierantonio","firstName":"A."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Iovino","firstName":"L."}]},"sentenceCased":true},{"key":"nguyenCorrectionEvaluationMachine2021","type":"article","fields":{"langid":["english"],"author":["Nguyen, P.T.","Di Rocco, J.","Iovino, L.","Di Ruscio, D.","Pierantonio, A."],"date":["2021"],"doi":["10.1007/s10270-021-00944-4"],"ids":["nguyenCorrectionEvaluationMachine2021a,nguyenCorrectionEvaluationMachine2021b,nguyenCorrectionEvaluationMachine2021d"],"issn":["16191366"],"journaltitle":["Softw. Syst. Model."],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0"],"number":["6"],"pages":["1823"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"title":["Correction to: Evaluation of a machine learning classifier for metamodels (Software and Systems Modeling, (2021), 20, 6, (1797-1821), 10.1007/S10270-021-00913-x)"],"volume":["20"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Iovino","firstName":"L."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"nguyenCrossRecSupportingSoftware2019","type":"article","fields":{"langid":["english"],"abstract":["When creating a new software system, or when evolving an existing one, developers do not reinvent the wheel but, rather, seek available libraries that suit their purpose. In such a context, open source software repositories contain rich resources that can provide developers with helpful advice to support their tasks. However, the heterogeneity of resources and the dependencies among them are the main obstacles to the e ective mining and exploitation of the available data. In this sense, advanced techniques and tools are needed to mine the metadata to bring in meaningful recommendations. In this paper, we present CrossRec, a recommender system to assist open source software developers in selecting suitable third-party libraries. CrossRec exploits a collaborative ltering technique to recommend libraries to developers by relying on the set of dependencies, which are currently included in the project being developed. We perform an empirical evaluation to compare the proposed approach with three state-of-theart baselines, i.e., LibRec, LibFinder, and LibCUP on three considerably large datasets. The experimental results show that CrossRec overcomes the limitation of the baselines by recommending also libraries with a speci c version. More importantly, it outperforms LibRec and LibCUP with respect to various quality metrics."],"author":["Nguyen, Phuong T","Rocco, Juri Di","Ruscio, Davide Di","Penta, Massimiliano Di"],"date":["2019"],"ids":["NGUYEN2019110460,Nguyen:2019:JSS:CrossRec,crossrec,nguyenCrossRecSupportingSoftware2020,nguyenCrossRecSupportingSoftware2020a"],"journaltitle":["J. Syst. Softw. - Elsevier"],"keywords":["Mining software repositories","Open Source software","Recommender systems"],"note":["cited By 35"],"pages":["54"],"publisher":["Elsevier BV"],"title":["CrossRec: Supporting Software Developers by Recommending Third-party Libraries"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T"},{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Penta","firstName":"Massimiliano Di"}]}},{"key":"nguyenDeepLibMachineTranslation2022","type":"article","fields":{"author":["Nguyen, Phuong Thanh","Di Rocco, Juri","Rubei, Riccardo","Di Sipio, Claudio","Di Ruscio, Davide"],"date":["2022"],"doi":["10.1016/j.eswa.2022.117267"],"ids":["nguyenDeepLibMachineTranslation2022a,nguyenDeepLibMachineTranslation2022b,nguyenDeepLibMachineTranslation2022c,nguyenDeepLibMachineTranslation2022e"],"journaltitle":["EXPERT Syst. Appl."],"keywords":["Bug fixes","Computational linguistics","Computer aided language translation","Deep learning","Deep neural networks","Encoder-decoder","Encoder–decoder neural network","Libraries","Mining software","Mining software repository","Network coding","Neural machine translation","Neural-networks","Software repositories","Third parties","Third-party library upgrade"],"note":["cited By 2 \n\ncited By 2 \n\ncited By 3"],"publisher":["Elsevier Ltd"],"title":["DeepLib: Machine translation techniques to recommend upgrades for third-party libraries"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong Thanh"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Rubei","firstName":"Riccardo"},{"lastName":"Di Sipio","firstName":"Claudio"},{"lastName":"Di Ruscio","firstName":"Davide"}]},"sentenceCased":true},{"key":"nguyenEmpiricalEvaluationGitHub2022","type":"inproceedings","fields":{"langid":["english"],"author":["Nguyen, Nhan","Nadi, Sarah"],"booktitle":["Proc. 19th Int. Conf. Min. Softw. Repos."],"date":["2022-05-23"],"doi":["10.1145/3524842.3528470"],"eventtitle":["MSR '22: 19th International Conference on Mining Software Repositories"],"ids":["10.1145/3524842.3528470"],"isbn":["978-1-4503-9303-4"],"keywords":["codex","empirical evaluation","GitHub copilot","program synthesis"],"location":["Pittsburgh Pennsylvania"],"pages":["1–5"],"pagetotal":["5"],"publisher":["ACM"],"title":["An empirical evaluation of GitHub copilot's code suggestions"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Nhan"},{"lastName":"Nadi","firstName":"Sarah"}]},"sentenceCased":true},{"key":"nguyenEnablingHeterogeneousRecommendations2019","type":"inproceedings","fields":{"langid":["english"],"abstract":["Open source software (OSS) forges contain rich data sources that are useful for supporting development activities. Research has been done to promote techniques and tools for providing open source developers with innovative features aiming at obtaining improvements in terms of development effort, cost savings, and developer productivity, just to mention a few. In the context of the EU H2020 CROSSMINER project we are conceiving a set of recommendations to assist software programmers in different phases of the development process. To this end, we defined a graph-based representation able to encode in a homogeneous manner different aspects of OSS ecosystems as well as to incorporate various well-founded recommendation techniques. Following the proposed paradigm, we have implemented recommender systems for providing various artifacts, such as third-party libraries and API usage. The preliminary results we achieved so far are promising: the proposed systems are able to suggest highly relevant items with respect to the current development context. In this paper, we describe what has been achieved so far as well as our planned medium and longer-term objectives. Furthermore, as a proof of concept, we present a use case where we built a context-aware recommender system to recommend API function calls and usage patterns."],"acmid":["3319353"],"author":["Nguyen, Phuong T","Rocco, Juri Di","Ruscio, Davide Di"],"booktitle":["ACM Int. Conf. Proceeding Ser."],"date":["2019"],"doi":["10.1145/3319008.3319353"],"ids":["Nguyen:2019:EHR:3319008.3319353,nguyenEnablingHeterogeneousRecommendations2019a,nguyenEnablingHeterogeneousRecommendations2019b,nguyenEnablingHeterogeneousRecommendations2019c"],"keywords":["machine learning","recommender systems","software engineering"],"location":["Copenhagen, Denmark"],"nodoi":["10.1145/3319008.3319353"],"note":["cited By 4 \n\ncited By 4 \n\nTL;DR \n\nA context-aware recommender system to recommend API function calls and usage patterns and a graph-based representation to encode in a homogeneous manner different aspects of OSS ecosystems as well as to incorporate various well-founded recommendation techniques are described."],"numpages":["6"],"pages":["6"],"title":["Enabling heterogeneous recommendations in OSS development: What's done and what's next in CROSSMINER"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T"},{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Ruscio","firstName":"Davide Di"}]},"sentenceCased":true},{"key":"nguyenEvaluationMachineLearning","type":"article","fields":{"langid":["english"],"abstract":["Modeling is a ubiquitous activity in the process of software development. In recent years, such an activity has reached a high degree of intricacy, guided by the heterogeneity of the components, data sources, and tasks. The democratized use of models has led to the necessity for suitable machinery for mining modeling repositories. Among others, the classification of metamodels into independent categories facilitates personalized searches by boosting the visibility of metamodels. Nevertheless, the manual classification of metamodels is not only a tedious but also an error-prone task. According to our observation, misclassification is the norm which leads to a reduction in reachability as well as re-usability of metamodels. Handling such complexity requires suitable tooling to leverage raw data into practical knowledge that can help modelers with their daily tasks. In our previous work, we proposed AURORA as a Machine Learning classifier for metamodels repositories. In this paper, we present a thorough evaluation of the system by taking into consideration different settings as well as evaluation metrics."],"author":["Nguyen, Phuong T","Rocco, Juri Di","Iovino, Ludovico","Ruscio, Davide Di","Pierantonio, Alfonso"],"pages":["25"],"title":["Evaluation of Machine Learning Classifiers for Metamodels"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T"},{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Pierantonio","firstName":"Alfonso"}]}},{"key":"nguyenFittingMissingAPI2023","type":"article","fields":{"abstract":["While implementing software projects, developers do not reinvent the wheel but try to reuse existing API calls and source code. In recent years, the problems related to recommending APIs and code snippets have been intensively investigated. Although current approaches have achieved encouraging performance, there is still the need to improve the recommendation process's effectiveness and efficiency. In this work, we reformulate the problem of API recommendations by proposing learning and recommending API sequences relevant to a given coding context. We present LUPE, a novel approach to API and code recommendation, exploiting cutting-edge deep learning techniques. Thanks to the underlying Encoder–Decoder architecture specialized in transforming sequences, LUPE can effectively learn the order in which invocations occur. The approach has been evaluated on two Android datasets and compared with GAPI and FACER, two state-of-the-art API recommender systems. Being fed with augmented training data, our conceived approach can obtain a high prediction accuracy, and produce a perfect match in several cases, hence outperforming the baselines. © 2022 Elsevier Ltd"],"author":["Nguyen, P.T.","Di Sipio, C.","Di Rocco, J.","Di Ruscio, D.","Di Penta, M."],"date":["2023"],"doi":["10.1016/j.eswa.2022.119477"],"issn":["09574174"],"journaltitle":["Expert Syst. Appl."],"keywords":["API calls","API recommendation","Computational linguistics","Computer aided language translation","Computer software reusability","Decoding","Encoder-decoder","Encoder–decoder LSTM","Learning systems","Long short-term memory","Machine translations","Neural machine translation","Project developers","Reuse","Signal encoding","Software project","Source code recommendation","Source codes"],"note":["cited By 0"],"publisher":["Elsevier Ltd"],"title":["Fitting missing API puzzles with machine translation techniques"],"volume":["216"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Di Penta","firstName":"M."}]},"sentenceCased":true},{"key":"nguyenKnowledgeawareRecommenderSystem2018","type":"inproceedings","fields":{"author":["Nguyen, Phuong T.","Di Rocco, Juri","Di Ruscio, Davide"],"booktitle":["CEUR Workshop Proc."],"date":["2018"],"ids":["nguyenKnowledgeawareRecommenderSystem2018a,nguyenKnowledgeawareRecommenderSystem2018b,nguyenKnowledgeawareRecommenderSystem2018c,nguyenKnowledgeawareRecommenderSystem2018d,nguyenKnowledgeawareRecommenderSystem2018e"],"keywords":["Autoencoders","DBpedia","Deep Learning","Knowledge graphs","Linked Open Data","Recommender Systems"],"location":["New York, NY, USA"],"note":["cited By 1 \n\ncited By 1"],"numpages":["7"],"pages":["16–22"],"publisher":["ACM"],"series":["KaRS 2018"],"title":["Knowledge-aware recommender system for software development"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066485946&partnerID=40&md5=94534bf5d2f89ffd911623f57945dd46"],"volume":["2290"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"}]},"sentenceCased":true},{"key":"nguyenMiningSoftwareRepositories2018","type":"inproceedings","fields":{"author":["Nguyen, Phuong","Di Rocco, Juri","Di Ruscio, Davide"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/conf/iir/NguyenRR18"],"booktitle":["CEUR Workshop Proc."],"date":["2018"],"ids":["DBLP:conf/iir/NguyenRR18,nguyenMiningSoftwareRepositories2018a,nguyenMiningSoftwareRepositories2018b,nguyenMiningSoftwareRepositories2018c,nguyenMiningSoftwareRepositories2018d"],"keywords":["Computer Science (all)"],"note":["cited By 1 \n\ncited By 1 \n\nTL;DR \n\nThe main research problems are presented as well the proposed approach together with some preliminary results, and cutting-edge technologies are applied, such as information retrieval and recommender systems to solve the problem of mining the rich metadata available at OSS repositories."],"publisher":["CEUR-WS"],"series":["CEUR WORKSHOP PROCEEDINGS"],"timestamp":["Tue, 24 Jul 2018 12:47:23 +0200"],"title":["Mining software repositories to support OSS developers: A recommender systems approach"],"url":["http://ceur-ws.org/"],"volume":["2140"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong"},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"}]},"sentenceCased":true},{"key":"nguyenRecommendingAPIFunction2021","type":"article","fields":{"author":["Nguyen, Phuong T.","Rocco, Juri Di","Sipio, Claudio Di","Ruscio, Davide Di","Penta, Massimiliano Di"],"date":["2021"],"eprint":["2102.07508"],"eprinttype":["arxiv"],"ids":["9359479,nguyenRecommendingAPIFunction2021a,nguyenRecommendingAPIFunction2022,nguyenRecommendingAPIFunction2022a,nguyenRecommendingAPIFunction2022b,nguyenRecommendingAPIFunction2022c"],"journaltitle":["CoRR"],"keywords":["API function calls","Application programming interfaces (API)","Computer software reusability","Context-Aware","Degree of complexity","Empirical evaluations","Google plays","Open source software","Open systems","Prediction accuracy","Software artifacts","Software design","Software repositories"],"note":["cited By 5 \n\ncited By 5 \n\ncited By 8"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Recommending API Function Calls and Code Snippets to Support Software Development"],"url":["https://arxiv.org/abs/2102.07508"],"volume":["abs/2102.07508"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Sipio","firstName":"Claudio Di"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Penta","firstName":"Massimiliano Di"}]}},{"key":"nguyenRecommendingThirdpartyLibrary2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["During the lifecycle of a software project, oftentimes developers have the need to update third-party libraries (TPLs) from an old version to a newer one. This aims to keep their code up-to-date with the latest functionalities offered by the libraries. In practice, choosing the next version for a library is a daunting task since it is crucial to maintain a harmonious relationship with other libraries. We propose DeepLib, a novel approach to the recommendation of an upgrade plan for software projects with respect to library usage. We mine migration history to build matrices and train deep neural networks, which are eventually used to forecast the subsequent versions of the related libraries. We evaluate the framework on a dataset from the Maven Central Repository. The results show promising outcomes: DeepLib can recommend the next version for the library of interest, earning a high prediction accuracy. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)."],"author":["Nguyen, P.T.","Di Rocco, J.","Rubei, R.","Di Sipio, C.","Di Ruscio, D."],"booktitle":["Proc. 11th Ital. Inf. Retr. Workshop 2021 Bari Italy Sept. 13-15 2021"],"date":["2021"],"editor":["Anelli V.W., Di Noia T., Ferro N., Narducci F."],"ids":["nguyenRecommendingThirdpartyLibrary2021a,nguyenRecommendingThirdpartyLibrary2021b,nguyenRecommendingThirdpartyLibrary2021c"],"issn":["16130073"],"keywords":["Deep learning","Deep neural networks","Libraries","Life cycle","Long short-term memory","LSTM","Migration history","Mining software","Mining software repository","Neural-networks","Software project","Software repositories","Third parties","Third-party library update"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 0"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"title":["Recommending third-party library updates with LSTM neural networks"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115622575&partnerID=40&md5=f443653def03b671eee29bfa20b3c5b1"],"volume":["2947"]},"creators":{"author":[{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Rubei","firstName":"R."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Di Ruscio","firstName":"D."}],"editor":[{"lastName":"Anelli V.W.","suffix":"Di Noia T.","firstName":"Ferro N., Narducci F."}]},"sentenceCased":true},{"key":"Nicolae2021","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["IEEE Electr. Des. Adv. Packag. Syst. Symp."],"affiliation":["University Politehnica of Bucharest, Romania; Infineon Technologies, Neubiberg, Germany"],"author":["Nicolae, G.","Buzo, A.","Feuerbaum, C.","Diaconu, C.V.","Cucu, H.","Pelz, G.","Burileanu, C."],"correspondence_address1":["Nicolae, G.; University Politehnica of BucharestRomania; email: georgian.nicolae@ieee.org"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/EDAPS53774.2021.9656996"],"isbn":["978-1-66546-613-4"],"issn":["21511225"],"note":["cited By 1"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["IEEE Electrical Design of Advanced Packaging and Systems Symposium"],"source":["Scopus"],"title":["Metamodel-based prediction of On Resistance for microelectronic power switches"],"volume":["2021-December"]},"creators":{"author":[{"lastName":"Nicolae","firstName":"G."},{"lastName":"Buzo","firstName":"A."},{"lastName":"Feuerbaum","firstName":"C."},{"lastName":"Diaconu","firstName":"C.V."},{"lastName":"Cucu","firstName":"H."},{"lastName":"Pelz","firstName":"G."},{"lastName":"Burileanu","firstName":"C."}]},"sentenceCased":true},{"key":"nielsenNeuralNetworksDeep2018","type":"article","fields":{"added-at":["2019-01-15T22:46:49.000+0100"],"author":["Nielsen, Michael A."],"biburl":["https://www.bibsonomy.org/bibtex/274383acee84241145ff4ffede9658206/slicside"],"date":["2018"],"interhash":["04d527cadd39f888fc3babcad3343362"],"intrahash":["74383acee84241145ff4ffede9658206"],"keywords":["ba-2018-hahnrico"],"note":["TL;DR \n\nAn overview of some of the different kinds of networks and their applications is given and how these architectures are used for business applications such as recommender systems is highlighted."],"publisher":["Determination Press"],"timestamp":["2019-01-15T22:46:49.000+0100"],"title":["Neural networks and deep learning"],"type":["misc"],"url":["http://neuralnetworksanddeeplearning.com/"]},"creators":{"author":[{"lastName":"Nielsen","firstName":"Michael A."}]},"sentenceCased":true},{"key":"Niemann:2013:NCF:2487575.2487656","type":"inproceedings","fields":{"acmid":["2487656"],"author":["Niemann, Katja","Wolpers, Martin"],"booktitle":["Proc. 19th ACM SIGKDD Int. Conf. Knowl. Discov. Data Min."],"date":["2013"],"ids":["10.1145/2487575.2487656"],"isbn":["978-1-4503-2174-7"],"keywords":["aggregate diversity","item-item similarity","long tail","niche items","recommender systems","usage context"],"location":["New York, NY, USA"],"nodoi":["10.1145/2487575.2487656"],"note":["TL;DR \n\nA new collaborative filtering approach that is based on the items' usage contexts is proposed that increases the rating predictions for niche items with fewer usage data available and improves the aggragate diversity of the recommendations."],"numpages":["9"],"pages":["955–963"],"pagetotal":["9"],"publisher":["ACM"],"series":["KDD '13"],"title":["A new collaborative filtering approach for increasing the aggregate diversity of recommender systems"],"url":["http://doi.acm.org/10.1145/2487575.2487656"]},"creators":{"author":[{"lastName":"Niemann","firstName":"Katja"},{"lastName":"Wolpers","firstName":"Martin"}]},"sentenceCased":true},{"key":"Niggemann201221","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Tagungsband - Dagstuhl-Workshop MBEES: Model. Entwickl. eingebetteter Systeme, MBEES"],"affiliation":["Fraunhofer IOSB - Competence Center Industrial Automation, Lemgo, Germany; IT - Institut Industrial IT, Hochschule Ostwestfalen-Lippe, Lemgo, Germany; Bauhaus-Universität Weimar, Germany"],"author":["Niggemann, O.","Stein, B.","Maier, A."],"correspondence_address1":["Niggemann, O.; Fraunhofer IOSB - Competence Center Industrial Automation, Lemgo, Germany; email: oliver.niggemann@iosb-ina.fraunhofer.de"],"date":["2012"],"document_type":["Conference Paper"],"keywords":["GOAL_Model-Classification","LOGSEQ","notion"],"note":["cited By 0"],"pages":["21–29"],"series":["Tagungsband - Dagstuhl-Workshop MBEES: Modellbasierte Entwicklung eingebetteter Systeme VIII, MBEES 2012"],"source":["Scopus"],"title":["Solving modeling problems with machine learning a classification scheme of model learning approaches for technical systems"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84873361603&partnerID=40&md5=dd7dfd4d9c468d595a967b9a1c21ce38"]},"creators":{"author":[{"lastName":"Niggemann","firstName":"O."},{"lastName":"Stein","firstName":"B."},{"lastName":"Maier","firstName":"A."}]},"sentenceCased":true},{"key":"nikanjamFaultsDeepReinforcement2021","type":"article","fields":{"abstract":["A growing demand is witnessed in both industry and academia for employing Deep Learning (DL) in various domains to solve real-world problems. Deep Reinforcement Learning (DRL) is the application of DL in the domain of Reinforcement Learning (RL). Like any software systems, DRL applications can fail because of faults in their programs. In this paper, we present the first attempt to categorize faults occurring in DRL programs. We manually analyzed 761 artifacts of DRL programs (from Stack Overflow posts and GitHub issues) developed using well-known DRL frameworks (OpenAI Gym, Dopamine, Keras-rl, Tensorforce) and identified faults reported by developers/users. We labeled and taxonomized the identified faults through several rounds of discussions. The resulting taxonomy is validated using an online survey with 19 developers/researchers. To allow for the automatic detection of faults in DRL programs, we have defined a meta-model of DRL programs and developed DRLinter, a model-based fault detection approach that leverages static analysis and graph transformations. The execution flow of DRLinter consists in parsing a DRL program to generate a model conforming to our meta-model and applying detection rules on the model to identify faults occurrences. The effectiveness of DRLinter is evaluated using 15 synthetic DRLprograms in which we injected faults observed in the analyzed artifacts of the taxonomy. The results show that DRLinter can successfully detect faults in all synthetic faulty programs."],"author":["Nikanjam, Amin","Morovati, Mohammad Mehdi","Khomh, Foutse","Braiek, Houssem Ben"],"date":["2021-01-05"],"eprint":["2101.00135"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv210100135 Cs"],"note":["TL;DR \n\nA meta-model of DRL programs is defined and a model-based fault detection approach that leverages static analysis and graph transformations is developed, DRLinter, which can successfully detect faults in both synthesized and real-world examples."],"shorttitle":["Faults in Deep Reinforcement Learning Programs"],"title":["Faults in Deep Reinforcement Learning Programs: A Taxonomy and A Detection Approach"],"url":["http://arxiv.org/abs/2101.00135"],"urldate":["2021-01-09"]},"creators":{"author":[{"lastName":"Nikanjam","firstName":"Amin"},{"lastName":"Morovati","firstName":"Mohammad Mehdi"},{"lastName":"Khomh","firstName":"Foutse"},{"lastName":"Braiek","firstName":"Houssem Ben"}]}},{"key":"Niknam202046","type":"article","fields":{"abstract":["There is a growing interest in the wireless communications community to complement the traditional model-driven design approaches with data-driven machine learning (ML)-based solutions. While conventional ML approaches rely on the assumption of having the data and processing heads in a central entity, this is not always feasible in wireless communications applications because of the inaccessibility of private data and large communication overhead required to transmit raw data to central ML processors. As a result, decentralized ML approaches that keep the data where it is generated are much more appealing. Due to its privacy-preserving nature, federated learning is particularly relevant for many wireless applications, especially in the context of fifth generation (5G) networks. In this article, we provide an accessible introduction to the general idea of federated learning, discuss several possible applications in 5G networks, and describe key technical challenges and open problems for future research on federated learning in the context of wireless communications. © 1979-2012 IEEE."],"art_number":["9141214"],"author":["Niknam, S.","Dhillon, H.S.","Reed, J.H."],"coden":["ICOMD"],"date":["2020"],"document_type":["Article"],"doi":["10.1109/MCOM.001.1900461"],"ids":["niknamFederatedLearningWireless2020a"],"issn":["01636804"],"journaltitle":["IEEE Commun. Mag."],"keywords":["Central-entity","Communication overheads","Data handling","Privacy preserving","Private data","Technical challenges","Traditional models","Wireless application","Wireless communications"],"note":["cited By 126 \n\ncited By 126"],"number":["6"],"pages":["46–51"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Federated learning for wireless communications: Motivation, opportunities, and challenges"],"volume":["58"]},"creators":{"author":[{"lastName":"Niknam","firstName":"S."},{"lastName":"Dhillon","firstName":"H.S."},{"lastName":"Reed","firstName":"J.H."}]},"sentenceCased":true},{"key":"nikolovConceptualizationScalableExecution2021","type":"article","fields":{"langid":["english"],"abstract":["Big Data processing, especially with the increasing proliferation of Internet of Things (IoT) technologies and convergence of IoT, edge and cloud computing technologies, involves handling massive and complex data sets on heterogeneous resources and incorporating different tools, frameworks, and processes to help organizations make sense of their data collected from various sources. This set of operations, referred to as Big Data workflows, requires taking advantage of Cloud infrastructures’ elasticity for scalability. In this article, we present the design and prototype implementation of a Big Data workflow approach based on the use of software container technologies, message-oriented middleware (MOM), and a domain-specific language (DSL) to enable highly scalable workflow execution and abstract workflow definition. We demonstrate our system in a use case and a set of experiments that show the practical applicability of the proposed approach for the specification and scalable execution of Big Data workflows. Furthermore, we compare our proposed approach’s scalability with that of Argo Workflows – one of the most prominent tools in the area of Big Data workflows – and provide a qualitative evaluation of the proposed DSL and overall approach with respect to the existing literature."],"author":["Nikolov, Nikolay","Dessalk, Yared Dejene","Khan, Akif Quddus","Soylu, Ahmet","Matskin, Mihhail","Payberah, Amir H.","Roman, Dumitru"],"date":["2021-12"],"doi":["10.1016/j.iot.2021.100440"],"issn":["25426605"],"journaltitle":["Internet of Things"],"keywords":["LOGSEQ"],"pages":["100440"],"title":["Conceptualization and scalable execution of big data workflows using domain-specific languages and software containers"],"volume":["16"]},"creators":{"author":[{"lastName":"Nikolov","firstName":"Nikolay"},{"lastName":"Dessalk","firstName":"Yared Dejene"},{"lastName":"Khan","firstName":"Akif Quddus"},{"lastName":"Soylu","firstName":"Ahmet"},{"lastName":"Matskin","firstName":"Mihhail"},{"lastName":"Payberah","firstName":"Amir H."},{"lastName":"Roman","firstName":"Dumitru"}]},"sentenceCased":true},{"key":"NIPS2019_8307","type":"incollection","fields":{"author":["Ilyas, Andrew","Santurkar, Shibani","Tsipras, Dimitris","Engstrom, Logan","Tran, Brandon","Madry, Aleksander"],"booktitle":["Advances in neural information processing systems 32"],"date":["2019"],"editor":["Wallach, H.","Larochelle, H.","Beygelzimer, A.","family=Buc, given=F., prefix=dAlché-, useprefix=true","Fox, E.","Garnett, R."],"pages":["125–136"],"publisher":["Curran Associates, Inc."],"title":["Adversarial examples are not bugs, they are features"],"url":["http://papers.nips.cc/paper/8307-adversarial-examples-are-not-bugs-they-are-features.pdf"]},"creators":{"author":[{"lastName":"Ilyas","firstName":"Andrew"},{"lastName":"Santurkar","firstName":"Shibani"},{"lastName":"Tsipras","firstName":"Dimitris"},{"lastName":"Engstrom","firstName":"Logan"},{"lastName":"Tran","firstName":"Brandon"},{"lastName":"Madry","firstName":"Aleksander"}],"editor":[{"lastName":"Wallach","firstName":"H."},{"lastName":"Larochelle","firstName":"H."},{"lastName":"Beygelzimer","firstName":"A."},{"lastName":"Buc","firstName":"F.","prefix":"dAlché-","useprefix":true},{"lastName":"Fox","firstName":"E."},{"lastName":"Garnett","firstName":"R."}]},"sentenceCased":true},{"key":"niuAPIUsagePattern2017","type":"article","fields":{"langid":["english"],"acmid":["3104977"],"author":["Niu, Haoran","Keivanloo, Iman","Zou, Ying"],"date":["2017-07"],"doi":["10.1016/j.jss.2016.07.026"],"ids":["Niu2017API,Niu:2017:AUP:3104915.3104977"],"issn":["01641212"],"issue_date":["July 2017"],"journaltitle":["J. Syst. Softw."],"keywords":["Clustering","Object usage","Usage pattern"],"noaddress":["New York, NY, USA"],"nodoi":["10.1016/j.jss.2016.07.026"],"numpages":["13"],"pages":["127–139"],"publisher":["Elsevier"],"title":["API usage pattern recommendation for software development"],"volume":["129"]},"creators":{"author":[{"lastName":"Niu","firstName":"Haoran"},{"lastName":"Keivanloo","firstName":"Iman"},{"lastName":"Zou","firstName":"Ying"}]},"sentenceCased":true},{"key":"noauthor_borrowing_nodate","type":"misc","fields":{"title":["Borrowing your enemy’s arrows: The case of code reuse in Android via direct inter-app code invocation | Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering"],"url":["https://dl-acm-org.univaq.clas.cineca.it/doi/abs/10.1145/3368089.3409745"],"urldate":["2021-03-11"]},"creators":{},"sentenceCased":true},{"key":"noauthor_neo4jneo4j-java-driver_2020","type":"misc","fields":{"abstract":["Neo4j Bolt driver for Java. Contribute to neo4j/neo4j-java-driver development by creating an account on GitHub."],"copyright":["Apache-2.0"],"date":["2020-06"],"keywords":["bolt","database","driver","java","neo4j","neo4j-driver"],"nopublisher":["Neo4j"],"note":["original-date: 2015-04-15T17:08:15Z"],"nourl":["https://github.com/neo4j/neo4j-java-driver"],"title":["Neo4j/Neo4j-Java-Driver"]},"creators":{}},{"key":"noiaRecommenderSystemsLinked2015","type":"inproceedings","fields":{"author":["Noia, Tommaso Di","Ostuni, Vito Claudio"],"bibsource":["dblp computer science bibliography, http://dblp.org"],"biburl":["http://dblp.org/rec/bib/conf/rweb/NoiaO15"],"booktitle":["Reason. Web Web Log. Rules - 11th Int. Summer Sch. 2015 Berl. Ger. July 31 - August 4 2015 Tutor. Lect."],"date":["2015"],"doi":["10.1007/978-3-319-21768-0_4"],"pages":["88–113"],"timestamp":["Sun, 21 May 2017 00:20:32 +0200"],"title":["Recommender systems and linked open data"]},"creators":{"author":[{"lastName":"Noia","firstName":"Tommaso Di"},{"lastName":"Ostuni","firstName":"Vito Claudio"}]},"sentenceCased":true},{"key":"nonamiAutonomousControlSystems2013","type":"book","fields":{"langid":["english"],"date":["2013"],"editor":["Nonami, Kenzo","International Conference on Intelligent Unmanned Systems","International Society of Intelligent Unmanned Systems"],"isbn":["978-4-431-54276-6 978-4-431-54275-9"],"location":["Tokyo"],"note":["Organized by the International Society of Intelligent Unmanned Systems (ISIUS) and locally by the Center for Bio-Micro Robotics Research at Chiba University, Japan. - The event was the 7th conference continuing from previous conferences held in Seoul, Korea (2005, 2006), Bali, Indonesia (2007), Nanjing, China (2008), Jeju, Korea (2009), and Bali, Indonesia (2010) Literaturangaben"],"number":["65"],"pagetotal":["315"],"publisher":["Springer"],"series":["International series on intelligent systems, control and automation: Science and engineering"],"shorttitle":["Autonomous control systems and vehicles"],"title":["Autonomous control systems and vehicles: Intelligent unmanned systems ; [International Conference on Intelligent Unmanned Systems (ICIUS) 2011 ... Chiba University, Japan ; collection of excellent papers that where updated after presentation]"]},"creators":{"editor":[{"lastName":"Nonami","firstName":"Kenzo"},{"literal":"International Conference on Intelligent Unmanned Systems"},{"literal":"International Society of Intelligent Unmanned Systems"}]},"sentenceCased":true},{"key":"nordmannSurveyDomainspecificLanguages2014","type":"incollection","fields":{"author":["Nordmann, Arne","Hochgeschwender, Nico","Wrede, Sebastian"],"booktitle":["Simulation, Modeling, and Programming for Autonomous Robots"],"date":["2014"],"pages":["195–206"],"publisher":["Springer"],"title":["A survey on domain-specific languages in robotics"],"url":["http://link.springer.com/chapter/10.1007/978-3-319-11900-7_17"],"urldate":["2015-04-21"]},"creators":{"author":[{"lastName":"Nordmann","firstName":"Arne"},{"lastName":"Hochgeschwender","firstName":"Nico"},{"lastName":"Wrede","firstName":"Sebastian"}]},"sentenceCased":true},{"key":"northropUltralargescaleSystemsSoftware2006","type":"book","fields":{"langid":["english"],"author":["Northrop, Linda","Feiler, Peter H","Pollak, Bill","Pipitone, Daniel"],"date":["2006"],"isbn":["978-0-9786956-0-6"],"location":["Pittsburgh, Pa."],"publisher":["Software Engineering Institute, Carnegie Mellon University"],"shorttitle":["Ultra-large-scale systems"],"title":["Ultra-large-scale systems: The software challenge of the future"]},"creators":{"author":[{"lastName":"Northrop","firstName":"Linda"},{"lastName":"Feiler","firstName":"Peter H"},{"lastName":"Pollak","firstName":"Bill"},{"lastName":"Pipitone","firstName":"Daniel"}]},"sentenceCased":true},{"key":"NoSQLDataModeling","type":"online","fields":{"title":["NoSQL Data Modeling | eBay Tech Blog"],"url":["http://www.ebaytechblog.com/2014/10/10/nosql-data-modeling/#.VRPVNfmJtrc"],"urldate":["2015-03-26"]},"creators":{}},{"key":"NoSQLDataModelinga","type":"online","fields":{"title":["NoSQL Data Modeling Techniques – Highly Scalable Blog"],"url":["https://highlyscalable.wordpress.com/2012/03/01/nosql-data-modeling-techniques/"],"urldate":["2018-05-06"]},"creators":{}},{"key":"notinfringing","type":"misc","fields":{"author":["Reda, Felix"],"title":["GitHub Copilot Is Not Infringing Your Copyright <span class=\"nocase\">https://felixreda.eu/2021/07/github-copilot-is-not-infringing-your-copyright/</span>"]},"creators":{"author":[{"lastName":"Reda","firstName":"Felix"}]}},{"key":"NotionAllinoneWorkspace","type":"online","fields":{"langid":["english"],"abstract":["A new tool that blends your everyday work apps into one. It's the all-in-one workspace for you and your team"],"ids":["NotionAllinoneWorkspacea,NotionAllinoneWorkspaceb,NotionAllinoneWorkspacec"],"organization":["Notion"],"title":["Notion – The all-in-one workspace for your notes, tasks, wikis, and databases."],"url":["https://www.notion.so"],"urldate":["2020-02-11"]},"creators":{},"sentenceCased":true},{"key":"NotionNotes","type":"misc","fields":{"title":["Notion notes"],"url":["https://www.notion.so/Publications-SoSyM-and-Visions-81b70721668c4e5d83b78bac2dbde571"]},"creators":{},"sentenceCased":true},{"key":"novielliLoveJoyAnger2020","type":"article","fields":{"langid":["english"],"author":["Novielli, Nicole","Calefato, Fabio","Lanubile, Filippo"],"date":["2020-05"],"doi":["10.1109/MS.2020.2968557"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nIs it possible to monitor the mood of a large team of coders to determine when and where a codebase needs additional help?"],"number":["3"],"pages":["86–91"],"shorttitle":["Love, Joy, Anger, Sadness, Fear, and Surprise"],"title":["Love, Joy, Anger, Sadness, Fear, and Surprise: SE Needs Special Kinds of AI: A Case Study on Text Mining and SE"],"volume":["37"]},"creators":{"author":[{"lastName":"Novielli","firstName":"Nicole"},{"lastName":"Calefato","firstName":"Fabio"},{"lastName":"Lanubile","firstName":"Filippo"}]}},{"key":"ntiMinireviewMachineLearning2022","type":"article","fields":{"langid":["english"],"abstract":["The availability of digital technology in the hands of every citizenry worldwide makes an available unprecedented massive amount of data. The capability to process these gigantic amounts of data in real-time with Big Data Analytics (BDA) tools and Machine Learning (ML) algorithms carries many paybacks. However, the high number of free BDA tools, platforms, and data mining tools makes it challenging to select the appropriate one for the right task. This paper presents a comprehensive mini-literature review of ML in BDA, using a keyword search; a total of 1512 published articles was identified. The articles were screened to 140 based on the study proposed novel taxonomy. The study outcome shows that deep neural networks (15%), support vector machines (15%), artificial neural networks (14%), decision trees (12%), and ensemble learning techniques (11%) are widely applied in BDA. The related applications fields, challenges, and most importantly the openings for future research, are detailed."],"author":["Nti, Isaac Kofi","Quarcoo, Juanita Ahia","Aning, Justice","Fosu, Godfred Kusi"],"date":["2022-06"],"doi":["10.26599/BDMA.2021.9020028"],"issn":["2096-0654"],"journaltitle":["Big Data Min. Anal."],"number":["2"],"pages":["81–97"],"shorttitle":["A mini-review of machine learning in big data analytics"],"title":["A mini-review of machine learning in big data analytics: Applications, challenges, and prospects"],"volume":["5"]},"creators":{"author":[{"lastName":"Nti","firstName":"Isaac Kofi"},{"lastName":"Quarcoo","firstName":"Juanita Ahia"},{"lastName":"Aning","firstName":"Justice"},{"lastName":"Fosu","firstName":"Godfred Kusi"}]},"sentenceCased":true},{"key":"Numediart","type":"online","fields":{"title":["Numediart"],"url":["http://www.numediart.org/2015/06/23/hci-seminar-research-advances-in-interactive-systems-modeling-%C2%BB/"],"urldate":["2016-01-23"]},"creators":{}},{"key":"oakesBuildingDomainSpecificMachine2022","type":"article","fields":{"abstract":["Domain experts are increasingly employing machine learning to solve their domain-specific problems. This article presents six key challenges that a domain expert faces in transforming their problem into a computational workflow, and then into an executable implementation. These challenges arise out of our conceptual framework which presents the \"route\" of options that a domain expert may choose to take while developing their solution. To ground our conceptual framework in the state-of-the-practice, this article discusses a selection of available textual and graphical workflow systems and their support for these six challenges. Case studies from the literature in various domains are also examined to highlight the tools used by the domain experts as well as a classification of the domain-specificity and machine learning usage of their problem, workflow, and implementation. The state-of-the-practice informs our discussion of the six key challenges, where we identify which challenges are not sufficiently addressed by available tools. We also suggest possible research directions for software engineering researchers to increase the automation of these tools and disseminate best-practice techniques between software engineering and various scientific domains."],"author":["Oakes, Bentley James","Famelis, Michalis","Sahraoui, Houari"],"date":["2022-03-16"],"eprint":["2203.08638"],"eprintclass":["cs"],"eprinttype":["arxiv"],"ids":["oakesBuildingDomainSpecificMachine2023"],"journaltitle":["ArXiv220308638 Cs"],"keywords":["Computer Science - Software Engineering","GOAL_MDE4AI"],"note":["Comment: 33 pages 14 figures \n\n<b>Contents</b> \n\n<ul> <li><a href=\"zotero://open-pdf/0_8KTK8B7W/1\">1 Introduction</a> <li><a href=\"zotero://open-pdf/0_8KTK8B7W/3\">2 Background</a> <li><a href=\"zotero://open-pdf/0_8KTK8B7W/4\">3 Overview of Our Framework</a> <li><a href=\"zotero://open-pdf/0_8KTK8B7W/6\">4 Layers and Intra-Layer Transformations</a> <li><a href=\"zotero://open-pdf/0_8KTK8B7W/10\">5 Inter-layer Transformations</a> <li><a href=\"zotero://open-pdf/0_8KTK8B7W/12\">6 Workflow Standards and Tools</a> <li><a href=\"zotero://open-pdf/0_8KTK8B7W/17\">7 Case Studies</a> <li><a href=\"zotero://open-pdf/0_8KTK8B7W/25\">8 Discussion</a> <li><a href=\"zotero://open-pdf/0_8KTK8B7W/29\">9 Conclusion</a> </ul> \n\nTL;DR \n\nThis article presents to software engineering researchers the six key challenges that a domain expert faces in addressing their problem with a computational workflow, and the underlying executable implementation and identifies which challenges and transformations are not sufficiently addressed by available tools."],"shorttitle":["Building Domain-Specific Machine Learning Workflows"],"title":["Building Domain-Specific Machine Learning Workflows: A Conceptual Framework for the State-of-the-Practice"],"url":["http://arxiv.org/abs/2203.08638"],"urldate":["2022-03-22"]},"creators":{"author":[{"lastName":"Oakes","firstName":"Bentley James"},{"lastName":"Famelis","firstName":"Michalis"},{"lastName":"Sahraoui","firstName":"Houari"}]}},{"key":"obrenovicQuotesIEEESoftware2018","type":"article","fields":{"abstract":["This alternative view of IEEE Software history presents quotes organized in conversations. Each conversation pairs a quote from the magazine’s early days (1984–1990) with a more contemporary quote, with at least 20 years between the two. The aim is to illustrate that some key ideas and topics are classic and have value even decades later. Additional pairs of quotes are available in the Web Extra at https://extras.computer.org/extra/mso2018050010s1.pdf. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Obrenović, Ž"],"date":["2018-09"],"doi":["10.1109/MS.2018.3571243"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nThis alternative view of IEEE Software history presents quotes organized in conversations, illustrating that some key ideas and topics are classic and have value even decades later."],"number":["5"],"pages":["10–13"],"title":["Quotes from IEEE Software History"],"volume":["35"]},"creators":{"author":[{"lastName":"Obrenović","firstName":"Ž"}]}},{"key":"ODMD14a","type":"inproceedings","fields":{"author":["Ostuni, Vito Claudio","Di Noia, Tommaso","Mirizzi, Roberto","Di Sciascio, Eugenio"],"booktitle":["15th Int. Conf. Electron. Commer. Web Technol."],"date":["2014"],"publisher":["Springer"],"series":["Lecture notes in business information processing"],"title":["A linked data recommender system using a neighborhood-based graph kernel"],"url":["http://sisinflab.poliba.it/sisinflab/publications/ 2014/ODMD14a"]},"creators":{"author":[{"lastName":"Ostuni","firstName":"Vito Claudio"},{"lastName":"Di Noia","firstName":"Tommaso"},{"lastName":"Mirizzi","firstName":"Roberto"},{"lastName":"Di Sciascio","firstName":"Eugenio"}]},"sentenceCased":true},{"key":"odonovanIndustrialBigData2015","type":"article","fields":{"langid":["english"],"abstract":["The term smart manufacturing refers to a future-state of manufacturing, where the real-time transmission and analysis of data from across the factory creates manufacturing intelligence, which can be used to have a positive impact across all aspects of operations. In recent years, many initiatives and groups have been formed to advance smart manufacturing, with the most prominent being the Smart Manufacturing Leadership Coalition (SMLC), Industry 4.0, and the Industrial Internet Consortium. These initiatives comprise industry, academic and government partners, and contribute to the development of strategic policies, guidelines, and roadmaps relating to smart manufacturing adoption. In turn, many of these recommendations may be implemented using data-centric technologies, such as Big Data, Machine Learning, Simulation, Internet of Things and Cyber Physical Systems, to realise smart operations in the factory. Given the importance of machine uptime and availability in smart manufacturing, this research centres on the application of data-driven analytics to industrial equipment maintenance. The main contributions of this research are a set of data and system requirements for implementing equipment maintenance applications in industrial environments, and an information system model that provides a scalable and fault tolerant big data pipeline for integrating, processing and analysing industrial equipment data. These contributions are considered in the context of highly regulated large-scale manufacturing environments, where legacy (e.g. automation controllers) and emerging instrumentation (e.g. internet-aware smart sensors) must be supported to facilitate initial smart manufacturing efforts."],"author":["O’Donovan, P.","Leahy, K.","Bruton, K.","O’Sullivan, D. T. J."],"date":["2015-12"],"doi":["10.1186/s40537-015-0034-z"],"issn":["2196-1115"],"journaltitle":["Journal of Big Data"],"number":["1"],"pages":["25"],"title":["An industrial big data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities"],"volume":["2"]},"creators":{"author":[{"lastName":"O’Donovan","firstName":"P."},{"lastName":"Leahy","firstName":"K."},{"lastName":"Bruton","firstName":"K."},{"lastName":"O’Sullivan","firstName":"D. T. J."}]},"sentenceCased":true},{"key":"Ogden202151","type":"inproceedings","fields":{"abstract":["Deep learning (DL) models are rapidly expanding in popularity in large part due to rapid innovations in model accuracy, as well as companies' enthusiasm in integrating deep learning into the existing application logic. This trend will inevitably lead to a deployment scenario, akin to the content delivery network for web objects, where many deep learning models-each with different popularity-run on a shared edge with limited resources. In this paper, we set out to answer the key question of how to manage many deep learning models at the edge effectively. Via an empirical study based on profiling more than twenty deep learning models and extrapolating from an open-source Microsoft Azure workload trace, we pinpoint a promising avenue of leveraging cheaper CPUs, rather than commonly promoted accelerators, for edge-based deep inference serving. Based on our empirical insights, we formulate the DL model management problem as a classical caching problem, which we refer to as model-level caching. As an initial step towards realizing model-level caching, we propose a simple cache eviction policy, called CremeBrulee, by adapting BeladyMIN to explicitly consider DL model-specific factors when calculating each in-cache object's utility. Using a small-scale testbed, we demonstrate that CremeBrulee can achieve a 50% reduction in memory while keeping load latency below 92% of execution latency and less than 36% of the penalty of using a random approach to model eviction. Further, when scaling to more models and requests in a simulation, we demonstrate that CremeBrulee can keep the model load delay lower than other eviction policies that only consider workload characteristics by up to 16.6%. Relevant research artifacts are available at https://github.com/cake-lab/CremeBrulee © 2021 IEEE."],"author":["Ogden, S.S.","Gilman, G.R.","Walls, R.J.","Guo, T."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/ACSOS52086.2021.00027"],"editor":["El-Araby E., Kalogeraki V., Lassabe F., Porter B., Ghahremani S., Nunes I., Bakhouya M., Tomforde S., Pianini D."],"isbn":["978-1-66541-261-2"],"note":["cited By 0 \n\nTL;DR \n\nThis paper proposes a simple cache eviction policy, called CremeBrulee, by adapting BeladyMIN to explicitly consider DL model-specific factors when calculating each in-cache object's utility, and formulate the DL model management problem as a classical caching problem, which it refers to as model-level caching."],"pages":["51–60"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2021"],"source":["Scopus"],"title":["Many models at the edge: Scaling deep inference via model-level caching"]},"creators":{"author":[{"lastName":"Ogden","firstName":"S.S."},{"lastName":"Gilman","firstName":"G.R."},{"lastName":"Walls","firstName":"R.J."},{"lastName":"Guo","firstName":"T."}],"editor":[{"lastName":"El-Araby E.","suffix":"Kalogeraki V.","firstName":"Lassabe F., Porter B., Ghahremani S., Nunes I., Bakhouya M., Tomforde S., Pianini D."}]},"sentenceCased":true},{"key":"Okewu2020273","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Centre for Information Technology and Systems, University of Lagos, Lagos, Nigeria; Department of Electrical and Information Engineering, Covenant University, Ota, Nigeria; Department of Computer Sciences, University of Alcala, Henares, Spain"],"author":["Okewu, E.","Misra, S.","Lius, F.-S."],"correspondence_address1":["Okewu, E.; Centre for Information Technology and Systems, Nigeria; email: eokewu@unilag.edu.ng"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-58817-5_21"],"editor":["Gervasi O., Murgante B., Garau C., Blecic I., Taniar D., Apduhan B.O., Rocha A.M.A.C., Tarantino E., Torre C.M., Karaca Y., Misra S."],"isbn":["9783030588168"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 1 \n\nTL;DR \n\nAn engineering problem-solving approach to the open-air defecation health problem and it is demonstrated that besides being used to model software systems, computational models (software architecture) are useful in documenting and promoting understanding of concepts in virtually all fields of human endeavour."],"pages":["273–288"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["A software engineering approach to implementation of SDG 6 in adum-aiona community of nigeria"],"volume":["12254 LNCS"]},"creators":{"author":[{"lastName":"Okewu","firstName":"E."},{"lastName":"Misra","firstName":"S."},{"lastName":"Lius","firstName":"F.-S."}],"editor":[{"lastName":"Gervasi O.","suffix":"Murgante B.","firstName":"Garau C., Blecic I., Taniar D., Apduhan B.O., Rocha A.M.A.C., Tarantino E., Torre C.M., Karaca Y., Misra S."}]},"sentenceCased":true},{"key":"Okobiah2014365","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - Int. Symp. Qual. Electron. Des., ISQED"],"affiliation":["NanoSystem Design Laboratory (NSDL), University of North Texas, Denton, TX 76207, United States"],"art_number":["6783349"],"author":["Okobiah, O.","Mohanty, S.P.","Kougianos, E."],"date":["2014"],"document_type":["Conference Paper"],"doi":["10.1109/ISQED.2014.6783349"],"isbn":["978-1-4799-3946-6"],"issn":["19483287"],"note":["cited By 3"],"pages":["365–372"],"publisher":["IEEE Computer Society"],"series":["Proceedings - International Symposium on Quality Electronic Design, ISQED"],"source":["Scopus"],"title":["Kriging bootstrapped neural network training for fast and accurate process variation analysis"]},"creators":{"author":[{"lastName":"Okobiah","firstName":"O."},{"lastName":"Mohanty","firstName":"S.P."},{"lastName":"Kougianos","firstName":"E."}]},"sentenceCased":true},{"key":"oladeleMLModelRegistry2022","type":"online","fields":{"langid":["american"],"abstract":["Imagine you are the only data scientist on your team, you start working on a machine learning project and perform a series of experiments that produce various ML models (and artifacts) that you “track” through non-standard naming conventions. Since the naming conventions you used for your model files were unclear, it took you a while…"],"author":["Oladele, Stephen"],"date":["2022-08-03T12:21:51+00:00"],"organization":["neptune.ai"],"shorttitle":["ML Model Registry"],"title":["ML Model Registry: The Ultimate Guide"],"url":["https://neptune.ai/blog/ml-model-registry"],"urldate":["2024-01-31"]},"creators":{"author":[{"lastName":"Oladele","firstName":"Stephen"}]}},{"key":"olsonPMLBLargeBenchmark2017","type":"article","fields":{"langid":["english"],"abstract":["Background: The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous publicly available real-world and simulated benchmark datasets have emerged from different sources, but their organization and adoption as standards have been inconsistent. As such, selecting and curating specific benchmarks remains an unnecessary burden on machine learning practitioners and data scientists. Results: The present study introduces an accessible, curated, and developing public benchmark resource to facilitate identification of the strengths and weaknesses of different machine learning methodologies. We compare meta-features among the current set of benchmark datasets in this resource to characterize the diversity of available data. Finally, we apply a number of established machine learning methods to the entire benchmark suite and analyze how datasets and algorithms cluster in terms of performance. From this study, we find that existing benchmarks lack the diversity to properly benchmark machine learning algorithms, and there are several gaps in benchmarking problems that still need to be considered. Conclusions: This work represents another important step towards understanding the limitations of popular benchmarking suites and developing a resource that connects existing benchmarking standards to more diverse and efficient standards in the future."],"author":["Olson, Randal S.","La Cava, William","Orzechowski, Patryk","Urbanowicz, Ryan J.","Moore, Jason H."],"date":["2017-12"],"doi":["10.1186/s13040-017-0154-4"],"issn":["1756-0381"],"journaltitle":["BioData Mining"],"keywords":["LOGSEQ"],"number":["1"],"pages":["36"],"shorttitle":["PMLB"],"title":["PMLB: A large benchmark suite for machine learning evaluation and comparison"],"volume":["10"]},"creators":{"author":[{"lastName":"Olson","firstName":"Randal S."},{"lastName":"La Cava","firstName":"William"},{"lastName":"Orzechowski","firstName":"Patryk"},{"lastName":"Urbanowicz","firstName":"Ryan J."},{"lastName":"Moore","firstName":"Jason H."}]},"sentenceCased":true},{"key":"omaEnergyefficientModelFog2018","type":"article","fields":{"langid":["english"],"abstract":["A huge number of devices like sensors in addition to computers are interconnected in the IoT (Internet of Things). In the cloud computing model, sensor data is transmitted to servers in networks and processed on the servers in a cloud. Here, networks are congested and servers are overloaded due to heavy traffic from sensors. In order to reduce the delay time and network traffic and increase the performance of the system, data and processes are distributed to not only servers in a cloud but also fog nodes in fog computing models. While the traffic of servers in a cloud can be reduced, the total electric energy consumed by fog nodes increases to process sensor data. In this paper, we newly propose a treebased fog computing (TBFC) model to distribute processes and data to servers and fog nodes so that the total electric energy consumption of nodes can be reduced in the IoT. In the evaluation, we show the total electric energy consumption of nodes in the TBFC model is smaller than the cloud computing model."],"author":["Oma, Ryuji","Nakamura, Shigenari","Duolikun, Dilawaer","Enokido, Tomoya","Takizawa, Makoto"],"date":["2018-09"],"doi":["10.1016/j.iot.2018.08.003"],"issn":["25426605"],"journaltitle":["Internet Things"],"pages":["14–26"],"title":["An energy-efficient model for fog computing in the Internet of Things (IoT)"],"volume":["1–2"]},"creators":{"author":[{"lastName":"Oma","firstName":"Ryuji"},{"lastName":"Nakamura","firstName":"Shigenari"},{"lastName":"Duolikun","firstName":"Dilawaer"},{"lastName":"Enokido","firstName":"Tomoya"},{"lastName":"Takizawa","firstName":"Makoto"}]},"sentenceCased":true},{"key":"OpenVsClosedloop","type":"online","fields":{"title":["Open- vs. Closed-loop control | Control Engineering"],"url":["http://www.controleng.com/single-article/open-vs-closed-loop-control/f8d8023a15738d0fcfe78d6a2d71dd60.html"],"urldate":["2016-11-01"]},"creators":{},"sentenceCased":true},{"key":"OrchestratingATLModel","type":"article","fields":{"note":["TL;DR \n\nWires*, a graphical executable language for the orchestration of ATL transformations, which provides appropriate mechanisms to enable the modular and compositional specification and execution of complex model transformations chains."],"title":["Orchestrating ATL Model Transformations"]},"creators":{}},{"key":"osgi","type":"misc","fields":{"title":["Eclipse Equinox"],"url":["https://www.eclipse.org/equinox/"]},"creators":{}},{"key":"OSGiModularityTutorial","type":"online","fields":{"title":["OSGi Modularity - Tutorial"],"url":["http://www.vogella.com/tutorials/OSGi/article.html#introduction-into-software-modularity-with-osgi"],"urldate":["2016-12-02"]},"creators":{}},{"key":"osmanSATToSE2017Postproceedings2017","type":"article","fields":{"author":["Osman, H.","Chis, A.","Ruscio, D.D.","Zaytsev, V."],"date":["2017"],"ids":["osmanSATToSE2017Postproceedings2017a"],"journaltitle":["CEUR Workshop Proc."],"note":["cited By 0 \n\ncited By 0"],"title":["SATToSE 2017: The post-proceedings editorial"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045455178&partnerID=40&md5=6babe4f6ad63c4a50a18de55f9115cc3"],"volume":["2070"]},"creators":{"author":[{"lastName":"Osman","firstName":"H."},{"lastName":"Chis","firstName":"A."},{"lastName":"Ruscio","firstName":"D.D."},{"lastName":"Zaytsev","firstName":"V."}]},"sentenceCased":true},{"key":"ostuniTopnRecommendationsImplicit2013","type":"inproceedings","fields":{"acmid":["2507172"],"author":["Ostuni, Vito Claudio","Di Noia, Tommaso","Di Sciascio, Eugenio","Mirizzi, Roberto"],"booktitle":["Proc. 7th ACM Conf. Recomm. Syst."],"date":["2013"],"isbn":["978-1-4503-2409-0"],"keywords":["dbpedia","hybrid recommender system","implicit feedback","learning to rank","linked data","top-n recommendations"],"location":["New York, NY, USA"],"nodoi":["10.1145/2507157.2507172"],"note":["TL;DR \n\nSPrank is presented, a novel hybrid recommendation algorithm able to compute top-N item recommendations from implicit feedback exploiting the information available in the so called Web of Data."],"numpages":["8"],"pages":["85–92"],"publisher":["ACM"],"series":["RecSys '13"],"title":["Top-n recommendations from implicit feedback leveraging linked open data"],"url":["http://doi.acm.org/10.1145/2507157.2507172"]},"creators":{"author":[{"lastName":"Ostuni","firstName":"Vito Claudio"},{"lastName":"Di Noia","firstName":"Tommaso"},{"lastName":"Di Sciascio","firstName":"Eugenio"},{"lastName":"Mirizzi","firstName":"Roberto"}]},"sentenceCased":true},{"key":"oubelliScalableModelBased2018","type":"article","fields":{"langid":["english"],"author":["Oubelli, Lynda Ait","Aït Ameur, Yamine","Bedouet, Judicael","Kervarc, Romain","Chausserie-Laprée, Benoit","Larzul, Béatrice"],"date":["2018-08"],"doi":["10.1016/j.cl.2018.08.001"],"issn":["14778424"],"journaltitle":["Comput. Lang. Syst. Struct."],"shorttitle":["A scalable model based approach for data model evolution"],"title":["A scalable model based approach for data model evolution: Application to space missions data models"]},"creators":{"author":[{"lastName":"Oubelli","firstName":"Lynda Ait"},{"lastName":"Aït Ameur","firstName":"Yamine"},{"lastName":"Bedouet","firstName":"Judicael"},{"lastName":"Kervarc","firstName":"Romain"},{"lastName":"Chausserie-Laprée","firstName":"Benoit"},{"lastName":"Larzul","firstName":"Béatrice"}]},"sentenceCased":true},{"key":"ouelletControlSwarmsAutonomous2011","type":"inproceedings","fields":{"author":["Ouellet, Dany","Givigi, Sidney N.","Beaulieu, Alain JG"],"booktitle":["Syst. Conf. SysCon 2011 IEEE Int."],"date":["2011"],"note":["TL;DR \n\nThis work focuses on swarms of robots, defined as the capability of robots to keep close to each other in formation, without colliding with neighbors and obstacles, and uses IBM Rational Rose Real-Time™ (RoseRT) to implement such a controller in emulation following the formalism of Model-Driven Development."],"pages":["512–519"],"publisher":["IEEE"],"title":["Control of swarms of autonomous robots using Model Driven Development-A state-based approach"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5929129"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Ouellet","firstName":"Dany"},{"lastName":"Givigi","firstName":"Sidney N."},{"lastName":"Beaulieu","firstName":"Alain JG"}]},"sentenceCased":true},{"key":"ouniSearchbasedSoftwareLibrary2017","type":"article","fields":{"langid":["english"],"acmid":["3032325"],"address":["Newton, MA, USA"],"author":["Ouni, Ali","Kula, Raula Gaikovina","Kessentini, Marouane","Ishio, Takashi","German, Daniel M.","Inoue, Katsuro"],"date":["2017-03"],"doi":["10.1016/j.infsof.2016.11.007"],"ids":["Ouni:2017:SSL:3032135.3032325"],"issn":["09505849"],"issue_date":["March 2017"],"journaltitle":["Inf. Softw. Technol."],"keywords":["Multi-objective optimization","Search-based software engineering","Software library","Software reuse"],"location":["Newton, MA, USA"],"nodoi":["10.1016/j.infsof.2016.11.007"],"numpages":["21"],"pages":["55–75"],"pagetotal":["21"],"publisher":["Butterworth-Heinemann"],"title":["Search-based software library recommendation using multi-objective optimization"],"volume":["83"]},"creators":{"author":[{"lastName":"Ouni","firstName":"Ali"},{"lastName":"Kula","firstName":"Raula Gaikovina"},{"lastName":"Kessentini","firstName":"Marouane"},{"lastName":"Ishio","firstName":"Takashi"},{"lastName":"German","firstName":"Daniel M."},{"lastName":"Inoue","firstName":"Katsuro"}]},"sentenceCased":true},{"key":"OverviewAutonomousSystems","type":"online","fields":{"title":["Overview of the Autonomous Systems Area | Wallenberg ASP"],"url":["http://wasp-sweden.org/research/overview-of-autonomous-systems-area/"],"urldate":["2016-08-26"]},"creators":{}},{"key":"ozkayaApplicationLargeLanguage2023","type":"article","fields":{"langid":["english"],"author":["Ozkaya, Ipek"],"date":["2023-05"],"doi":["10.1109/MS.2023.3248401"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"keywords":["LOGSEQ"],"number":["3"],"pages":["4–8"],"shorttitle":["Application of Large Language Models to Software Engineering Tasks"],"title":["Application of Large Language Models to Software Engineering Tasks: Opportunities, Risks, and Implications"],"volume":["40"]},"creators":{"author":[{"lastName":"Ozkaya","firstName":"Ipek"}]}},{"key":"Ozyegen2020148","type":"inproceedings","fields":{"abstract":["AIM: In this paper, we set out to understand the capabilities of conditional generative adversarial networks (cGANs) in the generation of electromagnetic engineered surfaces (EES). BACKGROUND: As the use of radio spectrum is increasing, one direction to increase the supply is by tapping into available high frequency spectrum and engineer the propagation environment through carefully designed electromagnetic engineered surfaces. Generative models such as GANs, can learn to generate new designs by training on existing dataset but have been traditionally applied in the domains of image processing and text generation. METHODOLOGY: We propose to train a cGAN for EES generation. The cGAN is first tested on the MNIST dataset to ensure convergent training. Next EES transfer functions categories of interest are defined and k-means clustering is used to assign EES designs in our dataset. The cGAN is then trained on the 9x9 EES dataset and its performance is evaluated using several metrics. RESULTS: Our results indicate that the proposed cGAN is able to generate different engineered surface designs given a desired transfer function, improving the accuracy by at least 3 fold compared to a random generation process. CONCLUSION: The application of cGANs on EES shows the applicability of machine learning such as generative models in engineering applications with design constraints. © 2019 Copyright held by the owner/author(s)."],"author":["Ozyegen, O.","Ethier, J.","Kavurmacioglu, E.","Basar, A."],"author_keywords":["Electromagnetic engineered surfaces; Generative adversarial networks; Machine learning; Mm-Wave spectrum; Smart environments"],"date":["2020"],"document_type":["Conference Paper"],"editor":["Pakfetrat T., Jourdan G.-V., Enenkel R., Kontogiannis K."],"keywords":["Adversarial networks","Design constraints","Engineered surfaces","Engineering applications","Engineering education","Generative model","High frequency spectrum","Image processing","K-means clustering","Millimeter waves","Propagation environment","Random generation","Software engineering","Transfer functions"],"note":["cited By 1"],"pages":["148–155"],"publisher":["Center for Advanced Studies on Collaborative Research"],"series":["CASCON 2019 Proceedings - Conference of the Centre for Advanced Studies on Collaborative Research - Proceedings of the 29th Annual International Conference on Computer Science and Software Engineering"],"source":["Scopus"],"title":["Generative adversarial networks in designing electromagnetic engineered surfaces for mm-wave band spectrum environments"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087415807&partnerID=40&md5=2f9c4b54b7bb3b545fa2d9492edd3929"]},"creators":{"author":[{"lastName":"Ozyegen","firstName":"O."},{"lastName":"Ethier","firstName":"J."},{"lastName":"Kavurmacioglu","firstName":"E."},{"lastName":"Basar","firstName":"A."}],"editor":[{"lastName":"Pakfetrat T.","suffix":"Jourdan G.-V.","firstName":"Enenkel R., Kontogiannis K."}]},"sentenceCased":true},{"key":"PaaSword","type":"online","fields":{"title":["PaaSword"],"url":["https://sites.google.com/site/paaswordeu/"],"urldate":["2015-04-08"]},"creators":{}},{"key":"Padget201435","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["IEEE Int. Workshop Artif. Intell. Requir. Eng., AIRE - Proc."],"affiliation":["Department of Computer Science, University of Bath, United Kingdom; National Institute of Informatics and Sokendai, Japan; National Institute of Informatics, Japan"],"art_number":["6894854"],"author":["Padget, J.","Elakehal, E.E.","Satoh, K.","Ishikawa, F."],"correspondence_address1":["Padget, J.; Department of Computer Science, University of BathUnited Kingdom"],"date":["2014"],"document_type":["Conference Paper"],"doi":["10.1109/AIRE.2014.6894854"],"isbn":["978-1-4799-6355-3"],"keywords":["GOAL_Model-Requirements","notion","TECHNIQUE_ASP"],"note":["ASP \n\ncited By 3"],"pages":["35–42"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["2014 IEEE 1st International Workshop on Artificial Intelligence for Requirements Engineering, AIRE 2014 - Proceedings"],"source":["Scopus"],"title":["On requirements representation and reasoning using answer set programming"]},"creators":{"author":[{"lastName":"Padget","firstName":"J."},{"lastName":"Elakehal","firstName":"E.E."},{"lastName":"Satoh","firstName":"K."},{"lastName":"Ishikawa","firstName":"F."}]},"sentenceCased":true},{"key":"pageLearningAutonomousSystems2017","type":"inproceedings","fields":{"author":["Page, Brian R.","Ziaeefard, Saeedeh","Moridian, Barzin","Mahmoudian, Nina"],"booktitle":["2017 IEEE Front. Educ. Conf. FIE"],"date":["2017-10"],"doi":["10.1109/FIE.2017.8190555"],"eventtitle":["2017 IEEE Frontiers in Education Conference (FIE)"],"isbn":["978-1-5090-5920-1"],"location":["Indianapolis, IN"],"pages":["1–7"],"publisher":["IEEE"],"title":["Learning autonomous systems — An interdisciplinary project-based experience"]},"creators":{"author":[{"lastName":"Page","firstName":"Brian R."},{"lastName":"Ziaeefard","firstName":"Saeedeh"},{"lastName":"Moridian","firstName":"Barzin"},{"lastName":"Mahmoudian","firstName":"Nina"}]},"sentenceCased":true},{"key":"paigeEvolvingModelsModelDriven2015","type":"article","fields":{"author":["Paige, Richard F.","Matragkas, Nicholas","Rose, Louis M."],"date":["2015"],"ids":["paigeEvolvingModelsModelDriven2016,wrro110199"],"journaltitle":["J. Syst. Softw."],"shorttitle":["Evolving Models in Model-Driven Engineering"],"title":["Evolving Models in Model-Driven Engineering: State-of-the-Art and Future Challenges"],"url":["http://www.sciencedirect.com/science/article/pii/S0164121215001909"],"urldate":["2015-10-19"]},"creators":{"author":[{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Matragkas","firstName":"Nicholas"},{"lastName":"Rose","firstName":"Louis M."}]}},{"key":"paigeProceedings2015ACM2015","type":"book","fields":{"date":["2015"],"doi":["10.1145/2814251"],"editor":["Paige, Richard F.","Ruscio, Davide Di","Völter, Markus"],"ids":["paigeProceedings2015ACM2015a"],"isbn":["978-1-4503-3686-4"],"publisher":["ACM"],"title":["Proceedings of the 2015 ACM SIGPLAN International Conference on Software Language Engineering, SLE 2015, Pittsburgh, PA, USA, October 25-27, 2015"]},"creators":{"editor":[{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Völter","firstName":"Markus"}]}},{"key":"paigeRigorousIdentificationEncoding2010","type":"article","fields":{"author":["Paige, Richard F.","Drivalos, Nikolaos","Kolovos, Dimitrios S.","Fernandes, Kiran J.","Power, Christopher","Olsen, Goran K.","Zschaler, Steffen"],"date":["2010"],"doi":["10.1007/s10270-010-0158-8"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nThis paper demonstrates how to identify the different kinds of trace-links that may appear in an end-to-end MDE process and describes a rigorous approach to defining semantically rich trace- links between models, where the models themselves may be constructed using diverse modelling languages."],"number":["4"],"pages":["469–487"],"title":["Rigorous identification and encoding of trace-links in model-driven engineering"],"volume":["10"]},"creators":{"author":[{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Drivalos","firstName":"Nikolaos"},{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"Fernandes","firstName":"Kiran J."},{"lastName":"Power","firstName":"Christopher"},{"lastName":"Olsen","firstName":"Goran K."},{"lastName":"Zschaler","firstName":"Steffen"}]},"sentenceCased":true},{"key":"pakdeetrakulwongRecommendationSystemsSoftware2014","type":"inproceedings","fields":{"author":["Pakdeetrakulwong, Udsanee","Wongthongtham, Pornpit","Siricharoen, Waralak V."],"date":["2014-12"],"isbn":["978-1-908320-39-1"],"nodoi":["10.1109/ICITST.2014.7038793"],"note":["TL;DR \n\nA survey of recommendation systems for software engineering focusing in particular on what they can assist users in each software development life cycle phase is conducted."],"pages":["137–142"],"publisher":["IEEE"],"shorttitle":["Recommendation systems for software engineering"],"title":["Recommendation systems for software engineering: A survey from software development life cycle phase perspective"],"url":["http://ieeexplore.ieee.org/document/7038793/"],"urldate":["2017-06-19"]},"creators":{"author":[{"lastName":"Pakdeetrakulwong","firstName":"Udsanee"},{"lastName":"Wongthongtham","firstName":"Pornpit"},{"lastName":"Siricharoen","firstName":"Waralak V."}]},"sentenceCased":true},{"key":"palyartMDE4HPCApproachUsing2011","type":"inproceedings","fields":{"author":["Palyart, Marc","Lugato, David","Ober, Ileana","Bruel, Jean-Michel"],"booktitle":["Int. SDL Forum"],"date":["2011"],"pages":["247–261"],"publisher":["Springer"],"shorttitle":["MDE4HPC"],"title":["MDE4HPC: An approach for using model-driven engineering in high-performance computing"],"url":["http://link.springer.com/10.1007%2F978-3-642-25264-8_19"],"urldate":["2017-02-23"]},"creators":{"author":[{"lastName":"Palyart","firstName":"Marc"},{"lastName":"Lugato","firstName":"David"},{"lastName":"Ober","firstName":"Ileana"},{"lastName":"Bruel","firstName":"Jean-Michel"}]},"sentenceCased":true},{"key":"PAM","type":"article","fields":{"author":["Fowkes, Jaroslav","Sutton, Charles"],"note":["last access 24.08.2018 \n\nlast access 24.08.2018 \n\nlast access 24.08.2018 \n\nlast access 24.08.2018 \n\nlast access 24.08.2018"],"title":["PAM: Probabilistic API miner"],"url":["https://github.com/mast-group/api-mining"]},"creators":{"author":[{"lastName":"Fowkes","firstName":"Jaroslav"},{"lastName":"Sutton","firstName":"Charles"}]},"sentenceCased":true},{"key":"panachEvaluatingModelDrivenDevelopment2021","type":"article","fields":{"author":["Panach, Jose Ignacio","Dieste, Oscar","Marin, Beatriz","Espana, Sergio","Vegas, Sira","Pastor, Oscar","Juristo, Natalia"],"date":["2021-01-01"],"doi":["10.1109/TSE.2018.2884706"],"issn":["0098-5589, 1939-3520, 2326-3881"],"journaltitle":["IIEEE Trans. Software Eng."],"note":["TL;DR \n\nSix replications of the baseline are reported to study the impact of problem complexity on software quality in the context of model-driven development, suggesting that MDD yields better quality for more complex problems."],"number":["1"],"pages":["130–145"],"shorttitle":["Evaluating Model-Driven Development Claims with Respect to Quality"],"title":["Evaluating Model-Driven Development Claims with Respect to Quality: A Family of Experiments"],"volume":["47"]},"creators":{"author":[{"lastName":"Panach","firstName":"Jose Ignacio"},{"lastName":"Dieste","firstName":"Oscar"},{"lastName":"Marin","firstName":"Beatriz"},{"lastName":"Espana","firstName":"Sergio"},{"lastName":"Vegas","firstName":"Sira"},{"lastName":"Pastor","firstName":"Oscar"},{"lastName":"Juristo","firstName":"Natalia"}]}},{"key":"panDevelopingHybridIntrusion2015","type":"article","fields":{"langid":["english"],"abstract":["Synchrophasor systems provide an immense volume of data for wide area monitoring and control of power systems to meet the increasing demand of reliable energy. The construction of traditional intrusion detection systems (IDSs) that use manually created rules based upon expert knowledge is knowledge-intensive and is not suitable in the context of this big data problem. This paper presents a systematic and automated approach to build a hybrid IDS that learns temporal state-based specifications for power system scenarios including disturbances, normal control operations, and cyber-attacks. A data mining technique called common path mining is used to automatically and accurately learn patterns for scenarios from a fusion of synchrophasor measurement data, and power system audit logs. As a proof of concept, an IDS prototype was implemented and validated. The IDS prototype accurately classifies disturbances, normal control operations, and cyber-attacks for the distance protection scheme for a two-line three-bus power transmission system."],"author":["Pan, Shengyi","Morris, Thomas","Adhikari, Uttam"],"date":["2015-11"],"doi":["10.1109/TSG.2015.2409775"],"issn":["1949-3053, 1949-3061"],"journaltitle":["IEEE Trans. Smart Grid"],"note":["TL;DR \n\nA systematic and automated approach to build a hybrid IDS that learns temporal state-based specifications for power system scenarios including disturbances, normal control operations, and cyber-attacks is presented."],"number":["6"],"pages":["3104–3113"],"title":["Developing a Hybrid Intrusion Detection System Using Data Mining for Power Systems"],"volume":["6"]},"creators":{"author":[{"lastName":"Pan","firstName":"Shengyi"},{"lastName":"Morris","firstName":"Thomas"},{"lastName":"Adhikari","firstName":"Uttam"}]}},{"key":"Panichella:2013:EUT:2486788.2486857","type":"inproceedings","fields":{"acmid":["2486857"],"author":["Panichella, Annibale","Dit, Bogdan","Oliveto, Rocco","Di Penta, Massimiliano","Poshyvanyk, Denys","De Lucia, Andrea"],"booktitle":["Proc. 2013 Int. Conf. Softw. Eng."],"date":["2013"],"isbn":["978-1-4673-3076-3"],"location":["Piscataway, NJ, USA"],"numpages":["10"],"pages":["522–531"],"publisher":["IEEE Press"],"series":["ICSE '13"],"title":["How to effectively use topic models for software engineering tasks? An approach based on genetic algorithms"],"url":["http://dl.acm.org.univaq.clas.cineca.it/citation.cfm?id=2486788.2486857"]},"creators":{"author":[{"lastName":"Panichella","firstName":"Annibale"},{"lastName":"Dit","firstName":"Bogdan"},{"lastName":"Oliveto","firstName":"Rocco"},{"lastName":"Di Penta","firstName":"Massimiliano"},{"lastName":"Poshyvanyk","firstName":"Denys"},{"lastName":"De Lucia","firstName":"Andrea"}]},"sentenceCased":true},{"key":"Pant2020504","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Adv. Intell. Sys. Comput."],"affiliation":["University of Bradford, Bradford, United Kingdom; University of La Laguna, Tenerife, Spain"],"author":["Pant, G.","Campean, F.","Korsunovs, A.","Neagu, D.","Garcia-Afonso, O."],"correspondence_address1":["Pant, G.; University of BradfordUnited Kingdom; email: g.pant@bradford.ac.uk"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-29933-0_42"],"editor":["Ju Z., Zhou D., Yang L., Yang C., Gegov A."],"isbn":["9783030299323"],"issn":["21945357"],"journaltitle":["Adv. Intell. Syst. Comput."],"keywords":["notion"],"note":["cited By 1"],"pages":["504–516"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Co-modelling strategy for development of airpath metamodel on multi-physics simulation platform"],"volume":["1043"]},"creators":{"author":[{"lastName":"Pant","firstName":"G."},{"lastName":"Campean","firstName":"F."},{"lastName":"Korsunovs","firstName":"A."},{"lastName":"Neagu","firstName":"D."},{"lastName":"Garcia-Afonso","firstName":"O."}],"editor":[{"lastName":"Ju Z.","suffix":"Zhou D.","firstName":"Yang L., Yang C., Gegov A."}]},"sentenceCased":true},{"key":"papagelisQualitativeAnalysisUserbased2005","type":"inproceedings","fields":{"abstract":["Recommendation agents employ prediction algorithms to provide users with items that match their interests. In this paper, we describe and evaluate several prediction algorithms, some of which are novel in that they combine user-based and item-based similarity measures derived from either explicit or implicit ratings. We compare both statistical and decision-support accuracy metrics of the algorithms against different levels of data sparsity and different operational thresholds. The first metric evaluates the accuracy in terms of average absolute deviation, while the second evaluates how effectively predictions help users to select high-quality items. Our experimental results indicate better performance of item-based predictions derived from explicit ratings in relation to both metrics. Category-boosted predictions can lead to slightly better predictions when combined with explicit ratings, while implicit ratings (in the sense that we have defined them here) perform much worse than explicit ratings."],"acmid":["1707132"],"address":["Tarrytown, NY, USA"],"author":["Papagelis, Manos","Plexousakis, Dimitris"],"booktitle":["Eng. Appl. Artif. Intell."],"date":["2005-10"],"editor":["Klusch, Matthias","Ossowski, Sascha","Kashyap, Vipul","Unland, Rainer"],"isbn":["978-3-540-30104-2"],"issue_date":["October, 2005"],"keywords":["Collaborative filtering","Recommendation algorithms","Similarity measures"],"location":["Berlin, Heidelberg"],"nodoi":["10.1016/j.engappai.2005.06.010"],"numpages":["9"],"pages":["152–166"],"publisher":["Pergamon Press, Inc."],"title":["Qualitative analysis of user-based and item-based prediction algorithms for recommendation agents"],"url":["http://dx.doi.org/10.1016/j.engappai.2005.06.010"],"volume":["18"]},"creators":{"author":[{"lastName":"Papagelis","firstName":"Manos"},{"lastName":"Plexousakis","firstName":"Dimitris"}],"editor":[{"lastName":"Klusch","firstName":"Matthias"},{"lastName":"Ossowski","firstName":"Sascha"},{"lastName":"Kashyap","firstName":"Vipul"},{"lastName":"Unland","firstName":"Rainer"}]},"sentenceCased":true},{"key":"papineniBleuMethodAutomatic2002","type":"inproceedings","fields":{"author":["Papineni, Kishore","Roukos, Salim","Ward, Todd","Zhu, Wei-Jing"],"booktitle":["Proc. 40th Annu. Meet. Assoc. Comput. Linguist."],"date":["2002-07"],"doi":["10.3115/1073083.1073135"],"eventtitle":["ACL 2002"],"location":["Philadelphia, Pennsylvania, USA"],"note":["TL;DR \n\nThis work proposes a method of automatic machine translation evaluation that is quick, inexpensive, and language-independent, that correlates highly with human evaluation, and that has little marginal cost per run."],"pages":["311–318"],"publisher":["Association for Computational Linguistics"],"shorttitle":["Bleu"],"title":["Bleu: A Method for Automatic Evaluation of Machine Translation"]},"creators":{"author":[{"lastName":"Papineni","firstName":"Kishore"},{"lastName":"Roukos","firstName":"Salim"},{"lastName":"Ward","firstName":"Todd"},{"lastName":"Zhu","firstName":"Wei-Jing"}]}},{"key":"PapyrusIoTModeling","type":"online","fields":{"note":["TL;DR \n\nA highlight to the current status of Papyrus, an open source Modeling Environment to tackle specific IoT’s challenges: from heterogeneous applications development and management, realtime models to supervision of critical running system."],"title":["Papyrus for IoT – A Modeling Solution for IoT"],"url":["https://www.eclipse.org/community/eclipse_newsletter/2016/april/article3.php"],"urldate":["2016-08-21"]},"creators":{}},{"key":"ParallelProgrammingModel","type":"online","fields":{"title":["1.3 A Parallel Programming Model"],"url":["http://www.mcs.anl.gov/~itf/dbpp/text/node9.html"],"urldate":["2017-02-23"]},"creators":{}},{"key":"Park2015","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Des. Eng. Tech. Conf."],"affiliation":["Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI 48202, United States; Group Leader, Advanced Steel Technology R and A Engineering, Ford Motor Company, Dearborn, MI 48124, United States"],"author":["Park, J.","Kim, K.-Y.","Sohmshetty, R."],"date":["2015"],"document_type":["Conference Paper"],"doi":["10.1115/DETC201546236"],"isbn":["978-0-7918-5707-6"],"keywords":["notion"],"note":["cited By 6"],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the ASME Design Engineering Technical Conference"],"source":["Scopus"],"title":["A prediction modeling framework: Toward integration of noisy manufacturing data and product design"],"volume":["2A-2015"]},"creators":{"author":[{"lastName":"Park","firstName":"J."},{"lastName":"Kim","firstName":"K.-Y."},{"lastName":"Sohmshetty","firstName":"R."}]},"sentenceCased":true},{"key":"Park202083","type":"article","fields":{"abstract":["In recent years, several kinds of machine learning tools have developed, each involving complex functions and tasks, which means usage knowledge varies between tools. Integrating the environment for effective AI machine learning can be regarded as a complicated task and may even consist of several separate tasks, such as building a test environment, data acquisition, data cleansing, machine learning training, and model management. In terms of the cognitive engineering approach, most tasks not only require knowledge-based cognitive control over skill-based or rule-based behaviours higher cognitive loads and workloads as well. Since complex knowledge and higher cognitive loads are required, the use of AI machine learning is limited and leads to ineffective work procedures. Thus, this research analysed the AI development process via various methods of cognitive task analysis in order to identify which tasks induce cognitive workload. Then, a new integrated AI development system was created, which was expected to reduce the number of ineffective tasks and workload. Experiments were conducted twice to validate the system’s effectiveness, and the results indicate that there were significant differences between the several different AI development tasks. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020."],"author":["Park, D.","Park, H.","Song, S."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-51828-8_12"],"editor":["Ahram T., Falcao C."],"isbn":["9783030518271"],"issn":["21945357"],"journaltitle":["Adv. Intell. Syst. Comput."],"note":["cited By 1 \n\nTL;DR \n\nThis research analysed the AI development process via various methods of cognitive task analysis in order to identify which tasks induce cognitive workload, and created a new integrated AI development system, which was expected to reduce the number of ineffective tasks and workload."],"pages":["83–96"],"publisher":["Springer"],"source":["Scopus"],"title":["Designing the ai developing system through ecological interface design"],"volume":["1217 AISC"]},"creators":{"author":[{"lastName":"Park","firstName":"D."},{"lastName":"Park","firstName":"H."},{"lastName":"Song","firstName":"S."}],"editor":[{"lastName":"Ahram T.","firstName":"Falcao C."}]},"sentenceCased":true},{"key":"parkIoTRoutingArchitecture2014","type":"inproceedings","fields":{"author":["Park, Soochang","Crespi, Noel","Park, Hosung","Kim, Sang-Ha"],"booktitle":["Internet Things WF-IoT 2014 IEEE World Forum On"],"date":["2014"],"note":["TL;DR \n\nA future-driven routing architecture for Internet of Things, addressing classification of diverse features of ASoTs, and exploring new challenges especially on inter-domain routing is presented."],"pages":["442–445"],"publisher":["IEEE"],"title":["IoT routing architecture with autonomous systems of things"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6803207"],"urldate":["2016-11-02"]},"creators":{"author":[{"lastName":"Park","firstName":"Soochang"},{"lastName":"Crespi","firstName":"Noel"},{"lastName":"Park","firstName":"Hosung"},{"lastName":"Kim","firstName":"Sang-Ha"}]},"sentenceCased":true},{"key":"parkSelfmanagementSystemBased2006","type":"inproceedings","fields":{"author":["Park, Jeongmin","Yoo, Giljong","Jeong, Chulho","Lee, Eunseok"],"booktitle":["Asia-Pac. Netw. Oper. Manag. Symp."],"date":["2006"],"pages":["372–382"],"publisher":["Springer"],"title":["Self-management system based on self-healing mechanism"],"url":["http://link.springer.com/chapter/10.1007/11876601_38"],"urldate":["2016-09-21"]},"creators":{"author":[{"lastName":"Park","firstName":"Jeongmin"},{"lastName":"Yoo","firstName":"Giljong"},{"lastName":"Jeong","firstName":"Chulho"},{"lastName":"Lee","firstName":"Eunseok"}]},"sentenceCased":true},{"key":"Parnas1971Information","type":"report","fields":{"author":["Parnas, David L."],"date":["1971"],"institution":["Departement of Computer Science, Carnegie Mellon University"],"location":["Pittsburgh"],"title":["Information distribution aspects of design methodology"]},"creators":{"author":[{"lastName":"Parnas","firstName":"David L."}]},"sentenceCased":true},{"key":"parnasCriteriaBeUsed1972","type":"article","fields":{"langid":["english"],"abstract":["This paper discusses modularization as a mechanism for improving the flexibility and comprehensibility of a system while allowing the shortening of its development time. The effectiveness of a \"modularization\" is dependent upon the criteria used in dividing the system into modules. A system design problem is presented and both a conventional and unconventional decomposition are described. It is shown that the unconventional decompositions have distinct advantages for the goals outlined. The criteria used in arriving at the decompositions are discussed. The unconventional decomposition, if implemented with the conventional assumption that a module consists of one or more subroutines, will be less efficient in most cases. An alternative approach to implementation which does not have this effect is sketched."],"author":["Parnas, D L"],"date":["1972"],"number":["12"],"pages":["6"],"title":["On the Criteria To Be Used in Decomposing Systems into Modules"],"volume":["15"]},"creators":{"author":[{"lastName":"Parnas","firstName":"D L"}]}},{"key":"parnin2012crowd","type":"article","fields":{"author":["Parnin, Chris","Treude, Christoph","Grammel, Lars","Storey, Margaret-Anne"],"date":["2012"],"journaltitle":["Ga. Inst. Technol. Tech Rep"],"title":["Crowd documentation: Exploring the coverage and the dynamics of API discussions on Stack Overflow"]},"creators":{"author":[{"lastName":"Parnin","firstName":"Chris"},{"lastName":"Treude","firstName":"Christoph"},{"lastName":"Grammel","firstName":"Lars"},{"lastName":"Storey","firstName":"Margaret-Anne"}]},"sentenceCased":true},{"key":"parra-ullauriEventdrivenTemporalModels2022","type":"article","fields":{"langid":["english"],"abstract":["Abstract Modern software systems are increasingly expected to show higher degrees of autonomy and self-management to cope with uncertain and diverse situations. As a consequence, autonomous systems can exhibit unexpected and surprising behaviours. This is exacerbated due to the ubiquity and complexity of Artificial Intelligence (AI)-based systems. This is the case of Reinforcement Learning (RL), where autonomous agents learn through trial-and-error how to find good solutions to a problem. Thus, the underlying decision-making criteria may become opaque to users that interact with the system and who may require explanations about the system’s reasoning. Available work for eXplainable Reinforcement Learning (XRL) offers different trade-offs: e.g. for runtime explanations, the approaches are model-specific or can only analyse results after-the-fact. Different from these approaches, this paper aims to provide an online model-agnostic approach for XRL towards trustworthy and understandable AI. We present ETeMoX, an architecture based on temporal models to keep track of the decision-making processes of RL systems. In cases where the resources are limited (e.g. storage capacity or time to response), the architecture also integrates complex event processing, an event-driven approach, for detecting matches to event patterns that need to be stored, instead of keeping the entire history. The approach is applied to a mobile communications case study that uses RL for its decision-making. In order to test the generalisability of our approach, three variants of the underlying RL algorithms are used: Q-Learning, SARSA and DQN. The encouraging results show that using the proposed configurable architecture, RL developers are able to obtain explanations about the evolution of a metric, relationships between metrics, and were able to track situations of interest happening over time windows."],"author":["Parra-Ullauri, Juan Marcelo","García-Domínguez, Antonio","Bencomo, Nelly","Zheng, Changgang","Zhen, Chen","Boubeta-Puig, Juan","Ortiz, Guadalupe","Yang, Shufan"],"date":["2022-06"],"doi":["10.1007/s10270-021-00952-4"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"keywords":["GOAL_ExplainableReinforcementLearning","notion","TECHNIQUE_ReinforcementLearning"],"number":["3"],"pages":["1091–1113"],"shorttitle":["Event-driven temporal models for explanations - ETeMoX"],"title":["Event-driven temporal models for explanations - ETeMoX: Explaining reinforcement learning"],"volume":["21"]},"creators":{"author":[{"lastName":"Parra-Ullauri","firstName":"Juan Marcelo"},{"lastName":"García-Domínguez","firstName":"Antonio"},{"lastName":"Bencomo","firstName":"Nelly"},{"lastName":"Zheng","firstName":"Changgang"},{"lastName":"Zhen","firstName":"Chen"},{"lastName":"Boubeta-Puig","firstName":"Juan"},{"lastName":"Ortiz","firstName":"Guadalupe"},{"lastName":"Yang","firstName":"Shufan"}]},"sentenceCased":true},{"key":"ParreirasSW07","type":"inproceedings","fields":{"langid":["english"],"author":["Parreiras, Fernando Silva","Staab, Steffen","Winter, Andreas"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Proc. 6th Jt. Meet. Eur. Softw. Eng. Conf. ACM SIGSOFT Int. Symp. Found. Softw. Eng. 2007 Dubrov. Croat. Sept. 3-7 2007"],"date":["2007"],"doi":["10.1145/1287624.1287687"],"editor":["Crnkovic, Ivica","Bertolino, Antonia"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["439–448"],"publisher":["ACM"],"timestamp":["Tue, 01 Feb 2022 10:45:16 +0100"],"title":["On marrying ontological and metamodeling technical spaces"]},"creators":{"author":[{"lastName":"Parreiras","firstName":"Fernando Silva"},{"lastName":"Staab","firstName":"Steffen"},{"lastName":"Winter","firstName":"Andreas"}],"editor":[{"lastName":"Crnkovic","firstName":"Ivica"},{"lastName":"Bertolino","firstName":"Antonia"}]},"sentenceCased":true},{"key":"Passant:2010:DMR:1940334.1940349","type":"inproceedings","fields":{"acmid":["1940349"],"author":["Passant, Alexandre"],"booktitle":["Proc. 9th Int. Semantic Web Conf. Semantic Web - Vol. Part II"],"date":["2010"],"isbn":["3-642-17748-4 978-3-642-17748-4"],"keywords":["DBpedia","linked data","recommendation systems","semantic distance","semantic web applications"],"location":["Berlin, Heidelberg"],"numpages":["16"],"pages":["209–224"],"publisher":["Springer-Verlag"],"series":["ISWC'10"],"title":["Dbrec: Music recommendations using DBpedia"],"url":["http://dl.acm.org/citation.cfm?id=1940334.1940349"]},"creators":{"author":[{"lastName":"Passant","firstName":"Alexandre"}]},"sentenceCased":true},{"key":"passantMeasuringSemanticDistance2010","type":"inproceedings","fields":{"added-at":["2012-02-17T00:00:00.000+0100"],"author":["Passant, Alexandre"],"biburl":["http://www.bibsonomy.org/bibtex/2cdd5d7e0e615eb104fe56a4c90ceb96a/dblp"],"booktitle":["AAAI Spring Symp. Linked Data Meets Artif. Intell."],"date":["2010"],"ee":["http://www.aaai.org/ocs/index.php/SSS/SSS10/paper/view/1147"],"interhash":["eee04621d061bb7f9143ce6b36b9ded6"],"intrahash":["cdd5d7e0e615eb104fe56a4c90ceb96a"],"keywords":["dblp"],"note":["TL;DR \n\nThis paper demonstrates how to measure semantic distance on Linked Data in order to identify relatedness between resources, and how such measures can be used to provide a new kind of self-explanatory recommendations."],"publisher":["AAAI"],"timestamp":["2012-02-17T00:00:00.000+0100"],"title":["Measuring semantic distance on linking data and using it for resources recommendations."],"url":["http://dblp.uni-trier.de/db/conf/aaaiss/aaaiss2010-7.html#Passant10"]},"creators":{"author":[{"lastName":"Passant","firstName":"Alexandre"}]},"sentenceCased":true},{"key":"pastorAdvancedInformationSystems2005","type":"book","fields":{"date":["2005"],"doi":["10.1007/b136788"],"editor":["Pastor, Oscar","family=Cunha, given=João Falcão, prefix=e, useprefix=false"],"isbn":["3-540-26095-1"],"publisher":["Springer"],"series":["Lecture Notes in Computer Science"],"title":["Advanced Information Systems Engineering, 17th International Conference, CAiSE 2005, Porto, Portugal, June 13-17, 2005, Proceedings"],"volume":["3520"]},"creators":{"editor":[{"lastName":"Pastor","firstName":"Oscar"},{"lastName":"Cunha","firstName":"JoãoFalcão","prefix":"e","useprefix":false}]}},{"key":"patelEnablingHighlevelApplication2015","type":"article","fields":{"author":["Patel, Pankesh","Cassou, Damien"],"date":["2015"],"journaltitle":["J. Syst. Softw."],"pages":["62–84"],"title":["Enabling high-level application development for the Internet of Things"],"url":["http://www.sciencedirect.com/science/article/pii/S0164121215000187"],"urldate":["2016-05-30"],"volume":["103"]},"creators":{"author":[{"lastName":"Patel","firstName":"Pankesh"},{"lastName":"Cassou","firstName":"Damien"}]},"sentenceCased":true},{"key":"pattersonCarbonEmissionsLarge2021","type":"article","fields":{"abstract":["The computation demand for machine learning (ML) has grown rapidly recently, which comes with a number of costs. Estimating the energy cost helps measure its environmental impact and finding greener strategies, yet it is challenging without detailed information. We calculate the energy use and carbon footprint of several recent large models-T5, Meena, GShard, Switch Transformer, and GPT-3-and refine earlier estimates for the neural architecture search that found Evolved Transformer. We highlight the following opportunities to improve energy efficiency and CO2 equivalent emissions (CO2e): Large but sparsely activated DNNs can consume <1/10th the energy of large, dense DNNs without sacrificing accuracy despite using as many or even more parameters. Geographic location matters for ML workload scheduling since the fraction of carbon-free energy and resulting CO2e vary ~5X-10X, even within the same country and the same organization. We are now optimizing where and when large models are trained. Specific datacenter infrastructure matters, as Cloud datacenters can be ~1.4-2X more energy efficient than typical datacenters, and the ML-oriented accelerators inside them can be ~2-5X more effective than off-the-shelf systems. Remarkably, the choice of DNN, datacenter, and processor can reduce the carbon footprint up to ~100-1000X. These large factors also make retroactive estimates of energy cost difficult. To avoid miscalculations, we believe ML papers requiring large computational resources should make energy consumption and CO2e explicit when practical. We are working to be more transparent about energy use and CO2e in our future research. To help reduce the carbon footprint of ML, we believe energy usage and CO2e should be a key metric in evaluating models, and we are collaborating with MLPerf developers to include energy usage during training and inference in this industry standard benchmark."],"author":["Patterson, David","Gonzalez, Joseph","Le, Quoc","Liang, Chen","Munguia, Lluis-Miquel","Rothchild, Daniel","So, David","Texier, Maud","Dean, Jeff"],"date":["2021-04-23"],"eprint":["2104.10350"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv210410350 Cs"],"keywords":["Computer Science - Computers and Society","Computer Science - Machine Learning"],"note":["TL;DR \n\nThe energy use and carbon footprint of several recent large models are calculated-T5, Meena, GShard, Switch Transformer, and GPT-3-and earlier estimates for the neural architecture search that found Evolved Transformer are refined to avoid miscalculations."],"title":["Carbon Emissions and Large Neural Network Training"],"url":["http://arxiv.org/abs/2104.10350"],"urldate":["2022-04-04"]},"creators":{"author":[{"lastName":"Patterson","firstName":"David"},{"lastName":"Gonzalez","firstName":"Joseph"},{"lastName":"Le","firstName":"Quoc"},{"lastName":"Liang","firstName":"Chen"},{"lastName":"Munguia","firstName":"Lluis-Miquel"},{"lastName":"Rothchild","firstName":"Daniel"},{"lastName":"So","firstName":"David"},{"lastName":"Texier","firstName":"Maud"},{"lastName":"Dean","firstName":"Jeff"}]}},{"key":"pautassoMicroservicesPracticePart2017","type":"article","fields":{"abstract":["Service-oriented architecture (SOA) and microservices insiders Mike Amundsen, James Lewis, and Nicolai Josuttis share their experiences and predictions with department editors Cesare Pautasso and Olaf Zimmermann."],"author":["Pautasso, Cesare","Zimmermann, Olaf","Amundsen, Mike","Lewis, James","Josuttis, Nicolai","undefined","undefined","undefined","undefined"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["software development","software engineering"],"note":["TL;DR \n\nService-oriented architecture and microservices insiders Mike Amundsen, James Lewis, and Nicolai Josuttis share their experiences and predictions with department editors Cesare Pautasso and Olaf Zimmermann."],"number":["1"],"pages":["91–98"],"shorttitle":["Microservices in Practice, Part 1"],"title":["Microservices in Practice, Part 1: Reality Check and Service Design"],"volume":["34"]},"creators":{"author":[{"lastName":"Pautasso","firstName":"Cesare"},{"lastName":"Zimmermann","firstName":"Olaf"},{"lastName":"Amundsen","firstName":"Mike"},{"lastName":"Lewis","firstName":"James"},{"lastName":"Josuttis","firstName":"Nicolai"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"Pazzani2007","type":"incollection","fields":{"author":["Pazzani, Michael J.","Billsus, Daniel"],"booktitle":["The adaptive web: Methods and strategies of web personalization"],"date":["2007"],"doi":["10.1007/978-3-540-72079-9₁0"],"editor":["Brusilovsky, Peter","Kobsa, Alfred","Nejdl, Wolfgang"],"isbn":["978-3-540-72079-9"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nThis chapter discusses content-based recommendation systems, i.e., systems that recommend an item to a user based upon a description of the item and a profile of the user's interests, which are used in a variety of domains ranging from recommending web pages, news articles, restaurants, television programs, and items for sale."],"pages":["325–341"],"publisher":["Springer Berlin Heidelberg"],"title":["Content-based recommendation systems"]},"creators":{"author":[{"lastName":"Pazzani","firstName":"Michael J."},{"lastName":"Billsus","firstName":"Daniel"}],"editor":[{"lastName":"Brusilovsky","firstName":"Peter"},{"lastName":"Kobsa","firstName":"Alfred"},{"lastName":"Nejdl","firstName":"Wolfgang"}]},"sentenceCased":true},{"key":"Pearce_Ahmad_Tan_Dolan-Gavitt_Karri_2021","type":"article","fields":{"author":["Pearce, Hammond","Ahmad, Baleegh","Tan, Benjamin","Dolan-Gavitt, Brendan","Karri, Ramesh"],"date":["2021-12"],"issue":["arXiv:2108.09293"],"note":["TL;DR \n\nThis work systematically investigates the prevalence and conditions that can cause GitHub Copilot to recommend insecure code, and explores Copilot’s performance on three distinct code generation axes—examining how it performs given diversity of weaknesses, diversity of prompts, and diversity of domains."],"publisher":["arXiv"],"title":["Asleep at the keyboard? Assessing the security of GitHub copilot’s code contributions"],"url":["http://arxiv.org/abs/2108.09293"]},"creators":{"author":[{"lastName":"Pearce","firstName":"Hammond"},{"lastName":"Ahmad","firstName":"Baleegh"},{"lastName":"Tan","firstName":"Benjamin"},{"lastName":"Dolan-Gavitt","firstName":"Brendan"},{"lastName":"Karri","firstName":"Ramesh"}]},"sentenceCased":true},{"key":"pearceAsleepKeyboardAssessing2021","type":"online","fields":{"abstract":["There is burgeoning interest in designing AI-based systems to assist humans in designing computing systems, including tools that automatically generate computer code. The most notable of these comes in the form of the first self-described `AI pair programmer', GitHub Copilot, a language model trained over open-source GitHub code. However, code often contains bugs - and so, given the vast quantity of unvetted code that Copilot has processed, it is certain that the language model will have learned from exploitable, buggy code. This raises concerns on the security of Copilot's code contributions. In this work, we systematically investigate the prevalence and conditions that can cause GitHub Copilot to recommend insecure code. To perform this analysis we prompt Copilot to generate code in scenarios relevant to high-risk CWEs (e.g. those from MITRE's \"Top 25\" list). We explore Copilot's performance on three distinct code generation axes – examining how it performs given diversity of weaknesses, diversity of prompts, and diversity of domains. In total, we produce 89 different scenarios for Copilot to complete, producing 1,689 programs. Of these, we found approximately 40% to be vulnerable."],"author":["Pearce, Hammond","Ahmad, Baleegh","Tan, Benjamin","Dolan-Gavitt, Brendan","Karri, Ramesh"],"date":["2021-12-16"],"eprint":["2108.09293"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Cryptography and Security","LOGSEQ"],"note":["Comment: Accepted for publication in IEEE Symposium on Security and Privacy 2022 \n\nTL;DR \n\nThis work systematically investigates the prevalence and conditions that can cause GitHub Copilot to recommend insecure code, and explores Copilot’s performance on three distinct code generation axes—examining how it performs given diversity of weaknesses, diversity of prompts, and diversity of domains."],"pubstate":["preprint"],"shorttitle":["Asleep at the Keyboard?"],"title":["Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributions"],"url":["http://arxiv.org/abs/2108.09293"],"urldate":["2023-04-24"]},"creators":{"author":[{"lastName":"Pearce","firstName":"Hammond"},{"lastName":"Ahmad","firstName":"Baleegh"},{"lastName":"Tan","firstName":"Benjamin"},{"lastName":"Dolan-Gavitt","firstName":"Brendan"},{"lastName":"Karri","firstName":"Ramesh"}]}},{"key":"pelliccioneArtificialIntelligenceSoftware","type":"article","fields":{"langid":["english"],"abstract":["ML and AI are increasingly dominating the high-tech industry. Organizations and technology companies are leveraging their big data to create new products or improve their processes to reach the next level in their market. However, ML and AI are not a silver bullet and Software 2.0 is not the end of software developers or software engineering. In this lecture I will introduce the course and I will argument on how software engineering can help ML and AI to become the key technology for (autonomous) systems of the near future. Software engineering best practices and achievements reached in the last decades might help, e.g., (i) democratising the use of ML/AI, (ii) composing, reusing, chaining ML/AI models to solve more complex problems, and (iii) supporting for reasoning about correctness, repeatability, explainability, traceability, fairness, ethics, while building an ML/AI pipeline."],"author":["Pelliccione, Patrizio","Ruscio, Davide Di","Begel, Andrew","Crnkovic, Ivica"],"note":["TL;DR \n\nManagers, business owners, computer literate individuals, and software developers alike are all seeking an understanding of artificial intelligence and wondering what its uses might be, and Derek Partridge helps to understand what AI can and cannot do."],"pages":["5"],"title":["Artificial Intelligence and Software Engineering"]},"creators":{"author":[{"lastName":"Pelliccione","firstName":"Patrizio"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Begel","firstName":"Andrew"},{"lastName":"Crnkovic","firstName":"Ivica"}]}},{"key":"penaModeldrivenArchitectureApproach2006","type":"inproceedings","fields":{"author":["Pena, Joaquin","Hinchey, Michael G.","Sterritt, Roy","Ruiz-Cortes, Antonio","Resinas, Manuel"],"booktitle":["2006 2nd IEEE Int. Symp. Dependable Auton. Secure Comput."],"date":["2006"],"note":["TL;DR \n\nThis paper proposes a set of UML-based models to specify autonomic and autonomous features along with the necessary procedures, based on modification and composition of models, to deploy a policy as an executing system."],"pages":["19–30"],"publisher":["IEEE"],"title":["A model-driven architecture approach for modeling, specifying and deploying policies in autonomous and autonomic systems"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4030862"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Pena","firstName":"Joaquin"},{"lastName":"Hinchey","firstName":"Michael G."},{"lastName":"Sterritt","firstName":"Roy"},{"lastName":"Ruiz-Cortes","firstName":"Antonio"},{"lastName":"Resinas","firstName":"Manuel"}]},"sentenceCased":true},{"key":"Peng20198935","type":"inproceedings","fields":{"abstract":["Unsupervised model transfer has the potential to greatly improve the generalizability of deep models to novel domains. Yet the current literature assumes that the separation of target data into distinct domains is known as a priori. In this paper, we propose the task of Domain-Agnostic Learning (DAL): How to transfer knowledge from a labeled source domain to unlabeled data from arbitrary target domains? To tackle this problem, we devise a novel Deep Adversarial Disentangled Autoencoder (DADA) capable of disentangling domain-specific features from class identity. We demonstrate experimentally that when the target domain labels are unknown, DADA leads to state-of-the-art performance on several image classification datascts. © 2019 International Machine Learning Society (IMLS)."],"author":["Peng, X.","Huang, Z.","Sun, X.","Saenko, K."],"date":["2019"],"document_type":["Conference Paper"],"isbn":["978-1-5108-8698-8"],"keywords":["Artificial intelligence","Auto encoders","Domain agnostics","Domain specific","Machine learning","Model transfer","Novel domain","Software engineering","State-of-the-art performance","Target domain","Unlabeled data"],"note":["cited By 54"],"pages":["8935–8946"],"publisher":["International Machine Learning Society (IMLS)"],"series":["36th International Conference on Machine Learning, ICML 2019"],"source":["Scopus"],"title":["Domain agnostic learning with disentangled representations"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078303667&partnerID=40&md5=68918f412d63c4ae07d47a24b7181b8f"],"volume":["2019-June"]},"creators":{"author":[{"lastName":"Peng","firstName":"X."},{"lastName":"Huang","firstName":"Z."},{"lastName":"Sun","firstName":"X."},{"lastName":"Saenko","firstName":"K."}]},"sentenceCased":true},{"key":"Peng20206","type":"inproceedings","fields":{"abstract":["With the increasing scale of network, attacks against network emerge one after another, and security problems become increasingly prominent. Network intrusion detection system is a widely used and effective security means at present. In addition, with the development of machine learning technology, various intelligent intrusion detection algorithms also start to sprout. By flexibly combining these intelligent methods with intrusion detection technology, the comprehensive performance of intrusion detection can be improved, but the vulnerability of machine learning model in the adversarial environment can not be ignored. In this paper, we study the defense problem of network intrusion detection system against adversarial samples. More specifically, we design a defense algorithm for NIDS against adversarial samples by using bidirectional generative adversarial network. The generator learns the data distribution of normal samples during training, which is an implicit model reflecting the normal data distribution. After training, the adversarial sample detection module calculates the reconstruction error and the discriminator matching error of sample. Then, the adversarial samples are removed, which improves the robustness and accuracy of NIDS in the adversarial environment. © 2020 IEEE."],"art_number":["9237728"],"author":["Peng, Y.","Fu, G.","Luo, Y.","Hu, J.","Li, B.","Yan, Q."],"author_keywords":["adversarial sample; defense technology; machine learning; network and data security; network intrusion system"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/ICSESS49938.2020.9237728"],"editor":["L., Wenzheng"],"isbn":["978-1-72816-578-3"],"issn":["23270586"],"keywords":["Adversarial environments","Comprehensive performance","Computer crime","Intrusion detection","Intrusion detection algorithms","Intrusion detection technologies","Machine learning","Machine learning models","Machine learning technology","Network intrusion detection systems","Network security","Reconstruction error","Software engineering"],"note":["cited By 4 \n\nTL;DR \n\nA defense algorithm for NIDS against adversarial samples is designed by using bidirectional generative adversarial network, which improves the robustness and accuracy of NIDS in the adversarial environment."],"pages":["6–10"],"publisher":["IEEE Computer Society"],"series":["Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS"],"source":["Scopus"],"title":["Detecting adversarial examples for network intrusion detection system with GAN"],"volume":["2020-October"]},"creators":{"author":[{"lastName":"Peng","firstName":"Y."},{"lastName":"Fu","firstName":"G."},{"lastName":"Luo","firstName":"Y."},{"lastName":"Hu","firstName":"J."},{"lastName":"Li","firstName":"B."},{"lastName":"Yan","firstName":"Q."}],"editor":[{"lastName":"L.","firstName":"Wenzheng"}]},"sentenceCased":true},{"key":"pereiraPlatformEnableSelfadaptive2020","type":"inproceedings","fields":{"langid":["english"],"abstract":["Self-Adaptive Systems (SASs) relect on both their state and on the environment and change their behavior to satisfy the expected objectives. Cloud systems are self-adaptive by nature, especially considering the resources used in a pay-as-you-go manner. Satisfying trustworthiness (worthiness of a service based on evidences of its trust) properties also demands self-adaptation capabilities. Unfortunately, developers lack an easy-to-use platform to support the assessment of such properties and to execute the required adaptions. This paper presents TMA, a platform that implements a MAPE-K control loop for cloud systems, supported by a distributed monitoring system based on probes. Quality Models are used to express trustworthiness properties, resulting in scores, which are used to plan adaptations through evaluation rules. These plans are executed by actuators. A demo shows the scaling up/down of the number of containers in a cloud application of a set of web services from TPC Benchmarks, as a result of changes observed in the environment."],"author":["Pereira, José D'Abruzzo","Silva, Rui","Antunes, Nuno","Silva, Jorge L. M.","family=França, given=Breno, prefix=de, useprefix=true","Moraes, Regina","Vieira, Marco"],"booktitle":["Proc. IEEEACM 15th Int. Symp. Softw. Eng. Adapt. Self-Manag. Syst."],"date":["2020-06-29"],"doi":["10.1145/3387939.3391608"],"eventtitle":["SEAMS '20: IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems"],"isbn":["978-1-4503-7962-5"],"keywords":["DONE"],"location":["Seoul Republic of Korea"],"note":["TL;DR \n\nTMA is presented, a platform that implements a MAPE-K control loop for cloud systems, supported by a distributed monitoring system based on probes, used to express trustworthiness properties and to plan adaptations through evaluation rules."],"pages":["71–77"],"publisher":["ACM"],"title":["A platform to enable self-adaptive cloud applications using trustworthiness properties"]},"creators":{"author":[{"lastName":"Pereira","firstName":"José D'Abruzzo"},{"lastName":"Silva","firstName":"Rui"},{"lastName":"Antunes","firstName":"Nuno"},{"lastName":"Silva","firstName":"Jorge L. M."},{"lastName":"França","firstName":"Breno","prefix":"de","useprefix":true},{"lastName":"Moraes","firstName":"Regina"},{"lastName":"Vieira","firstName":"Marco"}]},"sentenceCased":true},{"key":"perez-sanchezOnlineLearningAlgorithm2013","type":"article","fields":{"langid":["english"],"author":["Pérez-Sánchez, Beatriz","Fontenla-Romero, Oscar","Guijarro-Berdiñas, Bertha","Martínez-Rego, David"],"date":["2013-12"],"doi":["10.1016/j.eswa.2013.06.066"],"issn":["09574174"],"journaltitle":["Expert Syst. Appl."],"number":["18"],"pages":["7294–7304"],"title":["An online learning algorithm for adaptable topologies of neural networks"],"volume":["40"]},"creators":{"author":[{"lastName":"Pérez-Sánchez","firstName":"Beatriz"},{"lastName":"Fontenla-Romero","firstName":"Oscar"},{"lastName":"Guijarro-Berdiñas","firstName":"Bertha"},{"lastName":"Martínez-Rego","firstName":"David"}]},"sentenceCased":true},{"key":"Pérez-Soler2020207","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Universidad Autónoma de Madrid, Madrid, Spain"],"author":["Pérez-Soler, S.","Guerra, E.","family=Lara, given=J., prefix=de, useprefix=true"],"correspondence_address1":["Pérez-Soler, S.; Universidad Autónoma de MadridSpain; email: Sara.PerezS@uam.es"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-62522-1_15"],"editor":["Dobbie G., Frank U., Liddle S.W., Mayr H.C., Kappel G."],"isbn":["9783030625214"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"keywords":["GOAL_Model-Assistance","notion"],"note":["cited By 7 \n\nTL;DR \n\nChatbots are software services accessed via conversation in natural language that are increasingly used to help in all kinds of procedures like booking flights, querying visa information or assigning tasks to developers."],"pages":["207–222"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Model-driven chatbot development"],"volume":["12400 LNCS"]},"creators":{"author":[{"lastName":"Pérez-Soler","firstName":"S."},{"lastName":"Guerra","firstName":"E."},{"lastName":"Lara","firstName":"J.","prefix":"de","useprefix":true}],"editor":[{"lastName":"Dobbie G.","suffix":"Frank U.","firstName":"Liddle S.W., Mayr H.C., Kappel G."}]},"sentenceCased":true},{"key":"perryUsersWriteMore2022","type":"online","fields":{"abstract":["We conduct the first large-scale user study examining how users interact with an AI Code assistant to solve a variety of security related tasks across different programming languages. Overall, we find that participants who had access to an AI assistant based on OpenAI's codex-davinci-002 model wrote significantly less secure code than those without access. Additionally, participants with access to an AI assistant were more likely to believe they wrote secure code than those without access to the AI assistant. Furthermore, we find that participants who trusted the AI less and engaged more with the language and format of their prompts (e.g. re-phrasing, adjusting temperature) provided code with fewer security vulnerabilities. Finally, in order to better inform the design of future AI-based Code assistants, we provide an in-depth analysis of participants' language and interaction behavior, as well as release our user interface as an instrument to conduct similar studies in the future."],"author":["Perry, Neil","Srivastava, Megha","Kumar, Deepak","Boneh, Dan"],"date":["2022-12-16"],"eprint":["2211.03622"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Cryptography and Security"],"note":["Comment: 18 pages, 16 figures, update adds names of statistical tests and survey questions \n\nTL;DR \n\nA user study to examine how users interact with AI code assistants to solve a variety of security related tasks finds that participants who had access to an AI assistant wrote significantly less secure code."],"pubstate":["preprint"],"title":["Do Users Write More Insecure Code with AI Assistants?"],"url":["http://arxiv.org/abs/2211.03622"],"urldate":["2023-03-10"]},"creators":{"author":[{"lastName":"Perry","firstName":"Neil"},{"lastName":"Srivastava","firstName":"Megha"},{"lastName":"Kumar","firstName":"Deepak"},{"lastName":"Boneh","firstName":"Dan"}]}},{"key":"pervaizExaminingChallengesDevelopment2019","type":"inproceedings","fields":{"langid":["english"],"abstract":["The developing world has increasingly relied on data driven policies. Numerous development agencies have pushed for on-ground data collection to support the development work they pursue. Many governments have launched their own efforts for frequent information gathering. Overall, the amount of data collected is tremendous, yet there are significant issues in doing useful analysis. Most of these barriers manifest in data cleaning and merging, and require a data engineer to support some parts of the analysis. In this paper, we investigate the challenges of cleaning development data through an interview based study. We conducted face to face interviews of 13 stakeholders, eight from international development organizations and five government workers from Pakistan, including both managers and data analysts. From analysis of the interviews we identified common challenges faced in processing development data including correcting open text fields, merging hierarchical data, and extracting data from textual formats such as PDF. We construct a basic taxonomy of data cleaning challenges, and identify areas where support tools can improve the process. Ultimately, the objective is to empower regular data users to easily do the necessary data cleaning and scrubbing for analysis."],"author":["Pervaiz, Fahad","Vashistha, Aditya","Anderson, Richard"],"booktitle":["Proc. Conf. Comput. Sustain. Soc. - COMPASS 19"],"date":["2019"],"doi":["10.1145/3314344.3332496"],"eventtitle":["The 2nd ACM SIGCAS Conference"],"isbn":["978-1-4503-6714-1"],"location":["Accra, Ghana"],"note":["TL;DR \n\nA basic taxonomy of data cleaning challenges is constructed, and areas where support tools can improve the process are identified, to empower regular data users to easily do the necessary data cleaning and scrubbing for analysis."],"pages":["13–21"],"publisher":["ACM Press"],"title":["Examining the challenges in development data pipeline"]},"creators":{"author":[{"lastName":"Pervaiz","firstName":"Fahad"},{"lastName":"Vashistha","firstName":"Aditya"},{"lastName":"Anderson","firstName":"Richard"}]},"sentenceCased":true},{"key":"pescador2016dsl","type":"inproceedings","fields":{"langid":["english"],"author":["Pescador, Ana","family=Lara, given=Juan, prefix=de, useprefix=true"],"booktitle":["Proc. 31st IEEEACM Int. Conf. Autom. Softw. Eng."],"date":["2016"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nDSL-maps is proposed, a notation inspired by mind-maps, to represent requirements for DSLs, and is supported by a tool, which helps in the automated transition into an initial meta-model design, using a customizable transformation and recommendations from a catalogue of meta- model design patterns."],"pages":["438–443"],"title":["DSL-maps: From requirements to design of domain-specific languages"]},"creators":{"author":[{"lastName":"Pescador","firstName":"Ana"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true}]},"sentenceCased":true},{"key":"pescadorPatternBasedDevelopmentDomainSpecific2015","type":"inproceedings","fields":{"author":["Pescador, Ana","Garmendia, Antonio","Guerra, Esther","Cuadrado, Jesús Sánchez","family=Lara, given=Juan, prefix=de, useprefix=true"],"date":["2015"],"note":["TL;DR \n\nThis work proposes the construction of DSMLs and their modelling environments aided by patterns which gather knowledge of specific domains, design alternatives, concrete syntax, dynamic semantics and functionality for the modelling environment."],"publisher":["MODELS"],"title":["Pattern-Based Development of Domain-Specific Modelling Languages"],"url":["http://www.miso.es/pubs/DSLtao.pdf"],"urldate":["2015-09-24"]},"creators":{"author":[{"lastName":"Pescador","firstName":"Ana"},{"lastName":"Garmendia","firstName":"Antonio"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Cuadrado","firstName":"Jesús Sánchez"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true}]}},{"key":"petcuProcessingExtremeData2016","type":"article","fields":{"author":["Petcu, Dana","Iuhasz, Gabriel","Pop, Daniel","Talia, Domenico","Carretero, Jesus","Prodan, Radu","Fahringer, Thomas","Grasso, Ivan","Doallo, Ramon","Martin, Maria J.","Fraguela, Basilio B.","Trobec, Roman","Depolli, Matjaz","Rodriguez, Francisco Almeida","De Sande, Francisco","Da Costa, Georges","Pierson, Jean-Marc","Anastasiadis, Stergios","Bartzokas, Aristides","Lolis, Christos","Goncalves, Pedro","Brito, Fabrice","Brown, Nick"],"date":["2016-01-30"],"doi":["10.12694/scpe.v16i4.1134"],"issn":["1895-1767"],"journaltitle":["SCPE"],"keywords":["STARRED"],"note":["TL;DR \n\nThe starting point is the definition of new programming paradigms, APIs, runtime tools and methodologies for expressing data-intensive tasks on exascale systems, paving the way for the exploitation of massive parallelism over a simplified model of the system architecture."],"number":["4"],"pages":["467–490"],"title":["On Processing Extreme Data"],"volume":["16"]},"creators":{"author":[{"lastName":"Petcu","firstName":"Dana"},{"lastName":"Iuhasz","firstName":"Gabriel"},{"lastName":"Pop","firstName":"Daniel"},{"lastName":"Talia","firstName":"Domenico"},{"lastName":"Carretero","firstName":"Jesus"},{"lastName":"Prodan","firstName":"Radu"},{"lastName":"Fahringer","firstName":"Thomas"},{"lastName":"Grasso","firstName":"Ivan"},{"lastName":"Doallo","firstName":"Ramon"},{"lastName":"Martin","firstName":"Maria J."},{"lastName":"Fraguela","firstName":"Basilio B."},{"lastName":"Trobec","firstName":"Roman"},{"lastName":"Depolli","firstName":"Matjaz"},{"lastName":"Rodriguez","firstName":"Francisco Almeida"},{"lastName":"De Sande","firstName":"Francisco"},{"lastName":"Da Costa","firstName":"Georges"},{"lastName":"Pierson","firstName":"Jean-Marc"},{"lastName":"Anastasiadis","firstName":"Stergios"},{"lastName":"Bartzokas","firstName":"Aristides"},{"lastName":"Lolis","firstName":"Christos"},{"lastName":"Goncalves","firstName":"Pedro"},{"lastName":"Brito","firstName":"Fabrice"},{"lastName":"Brown","firstName":"Nick"}]}},{"key":"Petroll2021","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Symp. Des. X, DFX"],"affiliation":["Bundeswehr Research Institute for Materials, Fuels and Lubricants (WIWeB); Universität der Bundeswehr München (UniBwM), Germany; Technische Universität Dresden, Germany"],"author":["Petroll, C.","Denk, M.","Holtmannspötter, J.","Paetzold, K.","Höfer, P."],"correspondence_address1":["Petroll, C.Institutsweg 1, Germany; email: christophpetroll@bundeswehr.org"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.35199/dfx2021.11"],"editor":["Krause D., Paetzold K., Wartzack S."],"note":["cited By 0 \n\nTL;DR \n\nIt is discussed what are the requirements for solving an MDO problem with a metamodel taking into account functional and production-specific boundary conditions and how to create a data set with the right quality and quantity."],"publisher":["The Design Society"],"series":["Proceedings of the 32nd Symposium Design for X, DFX 2021"],"source":["Scopus"],"title":["Synthetic data generation for deep learning models"]},"creators":{"author":[{"lastName":"Petroll","firstName":"C."},{"lastName":"Denk","firstName":"M."},{"lastName":"Holtmannspötter","firstName":"J."},{"lastName":"Paetzold","firstName":"K."},{"lastName":"Höfer","firstName":"P."}],"editor":[{"lastName":"Krause D.","suffix":"Paetzold K.","firstName":"Wartzack S."}]},"sentenceCased":true},{"key":"pettigrewTastingProjectiveTechnique2008","type":"article","fields":{"abstract":["Purpose – The purpose of this paper is to investigate the benefits of tasting as a projective technique (PT) in explicating consumers' thoughts and feelings towards food and beverage products.Design/methodology/approach – In total, ten focus groups were conducted with 35 consumers, 14 wine producers, and 13 mediators. The mediator category included those involved in marketing, wholesaling, retailing, and judging wine. Participants in each focus group were given the same four wines to taste. Initially they were invited to discuss their views on wine quality. The participants were then presented with the wines and asked to discuss their responses to them, particularly their perceptions of the quality of the wines.Findings – The primary findings related to: the changes in apparent certainty levels amongst professionals and high‐involvement informants; exposure of real and contradictory preferences; role of cognitive, affective, and sensory responses to wine; and interpretation of the language of tasting.Research limitations/implications – Tasting as a PT has the potential to generate additional and insightful data that can increase our appreciation of the complexities involved in consumption experiences. In particular, it can reveal the uncertainty that can affect consumers' product evaluations and explicate the multiple evaluation pathways that can be used by consumers of food and beverage products.Originality/value – The paper is of value in showing that the ability of PTs to yield both stated and actual preferences provides insight into the salient external factors that impact on consumption decisions and gives an indication of where marketers could most effectively focus their product development and promotional attention."],"author":["Pettigrew, Simone","Charters, Stephen"],"date":["2008"],"eprint":["https://doi.org/10.1108/13522750810879048"],"journaltitle":["Qual. Mark. Res. Int. J."],"nodoi":["10.1108/13522750810879048"],"number":["3"],"pages":["331–343"],"title":["Tasting as a projective technique"],"url":["https://doi.org/10.1108/13522750810879048"],"volume":["11"]},"creators":{"author":[{"lastName":"Pettigrew","firstName":"Simone"},{"lastName":"Charters","firstName":"Stephen"}]},"sentenceCased":true},{"key":"pettinariProcessdrivenDevelopmentAnalysis","type":"thesis","fields":{"author":["Pettinari, Sara"],"title":["Process-driven Development and Analysis of Multi-Robot Systems.Pdf"]},"creators":{"author":[{"lastName":"Pettinari","firstName":"Sara"}]},"sentenceCased":true},{"key":"pezoaFoundationsJSONSchema2016","type":"inproceedings","fields":{"langid":["english"],"author":["Pezoa, Felipe","Reutter, Juan L.","Suarez, Fernando","Ugarte, Martín","Vrgoč, Domagoj"],"booktitle":["Proc. 25th Int. Conf. World Wide Web"],"date":["2016-04-11"],"doi":["10.1145/2872427.2883029"],"eventtitle":["WWW '16: 25th International World Wide Web Conference"],"isbn":["978-1-4503-4143-1"],"location":["Montréal Québec Canada"],"note":["TL;DR \n\nThis paper provides the first formal definition of syntax and semantics for JSON Schema and uses it to show that implementing this layer on top of JSON is feasible in practice."],"pages":["263–273"],"publisher":["International World Wide Web Conferences Steering Committee"],"title":["Foundations of JSON Schema"]},"creators":{"author":[{"lastName":"Pezoa","firstName":"Felipe"},{"lastName":"Reutter","firstName":"Juan L."},{"lastName":"Suarez","firstName":"Fernando"},{"lastName":"Ugarte","firstName":"Martín"},{"lastName":"Vrgoč","firstName":"Domagoj"}]}},{"key":"phuong_t_nguyen_2018_1476035","type":"article","fields":{"author":["Rocco, Di","Juri","Nguyen, Phuong T.","Rubei, Riccardo","Di Ruscio, Davide"],"date":["2018-10"],"doi":["10.5281/zenodo.1476035"],"note":["Last access 7.11.2018 \n\nLast access 7.11.2018 \n\nLast access 7.11.2018 \n\nLast access 7.11.2018 \n\nLast access 7.11.2018"],"title":["An automated approach to assess the similarity of GitHub repositories - online appendix"]},"creators":{"author":[{"lastName":"Rocco","firstName":"Di"},{"literal":"Juri"},{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Rubei","firstName":"Riccardo"},{"lastName":"Di Ruscio","firstName":"Davide"}]},"sentenceCased":true},{"key":"pierantonioalfonsoKeynoteJCRSTAFa","type":"article","fields":{"author":["Pierantonio, Alfonso"],"title":["Keynote JCR STAF"]},"creators":{"author":[{"literal":"Pierantonio, Alfonso"}]}},{"key":"pierantonioOpenAccessAll2020","type":"article","fields":{"langid":["english"],"author":["Pierantonio, Alfonso","family=Brand, given=Mark, prefix=van den, useprefix=true","Combemale, Benoit"],"date":["2020"],"doi":["10.5381/jot.2020.19.1.e1"],"issn":["1660-1769"],"journaltitle":["JOT"],"note":["TL;DR \n\nThis editorial presents the various forms of open access, discusses their pros and cons from the perspective of the Journal of Object Technology and its editors in chiefs, and illustrates how JOT implements a platinum open access model."],"number":["1"],"pages":["1"],"shorttitle":["Open Access"],"title":["Open Access: All you wanted to know and never dared to ask."],"volume":["19"]},"creators":{"author":[{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Brand","firstName":"Mark","prefix":"vanden","useprefix":true},{"lastName":"Combemale","firstName":"Benoit"}]},"sentenceCased":true},{"key":"Pinna Puissant2015461","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Softw. Syst. Model."],"affiliation":["Service de Génie Logiciel, Institut COMPLEXYS, Université de Mons, Place du Parc 20, Mons, 7000, Belgium; Software Languages Lab, Vrije Universiteit Brussel, Pleinlaan 2, Brussels, 1050, Belgium"],"author":["Pinna Puissant, J.","Van Der Straeten, R.","Mens, T."],"correspondence_address1":["Pinna Puissant, J.; Service de Génie Logiciel, Place du Parc 20, Belgium"],"date":["2015"],"document_type":["Article"],"doi":["10.1007/s10270-013-0317-9"],"issn":["16191366"],"journaltitle":["Softw. Syst. Model."],"keywords":["GOAL_Model-Repair","notion","TECHNIQUE_AutomatedRegressionPlanning"],"note":["cited By 32 \n\nTL;DR \n\nBadger is implemented, a regression planner in Prolog that generates resolution plans for UML models using both generated models and reverse-engineered models of varying sizes, the largest ones containing more than 10,000 model elements."],"number":["1"],"pages":["461–481"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Resolving model inconsistencies using automated regression planning"],"volume":["14"]},"creators":{"author":[{"lastName":"Pinna Puissant","firstName":"J."},{"lastName":"Van Der Straeten","firstName":"R."},{"lastName":"Mens","firstName":"T."}]},"sentenceCased":true},{"key":"PMID:25142186","type":"article","fields":{"author":["Zeng, Wei","Zeng, An","Liu, Hao","Shang, Ming-Sheng","Zhou, Tao"],"date":["2014"],"doi":["10.1038/srep06140"],"issn":["2045-2322"],"journaltitle":["Sci. Rep."],"pages":["6140"],"title":["Uncovering the information core in recommender systems"],"volume":["4"]},"creators":{"author":[{"lastName":"Zeng","firstName":"Wei"},{"lastName":"Zeng","firstName":"An"},{"lastName":"Liu","firstName":"Hao"},{"lastName":"Shang","firstName":"Ming-Sheng"},{"lastName":"Zhou","firstName":"Tao"}]},"sentenceCased":true},{"key":"poliniModelDrivenEngineeringIoT","type":"thesis","fields":{"langid":["english"],"author":["Polini, Andrea","Ruscio, Davide Di","Cleophas, Loek","Fedeli, Arianna"],"title":["Model-Driven Engineering for IoT Applications: A focus on Reusability and Portability"]},"creators":{"author":[{"lastName":"Polini","firstName":"Andrea"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Cleophas","firstName":"Loek"},{"lastName":"Fedeli","firstName":"Arianna"}]},"sentenceCased":true},{"key":"polyakovMachineLearningCybersecurity","type":"article","fields":{"langid":["english"],"author":["Polyakov, Alexander"],"pages":["23"],"title":["Machine Learning for Cybersecurity 10"]},"creators":{"author":[{"lastName":"Polyakov","firstName":"Alexander"}]}},{"key":"PolystoreDatabasesBe","type":"online","fields":{"title":["Polystore Databases to be Examined at IEEE, CIDR Conferences | Intel Science & Technology Center for Big Data"],"url":["http://istc-bigdata.org/index.php/polystore-databases-at-ieee-cidr-conferences/"],"urldate":["2018-04-16"]},"creators":{},"sentenceCased":true},{"key":"pontaMetadataCodecentricUsagebased2018","type":"article","fields":{"abstract":["The use of open-source software (OSS) is ever-increasing, and so is the number of open-source vulnerabilities being discovered and publicly disclosed. The gains obtained from the reuse of community-developed libraries may be offset by the cost of detecting, assessing, and mitigating their vulnerabilities in a timely fashion. In this paper we present a novel method to detect, assess and mitigate OSS vulnerabilities that improves on state-of-the-art approaches, which commonly depend on metadata to identify vulnerable OSS dependencies. Our solution instead is code-centric and combines static and dynamic analysis to determine the reachability of the vulnerable portion of libraries used (directly or transitively) by an application. Taking this usage into account, our approach then supports developers in choosing among the existing non-vulnerable library versions. VULAS, the tool implementing our code-centric and usage-based approach, is officially recommended by SAP to scan its Java software, and has been successfully used to perform more than 250000 scans of about 500 applications since December 2016. We report on our experience and on the lessons we learned when maturing the tool from a research prototype to an industrial-grade solution."],"author":["Ponta, Serena E.","Plate, Henrik","Sabetta, Antonino"],"date":["2018-06-15"],"eprint":["1806.05893"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv180605893 Cs"],"note":["Comment: To appear in the Proc. of the 2018 IEEE International Conference on Software Maintenance and Evolution (ICSME) Added: - acknowledgements - citation to Dashevskyi et al. (TSE 2018), DOI: 10.1109/TSE.2018.2816033 \n\nTL;DR \n\nA novel method to detect, assess and mitigate OSS vulnerabilities that improves on state-of-the-art approaches that combines static and dynamic analysis to determine the reachability of the vulnerable portion of libraries used by an application."],"shorttitle":["Beyond Metadata"],"title":["Beyond Metadata: Code-centric and Usage-based Analysis of Known Vulnerabilities in Open-source Software"],"url":["http://arxiv.org/abs/1806.05893"],"urldate":["2018-10-08"]},"creators":{"author":[{"lastName":"Ponta","firstName":"Serena E."},{"lastName":"Plate","firstName":"Henrik"},{"lastName":"Sabetta","firstName":"Antonino"}]}},{"key":"ponzanelli_prompter:_2016","type":"article","fields":{"langid":["english"],"abstract":["Developers often require knowledge beyond the one they possess, which boils down to asking co-workers for help or consulting additional sources of information, such as Application Programming Interfaces (API) documentation, forums, and Q&A websites. However, it requires time and energy to formulate one’s problem, peruse and process the results. We propose a novel approach that, given a context in the Integrated Development Environment (IDE), automatically retrieves pertinent discussions from Stack Overflow, evaluates their relevance using a multi-faceted ranking model, and, if a given confidence threshold is surpassed, notifies the developer. We have implemented our approach in PROMPTER, an Eclipse plug-in. PROMPTER was evaluated in two empirical studies. The first study was aimed at evaluatingPROMPTER’s ranking model and involved 33 participants."],"author":["Ponzanelli, Luca","Bavota, Gabriele","Di Penta, Massimiliano","Oliveto, Rocco","Lanza, Michele"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2016-10"],"doi":["10.1007/s10664-015-9397-1"],"issn":["1382-3256, 1573-7616"],"journaltitle":["Empir. Softw. Eng."],"number":["5"],"pages":["2190–2231"],"shorttitle":["Prompter"],"timestamp":["Thu, 15 Jun 2017 21:30:27 +0200"],"title":["Prompter: Turning the IDE into a self-confident programming assistant"],"volume":["21"]},"creators":{"author":[{"lastName":"Ponzanelli","firstName":"Luca"},{"lastName":"Bavota","firstName":"Gabriele"},{"lastName":"Di Penta","firstName":"Massimiliano"},{"lastName":"Oliveto","firstName":"Rocco"},{"lastName":"Lanza","firstName":"Michele"}]},"sentenceCased":true},{"key":"ponzanelliMiningStackOverflowTurn2014","type":"inproceedings","fields":{"langid":["english"],"acmid":["2597077"],"author":["Ponzanelli, Luca","Bavota, Gabriele","Di Penta, Massimiliano","Oliveto, Rocco","Lanza, Michele"],"date":["2014"],"doi":["10.1145/2597073.2597077"],"ids":["Ponzanelli:2014:MST:2597073.2597077,ponzanelliMiningStackOverflowTurn2014a"],"isbn":["978-1-4503-2863-0"],"keywords":["Developers Support","Empirical Studies","LOGSEQ","Recommender Systems"],"location":["Hyderabad, India"],"nodoi":["10.1145/2597073.2597077"],"note":["<h1>Annotazioni\n (14/1/2024, 21:41:37)</h1> \n\n“sources of information like” (Ponzanelli et al., 2014, p. 1) \n\n“API” (Ponzanelli et al., 2014, p. 1) \n\n“documentation” (Ponzanelli et al., 2014, p. 1) \n\n“forums” (Ponzanelli et al., 2014, p. 1) \n\n“Q&amp;A websites” (Ponzanelli et al., 2014, p. 1) \n\n“Knowing what to search for and how is nontrivial,” (Ponzanelli et al., 2014, p. 1) \n\n“given a context in the IDE,” (Ponzanelli et al., 2014, p. 1) \n\n“automatically retrieves pertinent discussions from Stack Overflow,” (Ponzanelli et al., 2014, p. 1) \n\n“valuates their relevance, and, if a given confidence threshold is surpassed, notifies the developer about the available help.” (Ponzanelli et al., 2014, p. 1) \n\n“ranking model” (Ponzanelli et al., 2014, p. 1) \n\n“usefulness” (Ponzanelli et al., 2014, p. 1) \n\n“Every time developers need to look for information, they interrupt their work flow,” (Ponzanelli et al., 2014, p. 1) \n\n“eave the IDE” (Ponzanelli et al., 2014, p. 1) \n\n“Web browser to perform and refine searches, and assess the results” (Ponzanelli et al., 2014, p. 1) \n\n“the problem context in the IDE. The information is retrieved from differen” (Ponzanelli et al., 2014, p. 1) This is a test [[P1]] \n\n“s forums, mailing lists [2], blogs, Q&amp;A websites, bug trackers [1]” (Ponzanelli et al., 2014, p. 1) \n\n“Recommender systems” (Ponzanelli et al., 2014, p. 1) \n\n“eR” (Ponzanelli et al., 2014, p. 1) \n\n“ose” (Ponzanelli et al., 2014, p. 1) \n\n“eepI” (Ponzanelli et al., 2014, p. 1) \n\n“suggest project artifacts in the IDE aiming at providing developers with additional information on specific parts of the system.” (Ponzanelli et al., 2014, p. 1) \n\n“Ideally, a recommender system should behave like a prompter in a theatre: Ready to provide suggestions whenever the actor needs them, and ready to autonomously give suggestions if it feels something is going wrong.” (Ponzanelli et al., 2014, p. 1) \n\n“driver” (Ponzanelli et al., 2014, p. 1) \n\n“e” (Ponzanelli et al., 2014, p. 1) \n\n“observer,” (Ponzanelli et al., 2014, p. 1) \n\n“interrupts the driver by giving suggestions.” (Ponzanelli et al., 2014, p. 1) \n\n“the driver can consult the observer whenever she needs it, making the observer” (Ponzanelli et al., 2014, p. 1) \n\n“the programming prompter of the programming actor.” (Ponzanelli et al., 2014, p. 1) \n\n“push notifications” (Ponzanelli et al., 2014, p. 1) \n\n“relevant Stack Overflow discussions to the developer. Prompter makes” (Ponzanelli et al., 2014, p. 1) \n\n“IDE” (Ponzanelli et al., 2014, p. 1) \n\n“silently observes and analyzes” (Ponzanelli et al., 2014, p. 1) \n\n“the code context in the IDE” (Ponzanelli et al., 2014, p. 1) \n\n“automatically searches for Stack Over-” (Ponzanelli et al., 2014, p. 1) \n\n“flow discussions on the Web” (Ponzanelli et al., 2014, p. 1) \n\n“evaluates their relevance by taking i” (Ponzanelli et al., 2014, p. 1) \n\n“consideration code aspects” (Ponzanelli et al., 2014, p. 1) \n\n“(i) receive and track notifications” (Ponzanelli et al., 2014, p. 2) \n\n“(ii) read the suggested Stack Overflow discussions.” (Ponzanelli et al., 2014, p. 2) \n\n“code contexts (1) every time a change in the source code occurs” (Ponzanelli et al., 2014, p. 2) \n\n“formulates a query starting from the code context (2)” (Ponzanelli et al., 2014, p. 2) \n\n“rompter submits a new search only if the query diff” (Ponzanelli et al., 2014, p. 2) \n\n“plug-in,” (Ponzanelli et al., 2014, p. 2) \n\n“the search engines to which the query is sent,” (Ponzanelli et al., 2014, p. 2) \n\n“Stack Overflow API” (Ponzanelli et al., 2014, p. 2) \n\n“Web search on the Stack Overflow website” (Ponzanelli et al., 2014, p. 2) \n\n“All resulting URLs are collected and duplicates removed (5).” (Ponzanelli et al., 2014, p. 2) \n\n“The service uses the Stack Overflow question ID to retrieve the discussion via the Stack Overflow API (6)” (Ponzanelli et al., 2014, p. 2) \n\n“discussion is, given the code context, ranked (7) a” (Ponzanelli et al., 2014, p. 3) \n\n“he ranked list of URLs is sent back to the plug-in where Prompter decides whether to fire a” (Ponzanelli et al., 2014, p. 3) \n\n“new notification in the IDE (8).” (Ponzanelli et al., 2014, p. 3) \n\n“Our previous work in this context [28] only used text similarity as a means to retrieve Stack Overflow discussions related to the actual code” (Ponzanelli et al., 2014, p. 3) \n\n“The approach we present here relies on several combined aspects, and has proven to be more robust and less error-prone.” (Ponzanelli et al., 2014, p. 3) \n\n“rompter waits until the developer stops writing” (Ponzanelli et al., 2014, p. 3) \n\n“current code ele-” (Ponzanelli et al., 2014, p. 3) \n\n“ment” (Ponzanelli et al., 2014, p. 3) \n\n“extracts the current context” (Ponzanelli et al., 2014, p. 3) \n\n“,packageName.ClassName f” (Ponzanelli et al., 2014, p. 3) \n\n“me for classes” (Ponzanelli et al., 2014, p. 3) \n\n“packageName.ClassName.methodSignature for methods;” (Ponzanelli et al., 2014, p. 3) \n\n“the source code of the modified element” (Ponzanelli et al., 2014, p. 3) \n\n“the types of the used API,” (Ponzanelli et al., 2014, p. 3) \n\n“the names of methods invoked in the API, again considering only external libraries and JDK only.” (Ponzanelli et al., 2014, p. 3) \n\n“automate the triggering of searche” (Ponzanelli et al., 2014, p. 3) \n\n“es” (Ponzanelli et al., 2014, p. 3) \n\n“treat the code as a bag of words” (Ponzanelli et al., 2014, p. 3) \n\n“(i) splitting identifiers and removing stop words” (Ponzanelli et al., 2014, p. 3) \n\n“(ii) ranking the obtained terms according to their frequency” (Ponzanelli et al., 2014, p. 3) \n\n“(iii) selecting the top-n most frequent terms” (Ponzanelli et al., 2014, p. 3) \n\n“d more discriminative terms” (Ponzanelli et al., 2014, p. 3) \n\n“term entropy can be used to lower the prominence of frequent terms that do not suffi” (Ponzanelli et al., 2014, p. 3) \n\n“the Query Generation Service selects the top n terms to devise the query, plus the word java.” (Ponzanelli et al., 2014, p. 3) \n\n“To overcome this problem, before selecting the n terms to create the query, we use the Levenshtein distance [21] to verify if in the context there are terms with a very high textual similarity.” (Ponzanelli et al., 2014, p. 3) \n\n“1. Textual Similarity:” (Ponzanelli et al., 2014, p. 3) \n\n“2. Code Similarity:” (Ponzanelli et al., 2014, p. 3) \n\n“3. API Types Similarity” (Ponzanelli et al., 2014, p. 3) \n\n“4. API Methods Similarity:” (Ponzanelli et al., 2014, p. 3) \n\n“JDT” (Ponzanelli et al., 2014, p. 3) \n\n“5. Question Score:” (Ponzanelli et al., 2014, p. 4) \n\n“sigmoid function:” (Ponzanelli et al., 2014, p. 4) \n\n“where x is the score and ̄ x is the average of the scores of all the questions in Stack Overflow according to the data dump of June 2013.” (Ponzanelli et al., 2014, p. 4) \n\n“6. Accepted Answer Score:” (Ponzanelli et al., 2014, p. 4) \n\n“7. User Reputation:” (Ponzanelli et al., 2014, p. 4) \n\n“8. Tags Similarity: T” (Ponzanelli et al., 2014, p. 4) \n\n“M. Robillard, R. Walker, and T. Zimmermann. Recommendation systems for software engineering. IEEE Software, pages 80–86, 2010.” (Ponzanelli et al., 2014, p. 10) \n\n“[42] L. Williams. Integrating pair programming into a software development process. In Proceedings of CSEET 2001, pages 27–36. IEEE, 2001.” (Ponzanelli et al., 2014, p. 10) \n\n<h1>Annotazioni\n (14/1/2024, 22:35:16)</h1> \n\n“sources of information like” (Ponzanelli et al., 2014, p. 1) \n\n“API” (Ponzanelli et al., 2014, p. 1) \n\n“documentation” (Ponzanelli et al., 2014, p. 1) \n\n“forums” (Ponzanelli et al., 2014, p. 1) \n\n“Q&amp;A websites” (Ponzanelli et al., 2014, p. 1) \n\n“Knowing what to search for and how is nontrivial,” (Ponzanelli et al., 2014, p. 1) \n\n“given a context in the IDE,” (Ponzanelli et al., 2014, p. 1) \n\n“automatically retrieves pertinent discussions from Stack Overflow,” (Ponzanelli et al., 2014, p. 1) \n\n“valuates their relevance, and, if a given confidence threshold is surpassed, notifies the developer about the available help.” (Ponzanelli et al., 2014, p. 1) \n\n“ranking model” (Ponzanelli et al., 2014, p. 1) \n\n“usefulness” (Ponzanelli et al., 2014, p. 1) \n\n“Every time developers need to look for information, they interrupt their work flow,” (Ponzanelli et al., 2014, p. 1) \n\n“eave the IDE” (Ponzanelli et al., 2014, p. 1) \n\n“Web browser to perform and refine searches, and assess the results” (Ponzanelli et al., 2014, p. 1) \n\n“the problem context in the IDE. The information is retrieved from differen” (Ponzanelli et al., 2014, p. 1) This is a test [[P1]] \n\n“s forums, mailing lists [2], blogs, Q&amp;A websites, bug trackers [1]” (Ponzanelli et al., 2014, p. 1) \n\n“Recommender systems” (Ponzanelli et al., 2014, p. 1) \n\n“eR” (Ponzanelli et al., 2014, p. 1) \n\n“ose” (Ponzanelli et al., 2014, p. 1) \n\n“eepI” (Ponzanelli et al., 2014, p. 1) \n\n“suggest project artifacts in the IDE aiming at providing developers with additional information on specific parts of the system.” (Ponzanelli et al., 2014, p. 1) \n\n“Ideally, a recommender system should behave like a prompter in a theatre: Ready to provide suggestions whenever the actor needs them, and ready to autonomously give suggestions if it feels something is going wrong.” (Ponzanelli et al., 2014, p. 1) \n\n“driver” (Ponzanelli et al., 2014, p. 1) \n\n“e” (Ponzanelli et al., 2014, p. 1) \n\n“observer,” (Ponzanelli et al., 2014, p. 1) \n\n“interrupts the driver by giving suggestions.” (Ponzanelli et al., 2014, p. 1) \n\n“the driver can consult the observer whenever she needs it, making the observer” (Ponzanelli et al., 2014, p. 1) \n\n“the programming prompter of the programming actor.” (Ponzanelli et al., 2014, p. 1) \n\n“push notifications” (Ponzanelli et al., 2014, p. 1) \n\n“relevant Stack Overflow discussions to the developer. Prompter makes” (Ponzanelli et al., 2014, p. 1) \n\n“IDE” (Ponzanelli et al., 2014, p. 1) \n\n“silently observes and analyzes” (Ponzanelli et al., 2014, p. 1) \n\n“the code context in the IDE” (Ponzanelli et al., 2014, p. 1) \n\n“automatically searches for Stack Over-” (Ponzanelli et al., 2014, p. 1) \n\n“flow discussions on the Web” (Ponzanelli et al., 2014, p. 1) \n\n“evaluates their relevance by taking i” (Ponzanelli et al., 2014, p. 1) \n\n“consideration code aspects” (Ponzanelli et al., 2014, p. 1) \n\n(Ponzanelli et al., 2014, p. 2) This is very interesting \n\n“(i) receive and track notifications” (Ponzanelli et al., 2014, p. 2) \n\n“(ii) read the suggested Stack Overflow discussions.” (Ponzanelli et al., 2014, p. 2) \n\n“code contexts (1) every time a change in the source code occurs” (Ponzanelli et al., 2014, p. 2) \n\n“formulates a query starting from the code context (2)” (Ponzanelli et al., 2014, p. 2) \n\n“rompter submits a new search only if the query diff” (Ponzanelli et al., 2014, p. 2) \n\n“plug-in,” (Ponzanelli et al., 2014, p. 2) \n\n“the search engines to which the query is sent,” (Ponzanelli et al., 2014, p. 2) \n\n“Stack Overflow API” (Ponzanelli et al., 2014, p. 2) \n\n“Web search on the Stack Overflow website” (Ponzanelli et al., 2014, p. 2) \n\n“All resulting URLs are collected and duplicates removed (5).” (Ponzanelli et al., 2014, p. 2) \n\n“The service uses the Stack Overflow question ID to retrieve the discussion via the Stack Overflow API (6)” (Ponzanelli et al., 2014, p. 2) \n\n“discussion is, given the code context, ranked (7) a” (Ponzanelli et al., 2014, p. 3) \n\n“he ranked list of URLs is sent back to the plug-in where Prompter decides whether to fire a” (Ponzanelli et al., 2014, p. 3) \n\n“new notification in the IDE (8).” (Ponzanelli et al., 2014, p. 3) \n\n“Our previous work in this context [28] only used text similarity as a means to retrieve Stack Overflow discussions related to the actual code” (Ponzanelli et al., 2014, p. 3) \n\n“The approach we present here relies on several combined aspects, and has proven to be more robust and less error-prone.” (Ponzanelli et al., 2014, p. 3) \n\n“rompter waits until the developer stops writing” (Ponzanelli et al., 2014, p. 3) \n\n“current code ele-” (Ponzanelli et al., 2014, p. 3) \n\n“ment” (Ponzanelli et al., 2014, p. 3) \n\n“extracts the current context” (Ponzanelli et al., 2014, p. 3) \n\n“,packageName.ClassName f” (Ponzanelli et al., 2014, p. 3) \n\n“me for classes” (Ponzanelli et al., 2014, p. 3) \n\n“packageName.ClassName.methodSignature for methods;” (Ponzanelli et al., 2014, p. 3) \n\n“the source code of the modified element” (Ponzanelli et al., 2014, p. 3) \n\n“the types of the used API,” (Ponzanelli et al., 2014, p. 3) \n\n“the names of methods invoked in the API, again considering only external libraries and JDK only.” (Ponzanelli et al., 2014, p. 3) \n\n“automate the triggering of searche” (Ponzanelli et al., 2014, p. 3) \n\n“es” (Ponzanelli et al., 2014, p. 3) \n\n“treat the code as a bag of words” (Ponzanelli et al., 2014, p. 3) \n\n“(i) splitting identifiers and removing stop words” (Ponzanelli et al., 2014, p. 3) \n\n“(ii) ranking the obtained terms according to their frequency” (Ponzanelli et al., 2014, p. 3) \n\n“(iii) selecting the top-n most frequent terms” (Ponzanelli et al., 2014, p. 3) \n\n“d more discriminative terms” (Ponzanelli et al., 2014, p. 3) \n\n“term entropy can be used to lower the prominence of frequent terms that do not suffi” (Ponzanelli et al., 2014, p. 3) \n\n“the Query Generation Service selects the top n terms to devise the query, plus the word java.” (Ponzanelli et al., 2014, p. 3) \n\n“To overcome this problem, before selecting the n terms to create the query, we use the Levenshtein distance [21] to verify if in the context there are terms with a very high textual similarity.” (Ponzanelli et al., 2014, p. 3) \n\n“1. Textual Similarity:” (Ponzanelli et al., 2014, p. 3) \n\n“2. Code Similarity:” (Ponzanelli et al., 2014, p. 3) \n\n“3. API Types Similarity” (Ponzanelli et al., 2014, p. 3) \n\n“4. API Methods Similarity:” (Ponzanelli et al., 2014, p. 3) \n\n“JDT” (Ponzanelli et al., 2014, p. 3) \n\n“5. Question Score:” (Ponzanelli et al., 2014, p. 4) \n\n“sigmoid function:” (Ponzanelli et al., 2014, p. 4) \n\n“where x is the score and ̄ x is the average of the scores of all the questions in Stack Overflow according to the data dump of June 2013.” (Ponzanelli et al., 2014, p. 4) \n\n“6. Accepted Answer Score:” (Ponzanelli et al., 2014, p. 4) \n\n“7. User Reputation:” (Ponzanelli et al., 2014, p. 4) \n\n“8. Tags Similarity: T” (Ponzanelli et al., 2014, p. 4) \n\n“M. Robillard, R. Walker, and T. Zimmermann. Recommendation systems for software engineering. IEEE Software, pages 80–86, 2010.” (Ponzanelli et al., 2014, p. 10) \n\n“[42] L. Williams. Integrating pair programming into a software development process. In Proceedings of CSEET 2001, pages 27–36. IEEE, 2001.” (Ponzanelli et al., 2014, p. 10)"],"numpages":["10"],"pages":["102–111"],"publisher":["ACM Press"],"title":["Mining StackOverflow to turn the IDE into a self-confident programming prompter"]},"creators":{"author":[{"lastName":"Ponzanelli","firstName":"Luca"},{"lastName":"Bavota","firstName":"Gabriele"},{"lastName":"Di Penta","firstName":"Massimiliano"},{"lastName":"Oliveto","firstName":"Rocco"},{"lastName":"Lanza","firstName":"Michele"}]},"sentenceCased":true},{"key":"ponzanelliSeahawkStackOverflow2013","type":"inproceedings","fields":{"author":["Ponzanelli, L.","Bacchelli, A.","Lanza, M."],"booktitle":["2013 35th Int. Conf. Softw. Eng. ICSE"],"date":["2013-05"],"doi":["10.1109/ICSE.2013.6606701"],"issn":["0270-5257"],"note":["TL;DR \n\nSeahawk is an Eclipse plugin that supports an integrated and largely automated approach to assist programmers using Stack Overflow, and formulates queries automatically from the active context in the IDE, presents a ranked and interactive list of results, and lets users import code samples in discussions through drag &amp; drop."],"pages":["1295–1298"],"title":["Seahawk: Stack overflow in the IDE"]},"creators":{"author":[{"lastName":"Ponzanelli","firstName":"L."},{"lastName":"Bacchelli","firstName":"A."},{"lastName":"Lanza","firstName":"M."}]},"sentenceCased":true},{"key":"poojaraServerlessDataPipeline2022","type":"article","fields":{"langid":["english"],"abstract":["With the increasing number of Internet of Things (IoT) devices, massive amounts of raw data is being generated. The latency, cost, and other challenges in cloud-based IoT data processing have driven the adoption of Edge and Fog computing models, where some data processing tasks are moved closer to data sources. Properly dealing with the flow of such data requires building data pipelines, to control the complete life cycle of data streams from data acquisition at the data source, edge and fog processing, to Cloud side storage and analytics. Data analytics tasks need to be executed dynamically at different distances from the data sources and often on very heterogeneous hardware devices. This can be streamlined by the use of a Serverless (or FaaS) cloud computing model, where tasks are defined as virtual functions, which can be migrated from edge to cloud (and vice versa) and executed in an event-driven manner on data streams. In this work, we investigate the benefits of building Serverless data pipelines (SDP) for IoT data analytics and evaluate three different approaches for designing SDPs: (1) Off-the-shelf data flow tool (DFT) based, (2) Object storage service (OSS) based and (3) MQTT based. Further, we applied these strategies on three fog applications (Aeneas, PocketSphinx, and custom Video processing application) and evaluated the performance by comparing their processing time (computation time, network communication and disk access time), and resource utilization. Results show that DFT is unsuitable for compute-intensive applications such as video or image processing, whereas OSS is best suitable for this task. However, DFT is nicely fit for bandwidthintensive applications due to the minimum use of network resources. On the other hand, MQTT-based SDP is observed with increase in CPU and Memory usage as the number of users rose, and experienced a drop in data units in the pipeline for PocketSphinx and custom video processing applications, however it performed well for Aeneas which had low size data units."],"author":["Poojara, Shivananda R.","Dehury, Chinmaya Kumar","Jakovits, Pelle","Srirama, Satish Narayana"],"date":["2022-05"],"doi":["10.1016/j.future.2021.12.012"],"issn":["0167739X"],"journaltitle":["Future Generation Computer Systems"],"pages":["91–105"],"title":["Serverless data pipeline approaches for IoT data in fog and cloud computing"],"volume":["130"]},"creators":{"author":[{"lastName":"Poojara","firstName":"Shivananda R."},{"lastName":"Dehury","firstName":"Chinmaya Kumar"},{"lastName":"Jakovits","firstName":"Pelle"},{"lastName":"Srirama","firstName":"Satish Narayana"}]},"sentenceCased":true},{"key":"PopoolaKR16","type":"inproceedings","fields":{"langid":["english"],"author":["Popoola, Saheed","Kolovos, Dimitrios S.","Rodriguez, Horacio Hoyos"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Theory Pract. Model Transform. - 9th Int. Conf. ICMTSTAF 2016 Vienna Austria July 4-5 2016 Proc."],"date":["2016"],"doi":["10.1007/978-3-319-42064-6\\_3"],"editor":["Gorp, Pieter Van","Engels, Gregor"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["36–51"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Mon, 05 Feb 2024 20:35:50 +0100"],"title":["EMG: A domain-specific transformation language for synthetic model generation"],"volume":["9765"]},"creators":{"author":[{"lastName":"Popoola","firstName":"Saheed"},{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"Rodriguez","firstName":"Horacio Hoyos"}],"editor":[{"lastName":"Gorp","firstName":"Pieter Van"},{"lastName":"Engels","firstName":"Gregor"}]},"sentenceCased":true},{"key":"Porres03","type":"inproceedings","fields":{"langid":["english"],"author":["Porres, Ivan"],"booktitle":["«UML» 2003 - Unified Model. Lang. Model. Lang. Appl. 6th Int. Conf. San Franc. CA USA Oct. 20-24 2003 Proc."],"date":["2003"],"doi":["10.1007/978-3-540-45221-8\\_16"],"editor":["Stevens, Perdita","Whittle, Jon","Booch, Grady"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper discusses how to define and execute model refactorings as rule-based transformations and presents an experimental tool to execute these transformations."],"pages":["159–174"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"title":["Model refactorings as rule-based update transformations"],"volume":["2863"]},"creators":{"author":[{"lastName":"Porres","firstName":"Ivan"}],"editor":[{"lastName":"Stevens","firstName":"Perdita"},{"lastName":"Whittle","firstName":"Jon"},{"lastName":"Booch","firstName":"Grady"}]},"sentenceCased":true},{"key":"portugalUseMachineLearning2015","type":"article","fields":{"author":["Portugal, Ivens","Alencar, Paulo","Cowan, Donald"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/journals/corr/PortugalAC15a"],"date":["2015"],"eprint":["1511.05263"],"eprinttype":["arxiv"],"ids":["DBLP:journals/corr/PortugalAC15a"],"journaltitle":["ArXiv Prepr. ArXiv151105263"],"shorttitle":["The Use of Machine Learning Algorithms in Recommender Systems"],"timestamp":["Mon, 13 Aug 2018 16:46:19 +0200"],"title":["The Use of Machine Learning Algorithms in Recommender Systems: A Systematic Review"],"url":["https://arxiv.org/abs/1511.05263"],"urldate":["2017-03-10"]},"creators":{"author":[{"lastName":"Portugal","firstName":"Ivens"},{"lastName":"Alencar","firstName":"Paulo"},{"lastName":"Cowan","firstName":"Donald"}]}},{"key":"pottsSoftwareengineeringResearchRevisited1993","type":"article","fields":{"author":["Potts, Colin"],"date":["1993"],"journaltitle":["IEEE Softw."],"number":["5"],"pages":["19–28"],"title":["Software-engineering research revisited"],"url":["http://ieeexplore.ieee.org/abstract/document/232392/"],"urldate":["2017-07-03"],"volume":["10"]},"creators":{"author":[{"lastName":"Potts","firstName":"Colin"}]},"sentenceCased":true},{"key":"potvinWhyGoogleStores2016","type":"article","fields":{"author":["Potvin, Rachel","Levenberg, Josh"],"date":["2016"],"journaltitle":["Commun. ACM"],"note":["TL;DR \n\nGoogle's monolithic repository provides a common source of truth for tens of thousands of developers around the world."],"number":["7"],"pages":["78–87"],"title":["Why Google stores billions of lines of code in a single repository"],"url":["http://dl.acm.org/citation.cfm?id=2854146"],"urldate":["2017-05-25"],"volume":["59"]},"creators":{"author":[{"lastName":"Potvin","firstName":"Rachel"},{"lastName":"Levenberg","firstName":"Josh"}]},"sentenceCased":true},{"key":"Pourpanah:2016:HMF:2884077.2884195","type":"article","fields":{"acmid":["2884195"],"address":["Tarrytown, NY, USA"],"author":["Pourpanah, Farhad","Lim, Chee Peng","Saleh, Junita Mohamad"],"date":["2016-05"],"issn":["0957-4174"],"issue_date":["May 2016"],"journaltitle":["Expert Syst. Appl."],"keywords":["Data classification","Fuzzy ARTMAP","Genetic algorithm","Q-learning","reinforcement learning","Rule extraction"],"nodoi":["10.1016/j.eswa.2015.11.009"],"number":["C"],"numpages":["12"],"pages":["74–85"],"publisher":["Pergamon Press, Inc."],"title":["A hybrid model of fuzzy ARTMAP and genetic algorithm for data classification and rule extraction"],"url":["https://doi.org/10.1016/j.eswa.2015.11.009"],"volume":["49"]},"creators":{"author":[{"lastName":"Pourpanah","firstName":"Farhad"},{"lastName":"Lim","firstName":"Chee Peng"},{"lastName":"Saleh","firstName":"Junita Mohamad"}]},"sentenceCased":true},{"key":"prasadConvolutionalNeuralNetworks","type":"article","fields":{"langid":["english"],"author":["Prasad, Ashu"],"pages":["28"],"title":["Convolutional Neural Networks with Tensor ow"]},"creators":{"author":[{"lastName":"Prasad","firstName":"Ashu"}]},"sentenceCased":true},{"key":"Pretschner05","type":"inproceedings","fields":{"langid":["english"],"abstract":["Model-based testing relies on behavior models for the generation of model traces: input and expected output—test cases—for an implementation. We use the case study of an automotive network controller to assess different test suites in terms of error detection, model coverage, and implementation coverage. Some of these suites were generated automatically with and without models, purely at random, and with dedicated functional test selection criteria. Other suites were derived manually, with and without the model at hand. Both automatically and manually derived model-based test suites detected significantly more requirements errors than hand-crafted test suites that were directly derived from the requirements. The number of detected programming errors did not depend on the use of models. Automatically generated model-based test suites detected as many errors as hand-crafted model-based suites with the same number of tests. A sixfold increase in the number of model-based tests led to an 11% increase in detected errors."],"author":["Pretschner, A.","Prenninger, W.","Wagner, S.","Kühnel, C.","Baumgartner, M.","Sostawa, B.","Zölch, R.","Stauner, T."],"booktitle":["Proc. 27th Int. Conf. Softw. 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CAV"],"date":["2011"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nA major new release of the PRISMprobabilistic model checker is described, adding, in particular, quantitative verification of (priced) probabilistic timed automata."],"pages":["585–591"],"publisher":["Springer"],"title":["PRISM 4.0: Verification of probabilistic real-time systems"],"volume":["6806"]},"creators":{"author":[{"lastName":"Kwiatkowska","firstName":"Marta Z."},{"lastName":"Norman","firstName":"Gethin"},{"lastName":"Parker","firstName":"David"}]},"sentenceCased":true},{"key":"Project2ACLAutonomous","type":"online","fields":{"title":["Project2 - ACL - Autonomous Systems and Robotics - Research Groups - Research - ACSE - The University of Sheffield"],"url":["https://www.sheffield.ac.uk/acse/research/groups/asrg/acl/project2"],"urldate":["2016-08-26"]},"creators":{}},{"key":"prokschHowBuildRecommendation2015","type":"incollection","fields":{"langid":["english"],"abstract":["Software developers must interact with large amounts of different types of information and perform many different activities to build a software system. To ease the finding of information and hone workflows, there has been growing interest in building recommenders that are intended to help software developers work more effectively. Building an effective recommender requires a deep understanding of the problem that is the target of a recommender, analysis of different aspects of the approach taken to perform the recommendations and design and evaluation of the mechanisms used to present recommendations to a developer. In this chapter, we outline the different steps that must be taken to develop an effective recommender system to aid software development."],"author":["Proksch, Sebastian","Bauer, Veronika","Murphy, Gail C."],"booktitle":["Software Engineering"],"date":["2015"],"doi":["10.1007/978-3-319-28406-4_1"],"editor":["Meyer, Bertrand","Nordio, Martin"],"isbn":["978-3-319-28405-7 978-3-319-28406-4"],"location":["Cham"],"pages":["1–42"],"publisher":["Springer International Publishing"],"title":["How to Build a Recommendation System for Software Engineering"],"volume":["8987"]},"creators":{"author":[{"lastName":"Proksch","firstName":"Sebastian"},{"lastName":"Bauer","firstName":"Veronika"},{"lastName":"Murphy","firstName":"Gail C."}],"editor":[{"lastName":"Meyer","firstName":"Bertrand"},{"lastName":"Nordio","firstName":"Martin"}]}},{"key":"PromptingFinetuningComparative2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["Taxonomies represent hierarchical relations between entities, frequently applied in various software modeling and natural language processing (NLP) activities. They are typically subject to a set of structural constraints restricting their content. However, manual taxonomy construction can be time-consuming, incomplete, and costly to maintain. Recent studies of large language models (LLMs) have demonstrated that appropriate user inputs (called prompting) can effectively guide LLMs, such as GPT-3, in diverse NLP tasks without explicit (re-)training. However, existing approaches for automated taxonomy construction typically involve fine-tuning a language model by adjusting model parameters. In this paper, we present a general framework for taxonomy construction that takes into account structural constraints. We subsequently conduct a systematic comparison between the prompting and fine-tuning approaches performed on a hypernym taxonomy and a novel computer science taxonomy dataset. Our result reveals the following: (1) Even without explicit training on the dataset, the prompting approach outperforms fine-tuning-based approaches. Moreover, the performance gap between prompting and fine-tuning widens when the training dataset is small. However, (2) taxonomies generated by the fine-tuning approach can be easily post-processed to satisfy all the constraints, whereas handling violations of the taxonomies produced by the prompting approach can be challenging. These evaluation findings provide guidance on selecting the appropriate method for taxonomy construction and highlight potential enhancements for both approaches."],"booktitle":["2021 ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion MODELS-C"],"date":["2021"],"eventtitle":["2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)"],"isbn":["978-1-66542-484-4"],"keywords":["LOGSEQ"],"location":["Fukuoka, Japan"],"note":["TL;DR \n\nA general framework for taxonomy construction that takes into account structural constraints is presented and a systematic comparison between the prompting and fine-tuning approaches performed on a hypernym taxonomy and a novel computer science taxonomy dataset is conducted."],"publisher":["IEEE"],"title":["Prompting or Fine-tuning? A Comparative Study of Large Language Models for Taxonomy Construction"]},"creators":{}},{"key":"Protasiewicz2020","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc Int Jt Conf Neural Networks"],"affiliation":["National Information Processing Institute, Warsaw, Poland"],"art_number":["9206996"],"author":["Protasiewicz, J."],"coden":["85OFA"],"correspondence_address1":["Protasiewicz, J.; National Information Processing InstitutePoland"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/IJCNN48605.2020.9206996"],"isbn":["978-1-72816-926-2"],"keywords":["notion"],"note":["cited By 0 \n\nTL;DR \n\nThe results and flexibility of use suggest that the neural toolbox should help users to develop prediction systems of electricity consumption more conveniently, as it is designed for that particular purpose."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings of the International Joint Conference on Neural Networks"],"source":["Scopus"],"title":["A neural network toolbox for electricity consumption forecasting"]},"creators":{"author":[{"lastName":"Protasiewicz","firstName":"J."}]},"sentenceCased":true},{"key":"provoostDingNetSelfAdaptiveInternetofThings2019","type":"inproceedings","fields":{"author":["Provoost, Michiel","Weyns, Danny"],"booktitle":["2019 IEEEACM 14th Int. Symp. Softw. Eng. Adapt. Self-Manag. Syst. SEAMS"],"date":["2019-05"],"doi":["10.1109/SEAMS.2019.00033"],"eventtitle":["2019 IEEE/ACM 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)"],"isbn":["978-1-72813-368-3"],"keywords":["DONE"],"location":["Montreal, QC, Canada"],"pages":["195–201"],"publisher":["IEEE"],"shorttitle":["DingNet"],"title":["DingNet: A Self-Adaptive Internet-of-Things Exemplar"]},"creators":{"author":[{"lastName":"Provoost","firstName":"Michiel"},{"lastName":"Weyns","firstName":"Danny"}]}},{"key":"PTMTorrentDatasetMining2023","type":"dataset","fields":{"langid":["english"],"abstract":["Due to the cost of developing and training deep learning models from scratch, machine learning engineers have begun to reuse pre-trained models (PTMs) and fine-tune them for downstream tasks. PTM registries known as “model hubs” support engineers in distributing and reusing deep learning models. PTM packages include pre-trained weights, documentation, model architectures, datasets, and metadata. Mining the information in PTM packages will enable the discovery of engineering phenomena and tools to support software engineers. However, accessing this information is difficult — there are many PTM registries, and both the registries and the individual packages may have rate limiting for accessing the data. We present an open-source dataset, PTMTorrent, to facilitate the evaluation and understanding of PTM packages. This paper describes the creation, structure, usage, and limitations of the dataset. The dataset includes a snapshot of 5 model hubs and a total of 15,913 PTM packages. These packages are represented in a uniform data schema for cross-hub mining. We describe prior uses of this data and suggest research opportunities for mining using our dataset. We provide links to the PTM Dataset and PTM Torrent Source Code."],"date":["2023-02-04"],"doi":["10.6084/m9.figshare.22009880.v4"],"publisher":["figshare"],"shorttitle":["PTMTorrent"],"title":["PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages"]},"creators":{}},{"key":"PtolemyProjectHome","type":"online","fields":{"title":["Ptolemy Project Home Page"],"url":["http://ptolemy.eecs.berkeley.edu/"],"urldate":["2016-01-26"]},"creators":{}},{"key":"PublicationsGEMOCInitiative","type":"online","fields":{"title":["Publications » The GEMOC Initiative"],"url":["http://gemoc.org/publications/"],"urldate":["2015-09-28"]},"creators":{}},{"key":"pulgattiDataMigrationDifferent","type":"article","fields":{"langid":["english"],"author":["Pulgatti, Leandro Duarte"],"pages":["80"],"title":["Data Migration Between Different Data Models of NoSql Databases"]},"creators":{"author":[{"lastName":"Pulgatti","firstName":"Leandro Duarte"}]}},{"key":"Pylianidis202145","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Wageningen University, Wageningen, Netherlands; AgResearch, Christchurch, New Zealand; CSIRO, Brisbane, Australia"],"author":["Pylianidis, C.","Snow, V.","Holzworth, D.","Bryant, J.","Athanasiadis, I.N."],"correspondence_address1":["Pylianidis, C.; Wageningen UniversityNetherlands; email: christos.pylianidis@wur.nl"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-68780-9_5"],"editor":["Del Bimbo A., Cucchiara R., Farinella G.M., Mei T., Bertini M., Escalante H.J., Vezzani R., Sclaroff S."],"isbn":["9783030687793"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 1"],"pages":["45–54"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Location-specific vs location-agnostic machine learning metamodels for predicting pasture nitrogen response rate"],"volume":["12666 LNCS"]},"creators":{"author":[{"lastName":"Pylianidis","firstName":"C."},{"lastName":"Snow","firstName":"V."},{"lastName":"Holzworth","firstName":"D."},{"lastName":"Bryant","firstName":"J."},{"lastName":"Athanasiadis","firstName":"I.N."}],"editor":[{"lastName":"Del Bimbo A.","suffix":"Cucchiara R.","firstName":"Farinella G.M., Mei T., Bertini M., Escalante H.J., Vezzani R., Sclaroff S."}]},"sentenceCased":true},{"key":"qianCommunicativeAgentsSoftware2023","type":"online","fields":{"abstract":["Software engineering is a domain characterized by intricate decision-making processes, often relying on nuanced intuition and consultation. Recent advancements in deep learning have started to revolutionize software engineering practices through elaborate designs implemented at various stages of software development. In this paper, we present an innovative paradigm that leverages large language models (LLMs) throughout the entire software development process, streamlining and unifying key processes through natural language communication, thereby eliminating the need for specialized models at each phase. At the core of this paradigm lies ChatDev, a virtual chat-powered software development company that mirrors the established waterfall model, meticulously dividing the development process into four distinct chronological stages: designing, coding, testing, and documenting. Each stage engages a team of \"software agents\", such as programmers, code reviewers, and test engineers, fostering collaborative dialogue and facilitating a seamless workflow. The chat chain acts as a facilitator, breaking down each stage into atomic subtasks. This enables dual roles, allowing for proposing and validating solutions through context-aware communication, leading to efficient resolution of specific subtasks. The instrumental analysis of ChatDev highlights its remarkable efficacy in software generation, enabling the completion of the entire software development process in under seven minutes at a cost of less than one dollar. It not only identifies and alleviates potential vulnerabilities but also rectifies potential hallucinations while maintaining commendable efficiency and cost-effectiveness. The potential of ChatDev unveils fresh possibilities for integrating LLMs into the realm of software development. Our code is available at https://github.com/OpenBMB/ChatDev."],"author":["Qian, Chen","Cong, Xin","Liu, Wei","Yang, Cheng","Chen, Weize","Su, Yusheng","Dang, Yufan","Li, Jiahao","Xu, Juyuan","Li, Dahai","Liu, Zhiyuan","Sun, Maosong"],"date":["2023-12-19"],"eprint":["2307.07924"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Computation and Language","Computer Science - Multiagent Systems","Computer Science - Software Engineering"],"note":["Comment: https://github.com/OpenBMB/ChatDev \n\nTL;DR \n\nAn innovative paradigm that leverages large language models (LLMs) throughout the entire software development process, streamlining and unifying key processes through natural language communication, thereby eliminating the need for specialized models at each phase."],"pubstate":["preprint"],"title":["Communicative Agents for Software Development"],"url":["http://arxiv.org/abs/2307.07924"],"urldate":["2024-02-14"]},"creators":{"author":[{"lastName":"Qian","firstName":"Chen"},{"lastName":"Cong","firstName":"Xin"},{"lastName":"Liu","firstName":"Wei"},{"lastName":"Yang","firstName":"Cheng"},{"lastName":"Chen","firstName":"Weize"},{"lastName":"Su","firstName":"Yusheng"},{"lastName":"Dang","firstName":"Yufan"},{"lastName":"Li","firstName":"Jiahao"},{"lastName":"Xu","firstName":"Juyuan"},{"lastName":"Li","firstName":"Dahai"},{"lastName":"Liu","firstName":"Zhiyuan"},{"lastName":"Sun","firstName":"Maosong"}]}},{"key":"Qiang20202508","type":"article","fields":{"abstract":["This letter provides a deep learning framework for massive grant-free random access in 6G cellular internet of things (IoT) networks. A model-driven deep learning algorithm for joint activity detection and channel estimation is proposed based on the principle of approximate massage passing (AMP). This algorithm only needs to learn four key parameters, but not the whole algorithm architecture. More importantly, it does not require the prior information about active probabilities and channel variance, and can significantly improve the performance with a finite number of training data. Simulation results validate the effectiveness of the proposed deep learning algorithm. © 1997-2012 IEEE."],"art_number":["9146533"],"author":["Qiang, Y.","Shao, X.","Chen, X."],"coden":["ICLEF"],"date":["2020"],"document_type":["Article"],"doi":["10.1109/LCOMM.2020.3011571"],"issn":["10897798"],"journaltitle":["IEEE Commun. Lett."],"note":["cited By 10 \n\nTL;DR \n\nA model-driven deep learning algorithm for joint activity detection and channel estimation is proposed based on the principle of approximate massage passing that does not require the prior information about active probabilities and channel variance, and can significantly improve the performance with a finite number of training data."],"number":["11"],"pages":["2508–2512"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["A model-driven deep learning algorithm for joint activity detection and channel estimation"],"volume":["24"]},"creators":{"author":[{"lastName":"Qiang","firstName":"Y."},{"lastName":"Shao","firstName":"X."},{"lastName":"Chen","firstName":"X."}]},"sentenceCased":true},{"key":"Qiao2021282","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - Int. Conf. Comput. Data Sci., CDS"],"affiliation":["Research Institute of Micro/Nano Science and Technology, Shanghai Jiao Tong University, Shanghai, China"],"art_number":["9463303"],"author":["Qiao, J."],"correspondence_address1":["Qiao, J.; Research Institute of Micro/Nano Science and Technology, China; email: qiao<sub>j</sub>ing<sub>y</sub>ang@163.com"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/CDS52072.2021.00056"],"isbn":["978-1-66540-428-0"],"note":["cited By 0"],"pages":["282–286"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2021 2nd International Conference on Computing and Data Science, CDS 2021"],"source":["Scopus"],"title":["Research on motion modeling and control of tracking car based on neural network"]},"creators":{"author":[{"lastName":"Qiao","firstName":"J."}]},"sentenceCased":true},{"key":"Qin2022","type":"article","fields":{"abstract":["Machine learning models are vulnerable to adversarial examples. We study the most realistic hard-label black-box attacks in this paper. The main limitation of the existing attacks is that they need a large number of model queries, making them inefficient and even infeasible in practice. Inspired by the very successful fuzz testing approach in traditional software engineering and computer security domains, we propose fuzzing-based hard-label black-box attacks against machine learning models. We design an AdvFuzzer to explore multiple paths between a source image and a guidance image, and design a LocalFuzzer to explore the nearby space around a given input for identifying potential adversarial examples. We demonstrate that our fuzzing attacks are feasible and effective in generating successful adversarial examples with significantly reduced number of model queries and L0 distance. More interestingly, given a successful example generated by either our or other attacks, LocalFuzzer can immediately generate more successful adversarial examples even with smaller L2 distance from the source example. © 2022 Elsevier Ltd"],"art_number":["102694"],"author":["Qin, Y.","Yue, C."],"author_keywords":["Adversarial example; Adversarial machine learning; Black-box attack; Fuzzing; Neural network"],"coden":["CPSED"],"date":["2022"],"document_type":["Article"],"doi":["10.1016/j.cose.2022.102694"],"issn":["01674048"],"journaltitle":["Comput. Secur."],"keywords":["Adversarial example","Adversarial machine learning","Black boxes","Black-box attack","Black-box testing","Fuzz Testing","Fuzzing","Machine learning","Machine learning models","Multiple-path","Neural-networks","Security domains","Security of data"],"note":["cited By 2"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Fuzzing-based hard-label black-box attacks against machine learning models"],"volume":["117"]},"creators":{"author":[{"lastName":"Qin","firstName":"Y."},{"lastName":"Yue","firstName":"C."}]},"sentenceCased":true},{"key":"Quinlan:1986:IDT:637962.637969","type":"article","fields":{"acmid":["637969"],"address":["Hingham, MA, USA"],"author":["Quinlan, J. R."],"date":["1986-03"],"issn":["0885-6125"],"journaltitle":["Mach. Learn."],"keywords":["classification","decision trees","expert systems","induction","information theory","knowledge acquisition"],"nodoi":["10.1023/A:1022643204877"],"number":["1"],"numpages":["26"],"pages":["81–106"],"publisher":["Kluwer Academic Publishers"],"title":["Induction of decision trees"],"url":["http://dx.doi.org/10.1023/A:1022643204877"],"volume":["1"]},"creators":{"author":[{"lastName":"Quinlan","firstName":"J. R."}]},"sentenceCased":true},{"key":"Quintero2016219","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Commun. Comput. Info. Sci."],"affiliation":["CUN-Corporación Unificada Nacional de Educación Superior, Bogotá, Colombia; Universidad Distrital Francisco José de Caldas, Bogotá, Colombia; Universidad de Oviedo, Oviedo, Spain"],"author":["Quintero, J.L.","García, V.H.M.","García, C.P."],"correspondence_address1":["García, V.H.M.; Universidad Distrital Francisco José de CaldasColombia; email: vmedina@udistrital.edu.co"],"date":["2016"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-319-42147-6_19"],"editor":["Liberona D., Feldmann B., Uden L."],"isbn":["9783319421469"],"issn":["18650929"],"journaltitle":["Commun. Comput. Inf. Sci."],"note":["cited By 1 \n\nTL;DR \n\nThe final result is the design of a functional architecture that permits integrating the Web 2.0 Application and a semantic analysis algorithm from unstructured information by applying machine learning techniques."],"pages":["219–232"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Knowledge management metamodel from social analysis of lessons learnt registered in the cloud"],"volume":["620"]},"creators":{"author":[{"lastName":"Quintero","firstName":"J.L."},{"lastName":"García","firstName":"V.H.M."},{"lastName":"García","firstName":"C.P."}],"editor":[{"lastName":"Liberona D.","suffix":"Feldmann B.","firstName":"Uden L."}]},"sentenceCased":true},{"key":"QVT","type":"manual","fields":{"langid":["english"],"author":["Omg"],"date":["2005"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["OMG doc. ptc/05-11-01"],"number":["ptc/05-11-01"],"publisher":["Object Management Group"],"title":["MOF QVT final adopted specification"],"type":["manual"]},"creators":{"author":[{"literal":"Omg"}]},"sentenceCased":true},{"key":"Rabbah2020","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Int. Conf. Intell. Comput. Data Sci., ICDS"],"affiliation":["Hassan Ii University, Ritm Laboratory, Ced Engineering Sciences, Casablanca, Morocco"],"art_number":["9268777"],"author":["Rabbah, J.","Ridouani, M.","Hassouni, L."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/ICDS50568.2020.9268777"],"editor":["Oubenaalla Y., Nfaoui E.H., Loqman C., Riffi J., Kozma R., Mestari M., Alippi C., Joumhidi J."],"isbn":["978-1-72818-084-7"],"note":["cited By 6"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["4th International Conference on Intelligent Computing in Data Sciences, ICDS 2020"],"source":["Scopus"],"title":["A new classification model based on stacknet and deep learning for fast detection of COVID 19 through X rays images"]},"creators":{"author":[{"lastName":"Rabbah","firstName":"J."},{"lastName":"Ridouani","firstName":"M."},{"lastName":"Hassouni","firstName":"L."}],"editor":[{"lastName":"Oubenaalla Y.","suffix":"Nfaoui E.H.","firstName":"Loqman C., Riffi J., Kozma R., Mestari M., Alippi C., Joumhidi J."}]},"sentenceCased":true},{"key":"Rabbi201749","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Western Norway University of Applied Sciences, Bergen, Norway; University of Oslo, Oslo, Norway"],"author":["Rabbi, F.","Lamo, Y.","Kristensen, L.M."],"correspondence_address1":["Rabbi, F.; Western Norway University of Applied SciencesNorway; email: Fazle.Rabbi@hvl.no"],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-319-59294-7_5"],"editor":["Carrascosa C., Julian Inglada V., Osman N., Criado Pacheco N."],"isbn":["9783319592930"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 0"],"pages":["49–57"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["An MDE approach for modelling and reasoning about multi-agent systems"],"volume":["10207 LNAI"]},"creators":{"author":[{"lastName":"Rabbi","firstName":"F."},{"lastName":"Lamo","firstName":"Y."},{"lastName":"Kristensen","firstName":"L.M."}],"editor":[{"lastName":"Carrascosa C.","suffix":"Julian Inglada V.","firstName":"Osman N., Criado Pacheco N."}]},"sentenceCased":true},{"key":"Rafique2018D126","type":"article","fields":{"abstract":["Networks are complex interacting systems involving cloud operations, core and metro transport, and mobile connectivity all the way to video streaming and similar user applications.With localized and highly engineered operational tools, it is typical of these networks to take days to weeks for any changes, upgrades, or service deployments to take effect. Machine learning, a sub-domain of artificial intelligence, is highly suitable for complex system representation. In this tutorial paper, we review several machine learning concepts tailored to the optical networking industry and discuss algorithm choices, data and model management strategies, and integration into existing network control and management tools. We then describe four networking case studies in detail, covering predictive maintenance, virtual network topology management, capacity optimization, and optical spectral analysis. © 2009-2012 OSA."],"art_number":["8501533"],"author":["Rafique, D.","Velasco, L."],"date":["2018"],"document_type":["Article"],"doi":["10.1364/JOCN.10.00D126"],"issn":["19430620"],"journaltitle":["J. Opt. Commun. Netw."],"note":["cited By 166 \n\nTL;DR \n\nThis tutorial paper reviews several machine learning concepts tailored to the optical networking industry and discusses algorithm choices, data and model management strategies, and integration into existing network control and management tools."],"number":["10"],"pages":["D126-D143"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Machine learning for network automation: Overview, architecture, and applications [Invited Tutorial]"],"volume":["10"]},"creators":{"author":[{"lastName":"Rafique","firstName":"D."},{"lastName":"Velasco","firstName":"L."}]},"sentenceCased":true},{"key":"Ragkhitwetsagul2018","type":"article","fields":{"abstract":["Copying and pasting of source code is a common activity in software engineering. Often, the code is not copied as it is and it may be modified for various purposes; e.g. refactoring, bug fixing, or even software plagiarism. These code modifications could affect the performance of code similarity analysers including code clone and plagiarism detectors to some certain degree. We are interested in two types of code modification in this study: pervasive modifications, i.e. transformations that may have a global effect, and local modifications, i.e. code changes that are contained in a single method or code block. We evaluate 30 code similarity detection techniques and tools using five experimental scenarios for Java source code. These are (1) pervasively modified code, created with tools for source code and bytecode obfuscation, and boiler-plate code, (2) source code normalisation through compilation and decompilation using different decompilers, (3) reuse of optimal configurations over different data sets, (4) tool evaluation using ranked-based measures, and (5) local + global code modifications. Our experimental results show that in the presence of pervasive modifications, some of the general textual similarity measures can offer similar performance to specialised code similarity tools, whilst in the presence of boiler-plate code, highly specialised source code similarity detection techniques and tools outperform textual similarity measures. Our study strongly validates the use of compilation/decompilation as a normalisation technique. Its use reduced false classifications to zero for three of the tools. Moreover, we demonstrate that optimal configurations are very sensitive to a specific data set. After directly applying optimal configurations derived from one data set to another, the tools perform poorly on the new data set. The code similarity analysers are thoroughly evaluated not only based on several well-known pair-based and query-based error measures but also on each specific type of pervasive code modification. This broad, thorough study is the largest in existence and potentially an invaluable guide for future users of similarity detection in source code."],"author":["Ragkhitwetsagul, Chaiyong","Krinke, Jens","Clark, David"],"date":["2018-08-01"],"doi":["10.1007/s10664-017-9564-7"],"issn":["1573-7616"],"journaltitle":["Empir. Softw. Eng."],"note":["TL;DR \n\nThis study strongly validates the use of compilation/decompilation as a normalisation technique and reduced false classifications to zero for three of the tools, and demonstrates that optimal configurations are very sensitive to a specific data set."],"number":["4"],"pages":["2464–2519"],"title":["A comparison of code similarity analysers"],"volume":["23"]},"creators":{"author":[{"lastName":"Ragkhitwetsagul","firstName":"Chaiyong"},{"lastName":"Krinke","firstName":"Jens"},{"lastName":"Clark","firstName":"David"}]},"sentenceCased":true},{"key":"ragoneSchemasummarizationLinkeddatabasedFeature2017","type":"inproceedings","fields":{"acmid":["3019837"],"author":["Ragone, Azzurra","Tomeo, Paolo","Magarelli, Corrado","Di Noia, Tommaso","Palmonari, Matteo","Maurino, Andrea","Di Sciascio, Eugenio"],"booktitle":["Proc. Symp. Appl. Comput."],"date":["2017"],"isbn":["978-1-4503-4486-9"],"keywords":["information gain","linked data","ontology summarization"],"location":["New York, NY, USA"],"nodoi":["10.1145/3019612.3019837"],"numpages":["6"],"pages":["330–335"],"publisher":["ACM"],"series":["SAC '17"],"title":["Schema-summarization in linked-data-based feature selection for recommender systems"],"url":["http://doi.acm.org/10.1145/3019612.3019837"]},"creators":{"author":[{"lastName":"Ragone","firstName":"Azzurra"},{"lastName":"Tomeo","firstName":"Paolo"},{"lastName":"Magarelli","firstName":"Corrado"},{"lastName":"Di Noia","firstName":"Tommaso"},{"lastName":"Palmonari","firstName":"Matteo"},{"lastName":"Maurino","firstName":"Andrea"},{"lastName":"Di Sciascio","firstName":"Eugenio"}]},"sentenceCased":true},{"key":"RahimiTRB23","type":"inproceedings","fields":{"langid":["english"],"author":["Rahimi, Abbas","Tisi, Massimo","Rahimi, Shekoufeh Kolahdouz","Berardinelli, Luca"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS 2023 Companion Västerås Swed. Oct. 1-6 2023"],"date":["2023"],"doi":["10.1109/MODELS-C59198.2023.00098"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nGenerative deep learning, in particular, Generative Adversarial Networks (GANs), are utilized to present an approach for generating new structurally realistic models, and preliminary statistical results illustrate that using GAN s can be promising for creating new realistic models."],"pages":["597–604"],"publisher":["IEEE"],"timestamp":["Fri, 05 Jan 2024 16:35:45 +0100"],"title":["Towards generating structurally realistic models by generative adversarial networks"]},"creators":{"author":[{"lastName":"Rahimi","firstName":"Abbas"},{"lastName":"Tisi","firstName":"Massimo"},{"lastName":"Rahimi","firstName":"Shekoufeh Kolahdouz"},{"lastName":"Berardinelli","firstName":"Luca"}]},"sentenceCased":true},{"key":"Rajaei2021149","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["CEUR Workshop Proc."],"affiliation":["MDSE Research Group, Department of Software Engineering, University of Isfahan, Iran; IMT Atlantique, LS2N (UMR CNRS 6004), Nantes, France; ERIS, ESEO-TECH, Angers, France"],"author":["Rajaei, Z.","Kolahdouz-Rahimi, S.","Tisi, M.","Jouault, F."],"correspondence_address1":["Rajaei, Z.; MDSE Research Group, Iran; email: z.rajaei@eng.ui.ac.ir"],"date":["2021"],"document_type":["Conference Paper"],"editor":["Iovino L., Kristensen L.M."],"issn":["16130073"],"note":["cited By 0 \n\nTL;DR \n\nA Domain-Specific Language (DSL) is introduced for configuring the encoding of models into suitable input for graph-learning tools, interpreted to automatically translate MDE datasets, enabling their use in machine-learning pipelines."],"pages":["149–161"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"source":["Scopus"],"title":["A DSL for encoding models for graph-learning processes"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118923715&partnerID=40&md5=0392ba00df3c85c19cc98510b244e3b9"],"volume":["2999"]},"creators":{"author":[{"lastName":"Rajaei","firstName":"Z."},{"lastName":"Kolahdouz-Rahimi","firstName":"S."},{"lastName":"Tisi","firstName":"M."},{"lastName":"Jouault","firstName":"F."}],"editor":[{"lastName":"Iovino L.","firstName":"Kristensen L.M."}]},"sentenceCased":true},{"key":"rajInternetThingsEnabling2017","type":"book","fields":{"langid":["english"],"author":["Raj, Pethuru","Raman, Anupama C."],"date":["2017"],"isbn":["978-1-4987-6128-4"],"keywords":["internet of things"],"location":["Boca Raton"],"pagetotal":["364"],"publisher":["CRC Press/Taylor & Francis Group"],"shorttitle":["The Internet of things"],"title":["The Internet of things: Enabling technologies, platforms, and use cases"]},"creators":{"author":[{"lastName":"Raj","firstName":"Pethuru"},{"lastName":"Raman","firstName":"Anupama C."}]},"sentenceCased":true},{"key":"ramasamyWorkflowAnalysisData2023","type":"article","fields":{"langid":["english"],"abstract":["Despite the ubiquity of data science, we are far from rigorously understanding how coding in data science is performed. Even though the scientific literature has hinted at the iterative and explorative nature of data science coding, we need further empirical evidence to understand this practice and its workflows in detail. Such understanding is critical to recognise the needs of data scientists and, for instance, inform tooling support. To obtain a deeper understanding of the iterative and explorative nature of data science coding, we analysed 470 Jupyter notebooks publicly available in GitHub repositories. We focused on the extent to which data scientists transition between different types of data science activities, or steps (such as data preprocessing and modelling), as well as the frequency and co-occurrence of such transitions. For our analysis, we developed a dataset with the help of five data science experts, who manually annotated the data science steps for each code cell within the aforementioned 470 notebooks. Using the first-order Markov chain model, we extracted the transitions and analysed the transition probabilities between the different steps. In addition to providing deeper insights into the implementation practices of data science coding, our results provide evidence that the steps in a data science workflow are indeed iterative and reveal specific patterns. We also evaluated the use of the annotated dataset to train machinelearning classifiers to predict the data science step(s) of a given code cell. We investigate the representativeness of the classification by comparing the workflow analysis applied to (a) the predicted data set and (b) the data set labelled by experts, finding an F1-score of about 71% for the 10-class data science step prediction problem."],"author":["Ramasamy, Dhivyabharathi","Sarasua, Cristina","Bacchelli, Alberto","Bernstein, Abraham"],"date":["2023-01"],"doi":["10.1007/s10664-022-10229-z"],"issn":["1382-3256, 1573-7616"],"journaltitle":["Empir Software Eng"],"keywords":["LOGSEQ"],"note":["TL;DR \n\nThe results provide evidence that the steps in a data science workflow are indeed iterative and reveal specific patterns, and the use of the annotated dataset to train machine-learning classifiers to predict the data science step(s) of a given code cell is evaluated."],"number":["1"],"pages":["7"],"title":["Workflow analysis of data science code in public GitHub repositories"],"volume":["28"]},"creators":{"author":[{"lastName":"Ramasamy","firstName":"Dhivyabharathi"},{"lastName":"Sarasua","firstName":"Cristina"},{"lastName":"Bacchelli","firstName":"Alberto"},{"lastName":"Bernstein","firstName":"Abraham"}]},"sentenceCased":true},{"key":"Ramaswamy201450","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["AAAI Spring Symp. Tech. Rep."],"affiliation":["Department of Computer and System Engineering, ENSTA-ParisTech, 828 Blvd Marechaux, Palaiseau, France; VeDeCom Institute, 77 rue des Chantiers, 78000 Versailles, France"],"author":["Ramaswamy, A.","Monsuez, B.","Tapus, A."],"date":["2014"],"document_type":["Conference Paper"],"isbn":["978-1-57735-655-4"],"note":["cited By 6 \n\nTL;DR \n\nThe importance of non- functional properties in humanmachine systems are highlighted and a metamodel for modeling those properties is proposed and a case study on assistive lane keeping in automobiles is presented to demonstrate how the non-functional properties can be modeled."],"pages":["50–55"],"publisher":["AI Access Foundation"],"series":["AAAI Spring Symposium - Technical Report"],"source":["Scopus"],"title":["Modeling non-functional properties for human-machine systems"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904888679&partnerID=40&md5=8255705b33be09a555b7c43d9218c3a7"],"volume":["SS-14-02"]},"creators":{"author":[{"lastName":"Ramaswamy","firstName":"A."},{"lastName":"Monsuez","firstName":"B."},{"lastName":"Tapus","firstName":"A."}]},"sentenceCased":true},{"key":"ramosUsingTFIDFDetermine1999","type":"article","fields":{"added-at":["2011-08-09T16:33:51.000+0200"],"author":["Ramos, Juan"],"biburl":["https://www.bibsonomy.org/bibtex/2e757decbf13ecf55dee0b5eae56f9ccd/reynares.e"],"date":["1999"],"interhash":["59140639220e47ed6a9636c3ee35ac1a"],"intrahash":["e757decbf13ecf55dee0b5eae56f9ccd"],"keywords":["ontologyₗearning"],"note":["TL;DR \n\nThis paper examines the results of applying Term Frequency Inverse Document Frequency to determine what words in a corpus of documents might be more favorable to use in a query and provides evidence that this simple algorithm efficiently categorizes relevant words that can enhance query retrieval."],"timestamp":["2013-05-16T22:34:47.000+0200"],"title":["Using TF-IDF to determine word relevance in document queries"]},"creators":{"author":[{"lastName":"Ramos","firstName":"Juan"}]},"sentenceCased":true},{"key":"randObjectiveCriteriaEvaluation1971","type":"article","fields":{"added-at":["2011-03-28T19:20:19.000+0200"],"author":["Rand, W.M."],"biburl":["https://www.bibsonomy.org/bibtex/26967eb207406719bb83669ebbebb2099/dunarel"],"date":["1971"],"interhash":["1afaf0170bc705a9e49b625f67679ee2"],"intrahash":["6967eb207406719bb83669ebbebb2099"],"issn":["0162-1459"],"journaltitle":["J. Am. Stat. Assoc."],"keywords":["imported"],"number":["336"],"owner":["root"],"pages":["846–850"],"publisher":["JSTOR"],"timestamp":["2011-03-28T19:20:21.000+0200"],"title":["Objective criteria for the evaluation of clustering methods"],"volume":["66"]},"creators":{"author":[{"lastName":"Rand","firstName":"W.M."}]},"sentenceCased":true},{"key":"Rangel-Patino2019733","type":"article","fields":{"langid":["english"],"abbrev_source_title":["IEEE Trans Comput Aided Des Integr Circuits Syst"],"affiliation":["Intel Corporation, Zapopan, 45109, Mexico; Department of Electronics, Systems, and Informatics, ITESO-The Jesuit University of Guadalajara, Tlaquepaque, 45604, Mexico; Intel Corporation, Santa Clara, CA 95052, United States"],"art_number":["8355951"],"author":["Rangel-Patino, F.E.","Rayas-Sanchez, J.E.","Viveros-Wacher, A.","Chavez-Hurtado, J.L.","Vega-Ochoa, E.A.","Hakim, N."],"coden":["ITCSD"],"correspondence_address1":["Rayas-Sanchez, J.E.; Department of Electronics, Mexico; email: erayas@iteso.mx"],"date":["2019"],"document_type":["Article"],"doi":["10.1109/TCAD.2018.2834403"],"issn":["02780070"],"journaltitle":["IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst."],"keywords":["notion"],"note":["cited By 4 \n\nTL;DR \n\nA metamodeling approach based on neural networks is proposed to efficiently simulate the effects of a receiver equalizer PHY tuning settings and is evaluated by comparing with measured responses on a real server HSIO link."],"number":["4"],"pages":["733–740"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Post-silicon receiver equalization metamodeling by artificial neural networks"],"volume":["38"]},"creators":{"author":[{"lastName":"Rangel-Patino","firstName":"F.E."},{"lastName":"Rayas-Sanchez","firstName":"J.E."},{"lastName":"Viveros-Wacher","firstName":"A."},{"lastName":"Chavez-Hurtado","firstName":"J.L."},{"lastName":"Vega-Ochoa","firstName":"E.A."},{"lastName":"Hakim","firstName":"N."}]},"sentenceCased":true},{"key":"Rasiman202235","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Utrecht University, Utrecht, Netherlands"],"author":["Rasiman, R.","Dalpiaz, F.","España, S."],"correspondence_address1":["Dalpiaz, F.; Utrecht UniversityNetherlands; email: f.dalpiaz@uu.nl"],"date":["2022"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-98464-9_4"],"editor":["Gervasi V., Vogelsang A."],"isbn":["9783030984632"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"keywords":["GOAL_Trace-link-recovery","notion","TECHNIQUE_Gradient_Boosted_Decision_Trees","TECHNIQUE_RandomForests"],"note":["cited By 0"],"pages":["35–51"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["How effective is automated trace link recovery in model-driven development?"],"volume":["13216 LNCS"]},"creators":{"author":[{"lastName":"Rasiman","firstName":"R."},{"lastName":"Dalpiaz","firstName":"F."},{"lastName":"España","firstName":"S."}],"editor":[{"lastName":"Gervasi V.","firstName":"Vogelsang A."}]},"sentenceCased":true},{"key":"Rausch2021127","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["University of Illinois at Urbana-Champaign, Urbana, IL, United States; Carnegie Mellon University, Pittsburgh, PA, United States"],"author":["Rausch, M.","Sanders, W.H."],"correspondence_address1":["Rausch, M.; University of Illinois at Urbana-ChampaignUnited States; email: mjrausc2@illinois.edu"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-85172-9_7"],"editor":["Abate A., Marin A."],"isbn":["9783030851712"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 0 \n\nTL;DR \n\nEvaluated metamodels found that the metamodels are reasonably accurate and are several thousand times faster than the corresponding models they emulate, and that stacking-based meta-models are significantly more accurate than state-of-the-practice meta-models."],"pages":["127–145"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Evaluating the effectiveness of metamodeling in emulating quantitative models"],"volume":["12846 LNCS"]},"creators":{"author":[{"lastName":"Rausch","firstName":"M."},{"lastName":"Sanders","firstName":"W.H."}],"editor":[{"lastName":"Abate A.","firstName":"Marin A."}]},"sentenceCased":true},{"key":"Raychev2014Code","type":"inproceedings","fields":{"author":["Raychev, Veselin","Vechev, Martin","Yahav, Eran"],"booktitle":["35th ACM SIGPLAN Conf. Program. Lang. Des. Implement."],"date":["2014"],"doi":["10.1145/2594291.2594321"],"isbn":["978-1-4503-2784-8"],"location":["New York"],"pages":["419–428"],"publisher":["ACM"],"title":["Code completion with statistical language models"]},"creators":{"author":[{"lastName":"Raychev","firstName":"Veselin"},{"lastName":"Vechev","firstName":"Martin"},{"lastName":"Yahav","firstName":"Eran"}]},"sentenceCased":true},{"key":"raySurveyInternetThings2018","type":"article","fields":{"langid":["english"],"abstract":["Internet of Things is a platform where every day devices become smarter, every day processing becomes intelligent, and every day communication becomes informative. While the Internet of Things is still seeking its own shape, its effects have already stared in making incredible strides as a universal solution media for the connected scenario. Architecture specific study does always pave the conformation of related field. The lack of overall architectural knowledge is presently resisting the researchers to get through the scope of Internet of Things centric approaches. This literature surveys Internet of Things oriented architectures that are capable enough to improve the understanding of related tool, technology, and methodology to facilitate developer’s requirements. Directly or indirectly, the presented architectures propose to solve real-life problems by building and deployment of powerful Internet of Things notions. Further, research challenges have been investigated to incorporate the lacuna inside the current trends of architectures to motivate the academics and industries get involved into seeking the possible way outs to apt the exact power of Internet of Things. A main contribution of this survey paper is that it summarizes the current state-of-the-art of Internet of Things architectures in various domains systematically."],"author":["Ray, P.P."],"date":["2018-07"],"doi":["10.1016/j.jksuci.2016.10.003"],"issn":["13191578"],"journaltitle":["Journal of King Saud University - Computer and Information Sciences"],"note":["TL;DR \n\nThis surveying paper’s central aspect is its comprehensive summary of the government in Internet of Things designs across multiple disciplines, and research gaps have also been examined to accommodate the gaps in the present architectural trends."],"number":["3"],"pages":["291–319"],"title":["A survey on Internet of Things architectures"],"volume":["30"]},"creators":{"author":[{"lastName":"Ray","firstName":"P.P."}]},"sentenceCased":true},{"key":"raySurveyIoTCloud2016","type":"article","fields":{"langid":["english"],"abstract":["Internet of Things (IoT) envisages overall merging of several “things” while utilizing internet as the backbone of the communication system to establish a smart interaction between people and surrounding objects. Cloud, being the crucial component of IoT, provides valuable application specific services in many application domains. A number of IoT cloud providers are currently emerging into the market to leverage suitable and specific IoT based services. In spite of huge possible involvement of these IoT clouds, no standard cum comparative analytical study has been found across the literature databases. This article surveys popular IoT cloud platforms in light of solving several service domains such as application development, device management, system management, heterogeneity management, data management, tools for analysis, deployment, monitoring, visualization, and research. A comparison is presented for overall dissemination of IoT clouds according to their applicability. Further, few challenges are also described that the researchers should take on in near future. Ultimately, the goal of this article is to provide detailed knowledge about the existing IoT cloud service providers and their pros and cons in concrete form."],"author":["Ray, Partha Pratim"],"date":["2016-12"],"doi":["10.1016/j.fcij.2017.02.001"],"issn":["23147288"],"journaltitle":["Future Computing and Informatics Journal"],"number":["1-2"],"pages":["35–46"],"title":["A survey of IoT cloud platforms"],"volume":["1"]},"creators":{"author":[{"lastName":"Ray","firstName":"Partha Pratim"}]},"sentenceCased":true},{"key":"RealWorldIoT","type":"online","fields":{"title":["Real World IoT: Architectures and Projects with Eclipse IoT | EclipseCon Europe 2016"],"url":["https://www.eclipsecon.org/europe2016/session/real-world-iot-architectures-and-projects-eclipse-iot"],"urldate":["2016-09-27"]},"creators":{}},{"key":"REBY199735","type":"article","fields":{"abstract":["The classification and recognition of individual characteristics and behaviours constitute a preliminary step and is an important objective in the behavioural sciences. Current statistical methods do not always give satisfactory results. To improve performance in this area, we present a methodology based on one of the principles of artificial neural networks: the backpropagation gradient. After summarizing the theoretical construction of the model, we describe how to parameterize a neural network using the example of the individual recognition of vocalizations of four fallow deer (Dama dama). With 100% recognition and %90% prediction success, the results are very promising."],"author":["Reby, David","Lek, Sovan","Dimopoulos, Ioannis","Joachim, Jean","Lauga, Jacques","Aulagnier, Stéphane"],"date":["1997"],"issn":["0376-6357"],"journaltitle":["Behav. Processes"],"keywords":["Classification","Deer","Mammal","Modelling","Neural network","Vocalization"],"number":["1"],"pages":["35–43"],"title":["Artificial neural networks as a classification method in the behavioural sciences"],"volume":["40"]},"creators":{"author":[{"lastName":"Reby","firstName":"David"},{"lastName":"Lek","firstName":"Sovan"},{"lastName":"Dimopoulos","firstName":"Ioannis"},{"lastName":"Joachim","firstName":"Jean"},{"lastName":"Lauga","firstName":"Jacques"},{"lastName":"Aulagnier","firstName":"Stéphane"}]},"sentenceCased":true},{"key":"reedTFICFNewTerm2006","type":"inproceedings","fields":{"acmid":["1193734"],"author":["Reed, Joel W.","Jiao, Yu","Potok, Thomas E.","Klump, Brian A.","Elmore, Mark T.","Hurson, Ali R."],"booktitle":["Proc. 5th Int. Conf. Mach. Learn. Appl."],"date":["2006"],"isbn":["0-7695-2735-3"],"location":["Washington, DC, USA"],"nodoi":["10.1109/ICMLA.2006.50"],"numpages":["6"],"pages":["258–263"],"publisher":["IEEE Computer Society"],"series":["ICMLA '06"],"title":["TF-ICF: A new term weighting scheme for clustering dynamic data streams"],"url":["http://dx.doi.org/10.1109/ICMLA.2006.50"]},"creators":{"author":[{"lastName":"Reed","firstName":"Joel W."},{"lastName":"Jiao","firstName":"Yu"},{"lastName":"Potok","firstName":"Thomas E."},{"lastName":"Klump","firstName":"Brian A."},{"lastName":"Elmore","firstName":"Mark T."},{"lastName":"Hurson","firstName":"Ali R."}]},"sentenceCased":true},{"key":"ReliableDataProcessing2021","type":"article","fields":{"langid":["english"],"date":["2021"],"pages":["15"],"title":["Reliable Data Processing with Minimal Toil"]},"creators":{}},{"key":"Rendon:2011:CIE:1959666.1959695","type":"inproceedings","fields":{"acmid":["1959695"],"author":["Rendón, Eréndira","Abundez, Itzel M.","Gutierrez, Citlalih","Zagal, Sergio Díaz","Arizmendi, Alejandra","Quiroz, Elvia M.","Arzate, H. Elsa"],"booktitle":["Proc. 2011 Am. Conf. Appl. Math. 5th WSEAS Int. Conf. Comput. Eng. 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Compt Comm"],"keywords":["cluster clustering entropy evaluation f-score fscore measure measures purity"],"note":["TL;DR \n\nA comparison between external and internal indexes is shown and results obtained indicate that internal indexes are more accurate in group determining in a given clustering structure."],"number":["1"],"numpages":["8"],"pages":["27–34"],"title":["Internal versus External cluster validation indexes"],"volume":["5"]},"creators":{"author":[{"lastName":"Rendón","firstName":"Eréndira"},{"lastName":"Abundez","firstName":"Itzel"},{"lastName":"Arizmendi","firstName":"Alejandra"},{"lastName":"Quiroz","firstName":"Elvia M."}]},"sentenceCased":true},{"key":"RePEc:eee:intfor:v:14:y:1998:i:1:p:35-62","type":"article","fields":{"author":["Zhang, Guoqiang","Eddy Patuwo, B.","Y. Hu, Michael"],"date":["1998"],"journaltitle":["Int. J. Forecast."],"note":["TL;DR \n\nThe planning, budgeting, and controlling processes (PBCP) largely subsume all of the planning and controlling activities of an organization within the context of a single management control system is discussed."],"number":["1"],"pages":["35–62"],"title":["Forecasting with artificial neural networks:: The state of the art"],"volume":["14"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Guoqiang"},{"lastName":"Eddy Patuwo","firstName":"B."},{"lastName":"Y. 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Intell. - Vol. 1"],"date":["1995"],"isbn":["1-55860-363-8 978-1-55860-363-9"],"location":["San Francisco, CA, USA"],"note":["TL;DR \n\nThis paper presents a new measure of semantic similarity in an IS-A taxonomy, based on the notion of information content, which performs encouragingly well and is significantly better than the traditional edge counting approach."],"numpages":["6"],"pages":["448–453"],"publisher":["Morgan Kaufmann Publishers Inc."],"series":["IJCAI'95"],"title":["Using information content to evaluate semantic similarity in a taxonomy"],"url":["http://dl.acm.org/citation.cfm?id=1625855.1625914"]},"creators":{"author":[{"lastName":"Resnik","firstName":"Philip"}]},"sentenceCased":true},{"key":"Results1stCall","type":"online","fields":{"abstract":["10 projects were selected for co-financing under the first H2020 call for proposals on Smart System Integration."],"organization":["Digital Agenda for Europe"],"title":["Results of the 1st call on Smart System Integration under H2020"],"url":["ec.europa.eu//digital-agenda/en/news/results-1st-call-smart-system-integration-under-h2020"],"urldate":["2015-04-08"]},"creators":{},"sentenceCased":true},{"key":"ReuseAutomatedIntegration2023","type":"article","fields":{"langid":["english"],"date":["2023"],"title":["Reuse and Automated Integration of Recommenders for Modelling Languages"]},"creators":{}},{"key":"revault1995metamodeling","type":"inproceedings","fields":{"langid":["english"],"author":["Revault, Nicolas","Sahraoui, Houari A","Blain, Gilles","Perrot, Jean-François"],"booktitle":["Proc. TOOLS"],"date":["1995"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["127–139"],"title":["A metamodeling technique: The METAGEN system"],"volume":["16"]},"creators":{"author":[{"lastName":"Revault","firstName":"Nicolas"},{"lastName":"Sahraoui","firstName":"Houari A"},{"lastName":"Blain","firstName":"Gilles"},{"lastName":"Perrot","firstName":"Jean-François"}]},"sentenceCased":true},{"key":"riahisfarRoadmapSecurityChallenges2018","type":"article","fields":{"langid":["english"],"abstract":["Unquestionably, communicating entities (object, or things) in the Internet of Things (IoT) context are playing an active role in human activities, systems and processes. The high connectivity of intelligent objects and their severe constraints lead to many security challenges, which are not included in the classical formulation of security problems and solutions. The Security Shield for IoT has been identified by DARPA (Defense Advanced Research Projects Agency) as one of the four projects with a potential impact broader than the Internet itself. To help interested researchers contribute to this research area, an overview of the IoT security roadmap overview is presented in this paper based on a novel cognitive and systemic approach. The role of each component of the approach is explained, we also study its interactions with the other main components, and their impact on the overall. A case study is presented to highlight the components and interactions of the systemic and cognitive approach. Then, security questions about privacy, trust, identification, and access control are discussed. According to the novel taxonomy of the IoT framework, different research challenges are highlighted, important solutions and research activities are revealed, and interesting research directions are proposed. In addition, current standardization activities are surveyed and discussed to the ensure the security of IoT components and applications."],"author":["Riahi Sfar, Arbia","Natalizio, Enrico","Challal, Yacine","Chtourou, Zied"],"date":["2018-04"],"doi":["10.1016/j.dcan.2017.04.003"],"issn":["23528648"],"journaltitle":["Digital Communications and Networks"],"number":["2"],"pages":["118–137"],"title":["A roadmap for security challenges in the Internet of Things"],"volume":["4"]},"creators":{"author":[{"lastName":"Riahi Sfar","firstName":"Arbia"},{"lastName":"Natalizio","firstName":"Enrico"},{"lastName":"Challal","firstName":"Yacine"},{"lastName":"Chtourou","firstName":"Zied"}]},"sentenceCased":true},{"key":"Ricci2011","type":"incollection","fields":{"abstract":["Recommender Systems (RSs) are software tools and techniques providing suggestions for items to be of use to a user. In this introductory chapter we briefly discuss basic RS ideas and concepts. Our main goal is to delineate, in a coherent and structured way, the chapters included in this handbook and to help the reader navigate the extremely rich and detailed content that the handbook offers."],"author":["Ricci, Francesco","Rokach, Lior","Shapira, Bracha"],"booktitle":["Recommender systems handbook"],"date":["2011"],"doi":["10.1007/978-0-387-85820-3_1"],"editor":["Ricci, Francesco","Rokach, Lior","Shapira, Bracha","Kantor, Paul B."],"isbn":["978-0-387-85820-3"],"location":["Boston, MA"],"pages":["1–35"],"publisher":["Springer US"],"title":["Introduction to recommender systems handbook"]},"creators":{"author":[{"lastName":"Ricci","firstName":"Francesco"},{"lastName":"Rokach","firstName":"Lior"},{"lastName":"Shapira","firstName":"Bracha"}],"editor":[{"lastName":"Ricci","firstName":"Francesco"},{"lastName":"Rokach","firstName":"Lior"},{"lastName":"Shapira","firstName":"Bracha"},{"lastName":"Kantor","firstName":"Paul B."}]},"sentenceCased":true},{"key":"richardsonVendorLandscapeFractured2016","type":"article","fields":{"langid":["english"],"author":["Richardson, Clay","Rymer, John R"],"date":["2016"],"pages":["23"],"title":["Vendor Landscape: The Fractured, Fertile Terrain Of Low-Code Application Platforms"]},"creators":{"author":[{"lastName":"Richardson","firstName":"Clay"},{"lastName":"Rymer","firstName":"John R"}]}},{"key":"Ries202141","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["MODELSWARD - Proc. Int. Conf. Model-Driven Eng. Softw. Dev."],"affiliation":["University of Luxembourg, Esch-sur-Alzette, Luxembourg"],"author":["Ries, B.","Guelfi, N.","Jahić, B."],"date":["2021"],"document_type":["Conference Paper"],"editor":["Hammoudi S., Pires L.F., Soley R., Seidewitz E."],"isbn":["978-989-758-487-9"],"note":["cited By 1 \n\nTL;DR \n\nBy analysing the datasets and learning outcomes of the training of neural networks, it is discovered that many issues were related to the poor specification of the datasets’ structure."],"pages":["41–52"],"publisher":["SciTePress"],"series":["MODELSWARD 2021 - Proceedings of the 9th International Conference on Model-Driven Engineering and Software Development"],"source":["Scopus"],"title":["An MDE method for improving deep learning dataset requirements engineering using alloy and UML"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103060952&partnerID=40&md5=4945b5c1de311257ad57a8d74cfc36ba"]},"creators":{"author":[{"lastName":"Ries","firstName":"B."},{"lastName":"Guelfi","firstName":"N."},{"lastName":"Jahić","firstName":"B."}],"editor":[{"lastName":"Hammoudi S.","suffix":"Pires L.F.","firstName":"Soley R., Seidewitz E."}]},"sentenceCased":true},{"key":"Rigou2020","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Int. Conf. Innov. Res. Appl. Sci., Eng. Technol., IRASET"],"affiliation":["D'informatique et de génie, UQAR, Département de mathématiques, Rimouski, Canada"],"art_number":["9092144"],"author":["Rigou, Y.","Lamontagne, D.","Khriss, I."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/IRASET48871.2020.9092144"],"editor":["Benhala B., Mansouri K., Qbadou M., Raihani A."],"isbn":["978-1-72814-979-0"],"keywords":["GOAL_Model-Search","notion","TECHNIQUE_DNN"],"note":["cited By 2"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2020"],"source":["Scopus"],"title":["A sketch of a deep learning approach for discovering UML class diagrams from system's textual specification"]},"creators":{"author":[{"lastName":"Rigou","firstName":"Y."},{"lastName":"Lamontagne","firstName":"D."},{"lastName":"Khriss","firstName":"I."}],"editor":[{"lastName":"Benhala B.","suffix":"Mansouri K.","firstName":"Qbadou M., Raihani A."}]},"sentenceCased":true},{"key":"Rivera2020631","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - IEEE/ACM Int. Conf. Softw. Eng. Workshops, ICSEW"],"affiliation":["University of Victoria, Victoria, BC, Canada; Universidad Icesi, Cali, Valle del Cauca, Colombia"],"author":["Rivera, L.F.","Müller, H.A.","Villegas, N.M.","Tamura, G.","Jiménez, M."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3387940.3392195"],"isbn":["978-1-4503-7963-2"],"keywords":["notion"],"note":["cited By 5 \n\nTL;DR \n\nAn architectural reference model that adopts self-adaptation, control, and model-driven engineering techniques to specify the structural and behavioural aspects of DTs and enable the evolution of their internal models is proposed, and an approach for engineering IoT-intensive Digital Twin Software Systems (DTSS) is introduced using GEMINIS' capabilities to deal with uncertain conditions that might compromise the fidelity of a DT."],"pages":["631–638"],"publisher":["Association for Computing Machinery, Inc"],"series":["Proceedings - 2020 IEEE/ACM 42nd International Conference on Software Engineering Workshops, ICSEW 2020"],"source":["Scopus"],"title":["On the engineering of IoT-Intensive digital twin software systems"]},"creators":{"author":[{"lastName":"Rivera","firstName":"L.F."},{"lastName":"Müller","firstName":"H.A."},{"lastName":"Villegas","firstName":"N.M."},{"lastName":"Tamura","firstName":"G."},{"lastName":"Jiménez","firstName":"M."}]},"sentenceCased":true},{"key":"RiveraDV09","type":"article","fields":{"langid":["english"],"author":["Rivera, José Eduardo","Durán, Francisco","Vallecillo, Antonio"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2009"],"doi":["10.1177/0037549709341635"],"journaltitle":["Simul,"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper explores the use of Maude as a formal notation for describing models, metamodels, and their dynamic behavior, making models amenable to formal analysis, reasoning, and simulation."],"number":["11-12"],"pages":["778–792"],"timestamp":["Thu, 14 Oct 2021 08:52:54 +0200"],"title":["Formal specification and analysis of domain specific models using maude"],"volume":["85"]},"creators":{"author":[{"lastName":"Rivera","firstName":"José Eduardo"},{"lastName":"Durán","firstName":"Francisco"},{"lastName":"Vallecillo","firstName":"Antonio"}]},"sentenceCased":true},{"key":"RiveraRLB09","type":"inproceedings","fields":{"langid":["english"],"author":["Rivera, José Eduardo","Ruiz-González, Daniel","López-Romero, Fernando","Bautista, José María"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["XIV Jorn. Ing. Softw. Bases Datos JISBD 2009 San Sebastián Spain Sept. 8-11 2009"],"date":["2009"],"editor":["Vallecillo, Antonio","Sagardui, Goiuria"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nAn arm attachment for an arm of a backhoe that attaches directly to a shovel to permit large objects to be picked up."],"pages":["158–161"],"timestamp":["Fri, 18 Sep 2009 13:16:59 +0200"],"title":["Wires* : A tool for orchestrating model transformations"]},"creators":{"author":[{"lastName":"Rivera","firstName":"José Eduardo"},{"lastName":"Ruiz-González","firstName":"Daniel"},{"lastName":"López-Romero","firstName":"Fernando"},{"lastName":"Bautista","firstName":"José María"}],"editor":[{"lastName":"Vallecillo","firstName":"Antonio"},{"lastName":"Sagardui","firstName":"Goiuria"}]},"sentenceCased":true},{"key":"Rivolli2021471","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Computing Department, Universidade Tecnológica Federal Do Paraná, Av. Alberto Carazzai, 1640, Cornélio Procópio, Paraná, 86300-000, Brazil; Department of Computer Science, University of Brasília, Campus Darcy Ribeiro, Asa Norte, Brasília, 70910-900, Brazil; Aeronautics Institute of Technology, Praça Marechal Eduardo Gomes, 50, São José dos Campos, São Paulo, 12228-900, Brazil; Institute of Mathematical and Computer Sciences, University of São Paulo, Av. Trabalhador São-carlense, 400, São Carlos, São Paulo, 13560-970, Brazil"],"author":["Rivolli, A.","Garcia, L.P.F.","Lorena, A.C.","family=Carvalho, given=A.C.P.L.F., prefix=de, useprefix=true"],"correspondence_address1":["Rivolli, A.; Computing Department, Av. Alberto Carazzai, 1640, Brazil; email: rivolli@utfpr.edu.br"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-85030-2_39"],"editor":["Rojas I., Joya G., Catala A."],"isbn":["9783030850296"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 1"],"pages":["471–483"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["A study of the correlation of metafeatures used for metalearning"],"volume":["12861 LNCS"]},"creators":{"author":[{"lastName":"Rivolli","firstName":"A."},{"lastName":"Garcia","firstName":"L.P.F."},{"lastName":"Lorena","firstName":"A.C."},{"lastName":"Carvalho","firstName":"A.C.P.L.F.","prefix":"de","useprefix":true}],"editor":[{"lastName":"Rojas I.","suffix":"Joya G.","firstName":"Catala A."}]},"sentenceCased":true},{"key":"robertsonProbabilisticRelevanceFramework2009","type":"article","fields":{"acmid":["1704810"],"address":["Hanover, MA, USA"],"author":["Robertson, Stephen","Zaragoza, Hugo"],"date":["2009-04"],"issn":["1554-0669"],"issue_date":["April 2009"],"journaltitle":["Found. Trends Inf. Retr."],"nodoi":["10.1561/1500000019"],"note":["TL;DR \n\nThis work presents the PRF from a conceptual point of view, describing the probabilistic modelling assumptions behind the framework and the different ranking algorithms that result from its application: the binary independence model, relevance feedback models, BM25 and BM25F."],"number":["4"],"numpages":["57"],"pages":["333–389"],"publisher":["Now Publishers Inc."],"title":["The probabilistic relevance framework: BM25 and beyond"],"url":["http://dx.doi.org/10.1561/1500000019"],"volume":["3"]},"creators":{"author":[{"lastName":"Robertson","firstName":"Stephen"},{"lastName":"Zaragoza","firstName":"Hugo"}]},"sentenceCased":true},{"key":"Robillard:2013:AAP:2498733.2498776","type":"article","fields":{"acmid":["2498776"],"address":["Piscataway, NJ, USA"],"author":["Robillard, Martin P.","Bodden, Eric","Kawrykow, David","Mezini, Mira","Ratchford, Tristan"],"date":["2013-05"],"issn":["0098-5589"],"issue_date":["May 2013"],"journaltitle":["IEEE Trans. Softw. Eng."],"keywords":["API evolution","API property","API usage pattern","Association rules","Context","data mining","interface","Itemsets","pattern mining","Programming","programming rules","protocols","Protocols","software engineering","specifications"],"nodoi":["10.1109/TSE.2012.63"],"number":["5"],"numpages":["25"],"pages":["613–637"],"publisher":["IEEE Press"],"title":["Automated API property inference techniques"],"url":["http://dx.doi.org/10.1109/TSE.2012.63"],"volume":["39"]},"creators":{"author":[{"lastName":"Robillard","firstName":"Martin P."},{"lastName":"Bodden","firstName":"Eric"},{"lastName":"Kawrykow","firstName":"David"},{"lastName":"Mezini","firstName":"Mira"},{"lastName":"Ratchford","firstName":"Tristan"}]},"sentenceCased":true},{"key":"robillardIntroductionRecommendationSystems2014","type":"incollection","fields":{"author":["Robillard, Martin P.","Walker, Robert J."],"booktitle":["Recommendation Systems in Software Engineering"],"date":["2014"],"note":["TL;DR \n\nThis introduction presents an overview of the issues and considerations involved in creating, evaluating, and using RSSEs, and presents a general outlook on the current state of research and development in the field of recommendation systems for highly technical domains."],"pages":["1–11"],"publisher":["Springer"],"title":["An introduction to recommendation systems in software engineering"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-45135-5_1"],"urldate":["2017-03-08"]},"creators":{"author":[{"lastName":"Robillard","firstName":"Martin P."},{"lastName":"Walker","firstName":"Robert J."}]},"sentenceCased":true},{"key":"robillardRecommendationSystemsSoftware2010","type":"article","fields":{"author":["Robillard, Martin","Walker, Robert","Zimmermann, Thomas"],"date":["2010"],"ids":["5235134"],"journaltitle":["IEEE Softw."],"keywords":["bug reports","coding tools and techniques","design tools and techniques","development tools","information space","programming environments","recommendation systems","recommender systems","software construction tools","software development","software engineering","software tool","software tools","time seeking information","value-producing task"],"note":["TL;DR \n\nThe authors provide an overview of recommendation systems for software engineering: what they are, what they can do for developers, and what they might do in the future."],"number":["4"],"pages":["80–86"],"title":["Recommendation systems for software engineering"],"url":["http://ieeexplore.ieee.org/abstract/document/5235134/"],"urldate":["2017-06-08"],"volume":["27"]},"creators":{"author":[{"lastName":"Robillard","firstName":"Martin"},{"lastName":"Walker","firstName":"Robert"},{"lastName":"Zimmermann","firstName":"Thomas"}]},"sentenceCased":true},{"key":"robillardRecommendationSystemsSoftware2014","type":"book","fields":{"langid":["english"],"date":["2014"],"doi":["10.1007/978-3-642-45135-5"],"editor":["Robillard, Martin P.","Maalej, Walid","Walker, Robert J.","Zimmermann, Thomas"],"ids":["robillard_recommendation_2014"],"isbn":["978-3-642-45134-8 978-3-642-45135-5"],"location":["Berlin, Heidelberg"],"note":["DOI: 10.1007/978-3-642-45135-5 \n\nTL;DR \n\nThis introduction presents an overview of the issues and considerations involved in creating, evaluating, and using RSSEs, and presents a general outlook on the current state of research and development in the field of recommendation systems for highly technical domains."],"publisher":["Springer Berlin Heidelberg"],"title":["Recommendation Systems in Software Engineering"]},"creators":{"editor":[{"lastName":"Robillard","firstName":"Martin P."},{"lastName":"Maalej","firstName":"Walid"},{"lastName":"Walker","firstName":"Robert J."},{"lastName":"Zimmermann","firstName":"Thomas"}]}},{"key":"robles-encisoTaskOffloadingComputing2022","type":"incollection","fields":{"langid":["english"],"author":["Robles-Enciso, Alberto","Skarmeta, Antonio F."],"booktitle":["Internet of Things"],"date":["2022"],"doi":["10.1007/978-3-031-20936-9_7"],"editor":["González-Vidal, Aurora","Mohamed Abdelgawad, Ahmed","Sabir, Essaid","Ziegler, Sébastien","Ladid, Latif"],"isbn":["978-3-031-20935-2 978-3-031-20936-9"],"location":["Cham"],"pages":["82–95"],"publisher":["Springer International Publishing"],"title":["Task Offloading in Computing Continuum Using Collaborative Reinforcement Learning"],"volume":["13533"]},"creators":{"author":[{"lastName":"Robles-Enciso","firstName":"Alberto"},{"lastName":"Skarmeta","firstName":"Antonio F."}],"editor":[{"lastName":"González-Vidal","firstName":"Aurora"},{"lastName":"Mohamed Abdelgawad","firstName":"Ahmed"},{"lastName":"Sabir","firstName":"Essaid"},{"lastName":"Ziegler","firstName":"Sébastien"},{"lastName":"Ladid","firstName":"Latif"}]}},{"key":"robles2012towards","type":"article","fields":{"langid":["english"],"author":["Robles, Karina","Fraga, Anabel","Morato, Jorge","Llorens, Juan"],"date":["2012"],"journaltitle":["Inf. Software Technol."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["1"],"pages":["72–86"],"title":["Towards an ontology-based retrieval of UML class diagrams"],"volume":["54"]},"creators":{"author":[{"lastName":"Robles","firstName":"Karina"},{"lastName":"Fraga","firstName":"Anabel"},{"lastName":"Morato","firstName":"Jorge"},{"lastName":"Llorens","firstName":"Juan"}]},"sentenceCased":true},{"key":"roblesExtensiveDatasetUML2017","type":"inproceedings","fields":{"langid":["english"],"author":["Robles, Gregorio","Ho-Quang, Truong","Hebig, Regina","Chaudron, Michel R.V.","Fernandez, Miguel Angel"],"booktitle":["2017 IEEEACM 14th Int. Conf. Min. Softw. Repos. MSR"],"date":["2017-05"],"doi":["10.1109/MSR.2017.48"],"eventtitle":["2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR)"],"ids":["robles2017extensive"],"isbn":["978-1-5386-1544-7"],"keywords":["/unread","⛔ No INSPIRE recid found"],"location":["Buenos Aires, Argentina"],"note":["TL;DR \n\nThis work systematically mined over 12 million GitHub projects to find UML files in them, and presents a semi-automated approach to collect UML stored in images, .xmi, and .uml files."],"pages":["519–522"],"publisher":["IEEE"],"title":["An Extensive Dataset of UML Models in GitHub"]},"creators":{"author":[{"lastName":"Robles","firstName":"Gregorio"},{"lastName":"Ho-Quang","firstName":"Truong"},{"lastName":"Hebig","firstName":"Regina"},{"lastName":"Chaudron","firstName":"Michel R.V."},{"lastName":"Fernandez","firstName":"Miguel Angel"}]}},{"key":"RoboticsAutonomousSystems","type":"online","fields":{"title":["Robotics and autonomous systems: Apply for innovation funding - News stories - GOV.UK"],"url":["https://www.gov.uk/government/news/robotics-and-autonomous-systems-apply-for-innovation-funding"],"urldate":["2016-08-26"]},"creators":{},"sentenceCased":true},{"key":"RoboticsProgrammingLaboratory","type":"online","fields":{"title":["Robotics Programming Laboratory"],"url":["http://se.inf.ethz.ch/courses/2013b_fall/rpl/#lectures"],"urldate":["2016-01-12"]},"creators":{}},{"key":"roccoMemoRecRecommenderSystem2022","type":"article","fields":{"author":["Rocco, Juri Di","Ruscio, Davide Di","Sipio, Claudio Di","Nguyen, Phuong T.","Pierantonio, Alfonso"],"date":["2022"],"doi":["10.48550/arXiv.2203.06068"],"eprint":["2203.06068"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"note":["TL;DR \n\nThe results demonstrate that MemoRec is capable of suggesting relevant items given a partial metamodel and supporting modelers in their task, and the quality of the work is assessed with respect to different metrics, i.e., success rate, precision, and recall."],"title":["MemoRec: A Recommender System for Assisting Modelers in Specifying Metamodels"],"volume":["abs/2203.06068"]},"creators":{"author":[{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Sipio","firstName":"Claudio Di"},{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Pierantonio","firstName":"Alfonso"}]}},{"key":"roccoResilienceSiriusEditors2018","type":"inproceedings","fields":{"author":["Rocco, Juri Di","Ruscio, Davide Di","Narayanankutty, Hrishikesh","Pierantonio, Alfonso"],"booktitle":["Proc. MODELS 2018 Workshop ModComp MRT OCL FlexMDE EXE COMMitMDE MDETools GEMOC MORSE MDE4IoT MDEbug MoDeVVa ME MULTI HuFaMo AMMoRe PAINS Co-Located ACMIEEE 21st Int. Conf. Model Driven Eng. Lang. Syst. MODELS 2018 Cph. Den. Oct. 14 2018"],"date":["2018"],"editor":["Hebig, Regina","Berger, Thorsten"],"note":["TL;DR \n\nA study is presented that analyzes the impact of meta-model changes over visual editors based on the Sir-ius framework to provide designers with the possibility to perform an early assessment of the early assessment of the editor consistency needed to restore the editor consistency."],"pages":["620–630"],"publisher":["CEUR-WS.org"],"series":["CEUR Workshop Proceedings"],"title":["Resilience in Sirius Editors: Understanding the Impact of Metamodel Changes"],"url":["http://ceur-ws.org/Vol-2245/me_paper_6.pdf"],"volume":["2245"]},"creators":{"author":[{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Narayanankutty","firstName":"Hrishikesh"},{"lastName":"Pierantonio","firstName":"Alfonso"}],"editor":[{"lastName":"Hebig","firstName":"Regina"},{"lastName":"Berger","firstName":"Thorsten"}]}},{"key":"roccoTopFilterApproachRecommend2020","type":"inproceedings","fields":{"author":["Rocco, Juri Di","Ruscio, Davide Di","Sipio, Claudio Di","Nguyen, Phuong T.","Rubei, Riccardo"],"booktitle":["ESEM 20 ACM IEEE Int. Symp. Empir. Softw. Eng. Meas. Bari Italy Oct. 5-7 2020"],"date":["2020"],"doi":["10.1145/3382494.3410690"],"editor":["Baldassarre, Maria Teresa","Lanubile, Filippo","Kalinowski, Marcos","Sarro, Federica"],"ids":["roccoTopFilterApproachRecommend2020a,roccoTopFilterApproachRecommend2020b"],"note":["cited By 7 \n\ncited By 7"],"pages":["21:1–21:11"],"publisher":["ACM"],"title":["TopFilter: An Approach to Recommend Relevant GitHub Topics"]},"creators":{"author":[{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Sipio","firstName":"Claudio Di"},{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Rubei","firstName":"Riccardo"}],"editor":[{"lastName":"Baldassarre","firstName":"Maria Teresa"},{"lastName":"Lanubile","firstName":"Filippo"},{"lastName":"Kalinowski","firstName":"Marcos"},{"lastName":"Sarro","firstName":"Federica"}]}},{"key":"rocklovDataScienceMachine2021","type":"article","fields":{"langid":["english"],"author":["Rocklöv, Joacim","Gayle, Albert A"],"date":["2021-01-23"],"doi":["10.1093/ije/dyaa111"],"issn":["0300-5771, 1464-3685"],"journaltitle":["Int. J. Epidemiol."],"keywords":["LOGSEQ"],"number":["6"],"pages":["2096–2096"],"shorttitle":["Data Science and Machine Learning"],"title":["Data Science and Machine Learning: Mathematical and Statistical Methods"],"volume":["49"]},"creators":{"author":[{"lastName":"Rocklöv","firstName":"Joacim"},{"lastName":"Gayle","firstName":"Albert A"}]}},{"key":"ROCKRobustClustering1999","type":"inproceedings","fields":{"acmid":["847264"],"booktitle":["Proc. 15th Int. Conf. Data Eng."],"date":["1999"],"isbn":["0-7695-0071-4"],"key":["!!"],"location":["Washington, DC, USA"],"note":["TL;DR \n\nThis work develops a robust hierarchical clustering algorithm, ROCK, that employs links and not distances when merging clusters, and shows that ROCK not only generates better quality clusters than traditional algorithms, but also exhibits good scalability properties."],"pages":["512-"],"publisher":["IEEE Computer Society"],"series":["ICDE '99"],"title":["ROCK: A robust clustering algorithm for categorical attributes"],"url":["http://dl.acm.org/citation.cfm?id=846218.847264"]},"creators":{},"sentenceCased":true},{"key":"rodriguez-graciaCollaborativeTestbedWeb2014","type":"article","fields":{"langid":["english"],"author":["Rodríguez-Gracia, D.","Criado, J.","Iribarne, L.","Padilla, N."],"date":["2014-12"],"doi":["10.1016/j.chb.2014.11.096"],"issn":["07475632"],"journaltitle":["Comput. Hum. Behav."],"title":["A collaborative testbed web tool for learning model transformation in software engineering education"]},"creators":{"author":[{"lastName":"Rodríguez-Gracia","firstName":"D."},{"lastName":"Criado","firstName":"J."},{"lastName":"Iribarne","firstName":"L."},{"lastName":"Padilla","firstName":"N."}]},"sentenceCased":true},{"key":"rodriguezMetamodelDependenciesExecutable2011","type":"incollection","fields":{"author":["Rodríguez, Carlos","Sánchez, Mario","Villalobos, Jorge"],"booktitle":["Objects, Models, Components, Patterns"],"date":["2011"],"doi":["10.1007/978-3-642-21952-8_8"],"editor":["Bishop, Judith","Vallecillo, Antonio"],"isbn":["978-3-642-21951-1 978-3-642-21952-8"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nThe goal of this paper is to discuss two alternative ways to establish dependencies, and illustrate their usage, benefits, and drawbacks in a concrete example."],"pages":["83–98"],"publisher":["Springer Berlin Heidelberg"],"title":["Metamodel Dependencies for Executable Models"],"volume":["6705"]},"creators":{"author":[{"lastName":"Rodríguez","firstName":"Carlos"},{"lastName":"Sánchez","firstName":"Mario"},{"lastName":"Villalobos","firstName":"Jorge"}],"editor":[{"lastName":"Bishop","firstName":"Judith"},{"lastName":"Vallecillo","firstName":"Antonio"}]}},{"key":"rohrModeldrivenDevelopmentSelfmanaging2006","type":"article","fields":{"author":["Rohr, Matthias","Boskovic, Marko","Giesecke, Simon","Hasselbring, Wilhelm"],"date":["2006"],"title":["Model-driven development of self-managing software systems"],"url":["http://eprints.uni-kiel.de/14544/1/MODELS2006.pdf"],"urldate":["2016-09-21"]},"creators":{"author":[{"lastName":"Rohr","firstName":"Matthias"},{"lastName":"Boskovic","firstName":"Marko"},{"lastName":"Giesecke","firstName":"Simon"},{"lastName":"Hasselbring","firstName":"Wilhelm"}]},"sentenceCased":true},{"key":"Rojas:1996:NNS:235222","type":"book","fields":{"author":["Rojas, Raúl"],"date":["1996"],"isbn":["3-540-60505-3"],"location":["Berlin, Heidelberg"],"publisher":["Springer-Verlag"],"title":["Neural networks: A systematic introduction"]},"creators":{"author":[{"lastName":"Rojas","firstName":"Raúl"}]},"sentenceCased":true},{"key":"Rokach2005","type":"incollection","fields":{"booktitle":["Data mining and knowledge discovery handbook"],"date":["2005"],"doi":["10.1007/0-387-25465-X₁5"],"editor":["Maimon, Oded","Rokach, Lior"],"isbn":["978-0-387-25465-4"],"location":["Boston, MA"],"pages":["321–352"],"publisher":["Springer US"],"title":["Clustering methods"]},"creators":{"editor":[{"lastName":"Maimon","firstName":"Oded"},{"lastName":"Rokach","firstName":"Lior"}]},"sentenceCased":true},{"key":"Rokon2020SourceFinderFM","type":"inproceedings","fields":{"author":["Rokon, Md Omar Faruk","Islam, Risul","Darki, Ahmad","Papalexakis, Evangelos E.","Faloutsos, Michalis"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/conf/raid/RokonIDPF20.bib"],"booktitle":["23rd Int. Symp. Res. Attacks Intrusions Def. RAID 2020 San Sebastian Spain Oct. 14-15 2020"],"date":["2020"],"editor":["Egele, Manuel","Bilge, Leyla"],"pages":["149–163"],"publisher":["USENIX Association"],"timestamp":["Thu, 17 Jun 2021 16:04:48 +0200"],"title":["SourceFinder: Finding malware source-code from publicly available repositories in GitHub"],"url":["https://www.usenix.org/conference/raid2020/presentation/omar"]},"creators":{"author":[{"lastName":"Rokon","firstName":"Md Omar Faruk"},{"lastName":"Islam","firstName":"Risul"},{"lastName":"Darki","firstName":"Ahmad"},{"lastName":"Papalexakis","firstName":"Evangelos E."},{"lastName":"Faloutsos","firstName":"Michalis"}],"editor":[{"lastName":"Egele","firstName":"Manuel"},{"lastName":"Bilge","firstName":"Leyla"}]},"sentenceCased":true},{"key":"Roldán2020","type":"article","fields":{"abstract":["The Internet of Things (IoT) is growing globally at a fast pace: people now find themselves surrounded by a variety of IoT devices such as smartphones and wearables in their everyday lives. Additionally, smart environments, such as smart healthcare systems, smart industries and smart cities, benefit from sensors and actuators interconnected through the IoT. However, the increase in IoT devices has brought with it the challenge of promptly detecting and combating the cybersecurity attacks and threats that target them, including malware, privacy breaches and denial of service attacks, among others. To tackle this challenge, this paper proposes an intelligent architecture that integrates Complex Event Processing (CEP) technology and the Machine Learning (ML) paradigm in order to detect different types of IoT security attacks in real time. In particular, such an architecture is capable of easily managing event patterns whose conditions depend on values obtained by ML algorithms. Additionally, a model-driven graphical tool for security attack pattern definition and automatic code generation is provided, hiding all the complexity derived from implementation details from domain experts. The proposed architecture has been applied in the case of a healthcare IoT network to validate its ability to detect attacks made by malicious devices. The results obtained demonstrate that this architecture satisfactorily fulfils its objectives. © 2020 Elsevier Ltd"],"art_number":["113251"],"author":["Roldán, J.","Boubeta-Puig, J.","Luis Martínez, J.","Ortiz, G."],"coden":["ESAPE"],"date":["2020"],"document_type":["Article"],"doi":["10.1016/j.eswa.2020.113251"],"issn":["09574174"],"journaltitle":["Expert Syst. Appl."],"note":["cited By 38"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Integrating complex event processing and machine learning: An intelligent architecture for detecting IoT security attacks"],"volume":["149"]},"creators":{"author":[{"lastName":"Roldán","firstName":"J."},{"lastName":"Boubeta-Puig","firstName":"J."},{"lastName":"Luis Martínez","firstName":"J."},{"lastName":"Ortiz","firstName":"G."}]},"sentenceCased":true},{"key":"romanBigDataPipelines2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["Organisations possess and continuously generate huge amounts of static and stream data, especially with the proliferation of Internet of Things technologies. Collected but unused data, i.e., Dark Data, mean loss in value creation potential. In this respect, the concept of Computing Continuum extends the traditional more centralised Cloud Computing paradigm with Fog and Edge Computing in order to ensure low latency pre-processing and filtering close to the data sources. However, there are still major challenges to be addressed, in particular related to management of various phases of Big Data processing on the Computing Continuum. In this paper, we set forth an ecosystem for Big Data pipelines in the Computing Continuum and introduce five relevant real-life example use cases in the context of the proposed ecosystem."],"author":["Roman, Dumitru","Nikolov, Nikolay","Soylu, Ahmet","Elvesaeter, Brian","Song, Hui","Prodan, Radu","Kimovski, Dragi","Marrella, Andrea","Leotta, Francesco","Matskin, Mihhail","Ledakis, Giannis","Theodosiou, Konstantinos","Simonet-Boulogne, Anthony","Perales, Fernando","Kharlamov, Evgeny","Ulisses, Alexandre","Solberg, Arnor","Ceccarelli, Raffaele"],"booktitle":["2021 IEEE Symp. Comput. Commun. ISCC"],"date":["2021-09-05"],"doi":["10.1109/ISCC53001.2021.9631410"],"eventtitle":["2021 IEEE Symposium on Computers and Communications (ISCC)"],"isbn":["978-1-66542-744-9"],"keywords":["LOGSEQ"],"location":["Athens, Greece"],"note":["TL;DR \n\nThis paper sets forth an ecosystem for Big Data pipelines in the Computing Continuum and introduces five relevant real-life example use cases in the context of the proposed ecosystem."],"pages":["1–4"],"publisher":["IEEE"],"shorttitle":["Big Data Pipelines on the Computing Continuum"],"title":["Big Data Pipelines on the Computing Continuum: Ecosystem and Use Cases Overview"]},"creators":{"author":[{"lastName":"Roman","firstName":"Dumitru"},{"lastName":"Nikolov","firstName":"Nikolay"},{"lastName":"Soylu","firstName":"Ahmet"},{"lastName":"Elvesaeter","firstName":"Brian"},{"lastName":"Song","firstName":"Hui"},{"lastName":"Prodan","firstName":"Radu"},{"lastName":"Kimovski","firstName":"Dragi"},{"lastName":"Marrella","firstName":"Andrea"},{"lastName":"Leotta","firstName":"Francesco"},{"lastName":"Matskin","firstName":"Mihhail"},{"lastName":"Ledakis","firstName":"Giannis"},{"lastName":"Theodosiou","firstName":"Konstantinos"},{"lastName":"Simonet-Boulogne","firstName":"Anthony"},{"lastName":"Perales","firstName":"Fernando"},{"lastName":"Kharlamov","firstName":"Evgeny"},{"lastName":"Ulisses","firstName":"Alexandre"},{"lastName":"Solberg","firstName":"Arnor"},{"lastName":"Ceccarelli","firstName":"Raffaele"}]}},{"key":"ronankiPromptSmellsOmen2024","type":"online","fields":{"abstract":["Recent Generative Artificial Intelligence (GenAI) trends focus on various applications, including creating stories, illustrations, poems, articles, computer code, music compositions, and videos. Extrinsic hallucinations are a critical limitation of such GenAI, which can lead to significant challenges in achieving and maintaining the trustworthiness of GenAI. In this paper, we propose two new concepts that we believe will aid the research community in addressing limitations associated with the application of GenAI models. First, we propose a definition for the \"desirability\" of GenAI outputs and three factors which are observed to influence it. Second, drawing inspiration from Martin Fowler's code smells, we propose the concept of \"prompt smells\" and the adverse effects they are observed to have on the desirability of GenAI outputs. We expect our work will contribute to the ongoing conversation about the desirability of GenAI outputs and help advance the field in a meaningful way."],"author":["Ronanki, Krishna","Cabrero-Daniel, Beatriz","Berger, Christian"],"date":["2024-01-23"],"eprint":["2401.12611"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Machine Learning","Computer Science - Software Engineering"],"note":["Comment: Accepted at CAIN 2024: Poster Track"],"pubstate":["preprint"],"shorttitle":["Prompt Smells"],"title":["Prompt Smells: An Omen for Undesirable Generative AI Outputs"],"url":["http://arxiv.org/abs/2401.12611"],"urldate":["2024-02-23"]},"creators":{"author":[{"lastName":"Ronanki","firstName":"Krishna"},{"lastName":"Cabrero-Daniel","firstName":"Beatriz"},{"lastName":"Berger","firstName":"Christian"}]}},{"key":"rosa-bilbaoCEPEDALoCoEventdrivenArchitecture2023","type":"article","fields":{"author":["Rosa-Bilbao, Jesús","Boubeta-Puig, Juan","Rutle, Adrian"],"date":["2023-05-01"],"doi":["10.1016/j.iot.2023.100802"],"journaltitle":["Internet of Things"],"keywords":["LOGSEQ"],"pages":["100802"],"shorttitle":["CEPEDALoCo"],"title":["CEPEDALoCo: An event-driven architecture for integrating Complex Event Processing and blockchain through low-code"],"volume":["22"]},"creators":{"author":[{"lastName":"Rosa-Bilbao","firstName":"Jesús"},{"lastName":"Boubeta-Puig","firstName":"Juan"},{"lastName":"Rutle","firstName":"Adrian"}]},"sentenceCased":true},{"key":"rosaSelfmanagementDistributedSystems2013","type":"incollection","fields":{"author":["Rosa, Liliana","Rodrigues, Luís","Lopes, Antónia"],"booktitle":["Software Engineering for Self-Adaptive Systems II"],"date":["2013"],"note":["TL;DR \n\nThis chapter presents an approach for the self-management of systems built from customizable components based on high-level goal policies, in response to changes in the execution context, the necessary system adaptations are automatically selected and deployed."],"pages":["162–190"],"publisher":["Springer"],"title":["Self-management of Distributed Systems Using High-Level Goal Policies"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-35813-5_7"],"urldate":["2016-09-21"]},"creators":{"author":[{"lastName":"Rosa","firstName":"Liliana"},{"lastName":"Rodrigues","firstName":"Luís"},{"lastName":"Lopes","firstName":"Antónia"}]},"sentenceCased":true},{"key":"roseComparisonModelMigration2010","type":"incollection","fields":{"author":["Rose, Louis M.","Herrmannsdoerfer, Markus","Williams, James R.","Kolovos, Dimitrios S.","Garcés, Kelly","Paige, Richard F.","Polack, Fiona AC"],"booktitle":["Model Driven Engineering Languages and Systems"],"date":["2010"],"note":["TL;DR \n\nA representative sample of migration tools - AML, COPE, Ecore2Ecore and Epsilon Flock - are compared using common migration examples to support users in selecting the most appropriate tool for their situation."],"pages":["61–75"],"publisher":["Springer"],"title":["A comparison of model migration tools"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-16145-2_5"],"urldate":["2015-03-20"]},"creators":{"author":[{"lastName":"Rose","firstName":"Louis M."},{"lastName":"Herrmannsdoerfer","firstName":"Markus"},{"lastName":"Williams","firstName":"James R."},{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"Garcés","firstName":"Kelly"},{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Polack","firstName":"Fiona AC"}]},"sentenceCased":true},{"key":"roseGenericityModelManagement2011","type":"article","fields":{"author":["Rose, Louis","Guerra, Esther","Lara, Juan","Etien, Anne","Kolovos, Dimitris","Paige, Richard"],"date":["2011"],"doi":["10.1007/s10270-011-0203-2"],"journaltitle":["Softw. Syst. Model."],"number":["1"],"pages":["201–219"],"title":["Genericity for model management operations"],"volume":["12"]},"creators":{"author":[{"lastName":"Rose","firstName":"Louis"},{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Lara","firstName":"Juan"},{"lastName":"Etien","firstName":"Anne"},{"lastName":"Kolovos","firstName":"Dimitris"},{"lastName":"Paige","firstName":"Richard"}]},"sentenceCased":true},{"key":"roseInternetThingsOverview2015","type":"article","fields":{"author":["Rose, Karen","Eldridge, Scott","Chapin, Lyman"],"date":["2015"],"journaltitle":["Internet Soc. ISOC"],"shorttitle":["The internet of things"],"title":["The internet of things: An overview"],"url":["http://www.internetsociety.org/sites/default/files/ISOC-IoT-Overview-20151014_0.pdf"],"urldate":["2016-05-30"]},"creators":{"author":[{"lastName":"Rose","firstName":"Karen"},{"lastName":"Eldridge","firstName":"Scott"},{"lastName":"Chapin","firstName":"Lyman"}]},"sentenceCased":true},{"key":"RoseKPPP14","type":"article","fields":{"langid":["english"],"author":["Rose, Louis M.","Kolovos, Dimitrios S.","Paige, Richard F.","Polack, Fiona A. C.","Poulding, Simon M."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2014"],"doi":["10.1007/S10270-012-0296-2"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["2"],"pages":["735–755"],"timestamp":["Fri, 18 Sep 2020 11:19:36 +0200"],"title":["Epsilon flock: A model migration language"],"volume":["13"]},"creators":{"author":[{"lastName":"Rose","firstName":"Louis M."},{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"Paige","firstName":"Richard F."},{"lastName":"Polack","firstName":"Fiona A. C."},{"lastName":"Poulding","firstName":"Simon M."}]},"sentenceCased":true},{"key":"Rossi:2012:DPU:2367861.2367871","type":"inproceedings","fields":{"acmid":["2367871"],"author":["Rossi, Ryan A.","Gleich, David F."],"booktitle":["Proc. 9th Int. Conf. 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Areas Commun."],"number":["9"],"pages":["1810–1821"],"title":["10 Lessons from 10 Years of Measuring and Modeling the Internet's Autonomous Systems"],"volume":["29"]},"creators":{"author":[{"lastName":"Roughan","firstName":"Matthew"},{"lastName":"Willinger","firstName":"Walter"},{"lastName":"Maennel","firstName":"Olaf"},{"lastName":"Perouli","firstName":"Debbie"},{"lastName":"Bush","firstName":"Randy"}]}},{"key":"rousseeuwSilhouettesGraphicalAid1987","type":"article","fields":{"abstract":["A new graphical display is proposed for partitioning techniques. Each cluster is represented by a so-called silhouette, which is based on the comparison of its tightness and separation. This silhouette shows which objects lie well within their cluster, and which ones are merely somewhere in between clusters. The entire clustering is displayed by combining the silhouettes into a single plot, allowing an appreciation of the relative quality of the clusters and an overview of the data configuration. The average silhouette width provides an evaluation of clustering validity, and might be used to select an ‘appropriate’ number of clusters."],"author":["Rousseeuw, Peter J."],"date":["1987"],"issn":["0377-0427"],"journaltitle":["J. Comput. Appl. Math."],"keywords":["classification","cluster analysis","clustering validity","Graphical display"],"nodoi":["https://doi.org/10.1016/0377-0427(87)90125-7"],"pages":["53–65"],"title":["Silhouettes: A graphical aid to the interpretation and validation of cluster analysis"],"url":["http://www.sciencedirect.com/science/article/pii/0377042787901257"],"volume":["20"]},"creators":{"author":[{"lastName":"Rousseeuw","firstName":"Peter J."}]},"sentenceCased":true},{"key":"roy-hubaraDesignMethodsNew2020","type":"article","fields":{"langid":["english"],"author":["Roy-Hubara, Noa","Sturm, Arnon"],"date":["2020-03"],"doi":["10.1007/s10270-019-00739-8"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"keywords":["DONE","TYPHONML"],"note":["TL;DR \n\nThe study found that current database design methods do not address non-functional requirements; tend to refer to a preselected database; and are lacking in their evaluation."],"number":["2"],"pages":["297–312"],"shorttitle":["Design methods for the new database era"],"title":["Design methods for the new database era: A systematic literature review"],"volume":["19"]},"creators":{"author":[{"lastName":"Roy-Hubara","firstName":"Noa"},{"lastName":"Sturm","firstName":"Arnon"}]},"sentenceCased":true},{"key":"roy-hubaraMethodDatabaseModel2019","type":"incollection","fields":{"langid":["english"],"author":["Roy-Hubara, Noa","Shoval, Peretz","Sturm, Arnon"],"booktitle":["Enterprise, Business-Process and Information Systems Modeling"],"date":["2019"],"doi":["10.1007/978-3-030-20618-5_18"],"editor":["Reinhartz-Berger, Iris","Zdravkovic, Jelena","Gulden, Jens","Schmidt, Rainer"],"isbn":["978-3-030-20617-8 978-3-030-20618-5"],"keywords":["TYPHONML"],"location":["Cham"],"note":["TL;DR \n\nThis paper proposes a structured method for database model selection that considers a variety of factors, including data-related requirements, functional requirements and non-functional requirements, and proposes the most appropriate database models for that application."],"pages":["261–275"],"publisher":["Springer International Publishing"],"title":["A Method for Database Model Selection"],"volume":["352"]},"creators":{"author":[{"lastName":"Roy-Hubara","firstName":"Noa"},{"lastName":"Shoval","firstName":"Peretz"},{"lastName":"Sturm","firstName":"Arnon"}],"editor":[{"lastName":"Reinhartz-Berger","firstName":"Iris"},{"lastName":"Zdravkovic","firstName":"Jelena"},{"lastName":"Gulden","firstName":"Jens"},{"lastName":"Schmidt","firstName":"Rainer"}]}},{"key":"roy-hubaraModelingGraphDatabase2017","type":"article","fields":{"author":["Roy-Hubara, Noa","Rokach, Lior","Shapira, Bracha","Shoval, Peretz"],"date":["2017-11"],"doi":["10.1109/MITP.2017.4241458"],"issn":["1520-9202"],"journaltitle":["IT Prof."],"note":["TL;DR \n\nThe authors present a new method for creating a graph database schema (GDBS) based on an entity-relationship diagram (ERD) of the application domain, which is mapped to a GDBS in a two-step process."],"number":["6"],"pages":["34–43"],"title":["Modeling Graph Database Schema"],"volume":["19"]},"creators":{"author":[{"lastName":"Roy-Hubara","firstName":"Noa"},{"lastName":"Rokach","firstName":"Lior"},{"lastName":"Shapira","firstName":"Bracha"},{"lastName":"Shoval","firstName":"Peretz"}]}},{"key":"roy-hubaraQuestDatabaseSelection","type":"article","fields":{"langid":["english"],"abstract":["New types of database have emerged over the last decade, aimed at answering new requirements in the Big Data era. The new databases, in additional to the Relational model, may fit to specific types of applications. Therefore, new challenges have also emerged, including the issue of which database model to select for a given application, and how to design the database based on the selected model. To the best of our knowledge, these two challenges have not been addressed by any systematic method. In this research we plan to devise a structured method for database model selection and design based on variety of factors, including data-related requirements, functional requirements, and non-functional requirements. Based on these requirements the method will recommend which database models are the most appropriate for that application and will suggest a design for the recommended models."],"author":["Roy-Hubara, Noa"],"keywords":["DONE","TYPHONML"],"note":["TL;DR \n\nThis research plans to devise a structured method for database model selection and design based on variety of factors, including data-related requirements, functional requirements, and non-functional requirements, which will recommend which database models are the most appropriate for that application and will suggest a design for the recommended models."],"pages":["9"],"title":["The Quest for a Database Selection and Design Method"]},"creators":{"author":[{"lastName":"Roy-Hubara","firstName":"Noa"}]}},{"key":"Rubei:ASE:2019","type":"inproceedings","fields":{"author":["Rubei, Riccardo","Di Sipio, Claudio","Nguyen, Phuong T.","Di Rocco, Juri","Di Ruscio"],"booktitle":["34th IEEEACM Int. Conf. Autom. Softw. Eng. ASE 2019 San Diego Calif. USA 2019"],"title":["Recommeding highly relevant StackOverflow posts with boosted multi-facet queries - manuscript under review"]},"creators":{"author":[{"lastName":"Rubei","firstName":"Riccardo"},{"lastName":"Di Sipio","firstName":"Claudio"},{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Di Rocco","firstName":"Juri"},{"literal":"Di Ruscio"}]},"sentenceCased":true},{"key":"Rubei2021477","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Companion Proc. - Int. Conf. Model-Driven Eng. Lang. Syst., MODELS-C"],"abstract":["The growing adoption of model-driven engineering raised the need for techniques and tools supporting modeling artifacts' reusability. In this respect, several model repositories have been proposed by academia and industry so that modelers can exploit advanced searching facilities to identify reusable artifacts that might fit the particular problem at hand. Despite the enduring quest for the right ways to search and retrieve modeling artifacts, satisfactory solutions are still missing. This paper investigates the adoption of general-purpose indexing and search features provided by Apache Lucene to support the classification and clustering of metamodel repositories. In particular, we show that Apache Lucene allows us to get accurate results whenever the mandatory requirements of more appropriate techniques, such as hierarchical clustering or neural networks, cannot be met. © 2021 IEEE."],"affiliation":["Università Degli Studi Dell'Aquila, L'Aquila, 67100, Italy"],"author":["Rubei, R.","Rocco, J.D.","Ruscio, D.D.","Nguyen, P.T.","Pierantonio, A."],"booktitle":["ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion MODELS 2021 Companion Fukuoka Jpn. Oct. 10-15 2021"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/MODELS-C53483.2021.00074"],"ids":["rubeiLightweightApproachAutomated2021,rubeiLightweightApproachAutomated2021a,rubeiLightweightApproachAutomated2021b,rubeiLightweightApproachAutomated2021c"],"isbn":["978-1-66542-484-4"],"keywords":["Apache Lucene","Automated classification","Automated clustering","Classification (of information)","Classification and clustering","Clusterings","GOAL_Model-Classification","Meta model","Model repositories","Model-driven Engineering","notion","Reusability","TEACHNIQUE_INDEXING","Techniques and tools","Tool supporting"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 1 \n\ncited By 1 \n\ncited By 1 \n\nTL;DR \n\nThis paper investigates the adoption of general-purpose indexing and search features provided by Apache Lucene to support the classification and clustering of metamodel repositories and shows thatapache Lucene allows us to get accurate results whenever the mandatory requirements of more appropriate techniques, such as hierarchical clustering or neural networks cannot be met."],"pages":["477–482"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Companion Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021"],"source":["Scopus"],"title":["A lightweight approach for the automated classification and clustering of metamodels"]},"creators":{"author":[{"lastName":"Rubei","firstName":"R."},{"lastName":"Rocco","firstName":"J.D."},{"lastName":"Ruscio","firstName":"D.D."},{"lastName":"Nguyen","firstName":"P.T."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"rubeiPostFinderMiningStack2020","type":"article","fields":{"langid":["english"],"abstract":["Context During the development of complex software systems, programmers look for external resources to understand better how to use speci c APIs and to get advice related to their current tasks. Stack Over ow provides developers with a broader insight into API usage as well as useful code examples. Given the circumstances, tools and techniques for mining Stack Over ow are highly desirable."],"author":["Rubei, Riccardo","Di Sipio, Claudio","Nguyen, Phuong T.","Di Rocco, Juri","Di Ruscio, Davide"],"date":["2020-11"],"doi":["10.1016/j.infsof.2020.106367"],"ids":["rubeiPostFinderMiningStack2020a,rubeiPostFinderMiningStack2020b"],"issn":["09505849"],"journaltitle":["Information and Software Technology"],"keywords":["Indexing posts","Mining Stack Overflow posts"],"note":["cited By 13"],"pages":["106367"],"shorttitle":["PostFinder"],"title":["PostFinder: Mining Stack Overflow posts to support software developers"],"volume":["127"]},"creators":{"author":[{"lastName":"Rubei","firstName":"Riccardo"},{"lastName":"Di Sipio","firstName":"Claudio"},{"lastName":"Nguyen","firstName":"Phuong T."},{"lastName":"Di Rocco","firstName":"Juri"},{"lastName":"Di Ruscio","firstName":"Davide"}]},"sentenceCased":true},{"key":"rubeiProvidingUpgradePlans2022","type":"article","fields":{"author":["Rubei, R.","Di Ruscio, D.","Di Sipio, C.","Di Rocco, J.","Nguyen, Phuong"],"date":["2022"],"doi":["10.1007/s10489-021-02911-4"],"eprint":["2201.08201"],"eprinttype":["arxiv"],"ids":["rubeiProvidingUpgradePlans2022b,rubeiProvidingUpgradePlans2022c,rubeiProvidingUpgradePlans2022d,rubeiProvidingUpgradePlans2022e"],"journaltitle":["Appl. IN℡LIGENCE"],"keywords":["API migration","Data mining","Error prones","F measure","Libraries","Migration path","Prediction performance","Project developers","Recommendation systems","Recommender systems","Ripple effects","Software project","Third parties"],"note":["cited By 1 \n\ncited By 1 \n\ncited By 2"],"publisher":["Springer"],"title":["Providing upgrade plans for third-party libraries: A recommender system using migration graphs"]},"creators":{"author":[{"lastName":"Rubei","firstName":"R."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Di Sipio","firstName":"C."},{"lastName":"Di Rocco","firstName":"J."},{"lastName":"Nguyen","firstName":"Phuong"}]},"sentenceCased":true},{"key":"rubinDeclarativeApproachModel2008","type":"inproceedings","fields":{"author":["Rubin, Julia","Chechik, Marsha","Easterbrook, Steve M."],"booktitle":["Proc. 2008 Int. Workshop Models Softw. Eng."],"date":["2008"],"note":["TL;DR \n\nThis paper proposes a declarative approach for model composition, which augments and strengthens existing structural and heuristic approaches, and defines a proof-of-concept prototype implementation of theDeclarative model composition framework using the Alloy Analyzer."],"pages":["7–14"],"publisher":["ACM"],"title":["Declarative approach for model composition"],"url":["http://dl.acm.org/citation.cfm?id=1370734"],"urldate":["2015-09-24"]},"creators":{"author":[{"lastName":"Rubin","firstName":"Julia"},{"lastName":"Chechik","firstName":"Marsha"},{"lastName":"Easterbrook","firstName":"Steve M."}]},"sentenceCased":true},{"key":"ruscioACMStudentResearch2017","type":"article","fields":{"author":["Ruscio, D.D.","Greenyer, J."],"date":["2017"],"journaltitle":["CEUR Workshop Proc."],"note":["cited By 0 \n\ncited By 0"],"pages":["547–548"],"title":["ACM student research competition at MoDELS 2017"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041444549&partnerID=40&md5=7fa947db7e86266ce08af757982fb3e6"],"volume":["2019"]},"creators":{"author":[{"lastName":"Ruscio","firstName":"D.D."},{"lastName":"Greenyer","firstName":"J."}]},"sentenceCased":true},{"key":"ruscioExtremeModellingXM2014","type":"article","fields":{"author":["Ruscio, Davide Di","Pierantonio, Alfonso","family=Lara, given=Juan, prefix=de, useprefix=false"],"date":["2014"],"doi":["10.5381/jot.2014.13.3.e1"],"ids":["ruscioExtremeModellingXM2014a"],"journaltitle":["J. Object Technol."],"number":["3"],"title":["Extreme Modelling (XM) 2012 Special Section"],"volume":["13"]},"creators":{"author":[{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Pierantonio","firstName":"Alfonso"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":false}]}},{"key":"ruscioInternationalWorkshopModel2012","type":"article","fields":{"author":["Ruscio, Davide Di","Kolovos, Dimitris S."],"date":["2012"],"doi":["10.5381/jot.2012.11.3.e1"],"ids":["ruscioInternationalWorkshopModel2012a"],"journaltitle":["J. Object Technol."],"number":["3"],"title":["International Workshop on Model Comparison"],"volume":["11"]},"creators":{"author":[{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Kolovos","firstName":"Dimitris S."}]}},{"key":"ruscioLeveragingPrivacyProfiles2022","type":"article","fields":{"author":["Ruscio, Davide Di","Inverardi, Paola","Migliarini, Patrizio","Nguyen, Phuong T."],"date":["2022"],"doi":["10.48550/arXiv.2204.00011"],"eprint":["2204.00011"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"note":["TL;DR \n\nThis work focuses on characterizing/collecting users’ privacy preferences and contributes a step in this direction through an empirical study on an existing dataset collected from the fitness domain, and implements a recommender system to provide users with suitable recommendations related to privacy choices."],"title":["Leveraging Privacy Profiles to Empower Users in the Digital Society"],"volume":["abs/2204.00011"]},"creators":{"author":[{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Inverardi","firstName":"Paola"},{"lastName":"Migliarini","firstName":"Patrizio"},{"lastName":"Nguyen","firstName":"Phuong T."}]}},{"key":"ruscioLowCode20212ndWorkshop2021","type":"inproceedings","fields":{"langid":["english"],"abstract":["Cloud-based low-code development platforms such as Google's AppSheet, Microsoft's PowerApps, OutSystems and Mendix have become increasingly popular over the last few years, owing to an increasing demand for bespoke, cost-efficient and reliable data-intensive (e.g., back-office) software solutions. Low-code development platforms are model-driven at their heart. Hence, closer interaction and cross-pollination are highly beneficial for the low-code and model-driven engineering communities. The Low-Code workshop aims to bring together vendors and users of low-code development platforms with model-driven engineering researchers and practitioners and explore opportunities for technology and experience transfer and collaboration between them. © 2021 IEEE."],"author":["Ruscio, D.D.","Kolovos, D.","De Lara, J.","Tisi, M.","Wimmer, M."],"booktitle":["Companion Proc. - 24th Int. Conf. Model-Driven Eng. Lang. Syst. MODELS-C 2021"],"date":["2021"],"doi":["10.1109/MODELS-C53483.2021.00014"],"ids":["ruscioLowCode20212ndWorkshop2021a,ruscioLowCode20212ndWorkshop2021b,ruscioLowCode20212ndWorkshop2021c,ruscioLowCode2021Mboxnd2021"],"isbn":["978-1-66542-484-4"],"keywords":["Cloud-based","Code development","Cost-efficient","Data intensive","Development platform","Google+","Low-code","MicroSoft","Model-driven Engineering","No-code"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0 \n\ncited By 1"],"pages":["45–46"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["LowCode 2021: 2ndWorkshop on Modeling in Low-Code Development Platforms"]},"creators":{"author":[{"lastName":"Ruscio","firstName":"D.D."},{"lastName":"Kolovos","firstName":"D."},{"lastName":"De Lara","firstName":"J."},{"lastName":"Tisi","firstName":"M."},{"lastName":"Wimmer","firstName":"M."}]}},{"key":"ruscioPostproceedingsSeventhSeminar2015","type":"book","fields":{"date":["2015"],"editor":["Ruscio, Davide 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Di"},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":false},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"ruscioProceedingsWorkshopScalability2013","type":"book","fields":{"date":["2013"],"editor":["Ruscio, Davide Di","Kolovos, Dimitris S.","Matragkas, Nicholas"],"ids":["ruscioProceedingsWorkshopScalability2013a"],"isbn":["978-1-4503-2165-5"],"publisher":["ACM"],"title":["Proceedings of the Workshop on Scalability in Model Driven Engineering, Budapest, Hungary, June 17, 2013"],"url":["http://dl.acm.org/citation.cfm?id=2487766"]},"creators":{"editor":[{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Kolovos","firstName":"Dimitris S."},{"lastName":"Matragkas","firstName":"Nicholas"}]}},{"key":"ruscioTheoryPracticeModel2014","type":"book","fields":{"date":["2014"],"doi":["10.1007/978-3-319-08789-4"],"editor":["Ruscio, Davide Di","Varró, Dániel"],"ids":["ruscioTheoryPracticeModel2014a"],"isbn":["978-3-319-08788-7"],"publisher":["Springer"],"series":["Lecture Notes in Computer Science"],"title":["Theory and Practice of Model Transformations - 7th International Conference, ICMT@STAF 2014, York, UK, July 21-22, 2014. Proceedings"],"volume":["8568"]},"creators":{"editor":[{"lastName":"Ruscio","firstName":"Davide Di"},{"lastName":"Varró","firstName":"Dániel"}]}},{"key":"Růžička2021105","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["CEUR Workshop Proc."],"affiliation":["Czech Technical University, Prague, Czech Republic; Charles University, Prague, Czech Republic; Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic"],"author":["Růžička, J.","Koza, J.","Tumpach, J.","Pitra, Z.","Holeňa, M."],"date":["2021"],"document_type":["Conference Paper"],"editor":["Krempl G., Lemaire V., Holzinger A., Hammer B., Kottke D."],"issn":["16130073"],"note":["cited By 0"],"pages":["105–120"],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"source":["Scopus"],"title":["Combining gaussian processes with neural networks for active learning in optimization"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124088084&partnerID=40&md5=489c84189b9e10b74826f211a50decf3"],"volume":["3079"]},"creators":{"author":[{"lastName":"Růžička","firstName":"J."},{"lastName":"Koza","firstName":"J."},{"lastName":"Tumpach","firstName":"J."},{"lastName":"Pitra","firstName":"Z."},{"lastName":"Holeňa","firstName":"M."}],"editor":[{"lastName":"Krempl G.","suffix":"Lemaire V.","firstName":"Holzinger A., Hammer B., Kottke D."}]},"sentenceCased":true},{"key":"rymerForresterWaveLowCode2019","type":"article","fields":{"langid":["english"],"author":["Rymer, John R","Koplowitz, Rob"],"date":["2019"],"keywords":["lowcode"],"pages":["17"],"title":["The Forrester Wave™: Low-Code Development Platforms For AD&D Professionals, Q1 2019"]},"creators":{"author":[{"lastName":"Rymer","firstName":"John R"},{"lastName":"Koplowitz","firstName":"Rob"}]}},{"key":"sahayAnalyzingBusinessProcess2023","type":"article","fields":{"langid":["english"],"abstract":["Low-code development platforms (LCDPs) aim to simplify software systems' development by providing easy-to-use graphical interfaces and drag-and-drop facilities. The system behaviors are defined through available data handling and workflow mechanisms enabling the specification of business processes from users that do not have strong programming skills. However, the number of LCDPs has grown significantly over the last few years. Consequently, it is not easy for inexpert users to understand their differences, especially in terms of provided modeling constructs. In this article, we analyze and compare eight low-code development platforms by focusing on their capabilities for specifying business processes. The analysis exploits business process modeling and notation (BPMN) as a reference modeling language. Thus, the core elements of BPMN are leveraged to analyze the workflow mechanisms provided by each of the analyzed LCDP. The article explains different types of process flows and data handling means of the different LCDPs aiming to give potential users objective elements that can be used to make educated decisions when selecting LCDPs."],"author":["Sahay, Apurvanand","Di Ruscio, Davide","Iovino, Ludovico","Pierantonio, Alfonso"],"date":["2023"],"doi":["10.1002/spe.3177"],"issn":["1097-024X"],"journaltitle":["Softw. Pract. Exp."],"keywords":["Business Process","business process management","Business process management","Business process modeling","Code development","Data handling","Development platform","Enterprise resource management","LOGSEQ","Low-code development platform","low-code development platforms","model-driven engineering","Model-driven Engineering","Modeling languages","Process management","Process management capabilities","Work-flows"],"note":["cited By 0"],"number":["4"],"pages":["1036–1060"],"publisher":["John Wiley and Sons Ltd"],"title":["Analyzing business process management capabilities of low-code development platforms"],"volume":["8168 LNCS"]},"creators":{"author":[{"lastName":"Sahay","firstName":"Apurvanand"},{"lastName":"Di Ruscio","firstName":"Davide"},{"lastName":"Iovino","firstName":"Ludovico"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"sahaySupportingUnderstandingComparison2020","type":"article","fields":{"abstract":["Low-code development platforms (LCDPs) are easy to use visual environments that are being increasingly introduced and promoted by major IT players to permit citizen developers to build their software systems even if they lack a programming background. Understanding and evaluating the LCDP to be employed for the particular problem at hand are difficult tasks mainly because decision-makers have to choose among hundreds of heterogeneous platforms, which are difficult to evaluate without dedicated support. Thus, a detailed classification is needed to elaborate on the existing low-code platforms and to help users find out the most appropriate platforms based on their requirements.In this paper, a technical survey of different LCDPs is presented by relying on a proposed conceptual comparative framework. In particular, by analyzing eight representative LCDPs, a corresponding set of features have been identified to distil the functionalities and the services that each considered platform can support. The final aim is facilitating the understanding and the comparison of the low-code platforms that can best accommodate given user requirements."],"author":["Sahay, A.","Indamutsa, A.","Di Ruscio, D.","Pierantonio, A."],"date":["2020"],"doi":["10.1109/SEAA51224.2020.00036"],"ids":["sahaySupportingUnderstandingComparison2020a,sahaySupportingUnderstandingComparison2020b"],"journaltitle":["46th Euromicro Conf. Softw. Eng. Adv. Appl. SEAA 2020 Portoroz Slov. August 26-28 2020"],"note":["cited By 50 \n\ncited By 50 \n\nTL;DR \n\nA technical survey of different LCDPs is presented by relying on a proposed conceptual comparative framework and a corresponding set of features have been identified to distil the functionalities and the services that each considered platform can support."],"pages":["171–178"],"title":["Supporting the understanding and comparison of low-code development platforms"]},"creators":{"author":[{"lastName":"Sahay","firstName":"A."},{"lastName":"Indamutsa","firstName":"A."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"sahayUnderstandingRoleModel2020","type":"inproceedings","fields":{"author":["Sahay, A.","Di Ruscio, D.","Pierantonio, A."],"booktitle":["Proc. - 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. MODELS-C 2020 - Companion Proc."],"date":["2020"],"doi":["10.1145/3417990.3420197"],"ids":["sahayUnderstandingRoleModel2020a,sahayUnderstandingRoleModel2020b"],"isbn":["978-1-4503-8135-2"],"keywords":["Low-code development platform","Model driven engineering","Model transformation","Model transformation composition"],"note":["cited By 3 \n\ncited By 3 \n\nTL;DR \n\nThe adoption of concepts and tools related to the composition of model transformations to support the specification of complex workflows in LCDPs are proposed."],"pages":["431–435"],"publisher":["Association for Computing Machinery, Inc"],"title":["Understanding the role of model transformation compositions in low-code development platforms"]},"creators":{"author":[{"lastName":"Sahay","firstName":"A."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Pierantonio","firstName":"A."}]},"sentenceCased":true},{"key":"sahooOntologybasedFeatureEngineering2022","type":"article","fields":{"langid":["english"],"abstract":["Biomedical ontologies are widely used to harmonize heterogeneous data and integrate large volumes of clinical data from multiple sources. This study analyzed the utility of ontologies beyond their traditional roles, that is, in addressing a challenging and currently underserved field of feature engineering in machine learning workflows. Machine learning workflows are being increasingly used to analyze medical records with heterogeneous phenotypic, genotypic, and related medical terms to improve patient care. We performed a retrospective study using neuropathology reports from the German Neuropathology Reference Center for Epilepsy Surgery at Erlangen, Germany. This cohort included 312 patients who underwent epilepsy surgery and were labeled with one or more diagnoses, including dual pathology, hippocampal sclerosis, malformation of cortical dysplasia, tumor, encephalitis, and gliosis. We modeled the diagnosis terms together with their microscopy, immunohistochemistry, anatomy, etiologies, and imaging findings using the description logic-based Web Ontology Language (OWL) in the Epilepsy and Seizure Ontology (EpSO). Three tree-based machine learning models were used to classify the neuropathology reports into one or more diagnosis classes with and without ontology-based feature engineering. We used five-fold cross validation to avoid overfitting with a fixed number of repetitions while leaving out one subset of data for testing, and we used recall, balanced accuracy, and hamming loss as performance metrics for the multi-label classification task. The epilepsy ontology-based feature engineering approach improved the performance of all the three learning models with an improvement of 35.7%, 54.5%, and 33.3% in logistics regression, random forest, and gradient tree boosting models respectively. The run time performance of all three models improved significantly with ontology-based feature engineering with gradient tree boosting model showing a 93.8% reduction in the time required for training and testing of the model. Although, all three models showed an overall improved performance across the three-performance metrics using ontology-based feature engineering, the rate of improvement was not consistent across all input features. To analyze this variation in performance, we computed feature importance scores and found that microscopy had the highest importance score across the three models, followed by imaging, immunohistochemistry, and anatomy in a decreasing order of importance scores. This study showed that ontologies have an important role in feature engineering to make heterogeneous clinical data accessible to machine learning models and also improve the performance of machine learning models in multilabel multiclass classification tasks."],"author":["Sahoo, Satya S.","Kobow, Katja","Zhang, Jianzhe","Buchhalter, Jeffrey","Dayyani, Mojtaba","Upadhyaya, Dipak P.","Prantzalos, Katrina","Bhattacharjee, Meenakshi","Blumcke, Ingmar","Wiebe, Samuel","Lhatoo, Samden D."],"date":["2022-11-12"],"doi":["10.1038/s41598-022-23101-3"],"issn":["2045-2322"],"issue":["1"],"journaltitle":["Sci Rep"],"keywords":["Epilepsy","Information technology","Scientific data","Software"],"number":["1"],"pages":["19430"],"publisher":["Nature Publishing Group"],"title":["Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records"],"volume":["12"]},"creators":{"author":[{"lastName":"Sahoo","firstName":"Satya S."},{"lastName":"Kobow","firstName":"Katja"},{"lastName":"Zhang","firstName":"Jianzhe"},{"lastName":"Buchhalter","firstName":"Jeffrey"},{"lastName":"Dayyani","firstName":"Mojtaba"},{"lastName":"Upadhyaya","firstName":"Dipak P."},{"lastName":"Prantzalos","firstName":"Katrina"},{"lastName":"Bhattacharjee","firstName":"Meenakshi"},{"lastName":"Blumcke","firstName":"Ingmar"},{"lastName":"Wiebe","firstName":"Samuel"},{"lastName":"Lhatoo","firstName":"Samden D."}]},"sentenceCased":true},{"key":"saidComparativeRecommenderSystem2014","type":"inproceedings","fields":{"langid":["english"],"author":["Said, Alan","Bellogín, Alejandro"],"booktitle":["Proc. 8th ACM Conf. Recomm. Syst. - RecSys 14"],"date":["2014"],"doi":["10.1145/2645710.2645746"],"eventtitle":["The 8th ACM Conference"],"isbn":["978-1-4503-2668-1"],"location":["Foster City, Silicon Valley, California, USA"],"note":["TL;DR \n\nThis work compares common recommendation algorithms as implemented in three popular recommendation frameworks and shows the necessity of clear guidelines when reporting evaluation of recommender systems to ensure reproducibility and comparison of results."],"pages":["129–136"],"publisher":["ACM Press"],"shorttitle":["Comparative recommender system evaluation"],"title":["Comparative recommender system evaluation: Benchmarking recommendation frameworks"]},"creators":{"author":[{"lastName":"Said","firstName":"Alan"},{"lastName":"Bellogín","firstName":"Alejandro"}]},"sentenceCased":true},{"key":"Saied2015Could","type":"inproceedings","fields":{"author":["Saied, Mohamed Aymen","Abdeen, Hani","Benomar, Omar","Sahraoui, Houari"],"booktitle":["23rd Int. Conf. Program Comprehension"],"date":["2015"],"location":["Piscataway"],"nodoi":["10.1109/ICPC.2015.16"],"pages":["71–81"],"publisher":["IEEE"],"title":["Could we infer unordered API usage patterns only using the library source code?"]},"creators":{"author":[{"lastName":"Saied","firstName":"Mohamed Aymen"},{"lastName":"Abdeen","firstName":"Hani"},{"lastName":"Benomar","firstName":"Omar"},{"lastName":"Sahraoui","firstName":"Houari"}]},"sentenceCased":true},{"key":"SAIED2018164","type":"article","fields":{"abstract":["Modern software systems are increasingly dependent on third-party libraries. It is widely recognized that using mature and well-tested third-party libraries can improve developers’ productivity, reduce time-to-market, and produce more reliable software. Today’s open-source repositories provide a wide range of libraries that can be freely downloaded and used. However, as software libraries are documented separately but intended to be used together, developers are unlikely to fully take advantage of these reuse opportunities. In this paper, we present a novel approach to automatically identify third-party library usage patterns, i.e., collections of libraries that are commonly used together by developers. Our approach employs a hierarchical clustering technique to group together software libraries based on external client usage. To evaluate our approach, we mined a large set of over 6000 popular libraries from Maven Central Repository and investigated their usage by over 38,000 client systems from the Github repository. Our experiments show that our technique is able to detect the majority (77%) of highly %consistent and cohesive library usage patterns across a considerable %number %of client systems."],"author":["Saied, Mohamed Aymen","Ouni, Ali","Sahraoui, Houari","Kula, Raula Gaikovina","Inoue, Katsuro","Lo, David"],"date":["2018"],"issn":["0164-1212"],"journaltitle":["J. Syst. Softw."],"keywords":["Clustering","Software libraries","Software reuse","Usage patterns"],"nodoi":["https://doi.org/10.1016/j.jss.2018.08.032"],"pages":["164–179"],"title":["Improving reusability of software libraries through usage pattern mining"],"url":["http://www.sciencedirect.com/science/article/pii/S0164121218301699"],"volume":["145"]},"creators":{"author":[{"lastName":"Saied","firstName":"Mohamed Aymen"},{"lastName":"Ouni","firstName":"Ali"},{"lastName":"Sahraoui","firstName":"Houari"},{"lastName":"Kula","firstName":"Raula Gaikovina"},{"lastName":"Inoue","firstName":"Katsuro"},{"lastName":"Lo","firstName":"David"}]},"sentenceCased":true},{"key":"saiedMiningMultilevelAPI2015","type":"inproceedings","fields":{"author":["Saied, M. A.","Benomar, O.","Abdeen, H.","Sahraoui, H."],"booktitle":["22nd Int. Conf. Softw. Anal. Evol. Reengineering"],"date":["2015"],"issn":["1534-5351"],"keywords":["API Documentation","API Usage","application program interfaces","application programming interface","Clustering algorithms","Context","data mining","Documentation","Graphical user interfaces","Java","Layout","MLUP","multilevel API usage pattern mining","Security","Software Clustering","software libraries","Usage Pattern"],"location":["Piscataway"],"pages":["23–32"],"publisher":["IEEE"],"title":["Mining multi-level API usage patterns"]},"creators":{"author":[{"lastName":"Saied","firstName":"M. A."},{"lastName":"Benomar","firstName":"O."},{"lastName":"Abdeen","firstName":"H."},{"lastName":"Sahraoui","firstName":"H."}]},"sentenceCased":true},{"key":"Saini2019714","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - ACM/IEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion, MODELS-C"],"affiliation":["Dept. of ECE, McGill University, Montréal, QC, Canada; School of Computer Science, McGill University, Montréal, QC, Canada"],"art_number":["8904688"],"author":["Saini, R.","Mussbacher, G.","Guo, J.L.C.","Kienzle, J."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/MODELS-C.2019.00108"],"editor":["Burgueno L., Burgueno L., Voss S., Chaudron M., Kienzle J., Volter M., Gerard S., Zahedi M., Bousse E., Rensink A., Polack F., Engels G., Kappel G., Pretschner A."],"ids":["sainiTeachingModellingLiteracy2019"],"isbn":["978-1-72815-125-0"],"keywords":["GOAL_Model-Teaching","notion","TECHNIQUE_DependencyGraph"],"note":["cited By 10 \n\nTL;DR \n\nThis paper proposes a framework called ModBud (a modelling buddy) to educate novice modellers about the art of abstraction and uses natural language processing and machine learning to create modelling bots with the aim of improving the modelling skills of novicemodellers and assisting other practitioners, too."],"pages":["714–719"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2019"],"source":["Scopus"],"title":["Teaching modelling literacy: An artificial intelligence approach"]},"creators":{"author":[{"lastName":"Saini","firstName":"R."},{"lastName":"Mussbacher","firstName":"G."},{"lastName":"Guo","firstName":"J.L.C."},{"lastName":"Kienzle","firstName":"J."}],"editor":[{"lastName":"Burgueno L.","suffix":"Burgueno L.","firstName":"Voss S., Chaudron M., Kienzle J., Volter M., Gerard S., Zahedi M., Bousse E., Rensink A., Polack F., Engels G., Kappel G., Pretschner A."}]},"sentenceCased":true},{"key":"Saini20221015","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Softw. Syst. Model."],"affiliation":["Department of Electrical and Computer Engineering, McGill University, Montréal, Canada; School of Computer Science, McGill University, Montréal, Canada"],"author":["Saini, R.","Mussbacher, G.","Guo, J.L.C.","Kienzle, J."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"correspondence_address1":["Saini, R.; Department of Electrical and Computer Engineering, Canada; email: rijul.saini@mail.mcgill.ca"],"date":["2022"],"document_type":["Article"],"doi":["10.1007/s10270-021-00942-6"],"ids":["SainiMGK22"],"issn":["16191366"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found","GOAL_Model-Assistance","notion","TECHNIQUE_Gradient_Boosted_Decision_Trees","TECHNIQUE_RandomForests"],"note":["cited By 0 \n\nTL;DR \n\nThis paper proposes an algorithm to discover alternative configurations during bot-modeller interactions and uses this algorithm to find alternative configurations and then present these configurations in the form of suggestions to modellers."],"number":["3"],"pages":["1015–1045"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"timestamp":["Fri, 29 Apr 2022 09:14:31 +0200"],"title":["Automated, interactive, and traceable domain modelling empowered by artificial intelligence"],"volume":["21"]},"creators":{"author":[{"lastName":"Saini","firstName":"R."},{"lastName":"Mussbacher","firstName":"G."},{"lastName":"Guo","firstName":"J.L.C."},{"lastName":"Kienzle","firstName":"J."}]},"sentenceCased":true},{"key":"sainiArtificialIntelligenceEmpowered2020","type":"inproceedings","fields":{"langid":["english"],"author":["Saini, Rijul"],"booktitle":["Proc. 23rd ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion Proc."],"date":["2020-10-16"],"doi":["10.1145/3417990.3419486"],"eventtitle":["MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems"],"isbn":["978-1-4503-8135-2"],"keywords":["GOAL_Model-Assistance","notion","TECHNIQUE_Clustering","TECHNIQUE_NLP"],"location":["Virtual Event Canada"],"pages":["1–6"],"publisher":["ACM"],"title":["Artificial intelligence empowered domain modelling bot"]},"creators":{"author":[{"lastName":"Saini","firstName":"Rijul"}]},"sentenceCased":true},{"key":"salehieSelfadaptiveSoftwareLandscape2009","type":"article","fields":{"author":["Salehie, Mazeiar","Tahvildari, Ladan"],"date":["2009"],"journaltitle":["ACM Trans. Auton. Adapt. Syst. TAAS"],"note":["TL;DR \n\nA taxonomy of research in self-adaptive software is presented, based on concerns of adaptation, that is, how, what, when and where, towards providing a unified view of this emerging area."],"number":["2"],"pages":["14"],"shorttitle":["Self-adaptive software"],"title":["Self-adaptive software: Landscape and research challenges"],"url":["http://dl.acm.org/citation.cfm?id=1516538"],"urldate":["2016-01-12"],"volume":["4"]},"creators":{"author":[{"lastName":"Salehie","firstName":"Mazeiar"},{"lastName":"Tahvildari","firstName":"Ladan"}]},"sentenceCased":true},{"key":"saleiroAequitasBiasFairness2019","type":"online","fields":{"abstract":["Recent work has raised concerns on the risk of unintended bias in AI systems being used nowadays that can affect individuals unfairly based on race, gender or religion, among other possible characteristics. While a lot of bias metrics and fairness definitions have been proposed in recent years, there is no consensus on which metric/definition should be used and there are very few available resources to operationalize them. Therefore, despite recent awareness, auditing for bias and fairness when developing and deploying AI systems is not yet a standard practice. We present Aequitas, an open source bias and fairness audit toolkit that is an intuitive and easy to use addition to the machine learning workflow, enabling users to seamlessly test models for several bias and fairness metrics in relation to multiple population sub-groups. Aequitas facilitates informed and equitable decisions around developing and deploying algorithmic decision making systems for both data scientists, machine learning researchers and policymakers."],"author":["Saleiro, Pedro","Kuester, Benedict","Hinkson, Loren","London, Jesse","Stevens, Abby","Anisfeld, Ari","Rodolfa, Kit T.","Ghani, Rayid"],"date":["2019-04-29"],"eprint":["1811.05577"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Computers and Society","Computer Science - Machine Learning"],"note":["Comment: Aequitas website: http://dsapp.uchicago.edu/aequitas"],"pubstate":["preprint"],"shorttitle":["Aequitas"],"title":["Aequitas: A Bias and Fairness Audit Toolkit"],"url":["http://arxiv.org/abs/1811.05577"],"urldate":["2023-03-09"]},"creators":{"author":[{"lastName":"Saleiro","firstName":"Pedro"},{"lastName":"Kuester","firstName":"Benedict"},{"lastName":"Hinkson","firstName":"Loren"},{"lastName":"London","firstName":"Jesse"},{"lastName":"Stevens","firstName":"Abby"},{"lastName":"Anisfeld","firstName":"Ari"},{"lastName":"Rodolfa","firstName":"Kit T."},{"lastName":"Ghani","firstName":"Rayid"}]}},{"key":"Salemi2016","type":"article","fields":{"abstract":["Simulation metamodeling is building a statistical model based on simulation output as an approximation to the system performance measure being estimated by the simulation model. In high-dimensional metamodeling problems, larger numbers of design points are needed to build an accurate and precise metamodel. Metamodeling techniques that are functions of all of these design points experience difficulties because of numerical instabilities and high computation times. We introduce a procedure to implement a local smoothing method called Moving Least Squares (MLS) regression in high-dimensional stochastic simulation metamodeling problems. Although MLS regression is known to work well when there are a very large number of design points, current procedures are focused on two- and three-dimensional cases. Furthermore, our procedure accounts for the fact that we can make replications and control the placement of design points in stochastic simulation. We provide a bound on the expected approximation error, show that the MLS predictor is consistent under certain conditions, and test the procedure with two examples that demonstrate better results than other existing simulation metamodeling techniques. © 2016 ACM."],"art_number":["16"],"author":["Salemi, P.","Nelson, B.L.","Staum, J."],"coden":["ATMCE"],"date":["2016"],"document_type":["Article"],"doi":["10.1145/2724708"],"issn":["10493301"],"journaltitle":["ACM Trans. Model. Comput. Simul."],"note":["cited By 8 \n\nTL;DR \n\nThis work introduces a procedure to implement a local smoothing method called Moving Least Squares (MLS) regression in high-dimensional stochastic simulation metamodeling problems and provides a bound on the expected approximation error and shows that the MLS predictor is consistent under certain conditions."],"number":["3"],"publisher":["Association for Computing Machinery"],"source":["Scopus"],"title":["Moving least squares regression for high-dimensional stochastic simulation metamodeling"],"volume":["26"]},"creators":{"author":[{"lastName":"Salemi","firstName":"P."},{"lastName":"Nelson","firstName":"B.L."},{"lastName":"Staum","firstName":"J."}]},"sentenceCased":true},{"key":"salman_controlled_2019","type":"article","fields":{"abstract":["Confirmation bias is a person’s tendency to look for evidence that strengthens his/her prior beliefs rather than refutes them. Manifestation of confirmation bias in software testing may have adverse effects on software quality. Psychology research suggests that time pressure could trigger confirmation bias."],"author":["Salman, Iflaah","Turhan, Burak","Vegas, Sira"],"date":["2019-08"],"doi":["10.1007/s10664-018-9668-8"],"issn":["1573-7616"],"journaltitle":["Empir. Softw. Eng."],"note":["TL;DR \n\nIt is found it necessary that testers develop self-awareness of confirmation bias and counter its potential adverse effects with a disconfirmatory attitude and further replications are recommended to investigate the effect of time pressure as a potential contributor to the manifestation of confirmation bias."],"number":["4"],"pages":["1727–1761"],"title":["A controlled experiment on time pressure and confirmation bias in functional software testing"],"volume":["24"]},"creators":{"author":[{"lastName":"Salman","firstName":"Iflaah"},{"lastName":"Turhan","firstName":"Burak"},{"lastName":"Vegas","firstName":"Sira"}]},"sentenceCased":true},{"key":"samadControlSystemsInternet2016","type":"article","fields":{"author":["Samad, Tariq"],"date":["2016-02"],"doi":["10.1109/MCS.2015.2495022"],"issn":["1066-033X"],"journaltitle":["IEEE Control Syst."],"note":["TL;DR \n\nThe relationship between control systems and the Internet of Things is discussed, including hybrid systems, embedded systems, cyberphysical systems (CPS), and systems of systems."],"number":["1"],"pages":["13–16"],"title":["Control Systems and the Internet of Things [Technical Activities]"],"volume":["36"]},"creators":{"author":[{"lastName":"Samad","firstName":"Tariq"}]}},{"key":"Samuel_2019","type":"thesis","fields":{"abstract":["Understandability and reproducibility of scientific results are vital in every field of science. Several reproducibility measures are being taken to make the data used in the publications findable and accessible. However, there are many challenges faced by scientists from the beginning of an experiment to the end in particular for data management. The explosive growth of heterogeneous research data and understanding how this data has been derived is one of the research problems faced in this context. Interlinking the data, the steps and the results from the computational and non-computational processes of a scientific experiment is important for the reproducibility. We introduce the notion of end-to-end provenance management’’ of scientific experiments to help scientists understand and reproduce the experimental results. The main contributions of this thesis are: (1) We propose a provenance modelREPRODUCE-ME’’ to describe the scientific experiments using semantic web technologies by extending existing standards. (2) We study computational reproducibility and important aspects required to achieve it. (3) Taking into account the REPRODUCE-ME provenance model and the study on computational reproducibility, we introduce our tool, ProvBook, which is designed and developed to demonstrate computational reproducibility. It provides features to capture and store provenance of Jupyter notebooks and helps scientists to compare and track their results of different executions. (4) We provide a framework, CAESAR (CollAborative Environment for Scientific Analysis with Reproducibility) for the end-to-end provenance management. This collaborative framework allows scientists to capture, manage, query and visualize the complete path of a scientific experiment consisting of computational and non-computational steps in an interoperable way. We apply our contributions to a set of scientific experiments in microscopy research projects."],"author":["Samuel, Sheeba"],"date":["2019"],"doi":["10.22032/dbt.40396"],"location":["Jena"],"title":["A provenance-based semantic approach to support understandability, reproducibility, and reuse of scientific experiments"]},"creators":{"author":[{"lastName":"Samuel","firstName":"Sheeba"}]},"sentenceCased":true},{"key":"sanchez-cuadradoBottomUpMetaModellingInteractive2012","type":"article","fields":{"author":["Sánchez-Cuadrado, Jesús","Lara, Juan","Guerra, Esther"],"date":["2012"],"doi":["10.1007/978-3-642-33666-9_2"],"journaltitle":["Model Driven Eng. Lang. Syst."],"pages":["3–19"],"title":["Bottom-Up Meta-Modelling: An Interactive Approach"],"volume":["7590"]},"creators":{"author":[{"lastName":"Sánchez-Cuadrado","firstName":"Jesús"},{"lastName":"Lara","firstName":"Juan"},{"lastName":"Guerra","firstName":"Esther"}]}},{"key":"sanchezBuildingModularYAWL2012","type":"article","fields":{"langid":["english"],"abstract":["Nowadays, novel strategies to develop and adapt workflow engines in efficient ways are required in order to have BPM and workflow solutions with the capacity to support frequent changes in the corporate environment. One key strategy is to build new engines by reusing as much as possible from existing components. This requires two things. Firstly, the mechanisms and technologies to build a library of reusable, extensible and adaptable workflow components. And secondly, a platform to integrate those components and form full applications. In this paper we show that Cumbia, being a platform for the development of workflow engines based on the modularisation of workflows according to concerns, suits this task. This is illustrated with YOC, a Cumbia-based implementation of YAWL."],"author":["Sanchez, Mario","Puentes, Diana","Villalobos, Jorge"],"date":["2012"],"doi":["10.1504/IJBPIM.2012.047912"],"issn":["1741-8763, 1741-8771"],"journaltitle":["IJBPIM"],"note":["TL;DR \n\nCumbia, being a platform for the development of workflow engines based on the modularisation of workflows according to concerns, suits this task and is illustrated with YOC, a Cumbia-based implementation of YAWL."],"number":["1"],"pages":["41"],"title":["Building a modular YAWL engine with Cumbia"],"volume":["6"]},"creators":{"author":[{"lastName":"Sanchez","firstName":"Mario"},{"lastName":"Puentes","firstName":"Diana"},{"lastName":"Villalobos","firstName":"Jorge"}]},"sentenceCased":true},{"key":"sanchezcuadradoApproachesModelTransformation2008","type":"article","fields":{"author":["Sánchez Cuadrado, Jesús","García Molina, Jesús"],"date":["2008"],"doi":["10.1007/978-3-540-69927-9_12"],"journaltitle":["Theory Pract. Model Transform."],"note":["TL;DR \n\nTwo approaches for reusing model transformation definitions are presented, tackling the creation of related model transformations and the composition of existing, separated transformation definitions so that they can be used to solve a concrete transformation problem."],"pages":["168–182"],"title":["Approaches for Model Transformation Reuse: Factorization and Composition"],"volume":["5063"]},"creators":{"author":[{"lastName":"Sánchez Cuadrado","firstName":"Jesús"},{"lastName":"García Molina","firstName":"Jesús"}]}},{"key":"sanchezcuadradoComponentModelModel2014","type":"article","fields":{"abstract":["Model-driven engineering promotes an active use of models to conduct the software development process. In this way, models are used to specify, simulate, verify, test and generate code for the final systems. Model transformations are key enablers for this approach, being used to manipulate instance models of a certain modelling language. However, while other development paradigms make available techniques to increase productivity through reutilization, there are few proposals for the reuse of model transformations across different modelling languages. As a result, transformations have to be developed from scratch even if other similar ones exist. In this paper, we propose a technique for the flexible reutilization of model transformations. Our proposal is based on generic programming for the definition and instantiation of transformation templates, and on component-based development for the encapsulation and composition of transformations. We have designed a component model for model transformations, supported by an implementation currently targeting the Atlas Transformation Language (ATL). To evaluate its reusability potential, we report on a generic transformation component to analyse workflow models through their transformation into Petri nets, which we have reused for eight workflow languages, including UML Activity Diagrams, YAWL and two versions of BPMN."],"author":["Sanchez Cuadrado, J.","Guerra, E.","De Lara, J."],"date":["2014-11"],"doi":["10.1109/TSE.2014.2339852"],"issn":["0098-5589"],"journaltitle":["IEEE Trans. Softw. Eng."],"note":["TL;DR \n\nThis paper designs a component model for model transformations, supported by an implementation currently targeting the Atlas Transformation Language (ATL), and reports on a generic transformation component to analyse workflow models through their transformation into Petri nets, which has reused for eight workflow languages."],"number":["11"],"pages":["1042–1060"],"title":["A Component Model for Model Transformations"],"volume":["40"]},"creators":{"author":[{"lastName":"Sanchez Cuadrado","firstName":"J."},{"lastName":"Guerra","firstName":"E."},{"lastName":"De Lara","firstName":"J."}]}},{"key":"sanchezSemanticbasedPrivacySettings2020","type":"article","fields":{"langid":["english"],"abstract":["By 2020, an individual is expected to own an average of 6.58 devices that share and integrate a wealth of personal user data. The management of privacy preferences across these devices is a complex task for which users are ill-equipped, which increases privacy risks. In this paper we propose an approach that exploits Semantic Web (SW) technology to manage the user’s IoT privacy preferences and negotiate the permissions for data sharing with third parties. SW technology comprises a web of data that can be processed by machines through a formal, universally shared representation. In our approach, SW enables a lightweight and interoperable communication between a Personal Data Manager (PDM) and the Third Parties (TPs) that request access to the user’s personal data. The PDM can handle multiple heterogeneous personal IoT devices and manages the negotiation process between the user and the TPs in a way that can relieve users from the burden of specifying their privacy requirement for each TP. The core of the approach is the definition of the Privacy Preference for IoT (PPIoT) Ontology which is based on the Privacy Preference Ontology, the W3C Semantic Sensor Network Ontology, the Fair Information Practices (FIP) principles, and state-of-the-art recommendation techniques for privacy protection in the IoT. This ontology aims to capture the complexity of privacy management in the IoT paradigm in light of the recent General Data Protection Regulation (GDPR) of the European Union. Along with presenting the ontology, in this paper we will provide an example on how to use the PPIoT ontology for the management of privacy preferences in the fitness IoT domain and we will show how the PDM handles the process of negotiation between the user and the TPs. The approach is based on an interactive PPIoT-based Privacy Preference Model (PPM) that meets the requirements of the GDPR to have transparent and simple TP privacy policies. Finally, we will report the results of an evaluation on a mockup fitness app that implements this PPM. The main contributions of this paper are: (i) to propose an ontology for privacy preference in the IoT context, which covers a knowledge gap in existing literature and can be used for IoT privacy management, (ii) to propose an interactive PPIoT-based Privacy Preference Model, which is in accordance with the GDPR objectives."],"author":["Sanchez, Odnan Ref","Torre, Ilaria","Knijnenburg, Bart P."],"date":["2020-10"],"doi":["10.1016/j.future.2019.10.024"],"issn":["0167739X"],"journaltitle":["Future Generation Computer Systems"],"pages":["879–898"],"title":["Semantic-based privacy settings negotiation and management"],"volume":["111"]},"creators":{"author":[{"lastName":"Sanchez","firstName":"Odnan Ref"},{"lastName":"Torre","firstName":"Ilaria"},{"lastName":"Knijnenburg","firstName":"Bart P."}]},"sentenceCased":true},{"key":"sandhuBigDataCloud2022","type":"article","fields":{"langid":["english"],"abstract":["With the recent advancements in computer technologies, the amount of data available is increasing day by day. However, excessive amounts of data create great challenges for users. Meanwhile, cloud computing services provide a powerful environment to store large volumes of data. They eliminate various requirements, such as dedicated space and maintenance of expensive computer hardware and software. Handling big data is a time-consuming task that requires large computational clusters to ensure successful data storage and processing. In this work, the definition, classification, and characteristics of big data are discussed, along with various cloud services, such as Microsoft Azure, Google Cloud, Amazon Web Services, International Business Machine cloud, Hortonworks, and MapR. A comparative analysis of various cloud-based big data frameworks is also performed. Various research challenges are defined in terms of distributed database storage, data security, heterogeneity, and data visualization."],"author":["Sandhu, Amanpreet Kaur"],"date":["2022"],"journaltitle":["Big Data Min. Anal."],"pages":["9"],"title":["Big Data with Cloud Computing: Discussions and Challenges"]},"creators":{"author":[{"lastName":"Sandhu","firstName":"Amanpreet Kaur"}]}},{"key":"sandhuIntegrationArtificialIntelligence2021","type":"inproceedings","fields":{"author":["Sandhu, Amandeep Kaur","Batth, Ranbir Singh"],"booktitle":["2021 2nd Int. Conf. Comput. Autom. Knowl. Manag. ICCAKM"],"date":["2021-01-19"],"doi":["10.1109/ICCAKM50778.2021.9357738"],"eventtitle":["2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)"],"isbn":["978-1-72819-491-2"],"location":["Dubai, United Arab Emirates"],"note":["TL;DR \n\nThis paper provides a roadmap of conventional reuse approaches to Software Intelligence approaches and concludes that Components Based Development fits best for modern applications as it supports object-oriented paradigm."],"pages":["357–362"],"publisher":["IEEE"],"shorttitle":["Integration of Artificial Intelligence into software reuse"],"title":["Integration of Artificial Intelligence into software reuse: An overview of Software Intelligence"]},"creators":{"author":[{"lastName":"Sandhu","firstName":"Amandeep Kaur"},{"lastName":"Batth","firstName":"Ranbir Singh"}]},"sentenceCased":true},{"key":"santhanamBotsSoftwareEngineering2022","type":"article","fields":{"langid":["english"],"abstract":["Bots have emerged from research prototypes to deployable systems due to the recent developments in machine learning, natural language processing and understanding techniques. In software engineering, bots range from simple automated scripts to decision-making autonomous systems. The spectrum of applications of bots in software engineering is so wide and diverse, that a comprehensive overview and categorization of such bots is needed. Existing works considered selective bots to be analyzed and failed to provide the overall picture. Hence it is significant to categorize bots in software engineering through analyzing why, what and how the bots are applied in software engineering. We approach the problem with a systematic mapping study based on the research articles published in this topic. This study focuses on classification of bots used in software engineering, the various dimensions of the characteristics, the more frequently researched area, potential research spaces to be explored and the perception of bots in the developer community. This study aims to provide an introduction and a broad overview of bots used in software engineering. Discussions of the feedback and results from several studies provide interesting insights and prospective future directions."],"author":["Santhanam, Sivasurya","Hecking, Tobias","Schreiber, Andreas","Wagner, Stefan"],"date":["2022-02-09"],"doi":["10.7717/peerj-cs.866"],"issn":["2376-5992"],"journaltitle":["PeerJ Comput. Sci."],"note":["TL;DR \n\nThis study focuses on classification of bots used in software engineering, the various dimensions of the characteristics, the more frequently researched area, potential research spaces to be explored and the perception of bots in the developer community."],"pages":["e866"],"shorttitle":["Bots in software engineering"],"title":["Bots in software engineering: A systematic mapping study"],"volume":["8"]},"creators":{"author":[{"lastName":"Santhanam","firstName":"Sivasurya"},{"lastName":"Hecking","firstName":"Tobias"},{"lastName":"Schreiber","firstName":"Andreas"},{"lastName":"Wagner","firstName":"Stefan"}]},"sentenceCased":true},{"key":"Saracevic:1995:EEI:215206.215351","type":"inproceedings","fields":{"acmid":["215351"],"author":["Saracevic, Tefko"],"booktitle":["Proc. 18th Annu. Int. ACM SIGIR Conf. Res. Dev. Inf. Retr."],"date":["1995"],"isbn":["0-89791-714-6"],"location":["New York, NY, USA"],"nodoi":["10.1145/215206.215351"],"numpages":["9"],"pages":["138–146"],"publisher":["ACM"],"series":["SIGIR '95"],"title":["Evaluation of evaluation in information retrieval"],"url":["http://doi.acm.org/10.1145/215206.215351"]},"creators":{"author":[{"lastName":"Saracevic","firstName":"Tefko"}]},"sentenceCased":true},{"key":"sarkarAllYouNeed","type":"article","fields":{"langid":["english"],"author":["Sarkar, Arjun"],"pages":["17"],"title":["All you need to know about ‘Attention’ and ‘Transformers’ — In-depth Understanding — Part 1"]},"creators":{"author":[{"lastName":"Sarkar","firstName":"Arjun"}]},"sentenceCased":true},{"key":"sartaj1stInternationalWorkshop","type":"article","fields":{"langid":["english"],"abstract":["Model-driven Engineering (MDE) and Large Language Models (LLMs) represent two transformative forces in software engineering and artificial intelligence. MDE enhances software systems’ productivity, quality, and maintainability by focusing on models as primary artifacts. On the other hand, LLMs, powered by machine learning algorithms, can understand and generate human-like text. Integrating LLMs into MDE can substantially improve tasks such as automating modeling, building modeling assistants, code generation from models, design automation, and verification. This synergy between MDE and LLMs could redefine the MDE process, making it more efficient and robust. This workshop aims to bring together researchers and industry professionals from diverse fields utilizing LLMs for different MDE tasks, promoting an environment of collaboration and knowledge exchange."],"author":["Sartaj, Hassan","Ali, Shaukat","Saadatmand, Mehrdad","Klikovits, Stefan"],"title":["1st International Workshop on Model-driven Engineering and Large Language Models (ModLLM’24)"]},"creators":{"author":[{"lastName":"Sartaj","firstName":"Hassan"},{"lastName":"Ali","firstName":"Shaukat"},{"lastName":"Saadatmand","firstName":"Mehrdad"},{"lastName":"Klikovits","firstName":"Stefan"}]}},{"key":"Sarwar:2001:ICF:371920.372071","type":"inproceedings","fields":{"acmid":["372071"],"author":["Sarwar, Badrul","Karypis, George","Konstan, Joseph","Riedl, John"],"booktitle":["10th Int. Conf. World Wide Web"],"date":["2001"],"ids":["IB-CF-2011"],"isbn":["1-58113-348-0"],"location":["New York"],"nodoi":["10.1145/371920.372071"],"numpages":["11"],"pages":["285–295"],"publisher":["ACM"],"title":["Item-based collaborative filtering recommendation algorithms"]},"creators":{"author":[{"lastName":"Sarwar","firstName":"Badrul"},{"lastName":"Karypis","firstName":"George"},{"lastName":"Konstan","firstName":"Joseph"},{"lastName":"Riedl","firstName":"John"}]},"sentenceCased":true},{"key":"sasGitRankingRankingGitHub2022","type":"article","fields":{"author":["Sas, Cezar","Capiluppi, Andrea","Sipio, Claudio Di","Rocco, Juri Di","Ruscio, Davide Di"],"date":["2022"],"doi":["10.48550/arXiv.2205.09379"],"eprint":["2205.09379"],"eprinttype":["arxiv"],"journaltitle":["CoRR"],"title":["GitRanking: A Ranking of GitHub Topics for Software Classification using Active Sampling"],"volume":["abs/2205.09379"]},"creators":{"author":[{"lastName":"Sas","firstName":"Cezar"},{"lastName":"Capiluppi","firstName":"Andrea"},{"lastName":"Sipio","firstName":"Claudio Di"},{"lastName":"Rocco","firstName":"Juri Di"},{"lastName":"Ruscio","firstName":"Davide Di"}]},"sentenceCased":true},{"key":"sasPerilsPitfallsClassifying","type":"article","fields":{"langid":["english"],"abstract":["Empirical results in software engineering have long started to show that findings and evidence are unlikely to be applicable to all software systems, or any domain: results need to be evaluated in specified contexts, and limited to the type of systems that they were extracted from."],"author":["Sas, Cezar","Capiluppi, Andrea"],"pages":["11"],"title":["The Perils and Pitfalls of Classifying Software Systems"]},"creators":{"author":[{"lastName":"Sas","firstName":"Cezar"},{"lastName":"Capiluppi","firstName":"Andrea"}]}},{"key":"SATToSE2017Postproceedings2017","type":"book","fields":{"date":["2017"],"ids":["SATToSE2017Postproceedings2017a"],"journaltitle":["CEUR Workshop Proceedings"],"publisher":["CEUR-WS"],"title":["SATToSE 2017: The post-proceedings editorial"],"volume":["2070"]},"creators":{},"sentenceCased":true},{"key":"Sauer201749","type":"inproceedings","fields":{"langid":["English; German"],"abbrev_source_title":["DFX: Proc. Symp. Des. X"],"affiliation":["Lehrstuhl fur Konstruktionstechnik (KTmfk), Friedrich-Alexander-Universität Erlangen-Nörnberg, Germany"],"author":["Sauer, C.","Köstner, C.","Schleich, B.","Wartzack, S."],"date":["2017"],"document_type":["Conference Paper"],"editor":["Krause D., Wartzack S., Paetzold K."],"isbn":["978-3-946094-20-3"],"note":["cited By 4"],"pages":["49–60"],"publisher":["TuTech Innovation Verlag"],"series":["DFX 2017: Proceedings of the 28th Symposium Design for X"],"source":["Scopus"],"title":["Use of deep learning on the locally resolved description of part properties [Einsatz von Deep Learning zur ortsaufgelösten Beschreibung von Bauteileigenschaften]"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85035053178&partnerID=40&md5=ef20b0fdc9966435df7632d5dc9badb7"]},"creators":{"author":[{"lastName":"Sauer","firstName":"C."},{"lastName":"Köstner","firstName":"C."},{"lastName":"Schleich","firstName":"B."},{"lastName":"Wartzack","firstName":"S."}],"editor":[{"lastName":"Krause D.","suffix":"Wartzack S.","firstName":"Paetzold K."}]}},{"key":"Sauer20182999","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Int. Des. Conf., DESIGN"],"affiliation":["Friedrich-Alexander Universität Erlangen-Nürnberg, Engineering Design (KTmfk), Martensstraße 9, Erlangen, 91058, Germany"],"author":["Sauer, C.","Schleich, B.","Wartzack, S."],"date":["2018"],"document_type":["Conference Paper"],"doi":["10.21278/idc.2018.0147"],"editor":["Bojcetic N., Storga M., Skec S., Pavkovic N., Marjanovic D."],"isbn":["978-953-7738-59-4"],"issn":["18479073"],"note":["cited By 9"],"pages":["2999–3010"],"publisher":["Faculty of Mechanical Engineering and Naval Architecture"],"series":["Proceedings of International Design Conference, DESIGN"],"source":["Scopus"],"title":["Deep learning in sheet-bulk metal forming part design"],"volume":["6"]},"creators":{"author":[{"lastName":"Sauer","firstName":"C."},{"lastName":"Schleich","firstName":"B."},{"lastName":"Wartzack","firstName":"S."}],"editor":[{"lastName":"Bojcetic N.","suffix":"Storga M.","firstName":"Skec S., Pavkovic N., Marjanovic D."}]},"sentenceCased":true},{"key":"savary-leblanc_software_2023","type":"article","fields":{"langid":["english"],"abstract":["The increasing essential complexity of software systems makes current software engineering methods and practices fall short in many occasions. Software assistants have the ability to help humans achieve a variety of tasks, including the development of software. Such assistants, which show human-like competences such as autonomy and intelligence, help software engineers do their job by empowering them with new knowledge. This article investigates the research efforts that have been conducted on the creation of assistants for software design, construction and maintenance paying special attention to the user-assistant interactions. To this end, we followed the standard systematic mapping study method to identify and classify relevant works in the state of the art. Out of the 7580 articles resulting from the automatic search, we identified 112 primary studies that present works which qualify as software assistants. We provide all the resources needed to reproduce our study. We report on the trends and goals of the assistants, the tasks they perform, how they interact with users, the technologies and mechanisms they exploit to embed intelligence and provide knowledge, and their level of automation. We propose a classification of software assistants based on interactions and present an analysis of the different automation patterns. As outcomes of our study, we provide a classification of software assistants dealing with the design, construction and maintenance phases of software development, we discuss the results, identify open lines of work and challenges and call for new innovative and rigorous research efforts in this field."],"author":["Savary-Leblanc, Maxime","Burgueño, Lola","Cabot, Jordi","Le Pallec, Xavier","Gérard, Sébastien"],"date":["2023"],"doi":["10.1002/spe.3170"],"issn":["1097-024X"],"journaltitle":["Softw. Pract. Exp."],"keywords":["software assistants","software construction","software design","software maintenance","systematic mapping study"],"note":["_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/spe.3170 \n\nTL;DR \n\nThis article investigates the research efforts that have been conducted on the creation of assistants for software design, construction and maintenance paying special attention to the user‐assistant interactions and proposes a classification of software assistants based on interactions and presents an analysis of the different automation patterns."],"number":["3"],"pages":["856–892"],"shorttitle":["Software assistants in software engineering"],"title":["Software assistants in software engineering: A systematic mapping study"],"volume":["53"]},"creators":{"author":[{"lastName":"Savary-Leblanc","firstName":"Maxime"},{"lastName":"Burgueño","firstName":"Lola"},{"lastName":"Cabot","firstName":"Jordi"},{"lastName":"Le Pallec","firstName":"Xavier"},{"lastName":"Gérard","firstName":"Sébastien"}]},"sentenceCased":true},{"key":"savolainenSELECTIONLOWCODEPLATFORMS","type":"article","fields":{"langid":["english"],"author":["Savolainen, Paula"],"keywords":["lowcode"],"pages":["86"],"title":["SELECTION OF LOW-CODE PLATFORMS BASED ON ORGANIZATION AND APPLICATION TYPE"]},"creators":{"author":[{"lastName":"Savolainen","firstName":"Paula"}]}},{"key":"sawant_fine-grape_2017","type":"article","fields":{"langid":["english"],"abstract":["An Application Programming Interface (API) provides a set of functionalities to a developer with the aim of enabling reuse. APIs have been investigated from different angles such as popularity usage and evolution to get a better understanding of their various characteristics. For such studies, software repositories are mined for API usage examples. However, many of the mining algorithms used for such purposes do not take type information into account. Thus making the results unreliable. In this paper, we aim to rectify this by introducing fine-GRAPE, an approach that produces fine-grained API usage information by taking advantage of type information while mining API method invocations and annotation. By means of fine-GRAPE, we investigate API usages from Java projects hosted on GitHub. We select five of the most popular APIs across GitHub Java projects and collect historical API usage information by mining both the release history of these APIs and the code history of every project that uses them. We perform two case studies on the resulting dataset. The first measures the lag time of each client. The second investigates the percentage of used API features. In the first case we find that for APIs that release more frequently clients are far less likely to upgrade to a more recent version of the API as opposed to clients of APIs that release infrequently. The second case study shows us that for most APIs there is a small number of features that is actually used and most of these features relate to those that have been introduced early in the APIs lifecycle."],"author":["Sawant, Anand Ashok","Bacchelli, Alberto"],"date":["2017-06"],"doi":["10.1007/s10664-016-9444-6"],"issn":["1382-3256, 1573-7616"],"journaltitle":["Empir. Softw. Eng."],"note":["TL;DR \n\nfine-GRAPE is introduced, an approach that produces fine-grained API usage information by taking advantage of type information while mining API method invocations and annotation, and investigates API usages from Java projects hosted on GitHub."],"number":["3"],"pages":["1348–1371"],"shorttitle":["Fine-GRAPE"],"title":["Fine-GRAPE: Fine-grained APi usage extractor – an approach and dataset to investigate API usage"],"volume":["22"]},"creators":{"author":[{"lastName":"Sawant","firstName":"Anand Ashok"},{"lastName":"Bacchelli","firstName":"Alberto"}]},"sentenceCased":true},{"key":"scavuzzoInteroperableDataMigration2014","type":"inproceedings","fields":{"langid":["italian"],"author":["Scavuzzo, Marco","Nitto, Elisabetta Di","Ceri, Stefano"],"date":["2014-09"],"doi":["10.1109/EDOCW.2014.32"],"isbn":["978-1-4799-5467-4"],"note":["TL;DR \n\nThis paper proposes an interoperable migration system for columnar NoSQL databases based on an orginal Metamodel, capable of preserving both strong and weak consistency between data updates, secondary indexes and various data types."],"pages":["154–162"],"publisher":["IEEE"],"title":["Interoperable Data Migration between NoSQL Columnar Databases"]},"creators":{"author":[{"lastName":"Scavuzzo","firstName":"Marco"},{"lastName":"Nitto","firstName":"Elisabetta Di"},{"lastName":"Ceri","firstName":"Stefano"}]}},{"key":"schaarschmidtAutomatedPolyglotPersistence","type":"article","fields":{"langid":["english"],"abstract":["In this paper, we present an innovative solution for providing automated polyglot persistence based on service level agreements defined over functional and non-functional requirements of database systems. Complex applications require polyglot persistence to deal with a wide range of database related needs. Until now, the overhead and the required know-how to manage multiple database systems prevents many applications from employing efficient polyglot persistence solutions. Instead, developers are often forced to implement one-size-fits-all solutions that do not scale well and cannot easily be upgraded. Therefore, we introduce the concept for a Polyglot Persistence Mediator (PPM), which allows for runtime decisions on routing data to different backends according to schema-based annotations. This enables applications to either employ polyglot persistence right from the beginning or employ new systems at any point with minimal overhead. We have implemented and evaluated the concept of automated polyglot persistence for a REST-based Database-as-a-Service setting. Evaluations were performed on various EC2 setups, showing a scalable writeperformance increase of 50-100% for a typical polyglot persistence scenario as well as drastically reduced latencies for reads and queries."],"author":["Schaarschmidt, Michael","Gessert, Felix","Ritter, Norbert"],"note":["TL;DR \n\nThis paper introduces the concept for a Polyglot Persistence Mediator (PPM), which allows for runtime decisions on routing data to different backends according to schema-based annotations and enables applications to either employ polyglot persistence right from the beginning or employ new systems at any point with minimal overhead."],"pages":["10"],"title":["Towards Automated Polyglot Persistence"]},"creators":{"author":[{"lastName":"Schaarschmidt","firstName":"Michael"},{"lastName":"Gessert","firstName":"Felix"},{"lastName":"Ritter","firstName":"Norbert"}]}},{"key":"schaefferSurveyGraphClustering2007","type":"article","fields":{"acmid":["2296057"],"address":["Amsterdam, The Netherlands, The Netherlands"],"author":["Schaeffer, Satu Elisa"],"date":["2007-08"],"issn":["1574-0137"],"issue_date":["August, 2007"],"journaltitle":["Comput. Sci. Rev."],"nodoi":["10.1016/j.cosrev.2007.05.001"],"note":["TL;DR \n\nThis survey overviews the definitions and methods for graph clustering, that is, finding sets of “related” vertices in graphs, and presents global algorithms for producing a clustering for the entire vertex set of an input graph."],"number":["1"],"numpages":["38"],"pages":["27–64"],"publisher":["Elsevier Science Publishers B. V."],"title":["Survey: Graph clustering"],"url":["http://dx.doi.org/10.1016/j.cosrev.2007.05.001"],"volume":["1"]},"creators":{"author":[{"lastName":"Schaeffer","firstName":"Satu Elisa"}]},"sentenceCased":true},{"key":"schafer_mining_2008","type":"inproceedings","fields":{"langid":["english"],"abstract":["Framework evolution may break existing users, which need to be migrated to the new framework version. This is a tedious and error-prone process that benefits from automation. Existing approaches compare two versions of the framework code in order to find changes caused by refactorings. However, other kinds of changes exist, which are relevant for the migration. In this paper, we propose to mine framework usage change rules from already ported instantiations, the latter being applications build on top of the framework, or test cases maintained by the framework developers. Our evaluation shows that our approach finds usage changes not only caused by refactorings, but also by conceptual changes within the framework. Further, it copes well with some issues that plague tools focusing on finding refactorings such as deprecated program elements or multiple changes applied to a single program element."],"author":["Schäfer, Thorsten","Jonas, Jan","Mezini, Mira"],"booktitle":["Procs 13th Int. Conf. Softw. Eng. - ICSE 08"],"date":["2008"],"doi":["10.1145/1368088.1368153"],"isbn":["978-1-60558-079-1"],"location":["Leipzig, Germany"],"nopublisher":["ACM Press"],"note":["TL;DR \n\nThis paper proposes to mine framework usage change rules from already ported instantiations, the latter being applications build on top of the framework, or test cases maintained by the framework developers, to find usage changes not only caused by refactorings, but also by conceptual changes within the framework."],"nourl":["http://portal.acm.org/citation.cfm?doid=1368088.1368153"],"pages":["471"],"title":["Mining framework usage changes from instantiation code"]},"creators":{"author":[{"lastName":"Schäfer","firstName":"Thorsten"},{"lastName":"Jonas","firstName":"Jan"},{"lastName":"Mezini","firstName":"Mira"}]},"sentenceCased":true},{"key":"Schafer:2007:CFR:1768197.1768208","type":"incollection","fields":{"author":["Schafer, J. Ben","Frankowski, Dan","Herlocker, Jon","Sen, Shilad"],"booktitle":["The adaptive web: Methods and strategies of web personalization"],"date":["2007"],"doi":["10.1007/978-3-540-72079-9_9"],"isbn":["978-3-540-72079-9"],"location":["Berlin, Heidelberg"],"pages":["291–324"],"publisher":["Springer Berlin Heidelberg"],"title":["Collaborative filtering recommender systems"]},"creators":{"author":[{"lastName":"Schafer","firstName":"J. Ben"},{"lastName":"Frankowski","firstName":"Dan"},{"lastName":"Herlocker","firstName":"Jon"},{"lastName":"Sen","firstName":"Shilad"}]},"sentenceCased":true},{"key":"schaferAdaptiveWeb2007","type":"incollection","fields":{"acmid":["1768208"],"author":["Schafer, J. Ben","Frankowski, Dan","Herlocker, Jon","Sen, Shilad"],"chapter":["Collaborative Filtering Recommender Systems"],"date":["2007"],"editor":["Brusilovsky, Peter","Kobsa, Alfred","Nejdl, Wolfgang"],"isbn":["978-3-540-72078-2"],"location":["Berlin, Heidelberg"],"numpages":["34"],"pages":["291–324"],"publisher":["Springer-Verlag"],"title":["The adaptive web"]},"creators":{"author":[{"lastName":"Schafer","firstName":"J. Ben"},{"lastName":"Frankowski","firstName":"Dan"},{"lastName":"Herlocker","firstName":"Jon"},{"lastName":"Sen","firstName":"Shilad"}],"editor":[{"lastName":"Brusilovsky","firstName":"Peter"},{"lastName":"Kobsa","firstName":"Alfred"},{"lastName":"Nejdl","firstName":"Wolfgang"}]},"sentenceCased":true},{"key":"schaferDyadRankingUsing2018","type":"article","fields":{"langid":["english"],"author":["Schäfer, Dirk","Hüllermeier, Eyke"],"date":["2018-05"],"doi":["10.1007/s10994-017-5694-9"],"issn":["0885-6125, 1573-0565"],"journaltitle":["Mach Learn"],"number":["5"],"pages":["903–941"],"title":["Dyad ranking using Plackett–Luce models based on joint feature representations"],"volume":["107"]},"creators":{"author":[{"lastName":"Schäfer","firstName":"Dirk"},{"lastName":"Hüllermeier","firstName":"Eyke"}]},"sentenceCased":true},{"key":"SchaferG20","type":"inproceedings","fields":{"langid":["english"],"author":["Schäfer, Marcel","Gogolla, Martin"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["MODELS 20 ACMIEEE 23rd Int. Conf. Model Driven Eng. Lang. Syst. Virtual Event Can. 18-23 Oct. 2020 Companion Proc."],"date":["2020"],"doi":["10.1145/3417990.3422011"],"editor":["Guerra, Esther","Iovino, Ludovico"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["14:1–14:5"],"publisher":["ACM"],"timestamp":["Wed, 23 Feb 2022 12:16:52 +0100"],"title":["Enhancing development and consistency of UML models and model executions with USE studio"]},"creators":{"author":[{"lastName":"Schäfer","firstName":"Marcel"},{"lastName":"Gogolla","firstName":"Martin"}],"editor":[{"lastName":"Guerra","firstName":"Esther"},{"lastName":"Iovino","firstName":"Ludovico"}]},"sentenceCased":true},{"key":"Schatten2017359","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Lect. Notes Comput. Sci."],"affiliation":["Artificial Intelligence Laboratory, Faculty of Organization and Informatics, University of Zagreb, Zagreb, Croatia"],"author":["Schatten, M.","Okreaša Ðurić, B.","Tomičič, I.","Ivkovič, N."],"correspondence_address1":["Schatten, M.; Artificial Intelligence Laboratory, Croatia; email: markus.schatten@foi.hr"],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-319-59930-4_38"],"editor":["Demazeau Y., Davidsson P., Bajo J., Vale Z."],"isbn":["9783319599298"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 1"],"pages":["359–363"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Automated MMORPG testing – An agent-based approach"],"volume":["10349 LNCS"]},"creators":{"author":[{"lastName":"Schatten","firstName":"M."},{"lastName":"Okreaša Ðurić","firstName":"B."},{"lastName":"Tomičič","firstName":"I."},{"lastName":"Ivkovič","firstName":"N."}],"editor":[{"lastName":"Demazeau Y.","suffix":"Davidsson P.","firstName":"Bajo J., Vale Z."}]},"sentenceCased":true},{"key":"schatzDesignSpaceExplorationConstraintBased2010","type":"article","fields":{"author":["Schätz, Bernhard","Hölzl, Florian","Lundkvist, Torbjörn"],"date":["2010"],"doi":["10.1109/ECBS.2010.25"],"journaltitle":["2010 17th IEEE Int. Conf. Workshop Eng. Comput. Based Syst."],"note":["TL;DR \n\nModel transformations based on a declarative, relational approach can be formalized as transformation rules guiding a mechanized exploration of possible design alternatives for the (semi-)automatic, incremental deployment of logical architectures to hardware platforms."],"pages":["173–182"],"title":["Design-Space Exploration through Constraint-Based Model-Transformation"]},"creators":{"author":[{"lastName":"Schätz","firstName":"Bernhard"},{"lastName":"Hölzl","firstName":"Florian"},{"lastName":"Lundkvist","firstName":"Torbjörn"}]}},{"key":"schelterDeequDataQuality","type":"article","fields":{"langid":["english"],"abstract":["Modern machine learning (ML) systems are comprised of complex ML pipelines which typically have many implicit assumptions about the data they consume (e.g., about the scales of variables, the presence of missing values or the dictionary of categorical values). Violations of these assumptions can result in crashes or wrong predictions. We therefore present Deequ, a library that allows users to explicitly specify their assumptions about the data in a declarative way. Deequ enables the efficient automatic validation of these assumptions on large datasets. It is an open source library based on Apache Spark and meets the requirements of production use cases at Amazon."],"author":["Schelter, Sebastian","Grafberger, Stefan","Schmidt, Philipp","Rukat, Tammo","Kiessling, Mario","Taptunov, Andrey","Biessmann, Felix","Lange, Dustin"],"note":["TL;DR \n\nDeequ is a library that allows users to explicitly specify their assumptions about the data in a declarative way and enables the efficient automatic validation of these assumptions on large datasets, and is designed to scale to datasets with billions of rows."],"pages":["3"],"title":["Deequ - Data Quality Validation for Machine Learning Pipelines"]},"creators":{"author":[{"lastName":"Schelter","firstName":"Sebastian"},{"lastName":"Grafberger","firstName":"Stefan"},{"lastName":"Schmidt","firstName":"Philipp"},{"lastName":"Rukat","firstName":"Tammo"},{"lastName":"Kiessling","firstName":"Mario"},{"lastName":"Taptunov","firstName":"Andrey"},{"lastName":"Biessmann","firstName":"Felix"},{"lastName":"Lange","firstName":"Dustin"}]}},{"key":"schlegelDesignAbstractionProcesses2010","type":"inproceedings","fields":{"author":["Schlegel, Christian","Steck, Andreas","Brugali, Davide","Knoll, Alois"],"booktitle":["Int. Conf. Simul. Model. Program. Auton. Robots"],"date":["2010"],"pages":["324–335"],"publisher":["Springer"],"shorttitle":["Design abstraction and processes in robotics"],"title":["Design abstraction and processes in robotics: From code-driven to model-driven engineering"],"url":["http://link.springer.com/content/pdf/10.1007/978-3-642-17319-6_31.pdf"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Schlegel","firstName":"Christian"},{"lastName":"Steck","firstName":"Andreas"},{"lastName":"Brugali","firstName":"Davide"},{"lastName":"Knoll","firstName":"Alois"}]},"sentenceCased":true},{"key":"schneiderSymbolicModelGeneration2017","type":"incollection","fields":{"langid":["english"],"author":["Schneider, Sven","Lambers, Leen","Orejas, Fernando"],"booktitle":["Fundamental Approaches to Software Engineering"],"date":["2017"],"doi":["10.1007/978-3-662-54494-5_13"],"editor":["Huisman, Marieke","Rubin, Julia"],"isbn":["978-3-662-54493-8 978-3-662-54494-5"],"keywords":["/unread","⛔ No INSPIRE recid found"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nIt is shown that the tableau-based reasoning method for graph properties as introduced by Lambers and Orejas paves the way for a symbolic model generation algorithm for graph Properties, which gradually generates a finite set of so-called symbolic models, where each symbolic model describes a set of finite graphs satisfying the graph property."],"pages":["226–243"],"publisher":["Springer Berlin Heidelberg"],"title":["Symbolic model generation for graph properties"],"volume":["10202"]},"creators":{"author":[{"lastName":"Schneider","firstName":"Sven"},{"lastName":"Lambers","firstName":"Leen"},{"lastName":"Orejas","firstName":"Fernando"}],"editor":[{"lastName":"Huisman","firstName":"Marieke"},{"lastName":"Rubin","firstName":"Julia"}]},"sentenceCased":true},{"key":"schonbockModelDrivenCoevolutionAgile2015","type":"inproceedings","fields":{"author":["Schonbock, J.","Etzlstorfer, J.","Kapsammer, E.","Kusel, A.","Retschitzegger, W.","Schwinger, W."],"date":["2015-01"],"doi":["10.1109/HICSS.2015.603"],"isbn":["978-1-4799-7367-5"],"note":["TL;DR \n\nThis paper provides an extensive survey evaluating various co-evolution approaches also from areas in software engineering like data, ontology, and grammar engineering on basis of a detailed set of criteria serving as a research roadmap for further developments in the area of co-Evolution for agile MDE."],"pages":["5094–5103"],"publisher":["IEEE"],"title":["Model-Driven Co-evolution for Agile Development"]},"creators":{"author":[{"lastName":"Schonbock","firstName":"J."},{"lastName":"Etzlstorfer","firstName":"J."},{"lastName":"Kapsammer","firstName":"E."},{"lastName":"Kusel","firstName":"A."},{"lastName":"Retschitzegger","firstName":"W."},{"lastName":"Schwinger","firstName":"W."}]}},{"key":"scikit-learn","type":"article","fields":{"author":["Pedregosa, F.","Varoquaux, G.","Gramfort, A.","Michel, V.","Thirion, B.","Grisel, O.","Blondel, M.","Prettenhofer, P.","Weiss, R.","Dubourg, V.","Vanderplas, J.","Passos, A.","Cournapeau, D.","Brucher, M.","Perrot, M.","Duchesnay, E."],"date":["2011"],"journaltitle":["J. Mach. Learn. Res."],"note":["TL;DR \n\nScikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems, focusing on bringing machine learning to non-specialists using a general-purpose high-level language."],"pages":["2825–2830"],"title":["Scikit-learn: Machine learning in Python"],"volume":["12"]},"creators":{"author":[{"lastName":"Pedregosa","firstName":"F."},{"lastName":"Varoquaux","firstName":"G."},{"lastName":"Gramfort","firstName":"A."},{"lastName":"Michel","firstName":"V."},{"lastName":"Thirion","firstName":"B."},{"lastName":"Grisel","firstName":"O."},{"lastName":"Blondel","firstName":"M."},{"lastName":"Prettenhofer","firstName":"P."},{"lastName":"Weiss","firstName":"R."},{"lastName":"Dubourg","firstName":"V."},{"lastName":"Vanderplas","firstName":"J."},{"lastName":"Passos","firstName":"A."},{"lastName":"Cournapeau","firstName":"D."},{"lastName":"Brucher","firstName":"M."},{"lastName":"Perrot","firstName":"M."},{"lastName":"Duchesnay","firstName":"E."}]},"sentenceCased":true},{"key":"sculleyHiddenTechnicalDebt","type":"article","fields":{"langid":["english"],"abstract":["Machine learning offers a fantastically powerful toolkit for building useful complex prediction systems quickly. This paper argues it is dangerous to think of these quick wins as coming for free. Using the software engineering framework of technical debt, we find it is common to incur massive ongoing maintenance costs in real-world ML systems. We explore several ML-specific risk factors to account for in system design. These include boundary erosion, entanglement, hidden feedback loops, undeclared consumers, data dependencies, configuration issues, changes in the external world, and a variety of system-level anti-patterns."],"author":["Sculley, D","Holt, Gary","Golovin, Daniel","Davydov, Eugene","Phillips, Todd","Ebner, Dietmar","Chaudhary, Vinay","Young, Michael","Crespo, Jean-François","Dennison, Dan"],"keywords":["DONE","machine learning"],"note":["<b>Green Annotations (18/12/2020, 18:46:01)</b> \n\n\"Undeclared Consumers. Oftentimes, a prediction from a machine learning model ma is made widely accessible, either at runtime or by writing to files or logs that may later be consumed by other systems. Without access controls, some of these consumers may be undeclared, silently using the output of a given model as an input to another system. In more classical software engineering, these issues are referred to as visibility debt [13].\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=2\">Sculley et al :10</a>) \n\n\"It may be surprising to the academic community to know that only a tiny fraction of the code in many ML systems is actually devoted to learning or prediction - see Figure 1. In the language of Lin and Ryaboy, much of the remainder may be described as \"plumbing\" [11].\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=4\">Sculley et al :12</a>) \n\n\"Using generic packages often results in a glue code system design pattern, in which a massive amount of supporting code is written to get data into and out of general-purpose packages.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=5\">Sculley et al :13</a>) \n\n\"Because a mature system might end up being (at most) 5% machine learning code and (at least) 95% glue code, it may be less costly to create a clean native solution rather than re-use a generic package.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=5\">Sculley et al :13</a>) \n\n\"An important strategy for combating glue-code is to wrap black-box packages into common API's. This allows supporting infrastructure to be more reusable and reduces the cost of changing packages.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=5\">Sculley et al :13</a>) \n\n\"he resulting system for preparing data in an ML-friendly format may become a jungle of scrapes, joins, and sampling steps, often with intermediate files output.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=5\">Sculley et al :13</a>) \n\n\"Managing these pipelines, detecting errors and recovering from failures are all difficult and costly [1].\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=5\">Sculley et al :13</a>) \n\n\"Abstraction Debt.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=5\">Sculley et al :13</a>) \n\n\"The above issues highlight the fact that there is a distinct lack of strong abstractions to support ML systems.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=5\">Sculley et al :13</a>) \n\n\"What is the right interface to describe a stream of data, or a model, or a prediction?\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=5\">Sculley et al :13</a>) \n\n<i>THAT'S THE KEY!!!! (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=5\">note on p.13</a>)</i> \n\n\"distributed learning in particular, there remains a lack of widely accepted abstractions.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=5\">Sculley et al :13</a>) \n\n<i>DISTRIBUTED LEARNING (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=5\">note on p.13</a>)</i> \n\n\"The lack of standard abstractions makes it all too easy to blur the lines between components.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=6\">Sculley et al :14</a>) \n\n\"using multiple languages often increases the cost of effective testing and can increase the difficulty of transferring ownership to other individuals.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=6\">Sculley et al :14</a>) \n\n<i>THAT SUPPORTS THE NEED FOR DOMAIN-SPECIFIC LANGUAGES (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=6\">note on p.14</a>)</i> \n\n\"Another potentially surprising area where debt can accumulate is in the configuration of machine learning systems. Any large system has a wide range of configurable options, including which features are used, how data is selected, a wide variety of algorithm-specific learning settings, potential preor post-processing, verification methods, etc.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=6\">Sculley et al :14</a>) \n\n\"n a mature system which is being actively developed, the number of lines of configuration can far exceed the number of lines of the traditional code. Each configuration line has a potential for mistakes.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=6\">Sculley et al :14</a>) \n\n\"It should be easy to specify a configuration as a small change from a previous configuration. • It should be hard to make manual errors, omissions, or oversights. • It should be easy to see, visually, the difference in configuration between two models. • It should be easy to automatically assert and verify basic facts about the configuration: number of features used, transitive closure of data dependencies, etc. • It should be possible to detect unused or redundant settings. • Configurations should undergo a full code review and be checked into a repository.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=6\">Sculley et al :14</a>) \n\n<i>Support for domain-specific language!!!! (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=6\">note on p.14</a>)</i> \n\n\"Thus if a model updates on new data, the old manually set threshold may be invalid. Manually updating many thresholds across many models is time-consuming and brittle. One mitigation strategy for this kind of problem appears in [14], in which thresholds are learned via simple evaluation on heldout validation data.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=7\">Sculley et al :15</a>) \n\n\"Unit testing of individual components and end-to-end tests of running systems are valuable, but in the face of a changing world such tests are not sufficient to provide evidence that a system is working as intended.\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=7\">Sculley et al :15</a>) \n\n\"data replaces code in ML systems\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=7\">Sculley et al :15</a>) \n\n\"code should be tested, then it seems clear that some amount of testing of input data is critical to a well-functioning system\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=7\">Sculley et al :15</a>) \n\n<i>Adversial Machine Learning??? (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=7\">note on p.15</a>)</i> \n\n\"non-determinism inherent in parallel learning\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=8\">Sculley et al :16</a>) \n\n\"Most of the use cases described in this paper have talked about the cost of maintaining a single model, but mature systems may have dozens or hundreds of models running simultaneously [14, 6].\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=8\">Sculley et al :16</a>) \n\n<i>THIS IS IMPORTANT ASPECTS TO BE MENTIONED AS MOTIVATION/CHALLENGE (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=8\">note on p.16</a>)</i> \n\n\"How easily can an entirely new algorithmic approach be tested at full scale?\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=8\">Sculley et al :16</a>) \n\n\"maintainable ML\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=8\">Sculley et al :16</a>) \n\n\"better abstractions\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=8\">Sculley et al :16</a>) \n\n\"testing methodologies\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=8\">Sculley et al :16</a>) \n\n\"design patterns\" (<a href=\"zotero://open-pdf/library/items/TJI3FLRY?page=8\">Sculley et al :16</a>)"],"pages":["9"],"title":["Hidden Technical Debt in Machine Learning Systems"]},"creators":{"author":[{"lastName":"Sculley","firstName":"D"},{"lastName":"Holt","firstName":"Gary"},{"lastName":"Golovin","firstName":"Daniel"},{"lastName":"Davydov","firstName":"Eugene"},{"lastName":"Phillips","firstName":"Todd"},{"lastName":"Ebner","firstName":"Dietmar"},{"lastName":"Chaudhary","firstName":"Vinay"},{"lastName":"Young","firstName":"Michael"},{"lastName":"Crespo","firstName":"Jean-François"},{"lastName":"Dennison","firstName":"Dan"}]}},{"key":"SEfSAS3challenges","type":"article","fields":{"title":["SEfSAS3-challenges"]},"creators":{}},{"key":"Segundo2017301","type":"article","fields":{"abstract":["This paper presents a decision support system (DSS) called DSScreening to rapidly detect inborn errors of metabolism (IEMs) in newborn screening (NS). The system has been created using the Aide-DS framework, which uses techniques imported from model-driven software engineering (MDSE) and soft computing, and it is available through eGuider, a web portal for the enactment of computerised clinical practice guidelines and protocols. MDSE provides the context and techniques to build new software artefacts based on models which conform to a specific metamodel. It also offers separation of concern, to disassociate medical from technological knowledge, thus allowing changes in one domain without affecting the other. The changes might include, for instance, the addition of new disorders to the DSS or new measures to the computation related to a disorder. Artificial intelligence and soft computing provide fuzzy logic to manage uncertainty and ambiguous situations. Fuzzy logic is embedded in an inference system to build a fuzzy inference system (FIS); specifically, a single-input rule modules connected zero-order Takagi-Sugeno FIS. The automatic creation of FISs is performed by the Aide-DS framework, which is capable of embedding the generated FISs in computerized clinical guidelines. It can also create a desktop application to execute the FIS. Technologically, it supports the addition of new target languages for the desktop applications and the inclusion of new ways of acquiring data. DSScreening has been tested by comparing its predictions with the results of 152 real analyses from two groups: (1) NS samples and (2) clinical samples belonging to individuals of all ages with symptoms that do not necessarily correspond to an IEM. The system has reduced the time needed by 98.7% when compared to the interpretation time spent by laboratory professionals. Besides, it has correctly classified 100% of the NS samples and obtained an accuracy of 70% for samples belonging to individuals with clinical symptoms. © 2017 Elsevier Ltd"],"author":["Segundo, U.","Aldámiz-Echevarría, L.","López-Cuadrado, J.","Buenestado, D.","Andrade, F.","Pérez, T.A.","Barrena, R.","Pérez-Yarza, E.G.","Pikatza, J.M."],"coden":["ESAPE"],"date":["2017"],"document_type":["Article"],"doi":["10.1016/j.eswa.2017.02.022"],"issn":["09574174"],"journaltitle":["Expert Syst. Appl."],"note":["cited By 10"],"pages":["301–318"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Improvement of newborn screening using a fuzzy inference system"],"volume":["78"]},"creators":{"author":[{"lastName":"Segundo","firstName":"U."},{"lastName":"Aldámiz-Echevarría","firstName":"L."},{"lastName":"López-Cuadrado","firstName":"J."},{"lastName":"Buenestado","firstName":"D."},{"lastName":"Andrade","firstName":"F."},{"lastName":"Pérez","firstName":"T.A."},{"lastName":"Barrena","firstName":"R."},{"lastName":"Pérez-Yarza","firstName":"E.G."},{"lastName":"Pikatza","firstName":"J.M."}]},"sentenceCased":true},{"key":"sehrawatDataMiningIoT2018","type":"article","fields":{"langid":["english"],"abstract":["Internet of Things (IoT) has provided enormous opportunities to make prevailing smart environment by influencing the increasing ubiquity of Radio Frequency Identification Devices (RFID), wireless network, and sensor devices. Recently, a large number of industrial IoT applications have embarked their presence. Rapid technological growth introduces tremendous information on the network. Big Data is an idea to assemble huge amount of data from IoT enabled devices like sensors, actuators in IoT smart environment to help monitor specific conditions, procedures, and system performance. In this new generation, it becomes more challenging to extract most relevant information quickly and efficiently. To solve this problem, a data mining technique widely known as automatic text summarization may also prove to be fruitful. Text summarization creates summarized information from a large text corpus. Various latest techniques used for text summarization viz. Classification, Particle Swarm Optimization, Genetic Algorithms, clustering, neural network and various hybridized approaches are presented in this paper. The latest and relevant algorithms may be customized in the context of IoT applications. This paper is aimed at reviewing these techniques and also discusses the challenges as well as other related research issues."],"author":["Sehrawat, Deepti","Department of Computer Science and Applications, Maharshi Dayanand University, Rohtak, Haryana, India","Gill, Nasib Singh","Department of Computer Science and Applications, Maharshi Dayanand University, Rohtak, Haryana, India"],"date":["2018-04-30"],"doi":["10.26438/ijcse/v6i4.289295"],"issn":["23472693"],"journaltitle":["ijcse"],"note":["<b>Blue Annotations (3/2/2022, 15:47:41)</b> \n\n\"Big Data collects, process and analyse huge relevant data from internet enabled devices like sensors attached to monitor specific conditions, usage and system performance.\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=5\">Sehrawat et al 2018:293</a>) \n\n\"Parallel programming model\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"find correlation among multi-faced data\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"text summarization techniques,\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"extracting useful information from huge text corpus by protecting data and providing privacy and security to the secret and private data.\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"Fast and effective data mining approaches for huge data corpus to read and write.\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"uncertain\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"Integration of heterogeneous, noisy, incomplete, fuzzy, structured and semi-structured unstructured data sources and data types.\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"and\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"Communication via diverse device types and systems and furthermore need to mine webpage data.\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"Need to extract complex knowledge after analyzing properties of the data and finding association among them.\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"Need to develop efficient and well-defined data mining framework which considers data security, data privacy, big data, and data sharing of prime importance\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"Need of enhanced parallel programming model by designing a dynamic multisource data mining model.\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>) \n\n\"data mining algorithms are not adapted to parallel platform and requires attention of researchers in this area.\" (<a href=\"zotero://open-pdf/library/items/3FC8SWRG?page=6\">Sehrawat et al 2018:294</a>)"],"number":["4"],"pages":["289–295"],"title":["Data Mining in IoT and its Challenges"],"volume":["6"]},"creators":{"author":[{"lastName":"Sehrawat","firstName":"Deepti"},{"literal":"Department of Computer Science and Applications, Maharshi Dayanand University, Rohtak, Haryana, India"},{"lastName":"Gill","firstName":"Nasib Singh"},{"literal":"Department of Computer Science and Applications, Maharshi Dayanand University, Rohtak, Haryana, India"}]},"sentenceCased":true},{"key":"seibelDedicatedLanguageContext2012","type":"incollection","fields":{"langid":["english"],"abstract":["Model-Driven Engineering (MDE) automates development activities by employing model transformations. Thereby, a plethora of model transformation approaches with individual capabilities have been developed. In certain cases, complex and automated MDE activities require the interaction of various, potentially heterogeneous, model transformations. This can be achieved by a loosely coupled and highly cohesive composition of model transformations implemented in different model transformation languages. However, existing approaches either do not support context composition, using other model transformations as additional context, or they violate the important black-box principle because they require adapting model transformations for context composition. In this paper, we present a dedicated model transformation composition framework (MoTCoF) that does not require the adaptation of model transformations and, thus, treats model transformations as true black-boxes. We illustrate our approach with an application example taken from an industrial case study."],"author":["Seibel, Andreas","Hebig, Regina","Neumann, Stefan","Giese, Holger"],"booktitle":["Software Language Engineering"],"date":["2012"],"editor":["Sloane, Anthony","Aßmann, Uwe"],"isbn":["978-3-642-28829-6 978-3-642-28830-2"],"keywords":["software engineering"],"number":["6940"],"pages":["19–39"],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture Notes in Computer Science"],"title":["A Dedicated Language for Context Composition and Execution of True Black-Box Model Transformations"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-28830-2_2"],"urldate":["2015-03-24"]},"creators":{"author":[{"lastName":"Seibel","firstName":"Andreas"},{"lastName":"Hebig","firstName":"Regina"},{"lastName":"Neumann","firstName":"Stefan"},{"lastName":"Giese","firstName":"Holger"}],"editor":[{"lastName":"Sloane","firstName":"Anthony"},{"lastName":"Aßmann","firstName":"Uwe"}]}},{"key":"SelectingThirdpartyLibraries","type":"article","fields":{"entrysubtype":["newspaper"],"title":["Selecting Third-party Libraries: The Data Scientist’s Perspective"]},"creators":{}},{"key":"SelfmanagingInformationSystems","type":"online","fields":{"title":["Self-managing information systems"],"url":["http://www.inf.u-szeged.hu/~jelasity/selfstar05.html"],"urldate":["2016-09-24"]},"creators":{},"sentenceCased":true},{"key":"selimAutomatedVerificationModel2013","type":"article","fields":{"author":["Selim, Gehan M. K.","Büttner, Fabian","Cordy, James R.","Dingel, Juergen","Wang, Shige"],"date":["2013"],"doi":["10.1007/978-3-642-41533-3_42"],"journaltitle":["Model-Driven Eng. Lang. Syst."],"note":["TL;DR \n\nThis study reports on applying an automated verification approach to the GM-to-AUTOSAR transformation that is based on checking the satisfiability of a relational transformation representation, or a transformation model, with respect to well-formedness OCL constraints."],"pages":["690–706"],"title":["Automated Verification of Model Transformations in the Automotive Industry"],"volume":["8107"]},"creators":{"author":[{"lastName":"Selim","firstName":"Gehan M. K."},{"lastName":"Büttner","firstName":"Fabian"},{"lastName":"Cordy","firstName":"James R."},{"lastName":"Dingel","firstName":"Juergen"},{"lastName":"Wang","firstName":"Shige"}]}},{"key":"selimModelTransformationsMigrating2012","type":"article","fields":{"author":["Selim, Gehan M. K.","Wang, Shige","Cordy, James R.","Dingel, Juergen"],"date":["2012"],"doi":["10.1007/978-3-642-31491-9_9"],"journaltitle":["Model. Found. Appl."],"pages":["90–101"],"title":["Model Transformations for Migrating Legacy Models: An Industrial Case Study"],"volume":["7349"]},"creators":{"author":[{"lastName":"Selim","firstName":"Gehan M. K."},{"lastName":"Wang","firstName":"Shige"},{"lastName":"Cordy","firstName":"James R."},{"lastName":"Dingel","firstName":"Juergen"}]}},{"key":"SemerathBLMV20","type":"inproceedings","fields":{"langid":["english"],"author":["Semeráth, Oszkár","Babikian, Aren A.","Li, Anqi","Marussy, Kristóf","Varró, Dániel"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["MoDELS 20 ACMIEEE 23rd Int. Conf. Model Driven Eng. Lang. Syst. Virtual Event Can. 18-23 Oct. 2020"],"date":["2020"],"doi":["10.1145/3365438.3410962"],"editor":["Syriani, Eugene","Sahraoui, Houari A.","family=Lara, given=Juan, prefix=de, useprefix=true","Abrahão, Silvia"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nA structural graph solver that uses partial models with an SMT-solver to automatically derive models which simultaneously fulfill structural and attribute constraints while key theoretical properties of model generation like completeness or diversity are still ensured are ensured."],"pages":["187–199"],"publisher":["ACM"],"timestamp":["Sat, 09 Apr 2022 12:34:15 +0200"],"title":["Automated generation of consistent models with structural and attribute constraints"]},"creators":{"author":[{"lastName":"Semeráth","firstName":"Oszkár"},{"lastName":"Babikian","firstName":"Aren A."},{"lastName":"Li","firstName":"Anqi"},{"lastName":"Marussy","firstName":"Kristóf"},{"lastName":"Varró","firstName":"Dániel"}],"editor":[{"lastName":"Syriani","firstName":"Eugene"},{"lastName":"Sahraoui","firstName":"Houari A."},{"lastName":"Lara","firstName":"Juan","prefix":"de","useprefix":true},{"lastName":"Abrahão","firstName":"Silvia"}]},"sentenceCased":true},{"key":"Sen2013236","type":"article","fields":{"abstract":["It is essential to estimate the Channel and detect symbol in multiple-input and multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems. Symbol detection by applying the maximum likelihood (ML) detector gives excellent performance but in systems with higher number of antennas and greater constellation size, the computational complexity of this algorithm becomes quite high. In this paper we apply a recently developed modified Differential Evolution (DE) algorithm with novel mutation, crossover as well as parameter adaptation strategies (MDE-pBX) for reducing the search space of the ML detector and the computational complexity of symbol detection in MIMO-OFDM systems. The performance of MDE-pBX have been compared with two classical symbol detectors namely ML and ZF and two famous evolutionary algorithm namely SaDE and CLPSO. © 2013 Springer International Publishing."],"author":["Sen, A.","Roy, S.","Das, S."],"date":["2013"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-319-03753-0_22"],"isbn":["9783319037523"],"issn":["03029743"],"issue":["PART 1"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 0 \n\nTL;DR \n\nA recently developed modified Differential Evolution DE algorithm with novel mutation, crossover as well as parameter adaptation strategies MDE_pBX is applied for reducing the search space of the ML detector and the computational complexity of symbol detection in MIMO-OFDM systems."],"pages":["236–247"],"source":["Scopus"],"title":["A modified differential evolution for symbol detection in MIMO-OFDM system"],"volume":["8297 LNCS"]},"creators":{"author":[{"lastName":"Sen","firstName":"A."},{"lastName":"Roy","firstName":"S."},{"lastName":"Das","firstName":"S."}]},"sentenceCased":true},{"key":"SenBV10","type":"article","fields":{"langid":["english"],"author":["Sen, Sagar","Baudry, Benoit","Vangheluwe, Hans"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2010"],"doi":["10.1177/0037549709340530"],"journaltitle":["Simul,"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper presents a methodology to synthesize model editors equipped with automatic completion from a modeling language’s declarative specification consisting of a meta-model with a visual syntax, powered by a first-order relational logic engine implemented in ALLOY."],"number":["2"],"pages":["109–126"],"timestamp":["Mon, 26 Oct 2020 08:24:52 +0100"],"title":["Towards domain-specific model editors with automatic model completion"],"volume":["86"]},"creators":{"author":[{"lastName":"Sen","firstName":"Sagar"},{"lastName":"Baudry","firstName":"Benoit"},{"lastName":"Vangheluwe","firstName":"Hans"}]},"sentenceCased":true},{"key":"SendallK03","type":"article","fields":{"langid":["english"],"author":["Sendall, Shane","Kozaczynski, Wojtek"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2003"],"doi":["10.1109/MS.2003.1231150"],"journaltitle":["IEEE Softw,"],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["5"],"pages":["42–45"],"timestamp":["Mon, 08 Jun 2020 22:31:27 +0200"],"title":["Model transformation: The heart and soul of model-driven software development"],"volume":["20"]},"creators":{"author":[{"lastName":"Sendall","firstName":"Shane"},{"lastName":"Kozaczynski","firstName":"Wojtek"}]},"sentenceCased":true},{"key":"serbanAdoptionEffectsSoftware2020","type":"inproceedings","fields":{"langid":["english"],"abstract":["Background. The increasing reliance on applications with machine learning (ML) components calls for mature engineering techniques that ensure these are built in a robust and future-proof manner. Aim. We aim to empirically determine the state of the art in how teams develop, deploy and maintain software with ML components. Method. We mined both academic and grey literature and identified 29 engineering best practices for ML applications. We conducted a survey among 313 practitioners to determine the degree of adoption for these practices and to validate their perceived effects. Using the survey responses, we quantified practice adoption, differentiated along demographic characteristics, such as geography or team size. We also tested correlations and investigated linear and non-linear relationships between practices and their perceived effect using various statistical models. Results. Our findings indicate, for example, that larger teams tend to adopt more practices, and that traditional software engineering practices tend to have lower adoption than ML specific practices. Also, the statistical models can accurately predict perceived effects such as agility, software quality and traceability, from the degree of adoption for specific sets of practices. Combining practice adoption rates with practice importance, as revealed by statistical models, we identify practices that are important but have low adoption, as well as practices that are widely adopted but are less important for the effects we studied. Conclusion. Overall, our survey and the analysis of responses received provide a quantitative basis for assessment and step-wise improvement of practice adoption by ML teams."],"author":["Serban, Alex","family=Blom, given=Koen, prefix=van der, useprefix=true","Hoos, Holger","Visser, Joost"],"booktitle":["Proc. 14th ACM IEEE Int. Symp. Empir. Softw. Eng. Meas. ESEM"],"date":["2020-10-05"],"doi":["10.1145/3382494.3410681"],"eventtitle":["ESEM '20: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement"],"ids":["serbanAdoptionEffectsSoftware2020a"],"isbn":["978-1-4503-7580-1"],"keywords":["best practices","machine learning","software engineering"],"location":["Bari Italy"],"note":["TL;DR \n\nThe findings indicate, for example, that larger teams tend to adopt more practices, and that traditional software engineering practices tend to have lower adoption than ML specific practices."],"pages":["1–12"],"publisher":["ACM"],"title":["Adoption and Effects of Software Engineering Best Practices in Machine Learning"]},"creators":{"author":[{"lastName":"Serban","firstName":"Alex"},{"lastName":"Blom","firstName":"Koen","prefix":"vander","useprefix":true},{"lastName":"Hoos","firstName":"Holger"},{"lastName":"Visser","firstName":"Joost"}]}},{"key":"serbanSurveyIntelligentAssistants2013","type":"article","fields":{"langid":["english"],"abstract":["Research and industry increasingly make use of large amounts of data to guide decision-making. To do this, however, data needs to be analyzed in typically nontrivial refinement processes, which require technical expertise about methods and algorithms, experience with how a precise analysis should proceed, and knowledge about an exploding number of analytic approaches. To alleviate these problems, a plethora of different systems have been proposed that “intelligently” help users to analyze their data. This article provides a first survey to almost 30 years of research on intelligent discovery assistants (IDAs). It explicates the types of help IDAs can provide to users and the kinds of (background) knowledge they leverage to provide this help. Furthermore, it provides an overview of the systems developed over the past years, identifies their most important features, and sketches an ideal future IDA as well as the challenges on the road ahead."],"author":["Serban, Floarea","Vanschoren, Joaquin","Kietz, Jörg-Uwe","Bernstein, Abraham"],"date":["2013-06"],"doi":["10.1145/2480741.2480748"],"issn":["0360-0300, 1557-7341"],"journaltitle":["ACM Comput. Surv."],"note":["TL;DR \n\nThe types of help IDAs can provide to users and the kinds of (background) knowledge they leverage to provide this help are explicated."],"number":["3"],"pages":["1–35"],"title":["A survey of intelligent assistants for data analysis"],"volume":["45"]},"creators":{"author":[{"lastName":"Serban","firstName":"Floarea"},{"lastName":"Vanschoren","firstName":"Joaquin"},{"lastName":"Kietz","firstName":"Jörg-Uwe"},{"lastName":"Bernstein","firstName":"Abraham"}]},"sentenceCased":true},{"key":"ServerlessApplicationsWhy","type":"online","fields":{"note":["TL;DR \n\nThis work analyzes 89 serverless applications from open source projects, industrial sources, academic literature, and scientific computing-presenting the most extensive study to date."],"title":["Serverless Applications: Why, When, and How?"],"url":["https://www.computer.org/csdl/magazine/so/2021/01/09190031/1mYZaiUIVhu"],"urldate":["2021-01-17"]},"creators":{}},{"key":"sevillaruizInferringVersionedSchemas2015","type":"incollection","fields":{"langid":["english"],"abstract":["While the concept of database schema plays a central role in relational database systems, most NoSQL systems are schemaless: these databases are created without having to formally define its schema. Instead, it is implicit in the stored data. This lack of schema definition offers a greater flexibility; more specifically, the schemaless databases ease both the recording of non-uniform data and data evolution. However, this comes at the cost of losing some of the benefits provided by schemas. In this article, a MDE-based reverse engineering approach for inferring the schema of aggregate-oriented NoSQL databases is presented. We show how the obtained schemas can be used to build database utilities that tackle some of the problems encountered using implicit schemas: a schema diagram viewer and a data validator generator are presented."],"author":["Sevilla Ruiz, Diego","Morales, Severino Feliciano","García Molina, Jesús"],"booktitle":["Conceptual Modeling"],"date":["2015"],"doi":["10.1007/978-3-319-25264-3_35"],"editor":["Johannesson, Paul","Lee, Mong Li","Liddle, Stephen W.","Opdahl, Andreas L.","Pastor López, Óscar"],"isbn":["978-3-319-25263-6 978-3-319-25264-3"],"location":["Cham"],"note":["TL;DR \n\nA MDE-based reverse engineering approach for inferring the schema of aggregate-oriented NoSQL databases is presented and it is shown how the obtained schemas can be used to build database utilities that tackle some of the problems encountered using implicit schemas."],"pages":["467–480"],"publisher":["Springer International Publishing"],"title":["Inferring Versioned Schemas from NoSQL Databases and Its Applications"],"volume":["9381"]},"creators":{"author":[{"lastName":"Sevilla Ruiz","firstName":"Diego"},{"lastName":"Morales","firstName":"Severino Feliciano"},{"lastName":"García Molina","firstName":"Jesús"}],"editor":[{"lastName":"Johannesson","firstName":"Paul"},{"lastName":"Lee","firstName":"Mong Li"},{"lastName":"Liddle","firstName":"Stephen W."},{"lastName":"Opdahl","firstName":"Andreas L."},{"lastName":"Pastor López","firstName":"Óscar"}]}},{"key":"shafiqMachineLearningSoftware2020","type":"article","fields":{"langid":["english"],"abstract":["Objective: This article addresses the aforementioned problem and aims to present a state-of-the-art on the growing number of uses of machine learning in software engineering. Method: We conduct a systematic mapping study on applications of machine learning to software engineering following the standard guidelines and principles of empirical software engineering. Results: This study introduces a machine learning for software engineering (MLSE) taxonomy classifying the state-of-the-art machine learning techniques according to their applicability to various software engineering life cycle stages. Overall, 227 articles were rigorously selected and analyzed as a result of this study. Conclusion: From the selected articles, we explore a variety of aspects that should be helpful to academics and practitioners alike in understanding the potential of adopting machine learning techniques during software engineering projects."],"author":["Shafiq, Saad","Mashkoor, Atif","Mayr-Dorn, Christoph","Egyed, Alexander"],"date":["2020-05-27"],"eprint":["2005.13299"],"eprintclass":["cs"],"eprinttype":["arxiv"],"ids":["Shafiq2020MachineLF"],"journaltitle":["ArXiv200513299 Cs"],"keywords":["machine learning"],"shorttitle":["Machine Learning for Software Engineering"],"title":["Machine Learning for Software Engineering: A Systematic Mapping"],"url":["http://arxiv.org/abs/2005.13299"],"urldate":["2020-10-26"]},"creators":{"author":[{"lastName":"Shafiq","firstName":"Saad"},{"lastName":"Mashkoor","firstName":"Atif"},{"lastName":"Mayr-Dorn","firstName":"Christoph"},{"lastName":"Egyed","firstName":"Alexander"}]}},{"key":"shahrivarBusinessModelCommercial2018","type":"article","fields":{"abstract":["Context Commercial open source software (COSS) and community open source software (OSS) are two types of open source software. The former is the newer concept with the grounds for research such as business model. However, in the literature of open source software, the revenue model has been studied as a business model, which is one component of the business model. Therefore, there is a need for a more complete review of the COSS business model with all components. Objective The purpose of this research is to describe and present the COSS business model with all its components. Method A systematic literature review of the COSS business model was conducted and 1157 studies were retrieved through search in six academic databases. The result of the process of selecting the primary studies was 21 studies. By backward snowballing, we discovered 10 other studies, and thus a total of 31 studies were found. Then, the grounded theory coding procedures were used to determine the characteristics and components of the COSS business model. Results The COSS business model was presented with value proposition, value creation & delivery, and value capture. This business model includes eight components: COSS products and complementarities, COSS clients and users, COSS competitive strategies, organizational aspects of COSS, position of COSS producers in the value network, resources and capabilities of COSS business, COSS revenue sources, and COSS cost-benefit. Conclusion This study provides a complete illustration of the COSS business model. Identifies COSS generic competitive strategies. By cost-benefit component, we have considered both tangible and intangible components. This business model is especially effective in developing countries. In future research, it is necessary to review the management of the COSS community, the organization, the new revenue models for disruptive ability of open source software, and the localization of open source software."],"author":["Shahrivar, Shahrokh","Elahi, Shaban","Hassanzadeh, Alireza","Montazer, Gholamali"],"date":["2018-11-01"],"doi":["10.1016/j.infsof.2018.06.018"],"issn":["0950-5849"],"journaltitle":["Information and Software Technology"],"pages":["202–214"],"shorttitle":["A business model for commercial open source software"],"title":["A business model for commercial open source software: A systematic literature review"],"volume":["103"]},"creators":{"author":[{"lastName":"Shahrivar","firstName":"Shahrokh"},{"lastName":"Elahi","firstName":"Shaban"},{"lastName":"Hassanzadeh","firstName":"Alireza"},{"lastName":"Montazer","firstName":"Gholamali"}]},"sentenceCased":true},{"key":"shaoQuantifyMusicArtist2008","type":"inproceedings","fields":{"acmid":["1458522"],"author":["Shao, Bo","Li, Tao","Ogihara, Mitsunori"],"booktitle":["Proc. 10th ACM Workshop Web Inf. Data Manag."],"date":["2008"],"isbn":["978-1-60558-260-3"],"keywords":["hierarchical co-clustering","music artist similarity","similarity quantification"],"location":["New York, NY, USA"],"nodoi":["10.1145/1458502.1458522"],"numpages":["6"],"pages":["119–124"],"publisher":["ACM"],"series":["WIDM '08"],"title":["Quantify music artist similarity based on style and mood"],"url":["http://doi.acm.org/10.1145/1458502.1458522"]},"creators":{"author":[{"lastName":"Shao","firstName":"Bo"},{"lastName":"Li","firstName":"Tao"},{"lastName":"Ogihara","firstName":"Mitsunori"}]},"sentenceCased":true},{"key":"Sharifnia2021","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Comput Ind Eng"],"affiliation":["Department of Industrial and Systems Engineering, The University of Tennessee, Knoxville, United States"],"art_number":["107693"],"author":["Sharifnia, S.M.E.","Amrollahi Biyouki, S.","Sawhney, R.","Hwangbo, H."],"coden":["CINDD"],"correspondence_address1":["Sharifnia, S.M.E.; Department of Industrial and Systems Engineering, United States; email: ssharifn@vols.utk.edu"],"date":["2021"],"document_type":["Article"],"doi":["10.1016/j.cie.2021.107693"],"issn":["03608352"],"journaltitle":["Comput. Ind. Eng."],"note":["cited By 2"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Robust simulation optimization for supply chain problem under uncertainty via neural network metamodeling"],"volume":["162"]},"creators":{"author":[{"lastName":"Sharifnia","firstName":"S.M.E."},{"lastName":"Amrollahi Biyouki","firstName":"S."},{"lastName":"Sawhney","firstName":"R."},{"lastName":"Hwangbo","firstName":"H."}]},"sentenceCased":true},{"key":"Sharma:2017:CGR:3084226.3084287","type":"inproceedings","fields":{"acmid":["3084287"],"author":["Sharma, Abhishek","Thung, Ferdian","Kochhar, Pavneet Singh","Sulistya, Agus","Lo, David"],"booktitle":["Proc. 21st Int. Conf. Eval. Assess. Softw. Eng."],"date":["2017"],"isbn":["978-1-4503-4804-1"],"keywords":["Genetic Algorithm","GitHub","Latent Dirichlet Allocation"],"location":["New York, NY, USA"],"nodoi":["10.1145/3084226.3084287"],"note":["TL;DR \n\nThis work explores the possibility of developing automatic cataloging system for GitHub by automatically extracting functionality descriptive text segments from readme files of GitHub repositories and demonstrates that additional meaningful categories which complement existing GitHub categories can be inferred."],"numpages":["6"],"pages":["314–319"],"publisher":["ACM"],"series":["EASE'17"],"title":["Cataloging GitHub repositories"],"url":["http://doi.acm.org.univaq.clas.cineca.it/10.1145/3084226.3084287"]},"creators":{"author":[{"lastName":"Sharma","firstName":"Abhishek"},{"lastName":"Thung","firstName":"Ferdian"},{"lastName":"Kochhar","firstName":"Pavneet Singh"},{"lastName":"Sulistya","firstName":"Agus"},{"lastName":"Lo","firstName":"David"}]},"sentenceCased":true},{"key":"shevtsovControlTheoreticalSoftwareAdaptation2018","type":"article","fields":{"langid":["english"],"abstract":["Modern software applications are subject to uncertain operating conditions, such as dynamics in the availability of services and variations of system goals. Consequently, runtime changes cannot be ignored, but often cannot be predicted at design time. Control theory has been identified as a principled way of addressing runtime changes and it has been applied successfully to modify the structure and behavior of software applications. Most of the times, however, the adaptation targeted the resources that the software has available for execution (CPU, storage, etc.) more than the software application itself. This paper investigates the research efforts that have been conducted to make software adaptable by modifying the software rather than the resource allocated to its execution. This paper aims to identify: the focus of research on control-theoretical software adaptation; how software is modeled and what control mechanisms are used to adapt software; what software qualities and controller guarantees are considered. To that end, we performed a systematic literature review in which we extracted data from 42 primary studies selected from 1,512 papers that resulted from an automatic search. The results of our investigation show that even though the behavior of software is considered non-linear, research efforts use linear models to represent it, with some success. Also, the control strategies that are most often considered are classic control, mostly in the form of Proportional and Integral controllers, and Model Predictive Control. The paper also discusses sensing and actuating strategies that are prominent for software adaptation and the (often neglected) proof of formal properties. Finally, we distill open challenges for control-theoretical software adaptation."],"author":["Shevtsov, Stepan","Berekmeri, Mihaly","Weyns, Danny","Maggio, Martina"],"date":["2018-08-01"],"doi":["10.1109/TSE.2017.2704579"],"issn":["0098-5589, 1939-3520, 2326-3881"],"journaltitle":["IIEEE Trans. Software Eng."],"number":["8"],"pages":["784–810"],"shorttitle":["Control-Theoretical Software Adaptation"],"title":["Control-Theoretical Software Adaptation: A Systematic Literature Review"],"volume":["44"]},"creators":{"author":[{"lastName":"Shevtsov","firstName":"Stepan"},{"lastName":"Berekmeri","firstName":"Mihaly"},{"lastName":"Weyns","firstName":"Danny"},{"lastName":"Maggio","firstName":"Martina"}]}},{"key":"Shi:2014:CFB:2620784.2556270","type":"article","fields":{"acmid":["2556270"],"address":["New York, NY, USA"],"articleno":["3"],"author":["Shi, Yue","Larson, Martha","Hanjalic, Alan"],"date":["2014-05"],"issn":["0360-0300"],"issue_date":["July 2014"],"journaltitle":["ACM Comput. Surv."],"keywords":["Algorithms","applications","challenges","collaborative filtering","recommender systems","social networks","survey"],"nodoi":["10.1145/2556270"],"number":["1"],"numpages":["45"],"pages":["3:1-3:45"],"publisher":["ACM"],"title":["Collaborative filtering beyond the user-item matrix: A survey of the state of the art and future challenges"],"url":["http://doi.acm.org/10.1145/2556270"],"volume":["47"]},"creators":{"author":[{"lastName":"Shi","firstName":"Yue"},{"lastName":"Larson","firstName":"Martha"},{"lastName":"Hanjalic","firstName":"Alan"}]},"sentenceCased":true},{"key":"Shi2021","type":"article","fields":{"abstract":["Traffic state estimation (TSE) bifurcates into two main categories, model-driven and data-driven (e.g., machine learning, ML) approaches, while each suffers from either deficient physics or small data. To mitigate these limitations, recent studies introduced hybrid methods, such as physics-informed deep learning (PIDL), which contains both model-driven and data-driven components. This paper contributes an improved paradigm, called physics-informed deep learning with a fundamental diagram learner (PIDL + FDL), which integrates ML terms into the model-driven component to learn a functional form of a fundamental diagram (FD), i.e., a mapping from traffic density to flow or velocity. The proposed PIDL + FDL has the advantages of performing the TSE learning, model parameter identification, and FD estimation simultaneously. This paper focuses on highway TSE with observed data from loop detectors, using traffic density or velocity as traffic variables. We demonstrate the use of PIDL + FDL to solve popular first-order and second-order traffic flow models and reconstruct the FD relation as well as model parameters that are outside the FD term. We then evaluate the PIDL + FDL-based TSE using the Next Generation SIMulation (NGSIM) dataset. The experimental results show the superiority of the PIDL + FDL in terms of improved estimation accuracy and data efficiency over advanced baseline TSE methods, and additionally, the capacity to properly learn the unknown underlying FD relation. IEEE"],"author":["Shi, R.","Mo, Z.","Huang, K.","Di, X.","Du, Q."],"date":["2021"],"document_type":["Article"],"doi":["10.1109/TITS.2021.3106259"],"issn":["15249050"],"journaltitle":["IEEE Trans. Intell. Transp. Syst."],"note":["cited By 0"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["A physics-informed deep learning paradigm for traffic state and fundamental diagram estimation"]},"creators":{"author":[{"lastName":"Shi","firstName":"R."},{"lastName":"Mo","firstName":"Z."},{"lastName":"Huang","firstName":"K."},{"lastName":"Di","firstName":"X."},{"lastName":"Du","firstName":"Q."}]},"sentenceCased":true},{"key":"shinDynamicAdaptationSoftwaredefined2020","type":"inproceedings","fields":{"langid":["english"],"author":["Shin, Seung Yeob","Nejati, Shiva","Sabetzadeh, Mehrdad","Briand, Lionel C.","Arora, Chetan","Zimmer, Frank"],"booktitle":["Proc. IEEEACM 15th Int. Symp. Softw. Eng. Adapt. Self-Manag. Syst."],"date":["2020-06-29"],"doi":["10.1145/3387939.3391603"],"eventtitle":["SEAMS '20: IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems"],"isbn":["978-1-4503-7962-5"],"keywords":["DONE"],"location":["Seoul Republic of Korea"],"pages":["137–148"],"publisher":["ACM"],"shorttitle":["Dynamic adaptation of software-defined networks for IoT systems"],"title":["Dynamic adaptation of software-defined networks for IoT systems: A search-based approach"]},"creators":{"author":[{"lastName":"Shin","firstName":"Seung Yeob"},{"lastName":"Nejati","firstName":"Shiva"},{"lastName":"Sabetzadeh","firstName":"Mehrdad"},{"lastName":"Briand","firstName":"Lionel C."},{"lastName":"Arora","firstName":"Chetan"},{"lastName":"Zimmer","firstName":"Frank"}]},"sentenceCased":true},{"key":"shinNoSQLDatabaseDesign2017","type":"article","fields":{"langid":["english"],"abstract":["In the Big Data era, relational databases and NoSQL databases coexist in Polyglot Persistence environment. Although data management is more essential in an environment where a variety of databases are, NoSQL databases only concentrate on solving non-functional requirements to run well on large clusters. This situation makes consistent data management standards difficult. To solve this problem, this study proposes NoSQL database design method using conceptual data model based on Peter Chen’s framework. The proposed design method is applied to the e-commerce business area in order to examine the applicability of it."],"author":["Shin, Kwangchul","Hwang, Chulhyun","Jung, Hoekyung"],"date":["2017"],"ids":["shinNoSQLDatabaseDesign2017a"],"note":["TL;DR \n\nThe proposed NoSQL database design method using conceptual data model based on Peter Chen’s framework is applied to the e-commerce business area in order to examine the applicability of it."],"number":["5"],"pages":["5"],"title":["NoSQL Database Design Using UML Conceptual Data Model Based on Peter Chen’s Framework"],"volume":["12"]},"creators":{"author":[{"lastName":"Shin","firstName":"Kwangchul"},{"lastName":"Hwang","firstName":"Chulhyun"},{"lastName":"Jung","firstName":"Hoekyung"}]}},{"key":"shresthaAutomaticGenerationSimulink2020","type":"inproceedings","fields":{"abstract":["Testing cyber-physical system (CPS) development tools such as MathWorks' Simulink is very important as they are widely used in design, simulation, and verification of CPS data-flow models. Existing randomized differential testing frameworks such as SLforge leverages semi-formal Simulink specifications to guide random model generation which requires significant research and engineering investment along with the need to manually update the tool, whenever MathWorks updates model validity rules. To address the limitations, we propose to learn validity rules automatically by learning a language model using our framework DeepFuzzSL from existing corpus of Simulink models. In our experiments, DeepFuz-zSL consistently generate over 90% valid Simulink models and also found 2 confirmed bugs by MathWorks Support. © 2020 ACM."],"author":["Shrestha, S.L."],"booktitle":["Proc. - 2020 ACMIEEE 42nd Int. Conf. Softw. Eng. Companion ICSE-Companion 2020"],"date":["2020"],"doi":["10.1145/3377812.3382163"],"isbn":["978-1-4503-7122-3"],"keywords":["Automatic Generation","Cyber Physical System","Cyber-physical systems (CPS)","Data flow analysis","Dataflow model","Deep learning","Development tools","Differential testing","Embedded systems","Language model","Learning systems","Model validity","Program debugging","Simulink models","Software engineering"],"note":["cited By 0 \n\nTL;DR \n\nThis work proposes to learn validity rules automatically by learning a language model using the authors' framework DeepFuzzSL from existing corpus of Simulink models, which consistently generate over 90% valid Simulinking models and also found 2 confirmed bugs by MathWorks Support."],"pages":["110–112"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["Automatic Generation of Simulink Models to Find Bugs in a Cyber-Physical System Tool Chain using Deep Learning"]},"creators":{"author":[{"lastName":"Shrestha","firstName":"S.L."}]},"sentenceCased":true},{"key":"Shriver:ICSE:2021","type":"inproceedings","fields":{"author":["Shriver, David","Elbaum, Sebastian","Dwyer, Matthew B."],"booktitle":["43rd Int. Conf. Softw. Eng."],"date":["2021"],"note":["TL;DR \n\nThis paper introduces a semantics-preserving reduction of multiple safety property types into a set of equivalid correctness problems amenable to adversarial attacks, and evaluates the reduction approach as an enabler of falsification on a range of DNN correctness problems and shows its cost-effectiveness and scalability."],"publisher":["IEEE"],"title":["Reducing DNN properties to enable falsification with adversarial attacks"]},"creators":{"author":[{"lastName":"Shriver","firstName":"David"},{"lastName":"Elbaum","firstName":"Sebastian"},{"lastName":"Dwyer","firstName":"Matthew B."}]},"sentenceCased":true},{"key":"Sidhu2022166","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Int J Comput Appl"],"affiliation":["Department of Computer Science and Engineering, Punjabi University, Patiala, India; University Computer Centre, Punjabi University, Patiala, India; Department of Computer Science, Punjabi University, Patiala, India"],"author":["Sidhu, B.K.","Singh, K.","Sharma, N."],"coden":["IJCAF"],"correspondence_address1":["Sidhu, B.K.; Department of Computer Science and Engineering, Punjab, India; email: brahmaleen.ce@pbi.ac.in"],"date":["2022"],"document_type":["Article"],"doi":["10.1080/1206212X.2020.1711616"],"issn":["1206212X"],"journaltitle":["Int. J. Comput. Appl."],"keywords":["GOAL_Model-Refactoring","notion","TECHNIQUE_DNN"],"note":["cited By 5 \n\nTL;DR \n\nIt is proposed that identifying design flaws at a higher level of granularity will save from the vicious cycle of small refactoring operations and their cascaded side-effects."],"number":["2"],"pages":["166–177"],"publisher":["Taylor and Francis Ltd."],"source":["Scopus"],"title":["A machine learning approach to software model refactoring"],"volume":["44"]},"creators":{"author":[{"lastName":"Sidhu","firstName":"B.K."},{"lastName":"Singh","firstName":"K."},{"lastName":"Sharma","firstName":"N."}]},"sentenceCased":true},{"key":"siegwartIntroductionAutonomousMobile2004","type":"book","fields":{"author":["Siegwart, Roland","Nourbakhsh, Illah Reza"],"date":["2004"],"isbn":["978-0-262-19502-7"],"location":["Cambridge, Mass"],"note":["\"A Bradford book.\" \n\nTL;DR \n\nBringing together all aspects of mobile robotics into one volume, Introduction to Autonomous Mobile Robots can serve as a textbook or a working tool for beginning practitioners."],"pagetotal":["321"],"publisher":["MIT Press"],"series":["Intelligent robots and autonomous agents"],"title":["Introduction to autonomous mobile robots"]},"creators":{"author":[{"lastName":"Siegwart","firstName":"Roland"},{"lastName":"Nourbakhsh","firstName":"Illah Reza"}]},"sentenceCased":true},{"key":"sierraSurveySelfadmittedTechnical2019","type":"article","fields":{"langid":["english"],"author":["Sierra, Giancarlo","Shihab, Emad","Kamei, Yasutaka"],"date":["2019-06"],"doi":["10.1016/j.jss.2019.02.056"],"issn":["01641212"],"journaltitle":["Journal of Systems and Software"],"pages":["70–82"],"title":["A survey of self-admitted technical debt"],"volume":["152"]},"creators":{"author":[{"lastName":"Sierra","firstName":"Giancarlo"},{"lastName":"Shihab","firstName":"Emad"},{"lastName":"Kamei","firstName":"Yasutaka"}]},"sentenceCased":true},{"key":"sifakisAutonomousSystemsArchitectural2019","type":"incollection","fields":{"langid":["english"],"author":["Sifakis, Joseph"],"booktitle":["Models, Languages, and Tools for Concurrent and Distributed Programming"],"date":["2019"],"doi":["10.1007/978-3-030-21485-2_21"],"editor":["Boreale, Michele","Corradini, Flavio","Loreti, Michele","Pugliese, Rosario"],"isbn":["978-3-030-21484-5 978-3-030-21485-2"],"location":["Cham"],"note":["TL;DR \n\nIt is concluded that autonomy is a kind of broad intelligence that should be associated with functionality and not with specific techniques, and a general computational model combining a system architecture model and an agent model is proposed."],"pages":["388–410"],"publisher":["Springer International Publishing"],"title":["Autonomous Systems – An Architectural Characterization"],"volume":["11665"]},"creators":{"author":[{"lastName":"Sifakis","firstName":"Joseph"}],"editor":[{"lastName":"Boreale","firstName":"Michele"},{"lastName":"Corradini","firstName":"Flavio"},{"lastName":"Loreti","firstName":"Michele"},{"lastName":"Pugliese","firstName":"Rosario"}]}},{"key":"Sikdar2014225","type":"article","fields":{"abstract":["In this paper we propose a modified differential evolution (MDE) based feature selection and ensemble learning algorithms for biochemical entity recognizer. Identification and classification of chemical entities are relatively more complex and challenging compared to the other related tasks. As chemical entities we focus on IUPAC and IUPAC related entities. The algorithm performs feature selection within the framework of a robust machine learning algorithm, namely Conditional Random Field. Features are identified and implemented mostly without using any domain specific knowledge and/or resources. In this paper we modify traditional differential evolution to perform two tasks, viz. determining relevant set of features as well as determining proper voting weights for constructing an ensemble. The feature selection technique produces a set of potential solutions on the final population. We develop many models of CRF using these feature combinations. In order to further improve the performance the outputs of these classifiers are combined together using a classifier ensemble technique based on modified DE. Our experiments with the benchmark datasets yield the recall, precision and F-measure values of 82.34%, 88.26% and 85.20%, respectively. © 2014 Springer-Verlag Berlin Heidelberg."],"author":["Sikdar, U.K.","Ekbal, A.","Saha, S."],"date":["2014"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-642-54906-9_18"],"isbn":["9783642549052"],"issn":["03029743"],"issue":["PART 1"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 2"],"pages":["225–236"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Modified differential evolution for biochemical name recognizer"],"volume":["8403 LNCS"]},"creators":{"author":[{"lastName":"Sikdar","firstName":"U.K."},{"lastName":"Ekbal","firstName":"A."},{"lastName":"Saha","firstName":"S."}]},"sentenceCased":true},{"key":"simGettingWholeStory2011","type":"article","fields":{"langid":["english"],"abstract":["When analyzing data elicited using the “war stories” technique, previously introduced by Lutters and Seaman (Inf Softw Technol 49(6):576–587, 2007), we encountered unexpected challenges in applying standard qualitative analysis techniques. After reviewing the literature on stories and storytelling, we realized that a richer analysis would be possible if we accorded more respect to the data’s structure and nature as stories, rather than treating our participants’ utterances simply as textual data. We report on five lessons learned regarding how we can better analyze war stories as stories: 1) war stories tend to be about exceptional situations; 2) war stories tend to be diverse and resistant to being combined into a single grand narrative; 3) the humanities can be a valuable resource for analyzing war stories; 4) war stories are not just text, they are also performances; and 5) war stories are not just data, they are also instructive and evocative."],"author":["Sim, Susan Elliott","Alspaugh, Thomas A."],"date":["2011-08"],"doi":["10.1007/s10664-011-9157-9"],"issn":["1382-3256, 1573-7616"],"journaltitle":["Empir Software Eng"],"number":["4"],"pages":["460–486"],"shorttitle":["Getting the whole story"],"title":["Getting the whole story: An experience report on analyzing data elicited using the war stories procedure"],"volume":["16"]},"creators":{"author":[{"lastName":"Sim","firstName":"Susan Elliott"},{"lastName":"Alspaugh","firstName":"Thomas A."}]},"sentenceCased":true},{"key":"SimilarityMatrix","type":"online","fields":{"langid":["british"],"abstract":["Petrinet Subject/dataset,petrinet2.ecore,PetriNet.ecore,petrinet_extendable.ecore,PetriNets.ecore,petri_nets.ecore,petrinet_tgg_rule.ecore,PetrinetDsl.ecore,PetriNet_extended.ecore,PetriNetModel.ecore,petri.ecore petrinet2.ecore,100,33,33,66,33,0,25,33,33,50 PetriNet.ecore,20,100,64,20,37,0,20,4..."],"organization":["Google Docs"],"title":["Similarity matrix"],"url":["https://docs.google.com/spreadsheets/d/1jJ7FGuN1I7cWJZw4J6dO-KYaU118AFtpbvNzC01re0c/edit?usp=sharing&usp=embed_facebook"],"urldate":["2020-02-11"]},"creators":{},"sentenceCased":true},{"key":"SimplifyingModelTransformation","type":"online","fields":{"title":["Simplifying Model Transformation Chains by Rule Composition - Springer"],"url":["http://link.springer.com/chapter/10.1007%2F978-3-642-21210-9_28"],"urldate":["2015-03-24"]},"creators":{}},{"key":"Singaravel20171497","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Build. Simul. Conf. Proc."],"affiliation":["Architectural Engineering Division, KU Leuven, Belgium; ESAT-STADIUS, KU Leuven, Belgium"],"author":["Singaravel, S.","Geyer, P.","Suykens, J."],"correspondence_address1":["Singaravel, S.; Architectural Engineering Division, Belgium; email: sundar.singaravel@kuleuven.be"],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.26868/25222708.2017.059"],"editor":["Barnaby C.S., Wetter M."],"isbn":["978-1-5108-7067-3"],"issn":["25222708"],"note":["cited By 1"],"pages":["1497–1506"],"publisher":["International Building Performance Simulation Association"],"series":["Building Simulation Conference Proceedings"],"source":["Scopus"],"title":["Component-based machine learning modelling approach for design stage building energy prediction: Weather conditions and size"],"volume":["3"]},"creators":{"author":[{"lastName":"Singaravel","firstName":"S."},{"lastName":"Geyer","firstName":"P."},{"lastName":"Suykens","firstName":"J."}],"editor":[{"lastName":"Barnaby C.S.","firstName":"Wetter M."}]},"sentenceCased":true},{"key":"singh_detection_2020","type":"article","fields":{"langid":["english"],"abstract":["Malicious software deliberately affects the computer systems. Malware are analyzed using static or dynamic analysis techniques. Using these techniques, unique patterns are extracted to detect malware correctly. In this paper, a behavior-based malware detection technique is proposed. Various runtime features are extracted by setting up a dynamic analysis environment using the Cuckoo sandbox. Three primary features are processed for developing malware classifier. Firstly, printable strings are processed word by word using text mining techniques which produced a very high dimension matrix of the string features. Then we apply the singular value decomposition technique for reducing dimensions of string features. Secondly, Shannon entropy is computed over the printable strings and API calls to consider the randomness of API and PSI features. In addition to these features, behavioral features regarding file operations, registry key modification and network activities are used in malware detection. Finally, all features are integrated in the training feature set to develop the malware classifiers using the machine learning algorithms. The proposed technique is validated with 16489 malware and 8422 benign files. Our experimental results show the accuracy of 99.54% in malware detection using ensemble machine learning algorithms. Moreover, it aims to develop a behavior-based malware detection technique of high accuracy by processing the runtime features in a new way."],"author":["Singh, Jagsir","Singh, Jaswinder"],"date":["2020-05"],"doi":["10.1016/j.infsof.2020.106273"],"issn":["0950-5849"],"journaltitle":["Inf. Softw. Technol."],"keywords":["Dynamic analysis","Machine learning algorithms","Malware","Random Forest","Static analysis"],"pages":["106273"],"title":["Detection of malicious software by analyzing the behavioral artifacts using machine learning algorithms"],"volume":["121"]},"creators":{"author":[{"lastName":"Singh","firstName":"Jagsir"},{"lastName":"Singh","firstName":"Jaswinder"}]},"sentenceCased":true},{"key":"sinnapoluIntegratingWearablesCloudbased2018","type":"article","fields":{"langid":["english"],"abstract":["Researchers and physicians have come a long way in inventing various types of wearable devices for health monitoring which makes it easier for medical professionals to monitor patients. Considering a situation, when a patient is driving, his/her health cannot be monitored or assisted immediately in case of emergency due to enormous drawbacks in the communication or the reporting system which is of today’s prime issue. The cloud-based communication helps solving the issue to some extent but inventing an application to integrate any wearable device to the Internet of things (IoT) and the cloud, considering portability and robustness will solve the prime issue. In this paper, we demonstrate a prototype working model along with the healthdetect iOS app for monitoring health data (heart rate) using wearables, if a serious heart rate data is detected by this app, from proximity sensor on the wearables, the microcontroller in the vehicle enables the healthlocateapp to locate and route to the nearest hospitals for the driver to drive. If the condition is critical and he/she is not responding for in-vehicle button press or driver related activity, then the microcontroller sends CAN message to activate the auto pilot to pull over for assistance."],"author":["Sinnapolu, GiriBabu","Alawneh, Shadi"],"date":["2018-09"],"doi":["10.1016/j.iot.2018.08.004"],"issn":["25426605"],"journaltitle":["Internet Things"],"pages":["40–54"],"title":["Integrating wearables with cloud-based communication for health monitoring and emergency assistance"],"volume":["1–2"]},"creators":{"author":[{"lastName":"Sinnapolu","firstName":"GiriBabu"},{"lastName":"Alawneh","firstName":"Shadi"}]},"sentenceCased":true},{"key":"Šircelj20206290","type":"inproceedings","fields":{"abstract":["With more research published on adversarial examples, we face a growing need for strong and insightful methods for evaluating the robustness of machine learning solutions against their adversarial threats. Previous work contains problematic and overly simplified evaluation methods, where different methods for generating adversarial examples are compared, even though they produce adversarial examples of differing perturbation magnitudes. This creates a biased evaluation environment, as higher perturbations yield naturally stronger adversarial examples. We propose a novel “accuracy-perturbation curve” that visualizes a classifiers classification accuracy response to adversarial examples of different perturbations. To demonstrate the utility of the curve we perform evaluation of responses of different image classifier architectures to four popular adversarial example methods. We also show how adversarial training improves the robustness of a classifier using the “accuracy-perturbation curve”. © 2020 IEEE"],"art_number":["9413143"],"author":["Šircelj, J.","Skočaj, D."],"coden":["PICRE"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/ICPR48806.2021.9413143"],"isbn":["978-1-72818-808-9"],"issn":["10514651"],"keywords":["Classification accuracy","Image Classifiers","Pattern recognition","Simplified evaluations","Software engineering"],"note":["cited By 1 \n\nTL;DR \n\nThis work proposes a novel “accuracy-perturbation curve” that visualizes a classifiers classification accuracy response to adversarial examples of different perturbations, and shows how adversarial training improves the robustness of a classifier using the “ Accumulation curve’."],"pages":["6290–6297"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - International Conference on Pattern Recognition"],"source":["Scopus"],"title":["Accuracy-perturbation curves for evaluation of adversarial attack and defence methods"]},"creators":{"author":[{"lastName":"Šircelj","firstName":"J."},{"lastName":"Skočaj","firstName":"D."}]},"sentenceCased":true},{"key":"sirresAugmentingStructuringUser2018","type":"article","fields":{"abstract":["Source code terms such as method names and variable types are often different from conceptual words mentioned in a search query. This vocabulary mismatch problem can make code search inefficient. In this paper, we present COde voCABUlary (CoCaBu), an approach to resolving the vocabulary mismatch problem when dealing with free-form code search queries. Our approach leverages common developer questions and the associated expert answers to augment user queries with the relevant, but missing, structural code entities in order to improve the performance of matching relevant code examples within large code repositories. To instantiate this approach, we build GitSearch, a code search engine, on top of GitHub and Stack Overflow Q&A data. We evaluate GitSearch in several dimensions to demonstrate that (1) its code search results are correct with respect to user-accepted answers; (2) the results are qualitatively better than those of existing Internet-scale code search engines; (3) our engine is competitive against web search engines, such as Google, in helping users solve programming tasks; and (4) GitSearch provides code examples that are acceptable or interesting to the community as answers for Stack Overflow questions."],"acmid":["3182513"],"author":["Sirres, Raphael","Bissyandé, Tegawendé F.","Kim, Dongsun","Lo, David","Klein, Jacques","Kim, Kisub","Traon, Yves Le"],"date":["2018-10-01"],"doi":["10.1007/s10664-017-9544-y"],"issn":["1573-7616"],"journaltitle":["Proc. 40th Int. Conf. Softw. Eng."],"location":["Gothenburg, Sweden"],"nodoi":["10.1145/3180155.3182513"],"note":["TL;DR \n\nThis paper builds GitSearch, a code search engine on top of GitHub and Stack Overflow Q&amp;A data that leverages common developer questions and the associated expert answers to augment user queries with the relevant, but missing, structural code entities in order to improve the performance of matching relevant code examples within large code repositories."],"number":["5"],"numpages":["1"],"pages":["2622–2654"],"series":["ICSE '18"],"title":["Augmenting and structuring user queries to support efficient free-form code search"],"volume":["23"]},"creators":{"author":[{"lastName":"Sirres","firstName":"Raphael"},{"lastName":"Bissyandé","firstName":"Tegawendé F."},{"lastName":"Kim","firstName":"Dongsun"},{"lastName":"Lo","firstName":"David"},{"lastName":"Klein","firstName":"Jacques"},{"lastName":"Kim","firstName":"Kisub"},{"lastName":"Traon","firstName":"Yves Le"}]},"sentenceCased":true},{"key":"sivieriBuildingInternetThings2016","type":"article","fields":{"langid":["english"],"author":["Sivieri, Alessandro","Mottola, Luca","Cugola, Gianpaolo"],"date":["2016-02"],"doi":["10.1016/j.comcom.2016.02.004"],"issn":["01403664"],"journaltitle":["Comput. Commun."],"title":["Building Internet of Things software with ELIoT"]},"creators":{"author":[{"lastName":"Sivieri","firstName":"Alessandro"},{"lastName":"Mottola","firstName":"Luca"},{"lastName":"Cugola","firstName":"Gianpaolo"}]},"sentenceCased":true},{"key":"SmartAnythingEverywhere","type":"online","fields":{"title":["Smart Anything Everywhere | EU H2020"],"url":["https://smartanythingeverywhere.eu/"],"urldate":["2015-04-08"]},"creators":{}},{"key":"SMR:SMR567","type":"article","fields":{"author":["Dit, Bogdan","Revelle, Meghan","Gethers, Malcom","Poshyvanyk, Denys"],"date":["2013"],"issn":["2047-7481"],"journaltitle":["J. Softw. Evol. Process"],"keywords":["concept location","Feature location","program comprehension","software maintenance and evolution"],"nodoi":["10.1002/smr.567"],"note":["TL;DR \n\nA systematic literature survey of feature location techniques is presented and eighty‐nine articles from 25 venues have been reviewed and classified within the taxonomy in order to organize and structure existing work in the field of feature locations."],"number":["1"],"pages":["53–95"],"publisher":["John Wiley & Sons, Ltd"],"title":["Feature location in source code: A taxonomy and survey"],"url":["http://dx.doi.org/10.1002/smr.567"],"volume":["25"]},"creators":{"author":[{"lastName":"Dit","firstName":"Bogdan"},{"lastName":"Revelle","firstName":"Meghan"},{"lastName":"Gethers","firstName":"Malcom"},{"lastName":"Poshyvanyk","firstName":"Denys"}]},"sentenceCased":true},{"key":"sobania2023analysis","type":"misc","fields":{"author":["Sobania, Dominik","Briesch, Martin","Hanna, Carol","Petke, Justyna"],"date":["2023"],"eprint":["2301.08653"],"eprintclass":["cs.SE"],"eprinttype":["arxiv"],"title":["An analysis of the automatic bug fixing performance of ChatGPT"]},"creators":{"author":[{"lastName":"Sobania","firstName":"Dominik"},{"lastName":"Briesch","firstName":"Martin"},{"lastName":"Hanna","firstName":"Carol"},{"lastName":"Petke","firstName":"Justyna"}]},"sentenceCased":true},{"key":"soeken2010verifying","type":"inproceedings","fields":{"langid":["english"],"author":["Soeken, Mathias","Wille, Robert","Kuhlmann, Mirco","Gogolla, Martin","Drechsler, Rolf"],"booktitle":["2010 Des. Autom. Test Eur. Conf. Exhib. DATE 2010"],"date":["2010"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper describes how the respective components of a verification problem, namely system states of a UML model, OCL constraints, and the actual verification task, can be encoded and afterwards automatically solved using an off-the-shelf SAT solver."],"pages":["1341–1344"],"publisher":["IEEE"],"title":["Verifying UML/OCL models using boolean satisfiability"]},"creators":{"author":[{"lastName":"Soeken","firstName":"Mathias"},{"lastName":"Wille","firstName":"Robert"},{"lastName":"Kuhlmann","firstName":"Mirco"},{"lastName":"Gogolla","firstName":"Martin"},{"lastName":"Drechsler","firstName":"Rolf"}]},"sentenceCased":true},{"key":"SoftwareEngineeringSelfAdaptive","type":"online","fields":{"title":["Software Engineering for Self-Adaptive Systems: A Second Research Roadmap - Springer"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-35813-5_1"],"urldate":["2016-02-17"]},"creators":{}},{"key":"soldatosBuildingBlocksIoT2016","type":"incollection","fields":{"langid":["english"],"author":["Soldatos, John"],"date":["2016"],"doi":["10.13052/rp-9788793519046"],"keywords":["Data analysis","DONE","internet of things"],"note":["TL;DR \n\nIoT analytics will be a major contributor to IoT business value in the coming years, as it will enable organizations to process and fully leverage large amounts of IoT data, which are nowadays largely underutilized."],"pages":["1–294"],"title":["Building Blocks for IoT Analytics"]},"creators":{"author":[{"lastName":"Soldatos","firstName":"John"}]}},{"key":"song2016machine","type":"article","fields":{"author":["Song, Qinbao","Zhu, Xiaoyan","Wang, Guangtao","Sun, Heli","Jiang, He","Xue, Chenhao","Xu, Baowen","Song, Wei"],"date":["2016"],"journaltitle":["J. Syst. Softw."],"note":["TL;DR \n\nA software process model automatically recommendation framework is proposed and different machine learning technologies are used to construct the recommendation models."],"pages":["85–100"],"publisher":["Elsevier"],"title":["A machine learning based software process model recommendation method"],"volume":["118"]},"creators":{"author":[{"lastName":"Song","firstName":"Qinbao"},{"lastName":"Zhu","firstName":"Xiaoyan"},{"lastName":"Wang","firstName":"Guangtao"},{"lastName":"Sun","firstName":"Heli"},{"lastName":"Jiang","firstName":"He"},{"lastName":"Xue","firstName":"Chenhao"},{"lastName":"Xu","firstName":"Baowen"},{"lastName":"Song","firstName":"Wei"}]},"sentenceCased":true},{"key":"spearmanProofMeasurementAssociation1904","type":"article","fields":{"author":["Spearman, Charles"],"date":["1904"],"journaltitle":["Am. J. Psychol."],"number":["1"],"pages":["72–101"],"publisher":["JSTOR"],"title":["The proof and measurement of association between two things"],"volume":["15"]},"creators":{"author":[{"lastName":"Spearman","firstName":"Charles"}]},"sentenceCased":true},{"key":"spin","type":"book","fields":{"langid":["english"],"author":["Holzmann, Gerard J."],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2004"],"isbn":["978-0-321-22862-8"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis is the most comprehensive reference guide to SPIN, written by the principal designer of the tool, and gives detailed advice on methods for tackling the most complex software verification problems."],"publisher":["Addison-Wesley"],"timestamp":["Thu, 14 Apr 2011 14:43:24 +0200"],"title":["The SPIN model checker - primer and reference manual"]},"creators":{"author":[{"lastName":"Holzmann","firstName":"Gerard J."}]},"sentenceCased":true},{"key":"spinellisSoftwareEngineeringInternetThings2017","type":"article","fields":{"author":["Spinellis, Diomidis"],"date":["2017"],"journaltitle":["IEEE Softw."],"keywords":["internet of things","iot"],"note":["TL;DR \n\nNew wiring transformed ENIAC into a versatile stored-program computer into a general-purpose computing fabric that changed how modern computation interfaces with the authors' environment."],"number":["1"],"pages":["4–6"],"title":["Software-Engineering the Internet of Things"],"url":["http://ieeexplore.ieee.org/abstract/document/7819398/"],"urldate":["2017-02-27"],"volume":["34"]},"creators":{"author":[{"lastName":"Spinellis","firstName":"Diomidis"}]}},{"key":"spinellisSuccessHeavenlyMarriage2018","type":"article","fields":{"abstract":["For a field that sprang out of a so-called software crisis, software engineering has done rather well over the past half-century. By riding on the coattails of Moore’s law, it has progressed phenomenally. The field’s achievements are visible through the large, complex, yet effective software systems that power our everyday lives. By looking at the drivers of the field’s progress and taking stock of its achievements, we can appreciate the challenges in front of us and confidently plan for the future. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Spinellis, D."],"date":["2018-09"],"doi":["10.1109/MS.2018.3571251"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nFor a field that sprang out of a so-called software crisis, software engineering has done rather well over the past half-century by riding on the coattails of Moore’s law."],"number":["5"],"pages":["3–6"],"title":["The Success of a Heavenly Marriage"],"volume":["35"]},"creators":{"author":[{"lastName":"Spinellis","firstName":"D."}]}},{"key":"spoletini_bias-aware_2018","type":"inproceedings","fields":{"abstract":["This innovative practice work in progress paper tackles the problem of unfairness and bias in software, that recently has emerged in countless cases. This unfairness can be present in the way software makes its decision or can limit the software functionalities to work only with certain populations. Well-known examples of this problem are the Microsoft Kinect facial recognition algorithm, which does not work properly with darker skin players, and the software used in 2016 by Amazon.com to determine the parts of the United States to which offer free same-day delivery that made decisions that prevented minority neighborhoods from participating in the program. The reasons behind these phenomena have often roots in the fact that software is created by humans who are biased and live in biased and non-inclusive environments. Recent research from the software engineering community is starting to tackle this problem at many levels from requirements analysis to the new automatic fairness testing technique (proposed first at FSE 2017 conference). However, research in bias of software is still a very undervalued and rarely discussed problem as software is often seen as a product immune to bias and non-inclusivity. This problem will be not addressed unless software engineering educators start to include this notion as a first-class problem in their foundation courses to future generation of scholars. In this work, we propose a set of bias-aware guidelines and taxonomy on how to flesh out this problem and possible solutions to it in software engineering curricula."],"author":["Spoletini, Paola","Parizi, Reza M."],"booktitle":["2018 IEEE Front. Educ. Conf. FIE"],"date":["2018-10"],"doi":["10.1109/FIE.2018.8659178"],"keywords":["Cultural differences","Ethics","Fairness","Software","Software engineering","Software engineering curricula","Software engineering education","Taxonomy","Testing","Tools"],"note":["ISSN: 2377-634X \n\nTL;DR \n\nA set of bias-aware guidelines and taxonomy on how to flesh out this problem of unfairness and bias in software and possible solutions to it in software engineering curricula are proposed."],"pages":["1–4"],"title":["Bias-aware guidelines and fairness-preserving Taxonomy in software engineering education"]},"creators":{"author":[{"lastName":"Spoletini","firstName":"Paola"},{"lastName":"Parizi","firstName":"Reza M."}]},"sentenceCased":true},{"key":"SprinkleK04","type":"article","fields":{"langid":["english"],"author":["Sprinkle, Jonathan","Karsai, Gabor"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2004"],"doi":["10.1016/J.JVLC.2004.01.006"],"journaltitle":["J. Vis. Lang. Comput."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["3-4"],"pages":["291–307"],"timestamp":["Fri, 09 Apr 2021 18:34:20 +0200"],"title":["A domain-specific visual language for domain model evolution"],"volume":["15"]},"creators":{"author":[{"lastName":"Sprinkle","firstName":"Jonathan"},{"lastName":"Karsai","firstName":"Gabor"}]},"sentenceCased":true},{"key":"Spruegel2018","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. NordDesign: Des. Era Digitalization, NordDesign"],"affiliation":["Friedrich-Alexander-Universität Erlangen-Nürnberg, Lehrstuhl für Konstruktionstechnik, Germany"],"author":["Spruegel, T.C.","Rothfelder, R.","Bickel, S.","Grauf, A.","Sauer, C.","Schleich, B.","Wartzack, S."],"date":["2018"],"document_type":["Conference Paper"],"isbn":["978-91-7685-185-2"],"note":["cited By 6 \n\nTL;DR \n\nAn approach to transfer different FE meshes, corresponding FE results and boundary conditions to an individual matrix of fixed size for very different structural mechanic FE simulation, using spherical detector surfaces to project three-dimensional information on its surface."],"publisher":["The Design Society"],"series":["Proceedings of NordDesign: Design in the Era of Digitalization, NordDesign 2018"],"source":["Scopus"],"title":["Methodology for plausibility checking of structural mechanics simulations using Deep Learning on existing simulation data"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057150108&partnerID=40&md5=3fa21ccaf4f28ff72326348e85cbde09"]},"creators":{"author":[{"lastName":"Spruegel","firstName":"T.C."},{"lastName":"Rothfelder","firstName":"R."},{"lastName":"Bickel","firstName":"S."},{"lastName":"Grauf","firstName":"A."},{"lastName":"Sauer","firstName":"C."},{"lastName":"Schleich","firstName":"B."},{"lastName":"Wartzack","firstName":"S."}]},"sentenceCased":true},{"key":"Sridhar2020351","type":"inproceedings","fields":{"abstract":["As the influence of machine learning grows over decisions in businesses and human life, so grows the need for Model Governance. In this paper, we motivate the need for, define the problem of, and propose a solution for Model Governance in production ML. We show that through our approach one can meaningfully track and understand the who, where, what, when, and how an ML prediction came to be. To the best of our knowledge, this is the first work providing a comprehensive framework for production Model Governance, building upon previous work in developer-focused Model Management. © Proceedings of the 2018 USENIX Annual Technical Conference, USENIX ATC 2018. All rights reserved."],"author":["Sridhar, V.","Subramanian, S.","Arteaga, D.","Sundararaman, S.","Roselli, D.","Talagala, N."],"date":["2020"],"document_type":["Conference Paper"],"isbn":["978-1-939133-02-1"],"note":["cited By 15"],"pages":["351–357"],"publisher":["USENIX Association"],"series":["Proceedings of the 2018 USENIX Annual Technical Conference, USENIX ATC 2018"],"source":["Scopus"],"title":["Model governance: Reducing the anarchy of production ML"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075761598&partnerID=40&md5=393aa3aa505e90fb80de134aad651b4f"]},"creators":{"author":[{"lastName":"Sridhar","firstName":"V."},{"lastName":"Subramanian","firstName":"S."},{"lastName":"Arteaga","firstName":"D."},{"lastName":"Sundararaman","firstName":"S."},{"lastName":"Roselli","firstName":"D."},{"lastName":"Talagala","firstName":"N."}]},"sentenceCased":true},{"key":"srinivasanWebAppSecurity2017","type":"article","fields":{"abstract":["Web app developers often face challenges in using the many available security-testing frameworks, owing to those frameworks' inherent complexity and the lack of proper documentation. No up-to-date criteria exist that can help practitioners and organizations select an appropriate framework. Consequently, numerous vulnerabilities go undetected in the final product, creating a potential for major attacks. To help practitioners select the right framework, researchers classified 26 frameworks, using 27 criteria."],"author":["Srinivasan, Satish M.","Sangwan, Raghvinder S.","undefined","undefined","undefined","undefined"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["software engineering"],"note":["TL;DR \n\nTo help practitioners select the right framework, researchers classified 26 frameworks, using 27 criteria, to help practitioners and organizations select an appropriate framework."],"number":["1"],"pages":["99–102"],"shorttitle":["Web App Security"],"title":["Web App Security: A Comparison and Categorization of Testing Frameworks"],"volume":["34"]},"creators":{"author":[{"lastName":"Srinivasan","firstName":"Satish M."},{"lastName":"Sangwan","firstName":"Raghvinder S."},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"sriramInternetThingsPerspectives2015","type":"article","fields":{"author":["Sriram, Ram D.","Sheth, Amit"],"date":["2015-05"],"doi":["10.1109/MITP.2015.43"],"issn":["1520-9202"],"journaltitle":["IT Prof."],"number":["3"],"pages":["60–63"],"title":["Internet of Things Perspectives"],"volume":["17"]},"creators":{"author":[{"lastName":"Sriram","firstName":"Ram D."},{"lastName":"Sheth","firstName":"Amit"}]}},{"key":"SS04","type":"article","fields":{"author":["Spinellis, D.","Szyperski, C."],"date":["2004-01"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["Automation","Business communication","Law","Licenses","Open source software","Operating systems","Packaging","Programming","Software libraries","Software packages"],"note":["TL;DR \n\nThe software development process is gaining from the widespread availability and use of sophisticated open source development platforms and tools, and the adoption of corresponding development and coding practices by the programmer community."],"number":["1"],"pages":["28–33"],"title":["How is open source affecting software development?"],"volume":["21"]},"creators":{"author":[{"lastName":"Spinellis","firstName":"D."},{"lastName":"Szyperski","firstName":"C."}]},"sentenceCased":true},{"key":"staab2010model","type":"incollection","fields":{"langid":["english"],"author":["Staab, Steffen","Walter, Tobias","Gröner, Gerd","Parreiras, Fernando Silva"],"booktitle":["Reasoning web international summer school"],"date":["2010"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nIt will turn out that ontology-based metamodels constitute a core means for exploiting expressive ontology reasoning in the software modeling domain while remaining flexible enough to accommodate varying needs of software modelers."],"pages":["62–98"],"title":["Model driven engineering with ontology technologies"]},"creators":{"author":[{"lastName":"Staab","firstName":"Steffen"},{"lastName":"Walter","firstName":"Tobias"},{"lastName":"Gröner","firstName":"Gerd"},{"lastName":"Parreiras","firstName":"Fernando Silva"}]},"sentenceCased":true},{"key":"stahlModeldrivenSoftwareDevelopment2006","type":"book","fields":{"langid":["english"],"author":["Stahl, Thomas","Völter, Markus"],"date":["2006"],"isbn":["978-0-470-02570-3"],"keywords":["Computer software","Development","Model-driven software architecture"],"location":["Chichester, England ; Hoboken, NJ"],"note":["TL;DR \n\nMDSD Tools: Roles, Architecture, SelectionCriteria, Selection Criteria, and Pointers, and MDSD Process Building Blocks and Best Practices."],"pagetotal":["428"],"publisher":["John Wiley"],"shorttitle":["Model-driven software development"],"title":["Model-driven software development: Technology, engineering, management"]},"creators":{"author":[{"lastName":"Stahl","firstName":"Thomas"},{"lastName":"Völter","firstName":"Markus"}]},"sentenceCased":true},{"key":"stankovicResearchDirectionsInternet2014","type":"article","fields":{"author":["Stankovic, John A."],"date":["2014-02"],"doi":["10.1109/JIOT.2014.2312291"],"ids":["stankovicResearchDirectionsInternet2014a"],"issn":["2327-4662"],"journaltitle":["IEEE Internet Things J."],"number":["1"],"pages":["3–9"],"title":["Research Directions for the Internet of Things"],"volume":["1"]},"creators":{"author":[{"lastName":"Stankovic","firstName":"John A."}]}},{"key":"stansburyGraduateProgramUnmanned2015","type":"article","fields":{"author":["Stansbury, Richard S.","Moncayo, Hever","Currier, Patrick"],"date":["2015"],"note":["TL;DR \n\nA detailed overview of the MSUASE program, its mission, objectives, and student outputs are provided including research projects used for capstone and thesis opportunities and issues related to the International Trade of Armaments Regulations (ITAR) will be discussed."],"title":["A Graduate Program in Unmanned and Autonomous Systems Engineering"],"url":["http://se.asee.org/proceedings/ASEE2015/papers2015/79.pdf"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Stansbury","firstName":"Richard S."},{"lastName":"Moncayo","firstName":"Hever"},{"lastName":"Currier","firstName":"Patrick"}]}},{"key":"staticRegistroCronologiaDi","type":"software","fields":{"abstract":["Dati della cronologia di lettura salvati da Chartero. NON modificare!"],"author":["static, volatile"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["chartero#33BF2A43{\"pages\":{\"0\":{\"p\":{\"1712269361\":1,\"1712269362\":1,\"1712269363\":1,\"1712269364\":1,\"1712269365\":1,\"1712269366\":1,\"1712269367\":1,\"1712269368\":1,\"1712269369\":1,\"1712269370\":1,\"1712269371\":1,\"1712269372\":1,\"1712269373\":1,\"1712269374\":1,\"1712269375\":1,\"1712269376\":1,\"1712269377\":1,\"1712269378\":1,\"1712269379\":1,\"1712269380\":1,\"1712269386\":1,\"1712269387\":1}},\"3\":{\"p\":{\"1712269385\":1}},\"5\":{\"p\":{\"1712269357\":1,\"1712269359\":1,\"1712269360\":1}}},\"numPages\":10} \n\nchartero#EYEUBGCW{\"pages\":{\"0\":{\"p\":{\"1712269395\":1,\"1712269396\":1,\"1712269397\":1,\"1712269398\":1,\"1712269399\":1}},\"5\":{\"p\":{\"1712269400\":1,\"1712269401\":1,\"1712269402\":1,\"1712269403\":1}},\"6\":{\"p\":{\"1712269404\":1,\"1712269405\":1,\"1712269406\":1,\"1712269407\":1}}},\"numPages\":26} 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\n\nchartero#I879APBF{\"pages\":{\"0\":{\"p\":{\"1712269734\":1,\"1712269735\":1,\"1712269741\":1}},\"1\":{\"p\":{\"1712269736\":1,\"1712269737\":1,\"1712269740\":1,\"1712269742\":1,\"1712269743\":1,\"1712269744\":1}},\"20\":{\"p\":{\"1712269733\":1}},\"30\":{\"p\":{\"1712269730\":1,\"1712269732\":1}}},\"numPages\":32} \n\nchartero#IG9WPQ8Z{\"pages\":{\"0\":{\"p\":{\"1712317131\":1}}},\"numPages\":22} \n\nchartero#ZH4DWQ5U{\"pages\":{\"15\":{\"p\":{\"1712269725\":1,\"1712269726\":1}}},\"numPages\":16} \n\nchartero#ZL97YJGC{\"pages\":{\"0\":{\"p\":{\"1712311103\":1}}},\"numPages\":20}"],"shorttitle":["Chartero"],"title":["Registro della cronologia di lettura"],"url":["https://github.com/volatile-static/Chartero"]},"creators":{"author":[{"lastName":"static","firstName":"volatile"}]},"sentenceCased":true},{"key":"steinbach00comparison","type":"inproceedings","fields":{"added-at":["2007-01-09T09:03:22.000+0100"],"author":["Steinbach, M.","Karypis, G.","Kumar, 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techniques"],"url":["http://citeseer.ist.psu.edu/steinbach00comparison.html"]},"creators":{"author":[{"lastName":"Steinbach","firstName":"M."},{"lastName":"Karypis","firstName":"G."},{"lastName":"Kumar","firstName":"V."}]},"sentenceCased":true},{"key":"Stephan201921","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - IEEE/ACM Int. Conf. Softw. Eng.: New Ideas Emerg. Results, ICSE-NIER"],"affiliation":["Department of Computer Science and Software Engineering, Miami University, Oxford, OH, United States"],"art_number":["8805738"],"author":["Stephan, M."],"correspondence_address1":["Stephan, M.; Department of Computer Science and Software Engineering, United States; email: stephamd@miamioh.edu"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/ICSE-NIER.2019.00014"],"isbn":["978-1-72811-758-4"],"keywords":["GOAL_Model-Assistance","notion"],"note":["cited By 8 \n\nHIGH LEVEL. NO SPECIFIC TECHNIQUES ARE MENTIONED. \n\nTL;DR \n\nThe vision in realizing a cognizant virtual software modeling assistant that provides suggestions to modelers performing model creation or extension in the form of complete models for insertion or guidance, and granular single-step operations is described."],"pages":["21–24"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2019 IEEE/ACM 41st International Conference on Software Engineering: New Ideas and Emerging Results, ICSE-NIER 2019"],"source":["Scopus"],"title":["Towards a cognizant virtual software modeling assistant using model clones"]},"creators":{"author":[{"lastName":"Stephan","firstName":"M."}]},"sentenceCased":true},{"key":"stereotypes2004","type":"inproceedings","fields":{"author":["Jiang","Yanbing, Weizhong Shao, Zhiyi Ma, Xiangwen Meng, Lu Zhang","Ma., Haohai"],"booktitle":["Int. Conf. Unified Model. 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The algorithms that control their movements are learning as the technology emerges. Self-driving cars represent a high-stakes test of the powers of machine learning, as well as a test case for social learning in technology governance. Society is learning about the technology while the technology learns about society. Understanding and governing the politics of this technology means asking ‘Who is learning, what are they learning and how are they learning?’ Focusing on the successes and failures of social learning around the much-publicized crash of a Tesla Model S in 2016, I argue that trajectories and rhetorics of machine learning in transport pose a substantial governance challenge. ‘Self-driving’ or ‘autonomous’ cars are misnamed. As with other technologies, they are shaped by assumptions about social needs, solvable problems, and economic opportunities. Governing these technologies in the public interest means improving social learning by constructively engaging with the contingencies of machine learning."],"author":["Stilgoe, Jack"],"date":["2018"],"journaltitle":["Soc. Stud. Sci."],"nodoi":["10.1177/0306312717741687"],"note":["PMID: 29160165 \n\nPMID: 29160165 \n\nTL;DR \n\nFocusing on the successes and failures of social learning around the much-publicized crash of a Tesla Model S in 2016, it is argued that trajectories and rhetorics of machine learning in transport pose a substantial governance challenge."],"number":["1"],"pages":["25–56"],"title":["Machine learning, social learning and the governance of self-driving cars"],"volume":["48"]},"creators":{"author":[{"lastName":"Stilgoe","firstName":"Jack"}]},"sentenceCased":true},{"key":"stolABCSoftwareEngineering2018","type":"article","fields":{"langid":["english"],"author":["Stol, Klaas-Jan","Fitzgerald, Brian"],"date":["2018-09-17"],"doi":["10.1145/3241743"],"issn":["1049331X"],"journaltitle":["ACM Trans. Softw. Eng. Methodol."],"note":["TL;DR \n\nA taxonomy from the social sciences is adopted, termed here the ABC framework for SE research, which offers a holistic view of eight archetypal research strategies, and six ways in which the framework can advance SE research."],"number":["3"],"pages":["1–51"],"title":["The ABC of Software Engineering Research"],"volume":["27"]},"creators":{"author":[{"lastName":"Stol","firstName":"Klaas-Jan"},{"lastName":"Fitzgerald","firstName":"Brian"}]}},{"key":"storzAnnotateTrainEvaluate2013","type":"article","fields":{"abstract":["The development of classifiers for object detection in images is a complex task that comprises the creation of representative and potentially large datasets from a target object by repetitive and time-consuming intellectual annotations, followed by a sequence of methods to train, evaluate and optimize the generated classifier. This is conventionally achieved by the usage and combination of many different tools. Here, we present a holistic approach to this scenario by providing a unified tool that covers the single development stages in one solution to facilitate the development process. We prove this concept by the example of creating a face detection classifier. © 2013 Springer-Verlag."],"author":["Storz, M.","Ritter, M.","Manthey, R.","Lietz, H.","Eibl, M."],"date":["2013"],"doi":["10.1007/978-3-642-39342-6_22"],"isbn":["9783642393419"],"issn":["03029743"],"issue":["PART 5"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"keywords":["Development process","Development stages","Holistic approach","Human computer interaction","Image processing","Large datasets","Learning systems","Model-driven","Object Detection","Object recognition","Target object","Tools","Workflow analysis"],"note":["cited By 3 \n\nTL;DR \n\nA holistic approach to the development of classifiers for object detection in images is presented by providing a unified tool that covers the single development stages in one solution to facilitate the development process."],"pages":["196–205"],"title":["Annotate. Train. Evaluate. A unified tool for the analysis and visualization of workflows in machine learning applied to object detection"],"volume":["8008 LNCS"]},"creators":{"author":[{"lastName":"Storz","firstName":"M."},{"lastName":"Ritter","firstName":"M."},{"lastName":"Manthey","firstName":"R."},{"lastName":"Lietz","firstName":"H."},{"lastName":"Eibl","firstName":"M."}]},"sentenceCased":true},{"key":"strittmatter2016challenges","type":"article","fields":{"author":["Syriani, Eugene","Gray, Jeff"],"date":["2016"],"doi":["10.1109/ICST.2012.198"],"journaltitle":["CEUR Workshop Proc."],"keywords":["duplicate-citation-key"],"note":["TL;DR \n\nThis paper proposes solution ideas to assist modelers in developing high quality transformation models by proposing to initiate a design pattern movement in the context of model transformation to satisfy quality attributes identified beforehand."],"pages":["30–39"],"title":["Challenges for Addressing Quality Factors in Model Transformation"],"volume":["1706"]},"creators":{"author":[{"lastName":"Syriani","firstName":"Eugene"},{"lastName":"Gray","firstName":"Jeff"}]}},{"key":"strittmatter2016challenges","type":"article","fields":{"langid":["english"],"abstract":["In model-driven engineering, modeling languages are developed to serve as basis for system design, simulation and code generation. Like any software artifact, modeling languages evolve over time. If, however, the metamodel that defines the language is badly designed, the effort needed for its maintenance is unnecessarily increased. In this paper, we present bad smells and anti-patterns that we discovered in a thorough metamodel review of the Palladio Component Model (PCM). The PCM is a good representative for big and old metamodels that have grown over time. Thus, these results are meaningful, as they reflect the types of smells that accumulate in such metamodels over time. Related work deals mainly with automatically detectable bad smells, anti-patterns and defects. However, there are smells and anti-patterns, which cannot be detected automatically. They should not be neglected. Thus, in this paper, we focus on both: automatically and non-automatically detectable smells."],"author":["Strittmatter, Misha","Hinkel, Georg","Langhammer, Michael"],"date":["2016"],"journaltitle":["CEUR Workshop Proc."],"keywords":["duplicate-citation-key"],"note":["TL;DR \n\nThis paper presents bad smells and anti-patterns that were discovered in a thorough metamodel review of the Palladio Component Model (PCM)."],"pages":["30–39"],"title":["Challenges in the Evolution of Metamodels: Smells and Anti-Patterns of a Historically-Grown Metamodel"],"volume":["1706"]},"creators":{"author":[{"lastName":"Strittmatter","firstName":"Misha"},{"lastName":"Hinkel","firstName":"Georg"},{"lastName":"Langhammer","firstName":"Michael"}]}},{"key":"strittmatterChallengesEvolvingMetamodels","type":"article","fields":{"langid":["english"],"abstract":["Like every other software artifact, metamodels are subject to change even in later phases of the software life cycle. In this problem description paper, we first classify metamodel changes. We then elaborate on the challenges of metamodel evolution. The main challenges are the tight coupling of code to metamodels and the pervasiveness of metamodel dependencies. As this is a problem description paper, we will only present a brief overview of possible solutions."],"author":["Strittmatter, Misha","Heinrich, Robert"],"note":["TL;DR \n\nThis problem description paper first classify metamodel changes, then elaborate on the challenges of metamodel evolution, and presents a brief overview of possible solutions."],"pages":["4"],"title":["Challenges in evolving Metamodels"]},"creators":{"author":[{"lastName":"Strittmatter","firstName":"Misha"},{"lastName":"Heinrich","firstName":"Robert"}]},"sentenceCased":true},{"key":"studerCRISPMLMachineLearning2021","type":"online","fields":{"abstract":["Machine learning is an established and frequently used technique in industry and academia but a standard process model to improve success and efficiency of machine learning applications is still missing. Project organizations and machine learning practitioners have a need for guidance throughout the life cycle of a machine learning application to meet business expectations. We therefore propose a process model for the development of machine learning applications, that covers six phases from defining the scope to maintaining the deployed machine learning application. The first phase combines business and data understanding as data availability oftentimes affects the feasibility of the project. The sixth phase covers state-of-the-art approaches for monitoring and maintenance of a machine learning applications, as the risk of model degradation in a changing environment is eminent. With each task of the process, we propose quality assurance methodology that is suitable to adress challenges in machine learning development that we identify in form of risks. The methodology is drawn from practical experience and scientific literature and has proven to be general and stable. The process model expands on CRISP-DM, a data mining process model that enjoys strong industry support but lacks to address machine learning specific tasks. Our work proposes an industry and application neutral process model tailored for machine learning applications with focus on technical tasks for quality assurance."],"author":["Studer, Stefan","Bui, Thanh Binh","Drescher, Christian","Hanuschkin, Alexander","Winkler, Ludwig","Peters, Steven","Mueller, Klaus-Robert"],"date":["2021-02-24"],"eprint":["2003.05155"],"eprintclass":["cs, stat"],"eprinttype":["arxiv"],"keywords":["Computer Science - Machine Learning","Computer Science - Software Engineering","Statistics - Machine Learning"],"note":["Comment: Machine Learning Applications, Quality Assurance Methodology, Process Model, Best Practices for Machine Learning Applications, Automotive Industry and Academia, Best Practices, Guidelines"],"pubstate":["preprint"],"shorttitle":["Towards CRISP-ML(Q)"],"title":["Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology"],"url":["http://arxiv.org/abs/2003.05155"],"urldate":["2022-08-04"]},"creators":{"author":[{"lastName":"Studer","firstName":"Stefan"},{"lastName":"Bui","firstName":"Thanh Binh"},{"lastName":"Drescher","firstName":"Christian"},{"lastName":"Hanuschkin","firstName":"Alexander"},{"lastName":"Winkler","firstName":"Ludwig"},{"lastName":"Peters","firstName":"Steven"},{"lastName":"Mueller","firstName":"Klaus-Robert"}]}},{"key":"Subahi2020","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Comput."],"affiliation":["Department of Computer Science, University College of Al Jamoum, Umm Al Qura University, P.O.Box 715, Mecca, Saudi Arabia"],"art_number":["27"],"author":["Subahi, A.F."],"correspondence_address1":["Subahi, A.F.; Department of Computer Science, P.O.Box 715, Saudi Arabia; email: AFSubahi@uqu.edu.sa"],"date":["2020"],"document_type":["Article"],"doi":["10.3390/computers9020027"],"issn":["2073431X"],"journaltitle":["Computers"],"keywords":["notion"],"note":["cited By 0"],"number":["2"],"publisher":["MDPI AG"],"source":["Scopus"],"title":["Cognification of program Synthesis—a systematic feature-oriented analysis and future direction"],"volume":["9"]},"creators":{"author":[{"lastName":"Subahi","firstName":"A.F."}]},"sentenceCased":true},{"key":"subramaniyaswamy_adaptive_2017","type":"article","fields":{"langid":["english"],"abstract":["Research for the generation of reliable recommendations has been the main goal focused by many researchers in recent years. Though many recommendation approaches have been developed to assist users in the selection of their interesting items in the online world, still the personalization problem exists. In this paper, we present a new recommendation approach to address the problems such as scalability, sparsity, and cold-start in a collective way. We have developed a knowledge-based domain specific ontology for the generation of personalized recommendations. We have also introduced two different ontology-based predictive models as minion representation model and prominent representation model for the effective generation of recommendations to all types of users. The prediction models are induced by data mining algorithms by correlating the user preferences and features of items for user modeling. We have proposed a new variant of KNN algorithm as Adaptive KNN for the collaborative filtering based recommender system. The proposed recommendation approach is validated with standard MovieLens dataset and obtained results are evaluated with Precision, Recall, F-Measure, and Accuracy. The experimental results had proved the better performance of our proposed AKNN algorithm over other algorithms with the highly sparse data taken for the recommendation generation."],"author":["Subramaniyaswamy, V.","Logesh, R."],"date":["2017-11"],"doi":["10.1007/s11277-017-4605-5"],"issn":["0929-6212, 1572-834X"],"journaltitle":["Wirel. Pers. Commun."],"number":["2"],"pages":["2229–2247"],"title":["Adaptive KNN based Recommender System through Mining of User Preferences"],"volume":["97"]},"creators":{"author":[{"lastName":"Subramaniyaswamy","firstName":"V."},{"lastName":"Logesh","firstName":"R."}]},"sentenceCased":true},{"key":"Suchänek202074","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["ENASE - Proc. Int. Conf. Eval. Novel Approaches Softw. Eng."],"affiliation":["Faculty of Information Technology, Czech Technical University in Prague, Thäkurova 9, Prague, Czech Republic; Normalized Systems Institute, University of Antwerp, Prinsstraat 13, Antwerp, Belgium; NSX Bvba, Wetenschapspark Universiteit Antwerpen, Galileilaan 15, Niel, 2845, Belgium"],"author":["Suchänek, M.","Mannaert, H.","Uhnäk, P.","Pergl, R."],"date":["2020"],"document_type":["Conference Paper"],"editor":["Ali R., Kaindl H., Maciaszek L., Maciaszek L."],"isbn":["978-989-758-421-3"],"note":["cited By 3 \n\nTL;DR \n\nThe potential advantages of having OWL representation of the NS model, the design of a bi-directional transformation between NS models and domain ontologies in OWL, and how the resulting ontology enables further work on the analytical level and leverages the system design are described."],"pages":["74–85"],"publisher":["SciTePress"],"series":["ENASE 2020 - Proceedings of the 15th International Conference on Evaluation of Novel Approaches to Software Engineering"],"source":["Scopus"],"title":["Bi-directional transformation between normalized systems elements and domain ontologies in OWL"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088385688&partnerID=40&md5=df36b44338dd85b1c2007e585a204b4d"]},"creators":{"author":[{"lastName":"Suchänek","firstName":"M."},{"lastName":"Mannaert","firstName":"H."},{"lastName":"Uhnäk","firstName":"P."},{"lastName":"Pergl","firstName":"R."}],"editor":[{"lastName":"Ali R.","suffix":"Kaindl H.","firstName":"Maciaszek L., Maciaszek L."}]},"sentenceCased":true},{"key":"Sun:2014:ESN:2627508.2627514","type":"inproceedings","fields":{"acmid":["2627514"],"author":["Sun, Xiaobing","Liu, Xiangyue","Hu, Jiajun","Zhu, Junwu"],"booktitle":["Proc. 2014 3rd Int Workshop Evidential Assess. Soft Tech"],"date":["2014"],"isbn":["978-1-4503-2965-1"],"keywords":["empirical studies","NLP techniques","Program comprehension","source code preprocessing"],"location":["New York, NY, USA"],"nodoi":["10.1145/2627508.2627514"],"note":["TL;DR \n\nThis paper conducts some empirical studies to show what are the differences before and after preprocessing the unstructured source code, and shows some interesting phenomena based on using or not using these preprocessing operations."],"numpages":["8"],"pages":["32–39"],"publisher":["ACM"],"series":["EAST 2014"],"title":["Empirical studies on the NLP techniques for source code data preprocessing"]},"creators":{"author":[{"lastName":"Sun","firstName":"Xiaobing"},{"lastName":"Liu","firstName":"Xiangyue"},{"lastName":"Hu","firstName":"Jiajun"},{"lastName":"Zhu","firstName":"Junwu"}]},"sentenceCased":true},{"key":"sunAIEnhancedOffloadingEdge2019","type":"article","fields":{"langid":["english"],"abstract":["The Industrial Internet of Things (IIoT) enables intelligent industrial operations by incorporating artificial intelligence (AI) and big data technologies. An AI-enabled framework typically requires prompt and private cloud-based service to process and aggregate manufacturing data. Thus, integrating intelligence into edge computing is without doubt a promising development trend. Nevertheless, edge intelligence brings heterogeneity to the edge servers, in terms of not only computing capability, but also service accuracy. Most works on offloading in edge computing focus on finding the power-delay trade-off, ignoring service accuracy provided by edge servers as well as the accuracy required by IIoT devices. In this vein, in this article we introduce an intelligent computing architecture with cooperative edge and cloud computing for IIoT. Based on the computing architecture, an AI enhanced offloading framework is proposed for service accuracy maximization, which considers service accuracy as a new metric besides delay, and intelligently disseminates the traffic to edge servers or through an appropriate path to remote cloud. A case study is performed on transfer learning to show the performance gain of the proposed framework."],"author":["Sun, Wen","Liu, Jiajia","Yue, Yanlin"],"date":["2019-09"],"doi":["10.1109/MNET.001.1800510"],"issn":["0890-8044, 1558-156X"],"journaltitle":["IEEE Network"],"keywords":["DONE","machine learning"],"note":["<b>Gray Annotations (17/12/2020, 23:14:22)</b> \n\n\"According to GE Digital, IIoT is estimated to unlock manufacturing savings and benefit 46 percent of the global economy [1]\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"Table 1 compares the existing works on AI applications in networks.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"Bisio et al. [10] studied the role of context awareness in IIoT applications such as smart health, smart factory, and smart home scenarios.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"Wang et al. [11] explored the trade-off between energy consumption and service latency in IIoT\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"Li et al. [13] applied deep learning for IoT in the edge computing environment. They designed a scheduling algorithm to maximize the number of tasks in edge computing with guaranteed quality of service (QoS) requirements.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n\"In [3], edge servers learn model parameters from data distributed at the edge nodes, using the gradient-descent method based on distributed learning, instead of sending data to the centralized cloud. They proposed a control algorithm for the trade-off between local update and global parameter aggregation to minimize loss function and under a given resource budget.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n\"[1] GE Digital Report, \"Everything You Need to Know about the Industrial Internet of Things,\" 2017; https://www.ge.com/ digital/blog/everything-you-needknow-about-industrial-internet-things\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=7\">Sun et al 2019:74</a>) \n\n<b>Green Annotations (17/12/2020, 23:14:22)</b> \n\n\"The Industrial Internet of Things (IIoT) enables intelligent industrial operations by incorporating artificial intelligence (AI) and big data technologies.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"An AI-enabled framework typically requires prompt and private cloud-based service to process and aggregate manufacturing data\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"integrating intelligence into edge computing is without doubt a promising development trend\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"edge intelligence brings heterogeneity to the edge servers, in terms of not only computing capability, but also service accuracy\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"this article we introduce an intelligent computing architecture with cooperative edge and cloud computing for IIoT\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"AI enhanced offloading framework is proposed for service accuracy maximization, which considers service accuracy as a new metric besides delay, and intelligently disseminates the traffic to edge servers or through an appropriate path to remote cloud.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"performance gain of the proposed framework\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"interconnects a multitude of industrial devices, actuators, and people at work\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"IIoT incorporates artificial intelligence (AI) technologies to process and analyze data from various sources and make advanced predictive analytics, such as fault class prediction, predictive maintenance, demand forecasting.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"smart manufacturing is a large connected and complex industrial process, which produces a large amount of multi-feature data, it is difficult to construct its operation process with an accurate mathematical model\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"AI algorithms are able to extract critical features without in-depth physical understanding of the concerned system\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"in IIoT, predictive maintenance relies on machine learning to detect anomalies in systems and then predict the failure of devices by correlating and analyzing the change in the pattern\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"IIoT typically requires prompt and private computing service to process and aggregate the manufacturing data\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"integrating intelligence into the edge is without doubt a promising development trend [2]\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"distributed computing service through small-scale data centers near the edge of the network.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"edge computing provides real-time data analytics with privacy preserving, increases network capabilities, and avoids congestion of backbone networks and the Internet core\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"Personalization: Customized AI models can be developed at the edge servers, which are tailored to individual users' behaviors and requirements to deliver accurate results to the users.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n<i>This might be related to the citizen developer / lowcode (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">note on p.68</a>)</i> \n\n\"Responsiveness: While the industrial process is time-varying and unpredictable, the computing service must be prompt and more adaptive and feasible to the new situation.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n<i>This might be related to the federated learning aspect mentioned by Luciano (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">note on p.68</a>)</i> \n\n\"Privacy Preserving: Especially for IIoT, the processing information owned by industrial companies may not be willing to transmit to the remote cloud for privacy issues; thus, the edge server provides private service.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"The AI service deployed on edge servers exhibits heterogeneity in terms of service accuracy due to the limited and heterogeneous computing capability of edge servers.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"The impacts of edge intelligence on computing offloading remains untouched.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"intelligent computing architecture with cooper-\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=1\">Sun et al 2019:68</a>) \n\n\"ative edge and cloud computing for IIoT. Then\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"AI enhanced offloading framework for service accuracy maximization is developed\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"service accuracy as a new metric besides delay,\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"intelligently disseminates the traffic to edge servers or through appropriate paths to remote cloud.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"Machine learning, as an application of AI, gives devices or computer systems the ability to \"learn\" with data without being explicitly programmed [2].\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"supervised learning conducts classification or regression tasks from labeled data\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"unsupervised learning categorizes the unlabeled data into clusters\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"Reinforcement learning indicates agents to take actions so as to maximize the cumulative reward\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"In IIoT, machine learning algorithms are leveraged to analyze the complex manufacturing data and believer insights about predictive maintenance, industrial prognostics, and demand forecasting.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"Generally, cloud computing is employed for data processing. However, it is difficult to transmit huge amounts of data to the remote cloud; thus, approximate and distributed computing service becomes necessary.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n<i>THIS IS A RELEVANT CASE, I.E., WHEN YOU CANNOT SEND HUDGE AMOUNT OF DATA TO THE CLOUD FOR PERFORMING DATA ANALYTICS TASKS!!! (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">note on p.69</a>)</i> \n\n\"There are edge servers that are actually designed for AI-enabled computing tasks such as the NVIDIA DGX workstation\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n\"analyzed video streams recorded on a number of surveillance cameras\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">Sun et al 2019:69</a>) \n\n<i>THIS MAKES SENSE FOR THE THE SCENARIO OF LUCIANO ON SMART BUILDING. IN SUCH CASES DATA NEED TO BE ANALYSED ON THE EDGE. (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=2\">note on p.69</a>)</i> \n\n\"The MEC application examined the video streams, classified what were normal and abnormal patterns, and then only needed to send the stream to the backbone when a potential security issue was identified.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n<i>YES! VERY IMPORTANT (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">note on p.70</a>)</i> \n\n\"AI tasks laid a heavy burden on edge servers with limited resources\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n\"Industrial MDs monitor the industrial parameters, and deliver the collected data to the data center for aggregation\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n\"The AI-enabled IIoT service includes self-monitoring, demand forecasting, fault detection, and workforce management.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n\"The decision is fed back to the IIoT devices and executed automatically.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n\"he intelligent computational architecture needs to be reshaped.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n\"two-layer intelligent data center, that is, edge layer and cloud layer\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n<i>THAT'S THE MAIN ARCHITECTURAL INNOVATION THAT THEY PROPOSE. (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">note on p.70</a>)</i> \n\n\"Edge Layer: It accommodates lightweight intelligent computing service for IIoT,\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n\"Cloud Layer: It provides powerful and comprehensive computing service for IIoT at the cost of latency and communication burden.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n\"The interaction between the edge layer and the cloud layer is at the cost of additional communication on the backbone network.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n\"how to deploy the computing service between the edge layer and cloud layer, and afterward assign the computing tasks of IIoT devices according to their requirements as well as the characteristics of heterogeneous edge servers and remote cloud, needs serious consideration.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">Sun et al 2019:70</a>) \n\n<i>THAT'S ANOTHER IMPORTANT *CHALLENGES* (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=3\">note on p.70</a>)</i> \n\n\"priority\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n\"accuracy\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n\"delay\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n\"(ui, ai, di), where ui is the degree of urgency of MD i, that is, priority (a scalar value within (0, 1)), and ai is the acceptable accuracy of MD i, and di is the acceptable delay of MD i\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n\"o choose an optimal jD i, it is imperative to estimate the delay and accuracy of offloading to available edge servers, and determine the optimal offloading option according to its requirement.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n\"Different from the previous research, the offloading decision depends not only on the estimated access delay but also on the accuracy the edge server can provide.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n<i>THAT'S IMPORTANT, IT IS RELATED TO THE WAY TASKS ARE DISTRIBUTED AND ASSIGNED TO THE DIFFERENT EDGE SERVERS. (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">note on p.71</a>)</i> \n\n\"near-optimal offloading framework for accuracy maximization offloading with latency constraints\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n\"Step 1: (Estimate the accuracy of computing task from IIoT MD i.)\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n\"Step 2: (Estimate the access delay of computing tasks from MD i.)\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n\"Step 3: (Offload to the appropriate edge servers.) According to the estimated accuracy and dela\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n\"For those MDs that did not find an appropriate edge server or remote server, it can be accomplished locally at the CPU of MDs. For those computing tasks with predicted delay to the remote cloud lower than its delay requirement, we tend to route the computing tasks to the remote cloud, since the remote cloud is most powerful and can provide the highest accuracy. Thus, through Step 3, the accuracy of MDs is deter\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n\"By the proposed offloading framework, traffic will be disseminated intelligently, according to its requirement, to the optimal edge servers or to the remote cloud through an appropriate path so that the pressure on the backbone network will be effectively alleviated.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=4\">Sun et al 2019:71</a>) \n\n\"y edge servers and therefore does not consume much bandwidth. Unlike large-scale training in remote cloud, transfer training requires only a small amount of targeted training data to achieve high accuracy of the network.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">Sun et al 2019:72</a>) \n\n\"trAnsfEr lEArnIn\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">Sun et al 2019:72</a>) \n\n\"IoT MDs turn to the edge servers for image processing to monitor the industrial process.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">Sun et al 2019:72</a>) \n\n<i>SIMILE SCENARIO PER NOI??? (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">note on p.72</a>)</i> \n\n\"The transfer-learning-based computing and offloading framework is done following five phases, that is, training the source neural network with large-scale data in the remote cloud, loading the pretrained neural network, customizing the predictive model, training the predictive model with small-scale data in the edge, and offloading tasks to appropriate edge servers.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">Sun et al 2019:72</a>) \n\n\"First, the source neural networks are trained in large-scale data in remote cloud\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">Sun et al 2019:72</a>) \n\n\"Then an edge server loads the pretrained neural network from remote cloud\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">Sun et al 2019:72</a>) \n\n\"he pretrained network then transforms to a customized predictive model\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">Sun et al 2019:72</a>) \n\n\"Finally, we assess the service accuracy of the predictive model and offload the computing tasks of IIoT devices according to AMLC.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">Sun et al 2019:72</a>) \n\n\"In order to develop lightweight machine learning technologies on edge servers in IIoT, transfer learning is adopted.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">Sun et al 2019:72</a>) \n\n\"Transfer learning is a popular approach in deep learning where pre-trained models are used as the starting point to learn a new task\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">Sun et al 2019:72</a>) \n\n<i>IMPORTANT FOR THE THINGS ABOUT FEDERATED VS DISTRIBUTED LEARNING MENTIONED BY LUCIANO (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=5\">note on p.72</a>)</i> \n\n\"This shows that at the edge layer, the customized predictive model on edge servers differs from each other due to different local data, even when the pretrained networks are the same.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=6\">Sun et al 2019:73</a>) \n\n\"we find it feasible to deploy machine learning applications to edge servers and employ service accuracy as a metric in the traffic offloading of MEC, while it also faces many challenges, such as the storage of training and test data, model training, and parameter updates\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=6\">Sun et al 2019:73</a>) \n\n<i>IMPORTANT CHALLENGES!!! (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=6\">note on p.73</a>)</i> \n\n\"in AI-enabled edge computing, it is also challenging to appropriately tailor the AI-based computing service to trade off between accuracy and the constrained computing resources.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=6\">Sun et al 2019:73</a>) \n\n<i>CHALLENGE (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=6\">note on p.73</a>)</i> \n\n\"proposed an intelligent computing architecture in IIoT with cooperation between edge servers and remote cloud.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=7\">Sun et al 2019:74</a>) \n\n<i>THAT'S THE IDEA OF THE PROPOSED APPROACH (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=7\">note on p.74</a>)</i> \n\n\"AI-driven offloading framework considering service accuracy as a new metric, intelligently disseminating traffic to edge servers or remote cloud\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=7\">Sun et al 2019:74</a>) \n\n\"AI-based computing service to trade off between accuracy and the constrained computing resources.\" (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=7\">Sun et al 2019:74</a>) \n\n<i>THAT'S A POSSIBLE FUTURE WORK (<a href=\"zotero://open-pdf/library/items/WXTJVNM8?page=7\">note on p.74</a>)</i> \n\nTL;DR \n\nAn AI enhanced offloading framework is proposed for service accuracy maximization, which considers service accuracy as a new metric besides delay, and intelligently disseminates the traffic to edge servers or through an appropriate path to remote cloud."],"number":["5"],"pages":["68–74"],"shorttitle":["AI-Enhanced Offloading in Edge Computing"],"title":["AI-Enhanced Offloading in Edge Computing: When Machine Learning Meets Industrial IoT"],"volume":["33"]},"creators":{"author":[{"lastName":"Sun","firstName":"Wen"},{"lastName":"Liu","firstName":"Jiajia"},{"lastName":"Yue","firstName":"Yanlin"}]}},{"key":"sunConvergenceRecommenderSystems2020","type":"article","fields":{"author":["Sun, Chuan","Li, Hui","Li, Xiuhua","Wen, Junhao","Xiong, Qingyu","Zhou, Wei"],"date":["2020"],"doi":["10.1109/ACCESS.2020.2978896"],"issn":["2169-3536"],"journaltitle":["IEEE Access"],"keywords":["internet of things","recommendation systems"],"note":["<b>Gray Annotations (18/12/2020, 15:41:24)</b> \n\n\"According to Cisco reports, nearly 850 ZB data will be generated each year by 2021, but the data center is only 20.6 ZB [10].\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n<i>QUESTO E' FONDAMENTALE PER MOTIVARE LA QUESTIONE EDGE E FEDERATED LEARNING (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">note on p.47119</a>)</i> \n\n\"It indicates that the location distribution of data sources is undergoing a transformation from data centers to an expanding number of edge devices\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n\"Nowadays, various machine learning-based intelligent services have been deployed at edge servers to meet the critical requirements (e.g., agility, heterogeneous data analysis, and privacy-policy strategy) of computation tasks [16][18].\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n<i>SUPPORTO MOTIVAZIONE (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">note on p.47119</a>)</i> \n\n<b>Green Annotations (18/12/2020, 15:41:24)</b> \n\n\"recommender systems have been used as an effective technology to lter useless information and attempt to recommend the most useful items\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=1\">Sun et al 2020:47118</a>) \n\n<i>USE OF RECSYS (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=1\">note on p.47118</a>)</i> \n\n\"Mobile edge computing is a novel computing paradigm via pushing computation/storage resource from the remote cloud servers to the network edge servers to provide more intelligent and personalized service.\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=1\">Sun et al 2020:47118</a>) \n\n\"collaborative ltering (CF)\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=1\">Sun et al 2020:47118</a>) \n\n\"content-based recommendation (CB)\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=1\">Sun et al 2020:47118</a>) \n\n\"nowledge-based recommendation (KB)\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=1\">Sun et al 2020:47118</a>) \n\n\"hybrid recommendation (HR)\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=1\">Sun et al 2020:47118</a>) \n\n\"CF achieves the best accuracy of predictions about how much someone is going to enjoy a movie in Netix Prize, however, it has sparseness and cold-start problems [6]\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=1\">Sun et al 2020:47118</a>) \n\n\"data sources contain the following key characteristics.\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n\"Sparsity: in the edge environment, the historical data sources stored in edge server comes from a small amount or even one user's proles\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n\"Heterogeneity: edge devices are produced by companies around the world\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n\"Mobility: the mobility is an inherent characteristic of users in the mobile networks\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n\"Volatility: the state of the mobile edge network is volatility, when one user invokes a service many times, the QoS data may be different each time.\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n\"recommender systems based on cloud computing have been proposed in traditional Internet environments, they are gradually unable to deal with these novel emerging services and massively distributed data in mobile edge network, they may fail to predict what users' interests and demands are.\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n<i>THIS IS A MOTIVATION STATEMENT! CHALLENGE (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">note on p.47119</a>)</i> \n\n\"1) cold-start problem, as data sources of active users are usually very sparse, even new or inactive users lack relevant proles, the cold-start problem occurs\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n\"2) exploration and exploitation problem, for example, in online shopping, exploration implies recommending new goods and exploitation entails reusing existing goods. How to nd an optimal trade-off between exploration and exploitation is crucial issu\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n\") security and privacy problem, the data sources are produced by various IoT devices and distributed at different edge platforms, resulting in potential leakage of user data security problem\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n\"Mobile edge computing (MEC)\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=2\">Sun et al 2020:47119</a>) \n\n\"four enabling technologies for building recommender systems and Edge computing:\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=3\">Sun et al 2020:47120</a>) \n\n\") Recommender systems on Edge\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=3\">Sun et al 2020:47120</a>) \n\n\"2) Recommender systems in Edge\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=3\">Sun et al 2020:47120</a>) \n\n\"3) Edge computing for recommender systems\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=3\">Sun et al 2020:47120</a>) \n\n\"4) Recommender systems for Edge computing\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=3\">Sun et al 2020:47120</a>) \n\n\"However, conventional recommender systems are gradually unable to meet the requirements of IoT services. Recently, a novel computing paradigm has been proposed by pushing computation and storage resources from the central cloud servers to network edges. Hence, deploying recommender systems applications at the edge servers can perform some lightweight processing to improve QoS.\" (<a href=\"zotero://open-pdf/library/items/YWLPYTI3?page=8\">Sun et al 2020:47125</a>)"],"pages":["47118–47132"],"shorttitle":["Convergence of Recommender Systems and Edge Computing"],"title":["Convergence of Recommender Systems and Edge Computing: A Comprehensive Survey"],"volume":["8"]},"creators":{"author":[{"lastName":"Sun","firstName":"Chuan"},{"lastName":"Li","firstName":"Hui"},{"lastName":"Li","firstName":"Xiuhua"},{"lastName":"Wen","firstName":"Junhao"},{"lastName":"Xiong","firstName":"Qingyu"},{"lastName":"Zhou","firstName":"Wei"}]}},{"key":"sundbergDemocratizingArtificialIntelligence2023","type":"article","fields":{"langid":["english"],"abstract":["Organizations are increasingly seeking to generate value and insights from their data by integrating advances in artificial intelligence (AI) such as machine learning (ML) systems into their operations. However, there are several managerial challenges associated with ML operations (MLOps). In this article we outline three key challenges and discuss how an emerging form of AI platforms – ‘no-code AI’ – may help organizations to address and overcome them. We outline how no-code AI can leverage MLOps by closing the gap between business and technology experts, enabling faster iterations between problems and solutions, and aiding infrastructure management. After outlining important remaining challenges associated with no-code AI and MLOps we propose three managerial Journal Pre-proof recommendations. By doing so, we provide insights into an important novel, emerging phenomenon in AI software and set the stage for further research in the area."],"author":["Sundberg, Leif","Holmström, Jonny"],"date":["2023-04"],"doi":["10.1016/j.bushor.2023.04.003"],"issn":["00076813"],"journaltitle":["Business Horizons"],"keywords":["LOGSEQ"],"pages":["S0007681323000502"],"shorttitle":["Democratizing artificial intelligence"],"title":["Democratizing artificial intelligence: How no-code AI can leverage machine learning operations"]},"creators":{"author":[{"lastName":"Sundberg","firstName":"Leif"},{"lastName":"Holmström","firstName":"Jonny"}]},"sentenceCased":true},{"key":"sunhareInternetThingsData2020","type":"article","fields":{"langid":["english"],"abstract":["Advancement in the fields of electronic communication, data processing, and internet technologies enable easy access to and interaction with a variety of physical devices throughout the globe. Our whole world is enveloped by a blanket of innumerable smart devices equipped with the sensors and actuators. Extensive research on the Internet of things (IoT) with cloud technologies, make it possible to accumulate tremendous data created from this heterogeneous environment and transform it into precious knowledge by utilizing data mining technologies. Furthermore, this generated knowledge will play a key role in intelligent decision making, system performance boosting, and optimum management of resources and services. With this background, this paper presents a systematic and detailed review of various data mining techniques employed in the large and small scale IoT applications to formulate an intelligent environment. It also presents an overview of cloud-assisted IoT Big data mining system to better understand the importance of data mining for an IoT environment."],"author":["Sunhare, Priyank","Chowdhary, Rameez R.","Chattopadhyay, Manju K."],"date":["2020-07"],"doi":["10.1016/j.jksuci.2020.07.002"],"issn":["13191578"],"journaltitle":["Journal of King Saud University - Computer and Information Sciences"],"pages":["S131915782030416X"],"shorttitle":["Internet of things and data mining"],"title":["Internet of things and data mining: An application oriented survey"]},"creators":{"author":[{"lastName":"Sunhare","firstName":"Priyank"},{"lastName":"Chowdhary","firstName":"Rameez R."},{"lastName":"Chattopadhyay","firstName":"Manju K."}]},"sentenceCased":true},{"key":"sunkleAIdrivenStreamlinedModeling2022","type":"article","fields":{"langid":["english"],"author":["Sunkle, Sagar","Saxena, Krati","Patil, Ashwini","Kulkarni, Vinay"],"date":["2022-06"],"doi":["10.1007/s10270-022-00982-6"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"keywords":["notion"],"note":["TL;DR \n\nFive industrial case studies where AI techniques are used in different modeling activities to help the researchers and practitioners make sense of various artifacts and data available to them and use applicable AI techniques to enhance suitable modeling activities."],"number":["3"],"pages":["1–23"],"shorttitle":["AI-driven streamlined modeling"],"title":["AI-driven streamlined modeling: Experiences and lessons learned from multiple domains"],"volume":["21"]},"creators":{"author":[{"lastName":"Sunkle","firstName":"Sagar"},{"lastName":"Saxena","firstName":"Krati"},{"lastName":"Patil","firstName":"Ashwini"},{"lastName":"Kulkarni","firstName":"Vinay"}]},"sentenceCased":true},{"key":"SunyePTJ01","type":"inproceedings","fields":{"langid":["english"],"author":["Sunyé, Gerson","Pollet, Damien","Traon, Yves Le","Jézéquel, Jean-Marc"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["«UML» 2001 - Unified Model. Lang. Model. Lang. Concepts Tools 4th Int. Conf. Tor. Can. Oct. 1-5 2001 Proc."],"date":["2001"],"doi":["10.1007/3-540-45441-1\\_11"],"editor":["Gogolla, Martin","Kobryn, Cris"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nA set of refactorings is presented and it is explained how they can be designed so as to preserve the behavior of a UML model."],"pages":["134–148"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Tue, 14 May 2019 10:00:55 +0200"],"title":["Refactoring UML models"],"volume":["2185"]},"creators":{"author":[{"lastName":"Sunyé","firstName":"Gerson"},{"lastName":"Pollet","firstName":"Damien"},{"lastName":"Traon","firstName":"Yves Le"},{"lastName":"Jézéquel","firstName":"Jean-Marc"}],"editor":[{"lastName":"Gogolla","firstName":"Martin"},{"lastName":"Kobryn","firstName":"Cris"}]},"sentenceCased":true},{"key":"suriModelbasedDevelopmentModular2017","type":"inproceedings","fields":{"author":["Suri, Kunal","Cuccuru, Arnaud","Cadavid, Juan","Gerard, Sebastien","Gaaloul, Walid","Tata, Samir"],"date":["2017"],"doi":["10.5220/0006210504870495"],"isbn":["978-989-758-210-3"],"pages":["487–495"],"publisher":["SCITEPRESS - Science and Technology Publications"],"shorttitle":["Model-based Development of Modular Complex Systems for Accomplishing System Integration for Industry 4.0"],"title":["Model-based Development of Modular Complex Systems for Accomplishing System Integration for Industry 4.0:"]},"creators":{"author":[{"lastName":"Suri","firstName":"Kunal"},{"lastName":"Cuccuru","firstName":"Arnaud"},{"lastName":"Cadavid","firstName":"Juan"},{"lastName":"Gerard","firstName":"Sebastien"},{"lastName":"Gaaloul","firstName":"Walid"},{"lastName":"Tata","firstName":"Samir"}]},"sentenceCased":true},{"key":"SurveyClusteringData","type":"online","fields":{"title":["A Survey of Clustering Data Mining Techniques - Springer"],"url":["http://link.springer.com/chapter/10.1007%2F3-540-28349-8_2"],"urldate":["2015-04-16"]},"creators":{}},{"key":"SurveyNoSQLDatabase","type":"online","fields":{"langid":["american"],"abstract":["With the development of the Internet and cloud computing, there need databases to be able to store and process big data effectively, demand for high-performance when reading and writing, so the traditional relational database is facing many new challenges. Especially in large scale and high-concurrency applications, such as search engines and SNS, using the relational database to store and query dynamic user data has appeared to be inadequate. In this case, NoSQL database created. This paper describes the background, basic characteristics, data model of NoSQL. In addition, this paper classifies NoSQL databases according to the CAP theorem. Finally, the mainstream NoSQL databases are separately described in detail, and extract some properties to help enterprises to choose NoSQL."],"note":["TL;DR \n\nThe background, basic characteristics, data model of NoSQL, and the mainstream NoSQL databases are separately described in detail, and some properties are extracted to help enterprises to choose NoSQL."],"title":["Survey on NoSQL database"],"url":["http://ieeexplore.ieee.org/abstract/document/6106531/?casa_token=skk-O-EQilsAAAAA:E0LtNJ8JtgHBiTRq54qaAudBrRo6Iz4BFciGElfCEkBSW7ZVSzK8lyjhT-MGt35cwpStASMZ"],"urldate":["2021-03-22"]},"creators":{},"sentenceCased":true},{"key":"sutskeverSequenceSequenceLearning2014","type":"article","fields":{"abstract":["Deep Neural Networks (DNNs) are powerful models that have achieved excellent performance on difficult learning tasks. Although DNNs work well whenever large labeled training sets are available, they cannot be used to map sequences to sequences. In this paper, we present a general end-to-end approach to sequence learning that makes minimal assumptions on the sequence structure. Our method uses a multilayered Long Short-Term Memory (LSTM) to map the input sequence to a vector of a fixed dimensionality, and then another deep LSTM to decode the target sequence from the vector. Our main result is that on an English to French translation task from the WMT'14 dataset, the translations produced by the LSTM achieve a BLEU score of 34.8 on the entire test set, where the LSTM's BLEU score was penalized on out-of-vocabulary words. Additionally, the LSTM did not have difficulty on long sentences. For comparison, a phrase-based SMT system achieves a BLEU score of 33.3 on the same dataset. When we used the LSTM to rerank the 1000 hypotheses produced by the aforementioned SMT system, its BLEU score increases to 36.5, which is close to the previous best result on this task. The LSTM also learned sensible phrase and sentence representations that are sensitive to word order and are relatively invariant to the active and the passive voice. Finally, we found that reversing the order of the words in all source sentences (but not target sentences) improved the LSTM's performance markedly, because doing so introduced many short term dependencies between the source and the target sentence which made the optimization problem easier."],"author":["Sutskever, Ilya","Vinyals, Oriol","Le, Quoc V."],"date":["2014-12-14"],"eprint":["1409.3215"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv14093215 Cs"],"keywords":["Computer Science - Computation and Language","Computer Science - Machine Learning"],"note":["Comment: 9 pages"],"title":["Sequence to Sequence Learning with Neural Networks"],"url":["http://arxiv.org/abs/1409.3215"],"urldate":["2021-03-31"]},"creators":{"author":[{"lastName":"Sutskever","firstName":"Ilya"},{"lastName":"Vinyals","firstName":"Oriol"},{"lastName":"Le","firstName":"Quoc V."}]}},{"key":"Svozil1997","type":"article","fields":{"author":["Svozil, Daniel","Kvasnicka, Vladimir","Pospíchal, Jiří"],"date":["1997-11"],"journaltitle":["Chemom. Intell. Lab. Syst."],"nodoi":["10.1016/S0169-7439(97)00061-0"],"pages":["43–62"],"title":["Introduction to multi-layer feed-forward neural networks"],"volume":["39"]},"creators":{"author":[{"lastName":"Svozil","firstName":"Daniel"},{"lastName":"Kvasnicka","firstName":"Vladimir"},{"lastName":"Pospíchal","firstName":"Jiří"}]},"sentenceCased":true},{"key":"svyatkovskiyPythiaAIassistedCode2019","type":"article","fields":{"langid":["english"],"abstract":["In this paper, we propose a novel end-to-end approach for AI-assisted code completion called Pythia. It generates ranked lists of method and API recommendations which can be used by software developers at edit time. The system is currently deployed as part of Intellicode extension in Visual Studio Code IDE. Pythia exploits state-of-the-art large-scale deep learning models trained on code contexts extracted from abstract syntax trees. It is designed to work at a high throughput predicting the best matching code completions on the order of 100 ms. We describe the architecture of the system, perform comparisons to frequency-based approach and invocation-based Markov Chain language model, and discuss challenges serving Pythia models on lightweight client devices. The offline evaluation results obtained on 2700 Python open source software GitHub repositories show a top-5 accuracy of 92%, surpassing the baseline models by 20% averaged over classes, for both intra and cross-project settings."],"author":["Svyatkovskiy, Alexey","Zhao, Ying","Fu, Shengyu","Sundaresan, Neel"],"date":["2019-07-25"],"doi":["10.1145/3292500.3330699"],"eprint":["1912.00742"],"eprinttype":["arxiv"],"journaltitle":["Proc. 25th ACM SIGKDD Int. Conf. Knowl. Discov. Data Min."],"keywords":["Computer Science - Machine Learning","Computer Science - Software Engineering"],"note":["Comment: Published in Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining (KDD '19)"],"pages":["2727–2735"],"shorttitle":["Pythia"],"title":["Pythia: AI-assisted Code Completion System"]},"creators":{"author":[{"lastName":"Svyatkovskiy","firstName":"Alexey"},{"lastName":"Zhao","firstName":"Ying"},{"lastName":"Fu","firstName":"Shengyu"},{"lastName":"Sundaresan","firstName":"Neel"}]}},{"key":"SwarmRobotsCan","type":"online","fields":{"title":["Swarm robots can learn by simply observing – ScienceDaily"],"url":["https://www.sciencedaily.com/releases/2016/08/160830083653.htm"],"urldate":["2016-08-30"]},"creators":{},"sentenceCased":true},{"key":"Symonds2016606","type":"article","fields":{"langid":["english"],"abbrev_source_title":["J. Build. Perform. Simul."],"affiliation":["Institute of Environmental Design and Engineering, University College London, Central House, 14 Woburn Place, London, WC1H 0NN, United Kingdom; London School of Hygiene and Tropical Medicine, 15–17 Tavistock Place, London, WC1H 9SH, United Kingdom; Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Didcot, United Kingdom"],"author":["Symonds, P.","Taylor, J.","Chalabi, Z.","Mavrogianni, A.","Davies, M.","Hamilton, I.","Vardoulakis, S.","Heaviside, C.","Macintyre, H."],"correspondence_address1":["Symonds, P.; Institute of Environmental Design and Engineering, Central House, 14 Woburn Place, United Kingdom; email: p.symonds@ucl.ac.uk"],"date":["2016"],"document_type":["Article"],"doi":["10.1080/19401493.2016.1166265"],"issn":["19401493"],"journaltitle":["J. Build. Perform. Simul."],"note":["cited By 28"],"number":["6"],"pages":["606–619"],"publisher":["Taylor and Francis Ltd."],"source":["Scopus"],"title":["Development of an England-wide indoor overheating and air pollution model using artificial neural networks"],"volume":["9"]},"creators":{"author":[{"lastName":"Symonds","firstName":"P."},{"lastName":"Taylor","firstName":"J."},{"lastName":"Chalabi","firstName":"Z."},{"lastName":"Mavrogianni","firstName":"A."},{"lastName":"Davies","firstName":"M."},{"lastName":"Hamilton","firstName":"I."},{"lastName":"Vardoulakis","firstName":"S."},{"lastName":"Heaviside","firstName":"C."},{"lastName":"Macintyre","firstName":"H."}]},"sentenceCased":true},{"key":"syrianiGuestEditorialTheme2021","type":"article","fields":{"langid":["english"],"abstract":["The networked combination of multi-physics systems (mechanical, electrical, hydraulic, biochemical, among others) with computational systems (control systems, signal processing, logical inference, planning, among others), often interacting with human actors, in uncertain environments, in a socio-economic context, has led to so-called Cyber-Physical Systems (CPS). The CPS that are engineered today are reaching a previously unseen level of complexity. To date, no unifying theory nor systematic design methods, techniques and tools exist for such systems. Individual (mechanical, electrical, network or software) engineering disciplines only offer partial solutions. Multi-Paradigm Modeling (MPM) proposes to model every part and aspect of such complex systems explicitly, at the most appropriate level(s) of abstraction, using the most appropriate modeling language(s)/formalism(s). This includes the explicit modeling of the often complex engineering workflows. Modular modeling language engineering, including model transformation and the study of modeling language semantics, are used to realize MPM, which has the potential to be an effective answer to the challenges of designing CPS. This sixth edition will be organised as a highly interactive workshop, promoting discussions and collaboration around a specific theme: we want to explore the notion of ”appropriateness” (of formalisms, of processes, of abstraction levels, of views, of architectures, etc.) that is at the core of the MPM approach. The Workshop will host paper presentations in the morning, and discussions and collaborative work in the afternoon, by bringing together international experts in the field for an intense one-day workshop."],"author":["Syriani, Eugene","Wimmer, Manuel"],"date":["2021-06"],"doi":["10.1007/s10270-021-00882-1"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"note":["TL;DR \n\nThis theme section covers papers on the foundations and applications of MPM for CPS, a continuation of the successful MPM workshop series with a stronger focus on CPS as especially these systems pose several new challenges on the engineering process and beyond."],"number":["3"],"pages":["607–609"],"title":["Guest editorial to the theme section on Multi-Paradigm Modeling for Cyber-Physical Systems"],"volume":["20"]},"creators":{"author":[{"lastName":"Syriani","firstName":"Eugene"},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"syrianiModelingModelTransformation2013","type":"article","fields":{"author":["Syriani, Eugene","Gray, Jeff","Vangheluwe, Hans"],"date":["2013"],"doi":["10.1007/978-3-642-36654-3_9"],"journaltitle":["Domain Eng."],"note":["TL;DR \n\nThis chapter introduces a language engineering technique for building MTLs that is based on treating each MTL as a domain-specific language, more specifically, as languages for describing specific classes of transformations."],"pages":["211–237"],"title":["Modeling a Model Transformation Language"]},"creators":{"author":[{"lastName":"Syriani","firstName":"Eugene"},{"lastName":"Gray","firstName":"Jeff"},{"lastName":"Vangheluwe","firstName":"Hans"}]}},{"key":"syrianiProceedings23rdACM2020","type":"book","fields":{"langid":["english"],"author":["Syriani, Eugene","Association for Computing Machinery","Special Interest Group on Software Engineering"],"date":["2020"],"isbn":["978-1-4503-7019-6"],"title":["Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems."],"url":["https://dl.acm.org/action/showBook?doi=10.1145/3365438"],"urldate":["2021-01-07"]},"creators":{"author":[{"lastName":"Syriani","firstName":"Eugene"},{"literal":"Association for Computing Machinery"},{"literal":"Special Interest Group on Software Engineering"}]}},{"key":"syrianiTCoreFrameworkCustombuilt2013","type":"article","fields":{"author":["Syriani, Eugene","Vangheluwe, Hans","LaShomb, Brian"],"date":["2013"],"doi":["10.1007/s10270-013-0370-4"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nT-Core is proposed, a framework where primitive transformation constructs can be combined to define and encapsulate reusable model transformation idioms and allows the transformation engineer to design transformations with the most appropriate constructs for the task at hand."],"title":["T-Core: A framework for custom-built model transformation engines"]},"creators":{"author":[{"lastName":"Syriani","firstName":"Eugene"},{"lastName":"Vangheluwe","firstName":"Hans"},{"lastName":"LaShomb","firstName":"Brian"}]},"sentenceCased":true},{"key":"SyrianiVMHME13","type":"inproceedings","fields":{"langid":["english"],"author":["Syriani, Eugene","Vangheluwe, Hans","Mannadiar, Raphael","Hansen, Conner","Van Mierlo, Simon","Ergin, Hüseyin"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["DemosPostersStudentResearch MoDELS"],"date":["2013"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis work introduces AToMPM, an open-source framework for designing domain-specific modeling environments, performing model transformations, manipulating and managing models, which is independent from any operating system, platform, or device it may execute on."],"pages":["21–25"],"publisher":["Citeseer"],"series":["CEUR workshop proceedings"],"shorttitle":["AToMPM"],"timestamp":["Fri, 10 Mar 2023 16:22:20 +0100"],"title":["AToMPM: A Web-based Modeling Environment."],"url":["http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.407.6965&rep=rep1&type=pdf"],"urldate":["2015-06-24"],"volume":["1115"]},"creators":{"author":[{"lastName":"Syriani","firstName":"Eugene"},{"lastName":"Vangheluwe","firstName":"Hans"},{"lastName":"Mannadiar","firstName":"Raphael"},{"lastName":"Hansen","firstName":"Conner"},{"lastName":"Van Mierlo","firstName":"Simon"},{"lastName":"Ergin","firstName":"Hüseyin"}]},"sentenceCased":true},{"key":"szvetitsSystematicLiteratureReview2013","type":"article","fields":{"langid":["english"],"author":["Szvetits, Michael","Zdun, Uwe"],"date":["2013-12-17"],"doi":["10.1007/s10270-013-0394-9"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nThis article analyzes the usage of models at runtime in the existing research literature using the Systematic Literature Review (SLR) research method to provide an overview and classification of current research approaches using models at Runtime and to identify research areas not covered by models atruntime so far."],"title":["Systematic literature review of the objectives, techniques, kinds, and architectures of models at runtime"]},"creators":{"author":[{"lastName":"Szvetits","firstName":"Michael"},{"lastName":"Zdun","firstName":"Uwe"}]},"sentenceCased":true},{"key":"TableContents2017","type":"article","fields":{"langid":["english"],"date":["2017-01"],"doi":["10.1109/MS.2017.23"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"number":["1"],"pages":["2–3"],"title":["Table of contents"],"volume":["34"]},"creators":{},"sentenceCased":true},{"key":"TableContentsIEEE","type":"online","fields":{"title":["Table of Contents - IEEE Software | IEEE Computer Society Digital Library"],"url":["https://www.computer.org/csdl/magazine/so/2022/05"],"urldate":["2022-09-09"]},"creators":{}},{"key":"Tadejko2020169","type":"article","fields":{"abstract":["Cognitive Services are cloud computing services available to help developers build intelligent applications based on Machine Learning (ML) methods with pre-trained models as a service. Machine Learning platforms are one of the fastest growing services of the cloud because ML and Artificial Intelligence (AI) platforms are available through diverse delivery models such as cognitive computing, automated machine learning, model management. Cognitive Computing is delivered as a set of APIs. Due to the nature of the technologies involved in ML ecosystems and Knowledge Hierarchy—Data, Information, Knowledge, Wisdom (DIKW) Pyramid, there is a natural overlap of a technologies and Knowledge Management (KM) processes. The modern architecture of software solutions can be developed with the use of a wide technology stack, including cloud computing technologies and Cognitive Services (CS). We can use a wide range of ML tools at all levels of the DIKW pyramid. In this paper, we propose a new CS based approach to build an architecture of Knowledge Management system. We have analyzed the possibilities of using CS at all levels of the DIKW pyramid. We discussed some of the relevant aspects of Cloud CS and ML in Knowledge Management context and possibilities implementation of Cognitive Services on knowledge processing. © Springer Nature Switzerland AG 2020."],"author":["Tadejko, P."],"date":["2020"],"document_type":["Book Chapter"],"doi":["10.1007/978-3-030-34706-2_9"],"issn":["23674512"],"journaltitle":["Lect. Notes Data Eng. Commun. Technol."],"note":["cited By 3 \n\nTL;DR \n\nA new CS based approach to build an architecture of Knowledge Management system is proposed and the possibilities of using CS at all levels of the DIKW pyramid are analyzed."],"pages":["169–190"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Cloud cognitive services based on machine learning methods in architecture of modern knowledge management solutions"],"volume":["40"]},"creators":{"author":[{"lastName":"Tadejko","firstName":"P."}]},"sentenceCased":true},{"key":"taentzerCotransformationGraphsType2012","type":"incollection","fields":{"langid":["english"],"author":["Taentzer, Gabriele","Mantz, Florian","Lamo, Yngve"],"booktitle":["Graph Transformations"],"date":["2012"],"doi":["10.1007/978-3-642-33654-6_22"],"editor":["Ehrig, Hartmut","Engels, Gregor","Kreowski, Hans-Jörg","Rozenberg, Grzegorz"],"editorb":["Hutchison, David","Kanade, Takeo","Kittler, Josef","Kleinberg, Jon M.","Mattern, Friedemann","Mitchell, John C.","Naor, Moni","Nierstrasz, Oscar","Pandu Rangan, C.","Steffen, Bernhard","Sudan, Madhu","Terzopoulos, Demetri","Tygar, Doug","Vardi, Moshe Y.","Weikum, Gerhard"],"editorbtype":["redactor"],"ids":["Taentzer_Mantz_Lamo_2012"],"isbn":["978-3-642-33653-9 978-3-642-33654-6"],"keywords":["/unread","⛔ No INSPIRE recid found"],"location":["Berlin, Heidelberg"],"pages":["326–340"],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture notes in computer science"],"title":["Co-transformation of Graphs and Type Graphs with Application to Model Co-evolution"],"volume":["7562"]},"creators":{"author":[{"lastName":"Taentzer","firstName":"Gabriele"},{"lastName":"Mantz","firstName":"Florian"},{"lastName":"Lamo","firstName":"Yngve"}],"editor":[{"lastName":"Ehrig","firstName":"Hartmut"},{"lastName":"Engels","firstName":"Gregor"},{"lastName":"Kreowski","firstName":"Hans-Jörg"},{"lastName":"Rozenberg","firstName":"Grzegorz"}],"editorb":[{"lastName":"Hutchison","firstName":"David"},{"lastName":"Kanade","firstName":"Takeo"},{"lastName":"Kittler","firstName":"Josef"},{"lastName":"Kleinberg","firstName":"Jon M."},{"lastName":"Mattern","firstName":"Friedemann"},{"lastName":"Mitchell","firstName":"John C."},{"lastName":"Naor","firstName":"Moni"},{"lastName":"Nierstrasz","firstName":"Oscar"},{"lastName":"Pandu Rangan","firstName":"C."},{"lastName":"Steffen","firstName":"Bernhard"},{"lastName":"Sudan","firstName":"Madhu"},{"lastName":"Terzopoulos","firstName":"Demetri"},{"lastName":"Tygar","firstName":"Doug"},{"lastName":"Vardi","firstName":"Moshe Y."},{"lastName":"Weikum","firstName":"Gerhard"}]},"sentenceCased":true},{"key":"TaentzerELW14","type":"article","fields":{"langid":["english"],"author":["Taentzer, Gabriele","Ermel, Claudia","Langer, Philip","Wimmer, Manuel"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2014"],"doi":["10.1007/S10270-012-0248-X"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["1"],"pages":["239–272"],"timestamp":["Thu, 14 Oct 2021 09:25:04 +0200"],"title":["A fundamental approach to model versioning based on graph modifications: From theory to implementation"],"volume":["13"]},"creators":{"author":[{"lastName":"Taentzer","firstName":"Gabriele"},{"lastName":"Ermel","firstName":"Claudia"},{"lastName":"Langer","firstName":"Philip"},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"taghaviNewInsightsDeveloping2018","type":"article","fields":{"langid":["english"],"author":["Taghavi, Mona","Bentahar, Jamal","Bakhtiyari, Kaveh","Hanachi, Chihab"],"date":["2018-03-01"],"doi":["10.1093/comjnl/bxx056"],"issn":["0010-4620, 1460-2067"],"journaltitle":["Comput. J."],"number":["3"],"pages":["319–348"],"title":["New Insights Towards Developing Recommender Systems"],"volume":["61"]},"creators":{"author":[{"lastName":"Taghavi","firstName":"Mona"},{"lastName":"Bentahar","firstName":"Jamal"},{"lastName":"Bakhtiyari","firstName":"Kaveh"},{"lastName":"Hanachi","firstName":"Chihab"}]}},{"key":"tahaModelingBasicAspects2013","type":"article","fields":{"author":["Taha, Walid","Philippsen, Roland"],"date":["2013"],"eprint":["1303.2792"],"eprinttype":["arxiv"],"journaltitle":["ArXiv Prepr. ArXiv13032792"],"title":["Modeling basic aspects of cyber-physical systems"],"url":["http://arxiv.org/abs/1303.2792"],"urldate":["2016-02-05"]},"creators":{"author":[{"lastName":"Taha","firstName":"Walid"},{"lastName":"Philippsen","firstName":"Roland"}]},"sentenceCased":true},{"key":"tairasCorpusbasedAnalysisDomainspecific2015","type":"article","fields":{"langid":["english"],"author":["Tairas, Robert","Cabot, Jordi"],"date":["2015-05"],"doi":["10.1007/s10270-013-0352-6"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nThis paper describes the utilization of corpus-based analysis techniques and exemplify them on the evaluation of the Puppet and ATL DSLs and outlines an Eclipse plug-in, which is a generic corpus- based DSL analysis tool that can accommodate the evaluationof different DSLs."],"number":["2"],"pages":["889–904"],"title":["Corpus-based analysis of domain-specific languages"],"volume":["14"]},"creators":{"author":[{"lastName":"Tairas","firstName":"Robert"},{"lastName":"Cabot","firstName":"Jordi"}]},"sentenceCased":true},{"key":"taivalsaariRoadmapProgrammableWorld2017","type":"article","fields":{"abstract":["The Internet of Things (IoT) represents the next significant step in the evolution of the Internet and software development. Although most IoT research focuses on data acquisition, analytics, and visualization, a subtler but equally important transition is underway. Hardware advances are making it possible to embed fully fledged virtual machines and dynamic language runtimes virtually everywhere, leading to a Programmable World in which all our everyday things are connected and programmable dynamically. The emergence of millions of remotely programmable devices in our surroundings will pose significant software development challenges. A roadmap from today's cloud-centric, data-centric IoT systems to the Programmable World highlights the technical challenges that deserve to be part of developer education and deserve deeper investigation beyond those IoT topics that receive the most attention today."],"author":["Taivalsaari, Antero","Mikkonen, Tommi","undefined","undefined","undefined","undefined"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["internet of things","software engineering"],"note":["TL;DR \n\nA roadmap from today's cloud-centric, data-centric IoT systems to the Programmable World highlights the technical challenges that deserve to be part of developer education and deserve deeper investigation beyond those IoT topics that receive the most attention today."],"number":["1"],"pages":["72–80"],"shorttitle":["A Roadmap to the Programmable World"],"title":["A Roadmap to the Programmable World: Software Challenges in the IoT Era"],"volume":["34"]},"creators":{"author":[{"lastName":"Taivalsaari","firstName":"Antero"},{"lastName":"Mikkonen","firstName":"Tommi"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"Tan2020566","type":"article","fields":{"abstract":["Big data and artificial intelligence methods are combined with information technology methods for engineering construction to develop an information model for slope design during construction of hydropower stations using the BIM technique and an information model. An information model management platform for slope construction was developed for hydropower projects based on intelligent construction theory for sense, analysis, and control with integrated scheduling, quality control and safety management. Results for the construction of the Baihetan Hydropower Project as an example show that the platform provides comprehensive digital management for design results, construction processes and slope construction for large hydropower projects. The system more effectively controls the construction progress, reduces safety risks and provides a comprehensive data archive for the entire slope construction process to improve the construction efficiency and economics. © 2020, Tsinghua University Press. All right reserved."],"author":["Tan, Y.","Chen, W.","Guo, Z.","Lin, E.","Lin, P.","Zhou, M.","Li, J."],"coden":["QDXKE"],"date":["2020"],"document_type":["Article"],"doi":["10.16511/j.cnki.qhdxxb.2020.26.004"],"issn":["10000054"],"journaltitle":["Qinghua Daxue XuebaoJournal Tsinghua Univ."],"note":["cited By 5"],"number":["7"],"pages":["566–574"],"publisher":["Press of Tsinghua University"],"source":["Scopus"],"title":["Information model for slope construction in hydropower projects [水电工程边坡施工全过程信息模型研究与应用]"],"volume":["60"]},"creators":{"author":[{"lastName":"Tan","firstName":"Y."},{"lastName":"Chen","firstName":"W."},{"lastName":"Guo","firstName":"Z."},{"lastName":"Lin","firstName":"E."},{"lastName":"Lin","firstName":"P."},{"lastName":"Zhou","firstName":"M."},{"lastName":"Li","firstName":"J."}]},"sentenceCased":true},{"key":"Tang2019385","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Int. Conf. Softw. Eng. Knowl. Eng., SEKE"],"affiliation":["School of Computer Science, Central China Normal University, Wuhan, China; Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan, China; School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China"],"author":["Tang, X.","Wang, Z.","Qi, J.","Li, Z."],"correspondence_address1":["Li, Z.; School of Computer Science, China; email: zengyangli@mail.ccnu.edu.cn"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.18293/SEKE2019-170"],"isbn":["1-891706-48-9"],"issn":["23259000"],"keywords":["GOAL_Code-generation","notion","TECHNIQUE_CNN","TECHNIQUE_SelfAttentionNetwork"],"note":["cited By 1 \n\nCNN and SelfAttention Network"],"pages":["385–390"],"publisher":["Knowledge Systems Institute Graduate School"],"series":["Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE"],"source":["Scopus"],"title":["Improving code generation from descriptive text by combining deep learning and syntax rules"],"volume":["2019-July"]},"creators":{"author":[{"lastName":"Tang","firstName":"X."},{"lastName":"Wang","firstName":"Z."},{"lastName":"Qi","firstName":"J."},{"lastName":"Li","firstName":"Z."}]},"sentenceCased":true},{"key":"tangBridgingGapRequirement2015","type":"inproceedings","fields":{"author":["Tang, Shan","Li, Liping","Cao, Xiaoxia","Tan, Wenan"],"booktitle":["Softw. Eng. Serv. Sci. ICSESS 2015 6th IEEE Int. Conf. On"],"date":["2015"],"pages":["1102–1105"],"publisher":["IEEE"],"title":["Bridging the gap between requirement analysis and architecture design of self-adaptive systems"],"url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7339244"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Tang","firstName":"Shan"},{"lastName":"Li","firstName":"Liping"},{"lastName":"Cao","firstName":"Xiaoxia"},{"lastName":"Tan","firstName":"Wenan"}]},"sentenceCased":true},{"key":"tangCollaborativeAgentsSoftware2024","type":"online","fields":{"abstract":["Code review is a heavily collaborative process, which aims at ensuring the overall quality and reliability of software. While it provides massive benefits, the implementation of code review in an organization faces several challenges that make its automation appealing. Automated code review tools have been around for a while and are now improving thanks to the adoption of novel AI models, which help can learn about standard practices and systematically check that the reviewed code adheres to them. Unfortunately, existing methods fall short: they often target a single input-output generative model, which cannot simulate the collaboration interactions in code review to account for various perspectives; they are also sub-performing on various critical code review sub-tasks. In this paper, we advance the state of the art in code review automation by introducing CodeAgent, a novel multi-agent-based system for code review. Fundamentally, CodeAgent is steered by QA-Checker (short for \"Question-Answer Checking\"), a supervision agent, designed specifically to ensure that all agents' contributions remain relevant to the initial review question. CodeAgent is autonomous, multi-agent, and Large language model-driven. To demonstrate the effectiveness of CodeAgent, we performed experiments to assess its capabilities in various tasks including 1) detection of inconsistencies between code changes and commit messages, 2) detection of vulnerability introduction by commits, and 3) validation of adherence to code style. Our website is accessed in \\url{https://code-agent-new.vercel.app/index.html}."],"author":["Tang, Daniel","Chen, Zhenghan","Kim, Kisub","Song, Yewei","Tian, Haoye","Ezzini, Saad","Huang, Yongfeng","Klein, Jacques","Bissyande, Tegawende F."],"date":["2024-02-06"],"eprint":["2402.02172"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Software Engineering"],"note":["TL;DR \n\nThe state of the art in code review automation is advanced by introducing CodeAgent, a novel multi-agent-based system for code review, steered by QA-Checker (short for\"Question-Answer Checking\"), a supervision agent designed specifically to ensure that all agents' contributions remain relevant to the initial review question."],"pubstate":["preprint"],"title":["Collaborative Agents for Software Engineering"],"url":["http://arxiv.org/abs/2402.02172"],"urldate":["2024-02-14"]},"creators":{"author":[{"lastName":"Tang","firstName":"Daniel"},{"lastName":"Chen","firstName":"Zhenghan"},{"lastName":"Kim","firstName":"Kisub"},{"lastName":"Song","firstName":"Yewei"},{"lastName":"Tian","firstName":"Haoye"},{"lastName":"Ezzini","firstName":"Saad"},{"lastName":"Huang","firstName":"Yongfeng"},{"lastName":"Klein","firstName":"Jacques"},{"lastName":"Bissyande","firstName":"Tegawende F."}]}},{"key":"Tao201910777","type":"inproceedings","fields":{"abstract":["The generative adversarial network (GAN) has received considerable attention recently as a model for data synthesis, without an explicit specification of a likelihood function. There has been commensurate interest in leveraging likelihood estimates to improve GAN training. To enrich the understanding of this fast-growing yet almost exclusively heuristic-driven subject, we elucidate the theoretical roots of some of the empirical attempts to stabilize and improve GAN training with the introduction of likelihoods. We highlight new insights from variational theory of diffusion processes to derive a likelihood-based regularizing scheme for GAN training, and present a novel approach to train GANs with an unnormalized distribution instead of empirical samples. To substantiate our claims, we provide experimental evidence on how our theoretically-inspired new algorithms improve upon current practice. © 36th International Conference on Machine Learning, ICML 2019. All rights reserved."],"author":["Tao, C.","Dai, S.","Chen, L.","Bai, K.","Chen, J.","Liu, C.","Zhang, R.","Bobashev, G.","Carin, L."],"date":["2019"],"document_type":["Conference Paper"],"isbn":["978-1-5108-8698-8"],"keywords":["Adversarial networks","Artificial intelligence","Current practices","Data synthesis","Diffusion process","Experimental evidence","Likelihood estimate","Likelihood functions","Machine learning","Software engineering","Variational theory"],"note":["cited By 1"],"pages":["10777–10786"],"publisher":["International Machine Learning Society (IMLS)"],"series":["36th International Conference on Machine Learning, ICML 2019"],"source":["Scopus"],"title":["Variational annealing of GANs: A langevin perspective"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078013392&partnerID=40&md5=4667134c5dc17d8a8f9e4b830ed65f02"],"volume":["2019-June"]},"creators":{"author":[{"lastName":"Tao","firstName":"C."},{"lastName":"Dai","firstName":"S."},{"lastName":"Chen","firstName":"L."},{"lastName":"Bai","firstName":"K."},{"lastName":"Chen","firstName":"J."},{"lastName":"Liu","firstName":"C."},{"lastName":"Zhang","firstName":"R."},{"lastName":"Bobashev","firstName":"G."},{"lastName":"Carin","firstName":"L."}]},"sentenceCased":true},{"key":"Tayarani-Najaran2022","type":"article","fields":{"langid":["english"],"abbrev_source_title":["IEEE Trans. Syst. Man Cybern. Syst."],"affiliation":["School of Computer Science, University of Hertfordshire, Hatfield AL10 9AB, U.K. (e-mail: tayaranm@herts.ac.uk)"],"author":["Tayarani-Najaran, M."],"date":["2022"],"document_type":["Article"],"doi":["10.1109/TSMC.2022.3143955"],"issn":["21682216"],"journaltitle":["IEEE Trans. Syst. Man Cybern. Syst."],"note":["cited By 0 \n\nTL;DR \n\nA population-based multiobjective optimization algorithm is developed, which uses the model to search through the policy space and finds a set of policies that minimize the cost induced to the society due to the policies and the growth rate of the pandemic."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["A novel ensemble machine learning and an evolutionary algorithm in modeling the COVID-19 epidemic and optimizing government policies"]},"creators":{"author":[{"lastName":"Tayarani-Najaran","firstName":"M."}]},"sentenceCased":true},{"key":"Teh:EtAl:06","type":"article","fields":{"abstract":["We consider problems involving groups of data, where each observation within a group is a draw from a mixture model, and where it is desirable to share mixture components between groups. We assume that the number of mixture components is unknown a priori and is to be inferred from the data. In this setting it is natural to consider sets of Dirichlet processes, one for each group, where the well-known clustering property of the Dirichlet process provides a nonparametric prior for the number of mixture componentswithin each group. Given our desire to tie the mixture models in the various groups, we consider a hierarchical model, specifically one in which the base measure for the child Dirichlet processes is itself distributed according to a Dirichlet process. Such a base measure being discrete, the child Dirichlet processes necessarily share atoms. Thus, as desired, the mixture models in the different groups necessarily share mixture components. We discuss representations of hierarchical Dirichlet processes in terms of a stick-breaking process, and a generalization of the Chinese restaurant process that we refer to as the \"Chinese restaurant franchise\". We present Markov chain Monte Carlo algorithms for posterior inference in hierarchical Dirichlet process mixtures, and describe applications to problems in information retrieval and text modelling."],"added-at":["2007-03-02T00:36:19.000+0100"],"author":["Teh, Yee Whye","Jordan, Michael I.","Beal, Matthew J.","Blei, David M."],"biburl":["https://www.bibsonomy.org/bibtex/2306a104860208c7a3c9be306ef709008/seandalai"],"date":["2006"],"interhash":["34e30f6d1538ed136344f6a9cf8a791b"],"intrahash":["306a104860208c7a3c9be306ef709008"],"journaltitle":["J. Am. Stat. Assoc."],"keywords":["2006 dirichlet bayesian"],"note":["TL;DR \n\nThis work considers problems involving groups of data where each observation within a group is a draw from a mixture model and where it is desirable to share mixture components between groups, and considers a hierarchical model, specifically one in which the base measure for the childDirichlet processes is itself distributed according to a Dirichlet process."],"number":["476"],"pages":["1566–1581"],"timestamp":["2007-03-02T00:36:19.000+0100"],"title":["Hierarchical dirichlet processes"],"url":["http://www.gatsby.ucl.ac.uk/~ywteh/research/npbayes/jasa2006.pdf"],"volume":["101"]},"creators":{"author":[{"lastName":"Teh","firstName":"Yee Whye"},{"lastName":"Jordan","firstName":"Michael I."},{"lastName":"Beal","firstName":"Matthew J."},{"lastName":"Blei","firstName":"David M."}]},"sentenceCased":true},{"key":"TemporalEMFTemporalMeta","type":"online","fields":{"title":["TemporalEMF: A Temporal (meta) modeling Framework"],"url":["https://modeling-languages.com/temporal-modeling-framework-emf/"],"urldate":["2018-08-10"]},"creators":{},"sentenceCased":true},{"key":"teyton_mining_2012","type":"inproceedings","fields":{"abstract":["Software systems intensively depend on external libraries, chosen at conception time. However, relevance of any library irremediably changes during projects and/or library life cycle. As a consequence, projects developers must periodically reconsider the libraries they depend on, and must think about library migration. When they want to migrate their libraries, they then have to identify candidate libraries that offer similar facilities and thus can substitute to each other. They also have to compare candidates to choose the one that best fits their needs. Finding a relevant library replacement is a well known tedious and time-consuming task. In this paper, we propose an approach that identifies sets of similar libraries and that produces what we call library migration graphs that show how existing projects have performed migrations among them. These graphs, constructed from the observation of a large number of software projects, ease the discovery and selection of library replacements."],"author":["Teyton, Cédric","Falleri, Jean-Rémy","Blanc, Xavier"],"booktitle":["2012 19th Work. Conf Reverse Eng."],"date":["2012-10"],"doi":["10.1109/WCRE.2012.38"],"keywords":["data mining","Data mining","dependencies management","external software library","Google","graph theory","Libraries","library life cycle","library migration graph mining","library replacement","Manuals","project life cycle","Search engines","Software","Software algorithms","software evolution","software libraries","software maintenance","software project","software system"],"pages":["289–298"],"title":["Mining Library Migration Graphs"]},"creators":{"author":[{"lastName":"Teyton","firstName":"Cédric"},{"lastName":"Falleri","firstName":"Jean-Rémy"},{"lastName":"Blanc","firstName":"Xavier"}]}},{"key":"thum2014featureide","type":"article","fields":{"author":["Thüm, Thomas","Kästner, Christian","Benduhn, Fabian","Meinicke, Jens","Saake, Gunter","Leich, Thomas"],"date":["2014"],"journaltitle":["Sci. Comput. Program."],"pages":["70–85"],"publisher":["Elsevier"],"title":["FeatureIDE: An extensible framework for feature-oriented software development"],"volume":["79"]},"creators":{"author":[{"lastName":"Thüm","firstName":"Thomas"},{"lastName":"Kästner","firstName":"Christian"},{"lastName":"Benduhn","firstName":"Fabian"},{"lastName":"Meinicke","firstName":"Jens"},{"lastName":"Saake","firstName":"Gunter"},{"lastName":"Leich","firstName":"Thomas"}]},"sentenceCased":true},{"key":"thummalapentaParsewebProgrammerAssistant2007","type":"inproceedings","fields":{"acmid":["1321663"],"author":["Thummalapenta, Suresh","Xie, Tao"],"booktitle":["Proc. Twenty-Second IEEEACM Int. Conf. Autom. Softw. Eng."],"date":["2007"],"isbn":["978-1-59593-882-4"],"keywords":["code examples","code reuse","code search engine","ranking code samples"],"location":["New York, NY, USA"],"nodoi":["10.1145/1321631.1321663"],"note":["TL;DR \n\nAn approach that takes queries of the form \"Source object type → Destination object type\" as input, and suggests relevant method-invocation sequences that can serve as solutions that yield the destination object from the source object given in the query is developed."],"numpages":["10"],"pages":["204–213"],"publisher":["ACM"],"series":["ASE '07"],"title":["Parseweb: A programmer assistant for reusing open source code on the web"],"url":["http://doi.acm.org/10.1145/1321631.1321663"]},"creators":{"author":[{"lastName":"Thummalapenta","firstName":"Suresh"},{"lastName":"Xie","firstName":"Tao"}]},"sentenceCased":true},{"key":"Thung2013Automated","type":"article","fields":{"title":["Thung et al. - 2013 - Automated library recommendation"]},"creators":{},"sentenceCased":true},{"key":"thungAPIRecommendationSystem2016","type":"inproceedings","fields":{"author":["Thung, Ferdian"],"booktitle":["Autom. Softw. Eng. ASE 2016 31st IEEEACM Int. Conf. On"],"date":["2016"],"note":["TL;DR \n\nThis work plans to automatically recommend relevant APIs to developers and is working on another system which can recommend web APIs (i.e., libraries) given a description of the task and a system that recommends correct parameters given an API method."],"pages":["896–899"],"publisher":["IEEE"],"title":["API recommendation system for software development"],"url":["http://ieeexplore.ieee.org/abstract/document/7582836/"],"urldate":["2017-06-19"]},"creators":{"author":[{"lastName":"Thung","firstName":"Ferdian"}]},"sentenceCased":true},{"key":"thungAutomaticRecommendationAPI2013","type":"inproceedings","fields":{"acmid":["3107694"],"author":["Thung, Ferdian","Wang, Shaowei","Lo, David","Lawall, Julia"],"booktitle":["Proc. 28th IEEEACM Int. Conf. Autom. Softw. Eng."],"date":["2013"],"ids":["Thung:2013:ARA:3107656.3107694"],"location":["Silicon Valley, CA, USA"],"nodoi":["10.1109/ASE.2013.6693088"],"note":["TL;DR \n\nThis work proposes an automated approach that takes as input a textual description of a feature request, and recommends methods in library APIs that developers can use to implement the feature."],"numpages":["11"],"pages":["290–300"],"publisher":["IEEE Press"],"title":["Automatic recommendation of API methods from feature requests"]},"creators":{"author":[{"lastName":"Thung","firstName":"Ferdian"},{"lastName":"Wang","firstName":"Shaowei"},{"lastName":"Lo","firstName":"David"},{"lastName":"Lawall","firstName":"Julia"}]},"sentenceCased":true},{"key":"thungDetectingSimilarApplications2012","type":"inproceedings","fields":{"acmid":["2473616"],"author":["Thung, Ferdian","Lo, David","Jiang, Lingxiao"],"booktitle":["Softw. Maint. ICSM 2012 28th IEEE Int. Conf. On"],"date":["2012"],"ids":["Lo:2012:DSA:2473496.2473616"],"keywords":["Cloning","Collaboration","Java","Search engines","Software systems","Tagging"],"nodoi":["10.1109/ICSM.2012.6405331"],"note":["TL;DR \n\nThis study complements the study by McMillan et al. by leveraging another source of information aside from API usage patterns, namely software tags, and shows that collaborative tagging is a promising source of Information useful for detecting similar software applications."],"numpages":["4"],"pages":["600–603"],"publisher":["IEEE"],"title":["Detecting similar applications with collaborative tagging"],"url":["http://ieeexplore.ieee.org/abstract/document/6405331/"],"urldate":["2017-03-14"]},"creators":{"author":[{"lastName":"Thung","firstName":"Ferdian"},{"lastName":"Lo","firstName":"David"},{"lastName":"Jiang","firstName":"Lingxiao"}]},"sentenceCased":true},{"key":"thurimellaGuidelinesManagingRequirements2017","type":"article","fields":{"abstract":["Requirements are identified and elaborated on the basis of stakeholders' decisions. The reasoning behind those decisions can be expressed as rationales. Systematic rationale management offers both short-term benefits, such as clearer requirements leading to fewer defects, and long-term benefits, such as simplified requirements evolution. However, little guidance exists for managing requirements rationales. This article presents guidelines to pragmatically capture, trace, maintain, and reuse such rationales. A list of questions augments the guidelines, improving their usability."],"author":["Thurimella, Anil Kumar","Schubanz, Mathias","Pleuss, Andreas","Botterweck, Goetz","undefined","undefined","undefined","undefined"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["software engineering"],"note":["TL;DR \n\nNew guidelines to pragmatically capture, trace, maintain, and reuse requirements rationales are presented, improving their usability."],"number":["1"],"pages":["82–90"],"title":["Guidelines for Managing Requirements Rationales"],"volume":["34"]},"creators":{"author":[{"lastName":"Thurimella","firstName":"Anil Kumar"},{"lastName":"Schubanz","firstName":"Mathias"},{"lastName":"Pleuss","firstName":"Andreas"},{"lastName":"Botterweck","firstName":"Goetz"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"ThWorkshopFlexible2018","type":"book","fields":{"date":["2018"],"journaltitle":["CEUR Workshop Proceedings"],"publisher":["CEUR-WS"],"title":["4 th workshop on flexible model-driven engineering (FlexMDE 2018)"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026811762&doi=10.1109%2fMiSE.2017.15&partnerID=40&md5=3a4d98c5291182c7be9acad3a7ea72c5"],"volume":["2245"]},"creators":{},"sentenceCased":true},{"key":"Tiarks2011","type":"article","fields":{"abstract":["Code reuse through copying and pasting leads to so-called software clones. These clones can be roughly categorized into identical fragments (type-1 clones), fragments with parameter substitution (type-2 clones), and similar fragments that differ through modified, deleted, or added statements (type-3 clones). Although there has been extensive research on detecting clones, detection of type-3 clones is still an open research issue due to the inherent vagueness in their definition. In this paper, we analyze type-3 clones detected by state-of-the-art tools and investigate type-3 clones in terms of their syntactic differences. Then, we derive their underlying semantic abstractions from their syntactic differences. Finally, we investigate whether there are code characteristics that indicate that a tool-suggested clone candidate is a real type-3 clone from a human's perspective. Our findings can help developers of clone detectors and clone refactoring tools to improve their tools."],"author":["Tiarks, Rebecca","Koschke, Rainer","Falke, Raimar"],"date":["2011-06-01"],"doi":["10.1007/s11219-010-9115-6"],"issn":["1573-1367"],"journaltitle":["Softw. Qual. J."],"note":["TL;DR \n\nThis paper analyzes type-3 clones detected by state-of-the-art tools and investigates type- 3 clones in terms of their syntactic differences, and derives their underlying semantic abstractions from their Syntactic differences."],"number":["2"],"pages":["295–331"],"title":["An extended assessment of type-3 clones as detected by state-of-the-art tools"],"volume":["19"]},"creators":{"author":[{"lastName":"Tiarks","firstName":"Rebecca"},{"lastName":"Koschke","firstName":"Rainer"},{"lastName":"Falke","firstName":"Raimar"}]},"sentenceCased":true},{"key":"tichyEmpiricalSoftwareResearch2011","type":"article","fields":{"author":["Tichy, Walter"],"date":["2011"],"issue":["June"],"journaltitle":["Ubiquity"],"note":["TL;DR \n\nWhen I began my studies at the Technical University of Munich in 1971, the authors had the luxury of an interactive, line-oriented editor for typing their programs, and switching from Assembler to Fortran, Algol, or Pascal was a no-brainer."],"pages":["2"],"shorttitle":["Empirical software research"],"title":["Empirical software research: An interview with Dag Sjøberg, University of Oslo, Norway"],"url":["http://dl.acm.org/citation.cfm?id=1998374"],"urldate":["2017-02-25"],"volume":["2011"]},"creators":{"author":[{"lastName":"Tichy","firstName":"Walter"}]},"sentenceCased":true},{"key":"Tijskens202120","type":"article","fields":{"langid":["english"],"abbrev_source_title":["J. Build. Perform. Simul."],"affiliation":["Department of Civil Engineering, Building Physics Section, KU Leuven, Kasteelpark Arenberg 40 Bus 2447, Heverlee, 3001, Belgium"],"author":["Tijskens, A.","Janssen, H.","Roels, S."],"correspondence_address1":["Tijskens, A.; Department of Civil Engineering, Kasteelpark Arenberg 40 Bus 2447, Belgium; email: astrid.tijskens@kuleuven.be"],"date":["2021"],"document_type":["Article"],"doi":["10.1080/19401493.2020.1832148"],"issn":["19401493"],"journaltitle":["J. Build. Perform. Simul."],"note":["cited By 2"],"number":["1"],"pages":["20–37"],"publisher":["Taylor and Francis Ltd."],"source":["Scopus"],"title":["The impact of a reduced training subspace on the prediction accuracy of neural networks for hygrothermal predictions"],"volume":["14"]},"creators":{"author":[{"lastName":"Tijskens","firstName":"A."},{"lastName":"Janssen","firstName":"H."},{"lastName":"Roels","firstName":"S."}]},"sentenceCased":true},{"key":"tisiLowcomoteTrainingNext2019","type":"article","fields":{"author":["Tisi, M.","Mottu, J.-M.","Kolovos, D.S.","family=Lara, given=J., prefix=de, useprefix=true","Guerra, E.","Di Ruscio, D.","Pierantonio, A.","Wimmer, M."],"date":["2019"],"ids":["tisiLowcomoteTrainingNext2019a,tisiLowcomoteTrainingNext2019b"],"journaltitle":["CEUR Workshop Proc."],"note":["cited By 13 \n\ncited By 13"],"pages":["73–78"],"series":["CEUR Workshop Proceedings"],"title":["Lowcomote: Training the next generation of experts in scalable low-code engineering platforms"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069741151&partnerID=40&md5=914fdb6e929cf085e7b9c50e11084ddb"],"volume":["2405"]},"creators":{"author":[{"lastName":"Tisi","firstName":"M."},{"lastName":"Mottu","firstName":"J.-M."},{"lastName":"Kolovos","firstName":"D.S."},{"lastName":"Lara","firstName":"J.","prefix":"de","useprefix":true},{"lastName":"Guerra","firstName":"E."},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Pierantonio","firstName":"A."},{"lastName":"Wimmer","firstName":"M."}]},"sentenceCased":true},{"key":"TisiPC13","type":"inproceedings","fields":{"langid":["english"],"author":["Tisi, Massimo","Perez, Salvador Martínez","Choura, Hassene"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Model-Driven Eng. Lang. Syst. - 16th Int. Conf. MODELS 2013 Miami FL USA Sept. 29 - Oct. 4 2013 Proc."],"date":["2013"],"doi":["10.1007/978-3-642-41533-3\\_40"],"editor":["Moreira, Ana","Schätz, Bernhard","Gray, Jeff","Vallecillo, Antonio","Clarke, Peter J."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nIt is shown that rule-based languages like ATL have strong parallelization properties, and a transformation engine can automatically parallelize execution when developing parallel model transformations in a general-purpose language."],"pages":["656–672"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Mon, 21 Jun 2021 12:26:18 +0200"],"title":["Parallel execution of ATL transformation rules"],"volume":["8107"]},"creators":{"author":[{"lastName":"Tisi","firstName":"Massimo"},{"lastName":"Perez","firstName":"Salvador Martínez"},{"lastName":"Choura","firstName":"Hassene"}],"editor":[{"lastName":"Moreira","firstName":"Ana"},{"lastName":"Schätz","firstName":"Bernhard"},{"lastName":"Gray","firstName":"Jeff"},{"lastName":"Vallecillo","firstName":"Antonio"},{"lastName":"Clarke","firstName":"Peter J."}]},"sentenceCased":true},{"key":"tisiTwinDrivenEngineeringOverview2021","type":"article","fields":{"langid":["english"],"author":["Tisi, M.","Bruneliere, H.","family=Lara, given=J., prefix=de, useprefix=true","Di Ruscio, D.","Kolovos, D."],"date":["2021"],"doi":["10.1007/978-3-030-85874-2_37"],"editor":["Dolgui A., Bernard A., Lemoine D., von Cieminski G., Romero D."],"ids":["tisiTwinDrivenEngineeringOverview2021a,tisiTwinDrivenEngineeringOverview2021b,tisiTwinDrivenEngineeringOverview2021c"],"isbn":["9783030858735"],"issn":["18684238"],"journaltitle":["IFIP Adv. Inf. Commun. Technol."],"keywords":["Analysis and verifications","Artificial intelligence","Complex physical systems","Control and management","Cyber Physical System","Cyber physical systems (CPSs)","Cyber-physical systems (CPS)","Digital twin","Embedded systems","Engineering activities","Engineering research","Industrial companies","Industrial management","Manufacture","Software engineering","System of systems","Virtual representations"],"note":["cited By 0 \n\ncited By 0 \n\ncited By 0"],"pages":["351–359"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"title":["Towards Twin-Driven Engineering: Overview of the State-of-The-Art and Research Directions"],"volume":["630 IFIP"]},"creators":{"author":[{"lastName":"Tisi","firstName":"M."},{"lastName":"Bruneliere","firstName":"H."},{"lastName":"Lara","firstName":"J.","prefix":"de","useprefix":true},{"lastName":"Di Ruscio","firstName":"D."},{"lastName":"Kolovos","firstName":"D."}],"editor":[{"lastName":"Dolgui A.","suffix":"Bernard A.","firstName":"Lemoine D., von Cieminski G., Romero D."}]}},{"key":"Tong2021298","type":"article","fields":{"abstract":["The traditional information management model has poor data transmission efficiency in the process of pushing information services. To solve this problem, this paper designs a hotel marketing information management model based on deep learning. Using Oracle relational database and MVC architecture to build a marketing information database, then use deep learning to extract information features, and classify marketing information of different service categories, connect hotel management and client, and integrate model management functions to provide information services for hotel managers and customers. The experimental results show that the data throughput and transmission rate of the above model are higher than those of the traditional model, and the information transmission efficiency is improved. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering."],"author":["Tong, L.","Wang, F."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-82562-1_28"],"editor":["Fu W., Xu Y., Zhang Y., Wang S."],"isbn":["9783030825614"],"issn":["18678211"],"journaltitle":["Lect. Notes Inst. Comput. Sci. Soc.-Inform. Telecommun. Eng. LNICST"],"note":["cited By 0"],"pages":["298–310"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Design of hotel marketing information management model based on deep learning"],"volume":["387"]},"creators":{"author":[{"lastName":"Tong","firstName":"L."},{"lastName":"Wang","firstName":"F."}],"editor":[{"lastName":"Fu W.","suffix":"Xu Y.","firstName":"Zhang Y., Wang S."}]},"sentenceCased":true},{"key":"Toscano20164358","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["IEEE Congr. Evol. Comput., CEC"],"affiliation":["CINVESTAV-Tamaulipas, Cd. Victoria, Tamaulipas, 87130, Mexico; Michigan State University, East LansingMI, United States"],"art_number":["7744344"],"author":["Toscano, G.","Deb, K."],"date":["2016"],"document_type":["Conference Paper"],"doi":["10.1109/CEC.2016.7744344"],"isbn":["978-1-5090-0622-9"],"note":["cited By 2 \n\nTL;DR \n\nBesides finding that Tchebycheff scalarizing function and Gaussian processes for machine learning are accurate methods to handle many-objective problems, one of the most important findings involves the capabilities of metamodeling techniques to approximate the ranking procedure from the information gathered from the parameter space."],"pages":["4358–4365"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["2016 IEEE Congress on Evolutionary Computation, CEC 2016"],"source":["Scopus"],"title":["Study of the approximation of the fitness landscape and the ranking process of scalarizing functions for many-objective problems"]},"creators":{"author":[{"lastName":"Toscano","firstName":"G."},{"lastName":"Deb","firstName":"K."}]},"sentenceCased":true},{"key":"totterdaleCASESTUDYUTILIZATION2018","type":"article","fields":{"langid":["english"],"abstract":["Research data must be collected and maintained in compliance with a myriad of laws and regulations that protect the privacy of participant’s information, and should be captured in a manner that is cost effective and timely. This paper discusses research data collection, explores challenges and approaches for collecting data, and describes how low-code development technology can be utilized to facilitate the secure and efficient collection of research data in the healthcare industry. This paper is based on research being conducted in the healthcare industry but has broad applicability across other industries and research areas that collect personally identifiable information, or other sensitive data protected by U.S. or international laws and regulations."],"author":["Totterdale, Robert L"],"date":["2018"],"number":["2"],"pages":["8"],"title":["CASE STUDY: THE UTILIZATION OF LOW-CODE DEVELOPMENT TECHNOLOGY TO SUPPORT RESEARCH DATA COLLECTION"],"volume":["19"]},"creators":{"author":[{"lastName":"Totterdale","firstName":"Robert L"}]}},{"key":"Toutiaee20201097","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - IEEE Int. Conf. Big Data, Big Data"],"affiliation":["University of Georgia, Computer Science Department, Athens, GA, United States"],"art_number":["9378132"],"author":["Toutiaee, M.","Miller, J.A."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/BigData50022.2020.9378132"],"editor":["Wu X., Jermaine C., Hu X.T., Kotevska O., Lu S., Xu W., Aluru S., Zhai C., Al-Masri E., Chen Z., Saltz J., Xiong L."],"isbn":["978-1-72816-251-5"],"note":["cited By 0"],"pages":["1097–1102"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020"],"source":["Scopus"],"title":["Gaussian function on response surface estimation"]},"creators":{"author":[{"lastName":"Toutiaee","firstName":"M."},{"lastName":"Miller","firstName":"J.A."}],"editor":[{"lastName":"Wu X.","suffix":"Jermaine C.","firstName":"Hu X.T., Kotevska O., Lu S., Xu W., Aluru S., Zhai C., Al-Masri E., Chen Z., Saltz J., Xiong L."}]},"sentenceCased":true},{"key":"trakadasArtificialIntelligenceBasedCollaboration2020","type":"article","fields":{"langid":["english"],"abstract":["The digitization of manufacturing industry has led to leaner and more efficient production, under the Industry 4.0 concept. Nowadays, datasets collected from shop floor assets and information technology (IT) systems are used in data-driven analytics efforts to support more informed business intelligence decisions. However, these results are currently only used in isolated and dispersed parts of the production process. At the same time, full integration of artificial intelligence (AI) in all parts of manufacturing systems is currently lacking. In this context, the goal of this manuscript is to present a more holistic integration of AI by promoting collaboration. To this end, collaboration is understood as a multi-dimensional conceptual term that covers all important enablers for AI adoption in manufacturing contexts and is promoted in terms of business intelligence optimization, human-in-the-loop and secure federation across manufacturing sites. To address these challenges, the proposed architectural approach builds on three technical pillars: (1) components that extend the functionality of the existing layers in the Reference Architectural Model for Industry 4.0; (2) definition of new layers for collaboration by means of human-in-the-loop and federation; (3) security concerns with AI-powered mechanisms. In addition, system implementation aspects are discussed and potential applications in industrial environments, as well as business impacts, are presented."],"author":["Trakadas, Panagiotis","Simoens, Pieter","Gkonis, Panagiotis","Sarakis, Lambros","Angelopoulos, Angelos","Ramallo-González, Alfonso P.","Skarmeta, Antonio","Trochoutsos, Christos","Calvο, Daniel","Pariente, Tomas","Chintamani, Keshav","Fernandez, Izaskun","Irigaray, Aitor Arnaiz","Parreira, Josiane Xavier","Petrali, Pierluigi","Leligou, Nelly","Karkazis, Panagiotis"],"date":["2020-01"],"doi":["10.3390/s20195480"],"issue":["19"],"journaltitle":["Sensors"],"keywords":["DONE"],"note":["<b>Gray Annotations (18/12/2020, 15:08:12)</b> \n\n\"Industry 4.0 concepts are expected to significantly increase their footprint in industrial sectors by 20% in the next five years, since they allow leaner and more ecient production [4,5]\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">Trakadas et al 2020:5481</a>) \n\n\"In this context, many manufacturing companies are interested in accelerating the adoption and integration of secure, trustworthy artificial intelligence (AI) [6]\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">Trakadas et al 2020:5481</a>) \n\n\"AI-based manufacturing has the potential to improve the business key performance indicators (KPIs) of manufacturing processes by leveraging heterogeneous industrial big data analysis, information modelling and federation [7-9]\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">Trakadas et al 2020:5481</a>) \n\n\"interconnection of AI-based manufacturing processes with currently deployed wireless networks is a challenging research field, especially when central processing is performed outside industrial premises [10,11]\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">Trakadas et al 2020:5481</a>) \n\n\"AI is critical to the cybersecurity aspect of an IIoT-enabled connected manufacturing environment, for accurately detecting and mitigating threats [16-19]\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">Trakadas et al 2020:5481</a>) \n\n\"Industry 4.0 will make machines increasingly smarter by using AI models [28]\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n<i>REFERENCE IMPORTANTE CHE MOTIVA ASPETTI DI INTEROPERABILITA' (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=4\">note on p.5483</a>)</i> \n\n\"TensorFlow Federated provide support for decentralized AI models learning or computation over locally controlled data sources [39].\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=7\">Trakadas et al 2020:5486</a>) \n\n\"adopting this novel approach [40], this scheme heavily reduces the administrative eort for key sharing and management, while ensuring end-to-end information protection\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=8\">Trakadas et al 2020:5487</a>) \n\n\"adversarial attacks, which is the core element of trustworthy AI, has recently received much attention [41].\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=8\">Trakadas et al 2020:5487</a>) \n\n\"The creation of models of the state and behavior can be done in a semi-automatic manner, using a newly devised AutoML tool that takes as input vector representations of sequential input data [46]\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">Trakadas et al 2020:5488</a>) \n\n<i>AUTOML (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">note on p.5488</a>)</i> \n\n\"Currently, federated learning is being adopted in dierent scenarios such as banking [61] and healthcare [62].\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">Trakadas et al 2020:5490</a>) \n\n<i>HERE WE HAVE COUPLE OF CONCRETE SCNEARIOS USING FEDERATED LEARNING (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">note on p.5490</a>)</i> \n\n\"There are currently many research activities to develop faster or more resource ecient PSI protocols [38,64].\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">Trakadas et al 2020:5490</a>) \n\n\"26. Sittón-Candanedo, I.; Alonso, R.C.; Rodríguez-González, S.; Alberto García Coria, J.; De La Prieta, F. Edge Computing Architectures in Industry 4.0: A General Survey and Comparison. In International Workshop on Soft Computing Models in Industrial and Environmental Applications; Springer: Cham, Switzerland, 2019; Volume 950.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=18\">Trakadas et al 2020:5497</a>) \n\n\"Comiter, M. Attacking Artificial Intelligence, AI's Security Vulnerability and What Policymakers about It. In Belfer Center Paper; Harvard Kenedy School: Cambridge, MA, USA, 2019.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=19\">Trakadas et al 2020:5498</a>) \n\n<b>Green Annotations (18/12/2020, 15:08:12)</b> \n\n\"important enablers for AI adoption in manufacturing contexts and is promoted in terms of business intelligence optimization, human-in-the-loop and secure federation across manufacturing sites\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=1\">Trakadas et al 2020:5480</a>) \n\n\"(1) components that extend the functionality of the existing layers in the Reference Architectural Model for Industry 4.0; (2) definition of new layers for collaboration by means of human-in-the-loop and federation; (3) security concerns with AI-powered mechanisms.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=1\">Trakadas et al 2020:5480</a>) \n\n\"most AI techniques are based on mathematical models that are dicult to understand by the general public, so most people use AI-based technology as a black box that they eventually start to trust based on their personal experience\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">Trakadas et al 2020:5481</a>) \n\n\"The application of human-centric AI (HAI) in internet of things (IoT) systems, so that IoT systems cannot only learn from users but also provide easy-to-understand explanations about decisions or estimations is a new research field [12].\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">Trakadas et al 2020:5481</a>) \n\n<i>ASPETTI MOTIVAZIONALI MOLTO IMPORTANTI. (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">note on p.5481</a>)</i> \n\n\"At the same time, introducing AI will lead to a more productive and safer working space, relieving human workers from routine procedures and employing intelligent machines and robots to perform heavy tasks, thus allowing human workers to focus on creativity, reasoning and decision making [20,21].\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">Trakadas et al 2020:5481</a>) \n\n<i>MOTIVATION (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">note on p.5481</a>)</i> \n\n\"to provide an IIoT-based system that increases performance and safety in the manufacturing domain.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">Trakadas et al 2020:5481</a>) \n\n<i>MAIN GOAL (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=2\">note on p.5481</a>)</i> \n\n\"AI solutions are implemented in dispersed and isolated components of manufacturing IT systems.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n\"Current Industry 4.0 reference architectures do not properly integrate the needed building blocks such as new deployment paradigms (e.g., edge-based learning to reduce bandwidth load on the enterprise network)\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n\"scalable data-processing pipelines and information models\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n\"AI-enabled digital twins used for monitoring and optimizing business intelligence [24-26]\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n<i>IMPORTANT MOTIVATIONS AND CONTEXT DESCRIPTION (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">note on p.5482</a>)</i> \n\n\"availability of big data has been one of the most important enablers for the recent wave of AI innovations [27]\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n\"Moreover, every phase of AI algorithm design requires high-level skills (model selection, training, hyperparameter optimization). In the agile manufacturing of the future, these costs must be amortized over low-volume batches (even lot-size-one).\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n<i>IMPORTANT MOTIVATIONS AND CONTEXT DESCRIPTION (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">note on p.5482</a>)</i> \n\n\"AI technologies should not only be used for data analytics in support of business intelligence, but also for automated decision making on manufacturing process parameters and configurations.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n\"AI algorithms are often black-box models (e.g., deep learning), while the inner workings of an algorithm fetched from a remote repository are not fully understood or the decisions of one algorithm create a conflict with other algorithmic decisions\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n\"Proper secure federation mechanisms and AI-based cyberattack risk analysis are crucial cross-cutting concerns in AI-based manufacturing systems.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n\"the performance of modern AI techniques requires large volumes of high-quality data which are often not available inside a single enterpris\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n<i>MOTIVA BENE LA QUESTIONE DI LUCIANO, PERCHE' SI HA BISOGNO DI FEDERATED LEARNING (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">note on p.5482</a>)</i> \n\n\"AI techniques will be used to extend and improve the levels of communication and collaboration between computer systems and human workers.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n\"new intelligent design and decision-making tools must be developed to promote human agency and oversight, simplifying the understanding and usage of AI results and considering multiple collaboration schemes depending on the situation. Human-AI will work in tandem in any phase of the product construction process, from design, over intelligent manufacturing execution monitoring to predictive maintenance.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">Trakadas et al 2020:5482</a>) \n\n<i>OBIETTIVI (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=3\">note on p.5482</a>)</i> \n\n\"collaborative and intelligent factory of the future.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=5\">Trakadas et al 2020:5484</a>) \n\n\"ration with other manufacturing sites, while security is aboration and for cross-cutting concern. In the following, we describe the functionality of each component as shown inis a cross-cutting Figure 2 concern\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=5\">Trakadas et al 2020:5484</a>) \n\n<i>LUCIANO (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=5\">note on p.5484</a>)</i> \n\n\"the factory-wide datasets so that the components of the upperyersistoperform layers can make decisions based on the outcome of AI algorithms running on top of such processedrlayerscanmake data streams or batch datasets. Raw (non-labeled) data generated by manufacturing devices ared data streams or processed alo batchdatasets\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=5\">Trakadas et al 2020:5484</a>) \n\n\"re functionality to deploy AI algorithms closer to the sensor (edgeer to the sensor computing) and to detect shifts in the dataset statistics, indicating a need to retrain algorithms. Inetrainalgorithms\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=5\">Trakadas et al 2020:5484</a>) \n\n\"AI-enabled data pipelines orchestrator component enables the creation and deployment ofnddeploymentof data processing pipelines, with two major objectivemajorobjectives:\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=5\">Trakadas et al 2020:5484</a>) \n\n\"(i) the component should allow the possibilitythepossibilityto to set up pipelines consisting of typical data processing tasks (feature conversion, feature reduction,rereduction,data data anonymization and fusion, data cleaning, labeling and annotation, etc.) and AI models (used inodels(usedin the the services of the upper latheupperlayers)\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=5\">Trakadas et al 2020:5484</a>) \n\n\"e factory; (ii) thei)thecomponent component should allow the deployment of the pipelines and the orchestration of the differentcomponents\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=5\">Trakadas et al 2020:5484</a>) \n\n\"automate the deployment process on distributed infrastructure (edge device, edge cloud, public cloud) and to orchestrate the dierent modules and exact frameworks needed to run the processes.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=6\">Trakadas et al 2020:5485</a>) \n\n<i>IMPORTANTE: RELATIVO AL AI PIPELINES (DESIGN AND DEPLOYMENT) (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=6\">note on p.5485</a>)</i> \n\n\"Edge-based learning is required for latency-sensitive situations and/or when upstream bandwidth is insucient, e.g., audio and video from an augmented reality (AR) headset or processing light detection and ranging (LIDAR) data on a mobile robot. The component will support novel neural network architectures that can be trained without requiring large amounts of labelled data and that are resource-ecient [36].\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=6\">Trakadas et al 2020:5485</a>) \n\n<i>IMPORTANTE LUCIANO (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=6\">note on p.5485</a>)</i> \n\n\"threat intelligence manager takes advantage of the collected and curated datasets and applies AI algorithms for executing threat analysis in order not only to predict potential cybersecurity incidents but most importantly to manage and mitigate such incidents in a timely manner.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=6\">Trakadas et al 2020:5485</a>) \n\n\"4.2. Functional and Business Intelligence\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=6\">Trakadas et al 2020:5485</a>) \n\n\"mirror the state of the production process in digital twins, including the logic that determines the transition to other production steps or states.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=6\">Trakadas et al 2020:5485</a>) \n\n\"This layer provides innovative tools that will facilitate intuitive and ecient collaboration between humans, machines and AI systems allowing them to take advantage of each other 's strengths for more eective cooperative and intuitive task execution and decision making\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=7\">Trakadas et al 2020:5486</a>) \n\n\"Federated Learning component aims at solving the problem of data collection for feeding or training AI models, while assuring the ownership and confidentiality of the data. In manufacturing, most (if not all) data and information are confidential because they relate directly to details of the production process, product characteristics, volumes, etc.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=7\">Trakadas et al 2020:5486</a>) \n\n\"The inter-manufacturing knowledge exchange serves as an interface for knowledge exchange across manufacturing sites or distinct manufacturing processes.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=7\">Trakadas et al 2020:5486</a>) \n\n\"ince there is a need to control what information is exposed and exchanged, rather than allowing open access to the local knowledge repository, this component contains a query engine to handle external requests. Such query engines also enable the realization of a federated query-processing mechanism over multiple sites.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=7\">Trakadas et al 2020:5486</a>) \n\n<i>FEDERATED QUERY-RPOCESSING METCHANISM OVER MULTIPLE SITES (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=7\">note on p.5486</a>)</i> \n\n\"4.5. Security and Authorization\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=8\">Trakadas et al 2020:5487</a>) \n\n\"security and authorization requirements on information and data sharing.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=8\">Trakadas et al 2020:5487</a>) \n\n\"Cybersecurity for Artificial Intelligence (AI)\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=8\">Trakadas et al 2020:5487</a>) \n\n\"Artificial intelligence attacks, i.e., attacks on the AI algorithm, can take two forms: input attacks and poisoning attacks. The former consists in manipulating the input to the AI system during the operation phase so that it delivers the wrong results. Input attacks are relatively easy to launch and succeed since they do not require a manipulated AI system. Poisoning attacks, on the other hand, have to do with the corruption of the process used to build the AI model. In this case, inaccurate or mislabeled data are provided to the model during the training phase to manipulate the learning process. This type of attack can also be launched against federated learning; in this case, manipulated data or an algorithm of a member of the federation can result in the corruption of the global model.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=8\">Trakadas et al 2020:5487</a>) \n\n<i>IMPORTANT! RELATED TO AML WORK!!! IT APPLIES ALSO IN THE CASE OF FEDERATED LEARNING (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=8\">note on p.5487</a>)</i> \n\n\"challenges regarding the implementation of the innovative AI-based components of the proposed system\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=8\">Trakadas et al 2020:5487</a>) \n\n\"AI-Driven Modelling of Manufacturing Assets\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=8\">Trakadas et al 2020:5487</a>) \n\n\"Digital twins are virtual, high-fidelity models of the current state and internal behavior of physical assets on the shop floor [25].\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=8\">Trakadas et al 2020:5487</a>) \n\n\"there is a lack of information models and process libraries that allow users to replicate and scale their digital twins.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=8\">Trakadas et al 2020:5487</a>) \n\n\"AutoML\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">Trakadas et al 2020:5488</a>) \n\n<i>DA VEDERE AUTOML (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">note on p.5488</a>)</i> \n\n\"For the IT resource aspect, processing all raw data on a public cloud infrastructure is an unscalable solution for many manufacturing companies, either because there is too much sensor data to upload, the latency to the cloud is prohibitive or because the sensor data is too sensitive and the company does not want to expose this. Therefore, edge computing has been proposed and several reference architectures for edge computing in Industry 4.0 have been proposed [26\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">Trakadas et al 2020:5488</a>) \n\n<i>LACK OF RESOURCES FOR AI IN INDUSTRY (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">note on p.5488</a>)</i> \n\n\"Techniques to make deep neural networks available for the latter form of edge computing start to find their way into production as more user-friendly tools become available. For instance, TensorFlow Lite allows converting a trained model for deployment on microcontrollers or embedded Graphics Processor Units (GPUs).\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">Trakadas et al 2020:5488</a>) \n\n<i>TensorFlow Lite: Come diceva Luciano (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">note on p.5488</a>)</i> \n\n\"5.2. Multi-Channel, Context-Aware Interaction on the Shop Floor\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">Trakadas et al 2020:5488</a>) \n\n<i>Relativo alla parte di NLI di Mariani (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">note on p.5488</a>)</i> \n\n\"The latest developments [48,49] allow humans to convey information with AI systems through multiple channels by integrating advanced human-machine interfaces (gestures, facial expressions). These interfaces, which can be obtained by using 2-D and/or 3-D cameras and other sensors, such as gyroscopes or accelerometers, oer information related to the context and the situation that is relevant to the interaction.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">Trakadas et al 2020:5488</a>) \n\n<i>Gesture, facial expressions interaction etc (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">note on p.5488</a>)</i> \n\n\"voice understanding\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">Trakadas et al 2020:5488</a>) \n\n\"experts in simulations and modelling are not available in SMEs and large enterprises, and that data-driven digital twins are usually trained on data collected at system level. These limitations make it economically costly to develop novel digital twins, which is often needed in modern manufacturing with agile reconfigurations.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">Trakadas et al 2020:5488</a>) \n\n<i>IMPORTANT - LACK OF EXPERTS (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">note on p.5488</a>)</i> \n\n\"Data-driven digital twins are built using machine learning.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">Trakadas et al 2020:5488</a>) \n\n\"DL comes with its own problems: it requires domain knowledge to select the appropriate machine learning pipeline and it is very resource hungry in terms of computing and storage resources [36,43,44]\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">Trakadas et al 2020:5488</a>) \n\n<i>PROBLEMS ON DEEP LEARNING (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=9\">note on p.5488</a>)</i> \n\n\"Intelligent Decision Support\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=10\">Trakadas et al 2020:5489</a>) \n\n\"increase the eciency in the decision-making process\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=10\">Trakadas et al 2020:5489</a>) \n\n\"urrent approaches fail to learn from decisions taken by humans.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=10\">Trakadas et al 2020:5489</a>) \n\n\"ontinuous learning functionalities\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=10\">Trakadas et al 2020:5489</a>) \n\n\"Threat Intelligence Manager (TIM)\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=10\">Trakadas et al 2020:5489</a>) \n\n\"In the case of malicious activity, various AI algorithms, such as naïve Bayes, random forests and support vector machine (SVM) have been proposed [55].\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=10\">Trakadas et al 2020:5489</a>) \n\n\"By exploiting advanced AI methods, the threat intelligence manager (TIM) component intends to model the dynamic interactions of Industry 4.0 subsystems and discover known and unknown attacks, while surpassing existing signatureand anomaly-based methods.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=10\">Trakadas et al 2020:5489</a>) \n\n\"Federated AI across Manufacturing Sites\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=10\">Trakadas et al 2020:5489</a>) \n\n\"In this context, federated query processing [59] is an active research field dealing with techniques for proper delegation of the execution of parts of queries to specific sources\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">Trakadas et al 2020:5490</a>) \n\n<i>IMPORTANT! FEDERATED QUERY PROCESSING (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">note on p.5490</a>)</i> \n\n\"To improve the scalability of such federations, aggregation techniques could be used, where one or more independent aggregators would continuously crawl sources, and maintain data summaries [60].\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">Trakadas et al 2020:5490</a>) \n\n\"Joining datasets held by dierent actors can address this issue. Oft\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">Trakadas et al 2020:5490</a>) \n\n<i>THAT'S THE GOAL TO ADDRESS THE ISSUE THAT SINGLE PARTY DOES NOT HAVE SUFFICIENTLY LARGE DATA SETS FOR TRAINING (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">note on p.5490</a>)</i> \n\n\"federated learning provides a solution enabling machine learning over distributed and decentralized datasets.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">Trakadas et al 2020:5490</a>) \n\n\"federated learning opens up new business models (AI as a Service, AIaaS) to analyze data provided by a customer\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">Trakadas et al 2020:5490</a>) \n\n\"federated learning represents a solution to this problem enabling both the service provider and its customer to achieve their objectives while preserving the business assets.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">Trakadas et al 2020:5490</a>) \n\n\"t is possible to generate in an automatic manner intelligent services in parts of the building blocks or in the process as a whole.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=11\">Trakadas et al 2020:5490</a>) \n\n\"handling and labeling of data of very dierent types.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=12\">Trakadas et al 2020:5491</a>) \n\n\"dierent system components can be exploited for optimizing manufacturing logistics processes, and facilitating zero-defect manufacturing\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=12\">Trakadas et al 2020:5491</a>) \n\n\"The current AMR production logistics is supposed to be carried out by the system illustrated in Figure 3a\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=12\">Trakadas et al 2020:5491</a>) \n\n\"t is assumed that there are two issues that need to be addressed in an ecient manner: (a) unpredictable delivery times and downtime, and (b) vulnerability to network attacks.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=12\">Trakadas et al 2020:5491</a>) \n\n\"le and machines at high levels of safety and tenance services for their AMRs\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=13\">Trakadas et al 2020:5492</a>) \n\n\"reduced by avoiding heavy vehicles like forklifts or tuggers in fast-moving intralogistics areasorevencompromise during pe site safety.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=13\">Trakadas et al 2020:5492</a>) \n\n\"neously, AMR downtime is undesirable andAMRstothenetwork should be reduced as much as possible. entcybersecurityriskduetodynamicsoftwarevulnerabilitiesthataffect This scenario assumes that a company has implemented a flmunicationprotocols.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=13\">Trakadas et al 2020:5492</a>) \n\n\"Advances leveraging the proposed platform\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=13\">Trakadas et al 2020:5492</a>) \n\n\"learning from patterns of business process models and anomaly detection techniques\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=13\">Trakadas et al 2020:5492</a>) \n\n\"prediction of AMR downtime can be done using multivariate statistical models on data of key AMR system parameters\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=13\">Trakadas et al 2020:5492</a>) \n\n\"Edge-based (i.e., on-robot) learning can be used to reduce the amount of data uploaded via the customer network to AMR supplier 's cloud back-end and assure the confidentiality of production activity related data\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=13\">Trakadas et al 2020:5492</a>) \n\n\"run AI observers that collect data about typical movement patterns on the floor (e.g., edge-based learning on surveillance camera data) and about how fleet behaviors relate to production goals (e.g., from Enterprise Resource Planning—ERP and Manufacturing Execution System—MES systems)\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=13\">Trakadas et al 2020:5492</a>) \n\n\"As unauthorized access to machines and data might compromise the physical integrity of human workers, communication between AMR, the platform and AMR supplier 's cloud back-end can be secured by signcryption schemes provided by the system.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=14\">Trakadas et al 2020:5493</a>) \n\n\"The number and the diversity of characteristics of the orders do not allow for common process standardization.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=15\">Trakadas et al 2020:5494</a>) \n\n<i>DIVERSITY (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=15\">note on p.5494</a>)</i> \n\n\"The data and information collected across the departments through manual and automatic procedures are solely processed by each department, without considering factory-wide optimization metrics.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=15\">Trakadas et al 2020:5494</a>) \n\n<i>FACTORY-WIDE OPTIMIZATION METRICS (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=15\">note on p.5494</a>)</i> \n\n\"The deficiencies are observed, in the majority of the cases, during the quality control of the final product, thus leaving no space for corrective actions.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=15\">Trakadas et al 2020:5494</a>) \n\n<i>NEEDS FOR EARLY CORRECTIVE ACTIONS (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=15\">note on p.5494</a>)</i> \n\n\"letting personnel only make the final decisions.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=15\">Trakadas et al 2020:5494</a>) \n\n<i>LACK OF PERSONNEL KNOWLEDGE AND TRAINING ON THE USE OF INNOVATIVE TOOLS (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=15\">note on p.5494</a>)</i> \n\n\"The combination of data analytics and In testing and validation procedure, the goal is to define a set of KPIs per potential use case andhat can be used for validate the performance of our proposed AI-barootcause analyses\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=15\">Trakadas et al 2020:5494</a>) \n\n<i>WHAT-IF ANALYSIS, PROJECTIONS, AND ROOT CAUSE ANALYSIS (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=15\">note on p.5494</a>)</i> \n\n\"manufacturers will be capable of realizing agile production processes and improve the quality of products and processes\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=16\">Trakadas et al 2020:5495</a>) \n\n<i>BUSINESS IMPACTS (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=16\">note on p.5495</a>)</i> \n\n\"more competitive in the market and thus increase their market share.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=16\">Trakadas et al 2020:5495</a>) \n\n\"The federated intelligence layer introduced in our approach enables new business models (e.g., high-quality AIaaS), as well as the collaboration of dierent industries towards the creation of digital twins\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=16\">Trakadas et al 2020:5495</a>) \n\n\"rchitecture that facilitates the collaboration between manufacturing machinery, AI and humans\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=16\">Trakadas et al 2020:5495</a>) \n\n<i>FACILITATING ARCHITECTURE!!! (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=16\">note on p.5495</a>)</i> \n\n\"Last but not least, companies with expertise in AI for manufacturing can create significantly higher revenues by being capable of integrating their components with IoT and IT systems from dierent vendors/creators.\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=16\">Trakadas et al 2020:5495</a>) \n\n<i>OPEN COLLABORATION AMONG COMPONENTS FROM DIFFERENT VENDORS/CREATIOS (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=16\">note on p.5495</a>)</i> \n\n\"components for timely data collection\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=17\">Trakadas et al 2020:5496</a>) \n\n\"processing and curation\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=17\">Trakadas et al 2020:5496</a>) \n\n\"elying on the dynamic instantiation of data pipelines\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=17\">Trakadas et al 2020:5496</a>) \n\n\"while addressing security, privacy and confidentiality concerns\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=17\">Trakadas et al 2020:5496</a>) \n\n\"cross the physical and virtual entities\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=17\">Trakadas et al 2020:5496</a>) \n\n\"The collected data and information models are transformed into AI-enabled functional intelligence, leading to business knowledge, actionable insights and informed decisions, while being capable of recognizing complex events and process deviations that cannot be captured easily and in a timely way through human judgment\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=17\">Trakadas et al 2020:5496</a>) \n\n<i>MAIN GOALS/BENEFITS (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=17\">note on p.5496</a>)</i> \n\n\"25. Tao, F.; Qi, Q.; Wang, L.; Nee, A.Y.C. Digital Twins and Cyber-Physical Systems toward Smart Manufacturing and Industry 4.0. Engineering 2019, 5, 653-661. [CrossRef]\" (<a href=\"zotero://open-pdf/library/items/K7JAGWW6?page=18\">Trakadas et al 2020:5497</a>) \n\nTL;DR \n\nThe goal of this manuscript is to present a more holistic integration of AI by promoting collaboration as a multi-dimensional conceptual term that covers all important enablers for AI adoption in manufacturing contexts and is promoted in terms of business intelligence optimization, human-in-the-loop and secure federation across manufacturing sites."],"number":["19"],"pages":["5480"],"publisher":["Multidisciplinary Digital Publishing Institute"],"shorttitle":["An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing"],"title":["An Artificial Intelligence-Based Collaboration Approach in Industrial IoT Manufacturing: Key Concepts, Architectural Extensions and Potential Applications"],"volume":["20"]},"creators":{"author":[{"lastName":"Trakadas","firstName":"Panagiotis"},{"lastName":"Simoens","firstName":"Pieter"},{"lastName":"Gkonis","firstName":"Panagiotis"},{"lastName":"Sarakis","firstName":"Lambros"},{"lastName":"Angelopoulos","firstName":"Angelos"},{"lastName":"Ramallo-González","firstName":"Alfonso P."},{"lastName":"Skarmeta","firstName":"Antonio"},{"lastName":"Trochoutsos","firstName":"Christos"},{"lastName":"Calvο","firstName":"Daniel"},{"lastName":"Pariente","firstName":"Tomas"},{"lastName":"Chintamani","firstName":"Keshav"},{"lastName":"Fernandez","firstName":"Izaskun"},{"lastName":"Irigaray","firstName":"Aitor Arnaiz"},{"lastName":"Parreira","firstName":"Josiane Xavier"},{"lastName":"Petrali","firstName":"Pierluigi"},{"lastName":"Leligou","firstName":"Nelly"},{"lastName":"Karkazis","firstName":"Panagiotis"}]}},{"key":"tranDependableControlSystems2015","type":"article","fields":{"langid":["english"],"author":["Tran, Tri","Ha, Q.P."],"date":["2015-11"],"doi":["10.1016/j.isatra.2015.08.008"],"issn":["00190578"],"journaltitle":["ISA Trans."],"pages":["303–313"],"title":["Dependable control systems with Internet of Things"],"volume":["59"]},"creators":{"author":[{"lastName":"Tran","firstName":"Tri"},{"lastName":"Ha","firstName":"Q.P."}]},"sentenceCased":true},{"key":"tranMultiBackEndsModel2013","type":"incollection","fields":{"author":["Tran, Ngoc Viet","Ganser, Andreas","Lichter, Horst"],"booktitle":["Computational Science and Its Applications–ICCSA 2013"],"date":["2013"],"pages":["160–174"],"publisher":["Springer"],"title":["Multi Back-Ends for a Model Library Abstraction Layer"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-39646-5_12"],"urldate":["2015-06-24"]},"creators":{"author":[{"lastName":"Tran","firstName":"Ngoc Viet"},{"lastName":"Ganser","firstName":"Andreas"},{"lastName":"Lichter","firstName":"Horst"}]}},{"key":"tsamardinosBootstrappingOutofsamplePredictions2018","type":"article","fields":{"langid":["english"],"author":["Tsamardinos, Ioannis","Greasidou, Elissavet","Borboudakis, Giorgos"],"date":["2018-12"],"doi":["10.1007/s10994-018-5714-4"],"issn":["0885-6125, 1573-0565"],"journaltitle":["Mach Learn"],"note":["TL;DR \n\nThis work presents an efficient bootstrap method that corrects for the bias, called Bootstrap Bias Corrected CV (BBC-CV), and employs again the idea of bootstrapping the out-of-sample predictions to speed up the CV process."],"number":["12"],"pages":["1895–1922"],"title":["Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation"],"volume":["107"]},"creators":{"author":[{"lastName":"Tsamardinos","firstName":"Ioannis"},{"lastName":"Greasidou","firstName":"Elissavet"},{"lastName":"Borboudakis","firstName":"Giorgos"}]},"sentenceCased":true},{"key":"Tsantalis:2018:AER:3180155.3180206","type":"inproceedings","fields":{"acmid":["3180206"],"author":["Tsantalis, Nikolaos","Mansouri, Matin","Eshkevari, Laleh M.","Mazinanian, Davood","Dig, Danny"],"booktitle":["Proc. 40th Int. Conf. Softw. Eng."],"date":["2018"],"isbn":["978-1-4503-5638-1"],"keywords":["abstract syntax tree","accuracy","commit","Git","Oracle","refactoring"],"location":["New York, NY, USA"],"nodoi":["10.1145/3180155.3180206"],"numpages":["12"],"pages":["483–494"],"publisher":["ACM"],"series":["ICSE '18"],"title":["Accurate and efficient refactoring detection in commit history"],"url":["http://doi.acm.org/10.1145/3180155.3180206"]},"creators":{"author":[{"lastName":"Tsantalis","firstName":"Nikolaos"},{"lastName":"Mansouri","firstName":"Matin"},{"lastName":"Eshkevari","firstName":"Laleh M."},{"lastName":"Mazinanian","firstName":"Davood"},{"lastName":"Dig","firstName":"Danny"}]},"sentenceCased":true},{"key":"TSEFOCUSJournalPaper","type":"online","fields":{"langid":["british"],"abstract":["Supporting software development with API function calls and usage patterns Link: https://github.com/MDEGroup/FOCUS/tree/master/TSE-FOCUS Journal: Transactions on Software Engineering (submission instruction) Introduction API function calls recommendation Issues (Redundancy, execution time) Liter..."],"organization":["Google Docs"],"title":["TSE-FOCUS Journal Paper"],"url":["https://docs.google.com/document/d/1_40QPw-9Ddk7yZ2fQy1HRaPtK5I1dI_TxOSuOWcHKkU/edit?usp=embed_facebook"],"urldate":["2020-02-11"]},"creators":{}},{"key":"Tun202113","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. Asia Pac. Softw. Eng. Conf. APSEC"],"affiliation":["Waseda University, Tokyo, Japan"],"author":["Tun, H.T.","Husen, J.H.","Yoshioka, N.","Washizaki, H.","Fukazawa, Y."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/APSECW53869.2021.00013"],"isbn":["978-1-66543-813-1"],"issn":["15301362"],"note":["cited By 1"],"pages":["13–16"],"publisher":["IEEE Computer Society"],"series":["Proceedings - Asia-Pacific Software Engineering Conference, APSEC"],"source":["Scopus"],"title":["Goal-centralized metamodel based requirements integration for machine learning systems"]},"creators":{"author":[{"lastName":"Tun","firstName":"H.T."},{"lastName":"Husen","firstName":"J.H."},{"lastName":"Yoshioka","firstName":"N."},{"lastName":"Washizaki","firstName":"H."},{"lastName":"Fukazawa","firstName":"Y."}]},"sentenceCased":true},{"key":"turkiRecommendingScholarlyArticles","type":"article","fields":{"langid":["english"],"abstract":["During the last years, many computer systems have been developed to track and monitor COVID-19 social network interactions. However, these systems have been mainly based on robust probabilistic approaches like Latent Dirichlet Allocation (LDA), Embeddings, and Deep Learning. Such approaches cannot be easily debugged and enhanced to achieve better accuracy rates and usually require advanced computer infrastructures that need lots of energy and money to be maintained. In this research paper, we propose to modify LDA by letting it be driven by knowledge resources and we demonstrate how we can apply our topic modeling method to local social network interactions about COVID-19 to generate precise topic clusters reflecting the social trends about the pandemic at a low cost. Then, we outline how terms in every topic cluster can be converted into a search query to generate scholarly publications from PubMed Central for adjusting COVID-19 trendy thoughts in a considered population."],"author":["Turki, Houcemeddine","Taieb, Mohamed Ali Hadj","Aouicha, Mohamed Ben"],"keywords":["LOGSEQ"],"pages":["11"],"title":["Recommending scholarly articles to monitor COVID-19 trends in social media based on low-cost topic modeling"]},"creators":{"author":[{"lastName":"Turki","firstName":"Houcemeddine"},{"lastName":"Taieb","firstName":"Mohamed Ali Hadj"},{"lastName":"Aouicha","firstName":"Mohamed Ben"}]},"sentenceCased":true},{"key":"Turney:2010:FMV:1861751.1861756","type":"article","fields":{"acmid":["1861756"],"address":["USA"],"author":["Turney, Peter D.","Pantel, Patrick"],"date":["2010-01"],"issn":["1076-9757"],"issue_date":["January 2010"],"journaltitle":["J. Artif. Int. Res."],"note":["TL;DR \n\nThe goal in this survey is to show the breadth of applications of VSMs for semantics, to provide a new perspective on VSMs, and to provide pointers into the literature for those who are less familiar with the field."],"number":["1"],"numpages":["48"],"pages":["141–188"],"publisher":["AI Access Foundation"],"title":["From frequency to meaning: Vector space models of semantics"],"url":["http://dl.acm.org/citation.cfm?id=1861751.1861756"],"volume":["37"]},"creators":{"author":[{"lastName":"Turney","firstName":"Peter D."},{"lastName":"Pantel","firstName":"Patrick"}]},"sentenceCased":true},{"key":"tversky1977features","type":"article","fields":{"abstract":["Questions the metric and dimensional assumptions that underlie the geometric representation of similarity on both theoretical and empirical grounds. A new set-theoretical approach to similarity is developed in which objects are represented as collections of features and similarity is described as a feature-matching process. Specifically, a set of qualitative assumptions is shown to imply the contrast model, which expresses the similarity between objects as a linear combination of the measures of their common and distinctive features. Several predictions of the contrast model are tested in studies of similarity with both semantic and perceptual stimuli. The model is used to uncover, analyze, and explain a variety of empirical phenomena such as the role of common and distinctive features, the relations between judgments of similarity and difference, the presence of asymmetric similarities, and the effects of context on judgments of similarity. The contrast model generalizes standard representations of similarity data in terms of clusters and trees. It is also used to analyze the relations of prototypicality and family resemblance. (39 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)"],"added-at":["2014-02-04T10:50:37.000+0100"],"address":["US"],"author":["Tversky, Amos"],"biburl":["https://www.bibsonomy.org/bibtex/26213352d60fe7cf406596d8f1db71f8a/jaeschke"],"date":["1977"],"interhash":["03a061a2e7ecca2b5e8d900655596144"],"intrahash":["6213352d60fe7cf406596d8f1db71f8a"],"issn":["19391471"],"journaltitle":["Psychol. Rev."],"keywords":["psychology similarity toread"],"nodoi":["10.1037/0033-295X.84.4.327"],"number":["4"],"pages":["327–352"],"publisher":["American Psychological Association"],"refid":["1978-09287-001"],"timestamp":["2014-07-28T15:57:31.000+0200"],"title":["Features of similarity"],"volume":["84"]},"creators":{"author":[{"lastName":"Tversky","firstName":"Amos"}]},"sentenceCased":true},{"key":"ugurelWhatCodeAutomatic2002","type":"inproceedings","fields":{"acmid":["775141"],"author":["Ugurel, Secil","Krovetz, Robert","Giles, C. Lee"],"booktitle":["Proc. Eighth ACM SIGKDD Int. Conf. Knowl. Discov. Data Min."],"date":["2002"],"isbn":["1-58113-567-X"],"location":["New York, NY, USA"],"nodoi":["10.1145/775047.775141"],"note":["TL;DR \n\nIt is shown that source code can be accurately and automatically classified into topical categories and can be identified to be in a specific programming language class."],"numpages":["7"],"pages":["632–638"],"publisher":["ACM"],"series":["KDD '02"],"title":["What's the code?: Automatic classification of source code archives"],"url":["http://doi.acm.org/10.1145/775047.775141"]},"creators":{"author":[{"lastName":"Ugurel","firstName":"Secil"},{"lastName":"Krovetz","firstName":"Robert"},{"lastName":"Giles","firstName":"C. Lee"}]},"sentenceCased":true},{"key":"undefinedDarkitectureRealitySkirted2017","type":"article","fields":{"abstract":["Just as physicists infer dark matter's presence on the basis of its gravitational effects on visible matter, we can conceptualize a \"darkitecture\" that outlines visible software architectures."],"author":["undefined","undefined","undefined","undefined"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"number":["1"],"pages":["103–105"],"shorttitle":["Darkitecture"],"title":["Darkitecture: The Reality Skirted by Architecture"],"volume":["34"]},"creators":{"author":[{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"undefinedKeyAbstractionsIoTOriented2017","type":"article","fields":{"abstract":["Despite the progress in Internet of Things (IoT) research, a general software engineering approach for systematic development of IoT systems and applications is still missing. A synthesis of the state of the art in the area can help frame the key abstractions related to such development. Such a framework could be the basis for guidelines for IoT-oriented software engineering."],"author":["undefined","undefined","undefined","undefined"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["internet of things","software development","software engineering"],"number":["1"],"pages":["38–45"],"title":["Key Abstractions for IoT-Oriented Software Engineering"],"volume":["34"]},"creators":{"author":[{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"undefinedPracticesTechnologiesComputer2017","type":"article","fields":{"abstract":["Computer games are rich, complex, and often large-scale software applications. They're a significant, interesting, and often compelling domain for innovative research in software engineering techniques and technologies. Computer games are progressively changing the everyday world in many positive ways. Game developers, whether focusing on entertainment market opportunities or game-based applications in nonentertainment domains such as education, healthcare, defense, or scientific research (that is, serious games), thus share a common interest in how best to engineer game software. This article examines techniques and technologies that inform contemporary computer game software engineering."],"author":["undefined","undefined","undefined","undefined"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["software engineering"],"note":["TL;DR \n\nTechniques and technologies that inform contemporary computer game software engineering are examined."],"number":["1"],"pages":["110–116"],"title":["Practices and Technologies in Computer Game Software Engineering"],"volume":["34"]},"creators":{"author":[{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"undefinedSoftwareEngineeringInternetThings2017","type":"article","fields":{"author":["undefined","undefined","undefined","undefined"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"number":["1"],"pages":["4–6"],"title":["Software-Engineering the Internet of Things"],"volume":["34"]},"creators":{"author":[{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"undefinedValueDoubt2017","type":"article","fields":{"abstract":["Doubt is key to becoming a good programmer. If you don't doubt the correctness of your work, you have no incentive to look for the hidden spoilers that are always there."],"author":["undefined","undefined","undefined","undefined"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"note":["TL;DR \n\nDoubt is key to becoming a good programmer because if you don't doubt the correctness of your work, you have no incentive to look for the hidden spoilers that are always there."],"number":["1"],"pages":["106–109"],"title":["The Value of Doubt"],"volume":["34"]},"creators":{"author":[{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"ungerAutonomousSystemsDevelopments2012","type":"book","fields":{"date":["2012"],"editor":["Unger, Herwig","Kyamaky, Kyandoghere","Kacprzyk, Janusz"],"isbn":["978-3-642-24805-4 978-3-642-24806-1"],"location":["Berlin, Heidelberg"],"note":["TL;DR \n\nThe Workshops on Autonomous Systems emanated from a gathering with the doctoral students of just three chairs at Fernuniversitt in Hagen, which has grown and matured in several respects and turned into a visible scientific event."],"publisher":["Springer Berlin Heidelberg"],"series":["Studies in Computational Intelligence"],"shorttitle":["Autonomous Systems"],"title":["Autonomous Systems: Developments and Trends"],"url":["http://link.springer.com/10.1007/978-3-642-24806-1"],"urldate":["2016-08-21"],"volume":["391"]},"creators":{"editor":[{"lastName":"Unger","firstName":"Herwig"},{"lastName":"Kyamaky","firstName":"Kyandoghere"},{"lastName":"Kacprzyk","firstName":"Janusz"}]}},{"key":"UniversitySouthAustralia","type":"online","fields":{"title":["University of South Australia > Course"],"url":["http://programs.unisa.edu.au/public/pcms/course.aspx?pageid=101801&y=2016"],"urldate":["2016-08-21"]},"creators":{}},{"key":"uppaal","type":"inproceedings","fields":{"langid":["english"],"author":["Bengtsson, Johan","Larsen, Kim Guldstrand","Larsson, Fredrik","Pettersson, Paul","Yi, Wang"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Hybrid Syst. III Verification Control Proc. DIMACSSYCON Workshop Verification Control Hybrid Syst. Oct. 22-25 1995 Ruttgers Univ. N. B. NJ USA"],"date":["1995"],"doi":["10.1007/BFB0020949"],"editor":["Alur, Rajeev","Henzinger, Thomas A.","Sontag, Eduardo D."],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["232–243"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Tue, 14 May 2019 10:00:42 +0200"],"title":["UPPAAL - a tool suite for automatic verification of real-time systems"],"volume":["1066"]},"creators":{"author":[{"lastName":"Bengtsson","firstName":"Johan"},{"lastName":"Larsen","firstName":"Kim Guldstrand"},{"lastName":"Larsson","firstName":"Fredrik"},{"lastName":"Pettersson","firstName":"Paul"},{"lastName":"Yi","firstName":"Wang"}],"editor":[{"lastName":"Alur","firstName":"Rajeev"},{"lastName":"Henzinger","firstName":"Thomas A."},{"lastName":"Sontag","firstName":"Eduardo D."}]},"sentenceCased":true},{"key":"UsingRecommenderSystems","type":"article","fields":{"entrysubtype":["newspaper"],"note":["TL;DR \n\nThe results of the experiments show that extending proactive modeling with a recommender system results in an average reciprocal hit-rank of 0.871 and user feedback shows that integrating recommender systems into DSMLs increases usability and learnability."],"title":["Using Recommender Systems to Improve Proactive Modeling"]},"creators":{}},{"key":"UsingTorPrivoxy","type":"online","fields":{"title":["Using Tor, Privoxy and Polipo ~ A little bit of everything"],"url":["http://teebeenator.blogspot.it/2014/03/using-tor-privoxy-and-polipo.html"],"urldate":["2015-03-30"]},"creators":{},"sentenceCased":true},{"key":"Usman202125","type":"inproceedings","fields":{"abstract":["This paper presents NEUROSPF, a tool for the symbolic analysis of neural networks. Given a trained neural network model, the tool extracts the architecture and model parameters and translates them into a Java representation that is amenable for analysis using the Symbolic PathFinder symbolic execution tool. Notably, NEUROSPF encodes specialized peer classes for parsing the model's parameters, thereby enabling efficient analysis. With NEUROSPF the user has the flexibility to specify either the inputs or the network internal parameters as symbolic, promoting the application of program analysis and testing approaches from software engineering to the field of machine learning. For instance, NEUROSPF can be used for coverage-based testing and test generation, finding adversarial examples and also constraint-based repair of neural networks, thus improving the reliability of neural networks and of the applications that use them. Video URL: https://youtu.be/seal8fG78L. © 2021 IEEE."],"author":["Usman, M.","Noller, Y.","Pasareanu, C.S.","Sun, Y.","Gopinath, D."],"author_keywords":["Neural Networks; Symbolic Execution; Symbolic PathFinder"],"coden":["PCSED"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/ICSE-Companion52605.2021.00027"],"isbn":["978-1-66541-219-3"],"issn":["02705257"],"keywords":["Application programs","Architectures and models","Efficient analysis","Internal parameters","Model checking","Modeling parameters","Neural network model","Neural-networks","Software testing","Symbolic analysis","Symbolic execution","Symbolic pathfinder","Trained neural networks"],"note":["cited By 2 \n\nTL;DR \n\nThis paper presents NEUROSPF, a tool for the symbolic analysis of neural networks, which extracts the architecture and model parameters and translates them into a Java representation that is amenable for analysis using the Symbolic PathFinder symbolic execution tool."],"pages":["25–28"],"publisher":["IEEE Computer Society"],"series":["Proceedings - International Conference on Software Engineering"],"source":["Scopus"],"title":["NEUROSPF: A tool for the symbolic analysis of neural networks"]},"creators":{"author":[{"lastName":"Usman","firstName":"M."},{"lastName":"Noller","firstName":"Y."},{"lastName":"Pasareanu","firstName":"C.S."},{"lastName":"Sun","firstName":"Y."},{"lastName":"Gopinath","firstName":"D."}]},"sentenceCased":true},{"key":"Vakil-Baghmisheh2003","type":"article","fields":{"abstract":["We present an algorithmic variant of the simplified fuzzy ARTMAP (SFAM) network, whose structure resembles those of feed-forward networks. Its difference with Kasuba's model is discussed, and their performances are compared on two benchmarks. We show that our algorithm is much faster than Kasuba's algorithm, and by increasing the number of training samples, the difference in speed grows enormously."],"author":["Vakil-Baghmisheh, Mohammad-Taghi","Pavešić, Nikola"],"date":["2003-06-01"],"doi":["10.1023/A:1026004816362"],"issn":["1573-773X"],"journaltitle":["Neural Process. Lett."],"number":["3"],"pages":["273–316"],"title":["A fast simplified fuzzy ARTMAP network"],"volume":["17"]},"creators":{"author":[{"lastName":"Vakil-Baghmisheh","firstName":"Mohammad-Taghi"},{"lastName":"Pavešić","firstName":"Nikola"}]},"sentenceCased":true},{"key":"VallecilloGBWH12","type":"inproceedings","fields":{"langid":["english"],"author":["Vallecillo, Antonio","Gogolla, Martin","Burgueño, Loli","Wimmer, Manuel","Hamann, Lars"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Form. Methods Model-Driven Eng. - 12th Int. Sch. Form. Methods Des. Comput. Commun. Softw. Syst. SFM 2012 Bertinoro Italy June 18-23 2012 Adv. Lect."],"date":["2012"],"doi":["10.1007/978-3-642-30982-3\\_11"],"editor":["Bernardo, Marco","Cortellessa, Vittorio","Pierantonio, Alfonso"],"keywords":["/unread","⛔ No INSPIRE recid found"],"pages":["399–437"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Tue, 14 May 2019 10:00:44 +0200"],"title":["Formal specification and testing of model transformations"],"volume":["7320"]},"creators":{"author":[{"lastName":"Vallecillo","firstName":"Antonio"},{"lastName":"Gogolla","firstName":"Martin"},{"lastName":"Burgueño","firstName":"Loli"},{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Hamann","firstName":"Lars"}],"editor":[{"lastName":"Bernardo","firstName":"Marco"},{"lastName":"Cortellessa","firstName":"Vittorio"},{"lastName":"Pierantonio","firstName":"Alfonso"}]},"sentenceCased":true},{"key":"vallecilloTypingModelTransformations2012","type":"article","fields":{"author":["Vallecillo, Antonio","Gogolla, Martin"],"date":["2012"],"doi":["10.1007/978-3-642-30476-7_4"],"journaltitle":["Theory Pract. Model Transform."],"note":["TL;DR \n\nA light-weight approach to type model transformations using tracts is presented, as well as the applicability of the proposal in several settings."],"pages":["56–71"],"title":["Typing Model Transformations Using Tracts"],"volume":["7307"]},"creators":{"author":[{"lastName":"Vallecillo","firstName":"Antonio"},{"lastName":"Gogolla","firstName":"Martin"}]}},{"key":"van2011numpy","type":"article","fields":{"author":["Van Der Walt, Stefan","Colbert, S Chris","Varoquaux, Gael"],"date":["2011"],"journaltitle":["Comput. Sci. Eng."],"number":["2"],"pages":["22–30"],"publisher":["IEEE"],"title":["The NumPy array: A structure for efficient numerical computation"],"volume":["13"]},"creators":{"author":[{"lastName":"Van Der Walt","firstName":"Stefan"},{"lastName":"Colbert","firstName":"S Chris"},{"lastName":"Varoquaux","firstName":"Gael"}]},"sentenceCased":true},{"key":"vanamstelUsingMetricsAssessing","type":"article","fields":{"author":["family=Amstel, prefix=van, useprefix=true","family=Brand, prefix=van den, useprefix=true"],"note":["TL;DR \n\nThis paper focuses on model transformations created using ATL, which ATL is currently one of the most widely used model transformation formalisms, and collects metrics data from a heterogeneous collection of seven model transformations to assess various quality attributes."],"title":["Using Metrics for Assessing the Quality of ATL Model Transformations"]},"creators":{"author":[{"lastName":"Amstel","prefix":"van","useprefix":true},{"lastName":"Brand","prefix":"vanden","useprefix":true}]}},{"key":"vanderdoncktApplyingDeepLearning2020","type":"inproceedings","fields":{"langid":["english"],"abstract":["When a self-adaptive system needs to adapt, it has to analyze the possible options for adaptation, i.e., the adaptation space. For systems with large adaptation spaces, this analysis process can be resource- and time-consuming. One approach to tackle this problem is using machine learning techniques to reduce the adaptation space to only the relevant adaptation options. However, existing approaches only handle threshold goals, while practical systems often need to address also optimization goals. To tackle this limitation, we propose a two-stage learning approach called Deep Learning for Adaptation Space Reduction (DLASeR). DLASeR applies a deep learner first to reduce the adaptation space for the threshold goals and then ranks these options for the optimization goal. A benefit of deep learning is that it does not require feature engineering. Results on two instances of the DeltaIoT artifact (with different sizes of adaptation space) show that DLASeR outperforms a state-of-the-art approach for settings with only threshold goals. The results for settings with both threshold goals and an optimization goal show that DLASeR is effective with a negligible effect on the realization of the adaptation goals. Finally, we observe no noteworthy effect on the effectiveness of DLASeR for larger sizes of adaptation spaces."],"author":["Van Der Donckt, Jeroen","Weyns, Danny","Quin, Federico","Van Der Donckt, Jonas","Michiels, Sam"],"booktitle":["Proc. IEEEACM 15th Int. Symp. Softw. Eng. Adapt. Self-Manag. Syst."],"date":["2020-06-29"],"doi":["10.1145/3387939.3391605"],"eventtitle":["SEAMS '20: IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems"],"isbn":["978-1-4503-7962-5"],"location":["Seoul Republic of Korea"],"note":["TL;DR \n\nThis work proposes a two-stage learning approach called Deep Learning for Adaptation Space Reduction (DLASeR), which applies a deep learner first to reduce the adaptation space for the threshold goals and then ranks these options for the optimization goal."],"pages":["20–30"],"publisher":["ACM"],"title":["Applying deep learning to reduce large adaptation spaces of self-adaptive systems with multiple types of goals"]},"creators":{"author":[{"lastName":"Van Der Donckt","firstName":"Jeroen"},{"lastName":"Weyns","firstName":"Danny"},{"lastName":"Quin","firstName":"Federico"},{"lastName":"Van Der Donckt","firstName":"Jonas"},{"lastName":"Michiels","firstName":"Sam"}]},"sentenceCased":true},{"key":"VanDerWaa2018","type":"inproceedings","fields":{"abstract":["Explainable AI becomes increasingly important as the use of intelligent systems becomes more widespread in high-risk domains. In these domains it is important that the user knows to which degree the system's decisions can be trusted. To facilitate this, we present the Intuitive Confidence Measure (ICM): A lazy learning meta-model that can predict how likely a given decision is correct. ICM is intended to be easy to understand which we validated in an experiment. We compared ICM with two different methods of computing confidence measures: The numerical output of the model and an actively learned metamodel. The validation was performed using a smart assistant for maritime professionals. Results show that ICM is easier to understand but that each user is unique in its desires for explanations. This user studies with domain experts shows what users need in their explanations and that personalization is crucial. © 2018 Copyright for the individual papers remains with the authors."],"author":["Van Der Waa, J.","Van DIggelen, J.","Neerincx, M."],"date":["2018"],"document_type":["Conference Paper"],"editor":["Said A., Komatsu T."],"issn":["16130073"],"note":["cited By 0 \n\nTL;DR \n\nA lazy learning meta-model that can predict how likely a given decision is correct and is intended to be easy to understand, which is validated in an experiment and shows that each user is unique in its desires for explanations."],"publisher":["CEUR-WS"],"series":["CEUR Workshop Proceedings"],"source":["Scopus"],"title":["The design and validation of an intuitive confidence measure"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044532830&partnerID=40&md5=2ed349cd86e9fe55b202cfbb8c2a5f7d"],"volume":["2068"]},"creators":{"author":[{"lastName":"Van Der Waa","firstName":"J."},{"lastName":"Van DIggelen","firstName":"J."},{"lastName":"Neerincx","firstName":"M."}],"editor":[{"lastName":"Said A.","firstName":"Komatsu T."}]},"sentenceCased":true},{"key":"VanGelder2014245","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Simul. Model. Pract. Theory"],"affiliation":["Building Physics Section, Department of Civil Engineering, KU Leuven, Kasteelpark Arenberg 40 Bus 2447, Heverlee, 3001, Belgium; Bartlett School of Graduate Studies, University College London, Central House, 14 Upper Woburn Place, London, WC1H 0NN, United Kingdom"],"author":["Van Gelder, L.","Das, P.","Janssen, H.","Roels, S."],"correspondence_address1":["Van Gelder, L.; Building Physics Section, Department of Civil Engineering, KU Leuven, Kasteelpark Arenberg 40 Bus 2447, Belgium"],"date":["2014"],"document_type":["Article"],"doi":["10.1016/j.simpat.2014.10.004"],"issn":["1569190X"],"journaltitle":["Simul. Model. Pract. Theory"],"note":["cited By 67"],"pages":["245–257"],"publisher":["Elsevier"],"source":["Scopus"],"title":["Comparative study of metamodelling techniques in building energy simulation: Guidelines for practitioners"],"volume":["49"]},"creators":{"author":[{"lastName":"Van Gelder","firstName":"L."},{"lastName":"Das","firstName":"P."},{"lastName":"Janssen","firstName":"H."},{"lastName":"Roels","firstName":"S."}]},"sentenceCased":true},{"key":"vanhooffFrameworkTransformationChain2006","type":"article","fields":{"author":["Vanhooff, Bert","Ayed, Dhouha","Berbers, Yolande"],"date":["2006"],"pages":["3–8"],"title":["A Framework for Transformation Chain Development Processes"]},"creators":{"author":[{"lastName":"Vanhooff","firstName":"Bert"},{"lastName":"Ayed","firstName":"Dhouha"},{"lastName":"Berbers","firstName":"Yolande"}]}},{"key":"vanhooffTransformationChainModeling2006","type":"article","fields":{"author":["Vanhooff, Bert","Baelen, Stefan","Hovsepyan, Aram","Joosen, Wouter","Berbers, Yolande"],"date":["2006"],"doi":["10.1007/11796435_6"],"journaltitle":["Embed. Comput. Syst. Archit. Model. Simul."],"note":["TL;DR \n\nThis paper proposes a metamodel for a transformation chain modeling language that enables implementation independent composition of transformations and proposes a concrete syntax for this language that is based on UML activity diagrams."],"pages":["39–48"],"title":["Towards a Transformation Chain Modeling Language"],"volume":["4017"]},"creators":{"author":[{"lastName":"Vanhooff","firstName":"Bert"},{"lastName":"Baelen","firstName":"Stefan"},{"lastName":"Hovsepyan","firstName":"Aram"},{"lastName":"Joosen","firstName":"Wouter"},{"lastName":"Berbers","firstName":"Yolande"}]}},{"key":"varaminybahnemiry2021automated","type":"inproceedings","fields":{"langid":["english"],"author":["VaraminyBahnemiry, Zahra","Galasso, Jessie","Belharbi, Khalid","Sahraoui, Houari"],"booktitle":["2021 ACMIEEE 24th Int. Conf. Model Driven Eng. Lang. Syst. MODELS"],"date":["2021"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper proposes an approach for fixing semantic errors in ATL transformation rules without predefined patch templates for specific error types, and shows that it can fix most of the errors for transformations with one or two errors."],"pages":["13–23"],"title":["Automated patch generation for fixing semantic errors in ATL transformation rules"]},"creators":{"author":[{"lastName":"VaraminyBahnemiry","firstName":"Zahra"},{"lastName":"Galasso","firstName":"Jessie"},{"lastName":"Belharbi","firstName":"Khalid"},{"lastName":"Sahraoui","firstName":"Houari"}]},"sentenceCased":true},{"key":"Varaminybahnemiry2021fixing","type":"article","fields":{"langid":["english"],"author":["family=Varaminybahnemiry¡/a¿, given=¡a, prefix=href=\"/contents.php?query=Varaminybahnemiry\"¿Zahra, useprefix=false","family=Galasso¡/a¿, given=¡a, prefix=href=\"/contents.php?query=Galasso\"¿Jessie, useprefix=false","family=Sahraoui¡/a¿, given=¡a, prefix=href=\"/contents.php?query=Sahraoui\"¿Houari, useprefix=false"],"date":["2021"],"journaltitle":["J. Object Technol."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["3"],"pages":["9:1-14"],"title":["Fixing multiple type errors in model transformations with alternative oracles to test cases"],"volume":["20"]},"creators":{"author":[{"lastName":"Varaminybahnemiry¡/a¿","firstName":"¡a","prefix":"href=\"/contents.php?query=Varaminybahnemiry\"¿Zahra","useprefix":false},{"lastName":"Galasso¡/a¿","firstName":"¡a","prefix":"href=\"/contents.php?query=Galasso\"¿Jessie","useprefix":false},{"lastName":"Sahraoui¡/a¿","firstName":"¡a","prefix":"href=\"/contents.php?query=Sahraoui\"¿Houari","useprefix":false}]},"sentenceCased":true},{"key":"Vargas_sales_diversity_14","type":"inproceedings","fields":{"author":["Vargas, Saúl","Castells, Pablo"],"bibsource":["dblp computer science bibliography, http://dblp.org"],"biburl":["http://dblp.uni-trier.de/rec/bib/conf/recsys/VargasC14"],"booktitle":["Eighth ACM Conf. Recomm. Syst. RecSys 14 Foster City Silicon Val. CA USA - Oct. 06 - 10 2014"],"date":["2014"],"doi":["10.1145/2645710.2645744"],"note":["TL;DR \n\nThis work explores the inversion of the recommendation task as a means to enhance sales diversity - and indirectly novelty - by selecting which users an item should be recommended to instead of the other way around, and addresses the inverted task by inverting the rating matrix."],"pages":["145–152"],"timestamp":["Thu, 02 Oct 2014 08:41:01 +0200"],"title":["Improving sales diversity by recommending users to items"]},"creators":{"author":[{"lastName":"Vargas","firstName":"Saúl"},{"lastName":"Castells","firstName":"Pablo"}]},"sentenceCased":true},{"key":"vargasRankRelevanceNovelty2011","type":"inproceedings","fields":{"acmid":["2043955"],"author":["Vargas, Saúl","Castells, Pablo"],"booktitle":["Proc. Fifth ACM Conf. Recomm. Syst."],"date":["2011"],"ids":["10.1145/2043932.2043955"],"isbn":["978-1-4503-0683-6"],"keywords":["diversity","evaluation","metrics","novelty","recommender systems"],"location":["New York, NY, USA"],"nodoi":["10.1145/2043932.2043955"],"note":["TL;DR \n\nA formal framework for the definition of novelty and diversity metrics is presented that unifies and generalizes several state of the art metrics and identifies three essential ground concepts at the roots of noveltyand diversity: choice, discovery and relevance, upon which the framework is built."],"numpages":["8"],"pages":["109–116"],"pagetotal":["8"],"publisher":["ACM"],"series":["RecSys '11"],"title":["Rank and relevance in novelty and diversity metrics for recommender systems"],"url":["http://doi.acm.org/10.1145/2043932.2043955"]},"creators":{"author":[{"lastName":"Vargas","firstName":"Saúl"},{"lastName":"Castells","firstName":"Pablo"}]},"sentenceCased":true},{"key":"vargasRealisticPublicDataset2019","type":"article","fields":{"langid":["english"],"abstract":["Detection of undesirable events in oil and gas wells can help prevent production losses, environmental accidents, and human casualties and reduce maintenance costs. The scarcity of measurements in such processes is a drawback due to the low reliability of instrumentation in such hostile environments. Another issue is the absence of adequately structured data related to events that should be detected. To contribute to providing a priori knowledge about undesirable events for diagnostic algorithms in offshore naturally flowing wells, this work presents an original and valuable dataset with instances of eight types of undesirable events characterized by eight process variables. Many hours of expert work were required to validate historical instances and to produce simulated and hand-drawn instances that can be useful to distinguish normal and abnormal actual events under different operating conditions. The choices made during this dataset's preparation are described and justified, and specific benchmarks that practitioners and researchers can use together with the published dataset are defined. This work has resulted in two relevant contributions. A challenging public dataset that can be used as a benchmark for the development of (i) machine learning techniques related to inherent difficulties of actual data, and (ii) methods for specific tasks associated with detecting and diagnosing undesirable events in offshore naturally flowing oil and gas wells. The other contribution is the proposal of the defined benchmarks."],"author":["Vargas, Ricardo Emanuel Vaz","Munaro, Celso José","Ciarelli, Patrick Marques","Medeiros, André Gonçalves","family=Amaral, given=Bruno Guberfain, prefix=do, useprefix=false","Barrionuevo, Daniel Centurion","family=Araújo, given=Jean Carlos Dias, prefix=de, useprefix=false","Ribeiro, Jorge Lins","Magalhães, Lucas Pierezan"],"date":["2019-10"],"doi":["10.1016/j.petrol.2019.106223"],"issn":["09204105"],"journaltitle":["Journal of Petroleum Science and Engineering"],"pages":["106223"],"title":["A realistic and public dataset with rare undesirable real events in oil wells"],"volume":["181"]},"creators":{"author":[{"lastName":"Vargas","firstName":"Ricardo Emanuel Vaz"},{"lastName":"Munaro","firstName":"Celso José"},{"lastName":"Ciarelli","firstName":"Patrick Marques"},{"lastName":"Medeiros","firstName":"André Gonçalves"},{"lastName":"Amaral","firstName":"BrunoGuberfain","prefix":"do","useprefix":false},{"lastName":"Barrionuevo","firstName":"Daniel Centurion"},{"lastName":"Araújo","firstName":"JeanCarlosDias","prefix":"de","useprefix":false},{"lastName":"Ribeiro","firstName":"Jorge Lins"},{"lastName":"Magalhães","firstName":"Lucas Pierezan"}]},"sentenceCased":true},{"key":"varro2007automating","type":"inproceedings","fields":{"langid":["english"],"author":["Varró, Dániel","Balogh, Zoltán"],"booktitle":["Proc. 2007 ACM Symp. Appl. Comput."],"date":["2007"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper automates the approach to model transformation by example using inductive logic programming which aims at the inductive construction of first-order clausal theories from examples and background knowledge."],"pages":["978–984"],"title":["Automating model transformation by example using inductive logic programming"]},"creators":{"author":[{"lastName":"Varró","firstName":"Dániel"},{"lastName":"Balogh","firstName":"Zoltán"}]},"sentenceCased":true},{"key":"vasilescu_stackoverflow_2013","type":"inproceedings","fields":{"abstract":["Stack Overflow is a popular on-line programming question and answer community providing its participants with rapid access to knowledge and expertise of their peers, especially benefitting coders. Despite the popularity of Stack Overflow, its role in the work cycle of open-source developers is yet to be understood: on the one hand, participation in it has the potential to increase the knowledge of individual developers thus improving and speeding up the development process. On the other hand, participation in Stack Overflow may interrupt the regular working rhythm of the developer, hence also possibly slow down the development process. In this paper we investigate the interplay between Stack Overflow activities and the development process, reflected by code changes committed to the largest social coding repository, GitHub. Our study shows that active GitHub committers ask fewer questions and provide more answers than others. Moreover, we observe that active Stack Overflow askers distribute their work in a less uniform way than developers that do not ask questions. Finally, we show that despite the interruptions incurred, the Stack Overflow activity rate correlates with the code changing activity in GitHub."],"author":["Vasilescu, Bogdan","Filkov, Vladimir","Serebrenik, Alexander"],"booktitle":["2013 Int. Conf. Soc. Comput."],"date":["2013-09"],"doi":["10.1109/SocialCom.2013.35"],"keywords":["Communities","crowdsourced knowledge","Electronic mail","GitHub","Indexes","knowledge based systems","Merging","online programming question-and-answer community","Productivity","Rhythm","social coding repository","social media","Software","software development","software maintenance","StackOverflow"],"note":["TL;DR \n\nThis paper investigates the interplay between Stack Overflow activities and the development process, reflected by code changes committed to the largest social coding repository, GitHub, and shows that active GitHub committers ask fewer questions and provide more answers than others."],"pages":["188–195"],"shorttitle":["StackOverflow and GitHub"],"title":["StackOverflow and GitHub: Associations between Software Development and Crowdsourced Knowledge"]},"creators":{"author":[{"lastName":"Vasilescu","firstName":"Bogdan"},{"lastName":"Filkov","firstName":"Vladimir"},{"lastName":"Serebrenik","firstName":"Alexander"}]}},{"key":"vasilescuHowHealthyAre2014","type":"article","fields":{"langid":["english"],"author":["Vasilescu, Bogdan","Serebrenik, Alexander","Mens, Tom","family=Brand, given=Mark G.J., prefix=van den, useprefix=true","Pek, Ekaterina"],"date":["2014-09"],"doi":["10.1016/j.scico.2014.01.016"],"issn":["01676423"],"journaltitle":["Sci. Comput. Program."],"pages":["251–272"],"title":["How healthy are software engineering conferences?"],"volume":["89"]},"creators":{"author":[{"lastName":"Vasilescu","firstName":"Bogdan"},{"lastName":"Serebrenik","firstName":"Alexander"},{"lastName":"Mens","firstName":"Tom"},{"lastName":"Brand","firstName":"MarkG.J.","prefix":"vanden","useprefix":true},{"lastName":"Pek","firstName":"Ekaterina"}]},"sentenceCased":true},{"key":"vassevAutonomyRequirementsEngineering2013","type":"inproceedings","fields":{"author":["Vassev, Emil","Hinchey, Mike"],"booktitle":["Proc. Int. C Conf. Comput. Sci. Softw. Eng."],"date":["2013"],"pages":["31–41"],"publisher":["ACM"],"shorttitle":["Autonomy requirements engineering"],"title":["Autonomy requirements engineering: A case study on the BepiColombo mission"],"url":["http://dl.acm.org/citation.cfm?id=2494472"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Vassev","firstName":"Emil"},{"lastName":"Hinchey","firstName":"Mike"}]},"sentenceCased":true},{"key":"Vaswani:2017lxt","type":"article","fields":{"abstract":["The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an attention mechanism. We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. Experiments on two machine translation tasks show these models to be superior in quality while being more parallelizable and requiring significantly less time to train. Our model achieves 28.4 BLEU on the WMT 2014 English-to-German translation task, improving over the existing best results, including ensembles by over 2 BLEU. On the WMT 2014 English-to-French translation task, our model establishes a new single-model state-of-the-art BLEU score of 41.8 after training for 3.5 days on eight GPUs, a small fraction of the training costs of the best models from the literature. We show that the Transformer generalizes well to other tasks by applying it successfully to English constituency parsing both with large and limited training data."],"author":["Vaswani, Ashish","Shazeer, Noam","Parmar, Niki","Uszkoreit, Jakob","Jones, Llion","Gomez, Aidan N.","Kaiser, Lukasz","Polosukhin, Illia"],"date":["2017-12-05"],"eprint":["1706.03762"],"eprintclass":["cs.CL"],"eprinttype":["arxiv"],"journaltitle":["arXiv:1706.03762 [cs.CL]"],"keywords":["Computer Science - Computation and Language","Computer Science - Machine Learning","LOGSEQ"],"note":["Comment: 15 pages, 5 figures"],"title":["Attention Is All You Need"],"url":["http://arxiv.org/abs/1706.03762"],"urldate":["2022-08-26"]},"creators":{"author":[{"lastName":"Vaswani","firstName":"Ashish"},{"lastName":"Shazeer","firstName":"Noam"},{"lastName":"Parmar","firstName":"Niki"},{"lastName":"Uszkoreit","firstName":"Jakob"},{"lastName":"Jones","firstName":"Llion"},{"lastName":"Gomez","firstName":"Aidan N."},{"lastName":"Kaiser","firstName":"Lukasz"},{"lastName":"Polosukhin","firstName":"Illia"}]}},{"key":"vathy-fogarassyUniformDataAccess2017","type":"article","fields":{"langid":["english"],"abstract":["Integration of data stored in heterogeneous database systems is a very challenging task and it may hide several difficulties. As NoSQL databases are growing in popularity, integration of different NoSQL systems and interoperability of NoSQL systems with SQL databases become an increasingly important issue. In this paper, we propose a novel data integration methodology to query data individually from different relational and NoSQL database systems. The suggested solution does not support joins and aggregates across data sources; it only collects data from different separated database management systems according to the filtering options and migrates them. The proposed method is based on a metamodel approach and it covers the structural, semantic and syntactic heterogeneities of source systems. To introduce the applicability of the proposed methodology, we developed a web-based application, which convincingly confirms the usefulness of the novel method."],"author":["Vathy-Fogarassy, Ágnes","Hugyák, Tamás"],"date":["2017-09"],"doi":["10.1016/j.is.2017.04.002"],"issn":["03064379"],"journaltitle":["Inf. Syst."],"pages":["93–105"],"title":["Uniform data access platform for SQL and NoSQL database systems"],"volume":["69"]},"creators":{"author":[{"lastName":"Vathy-Fogarassy","firstName":"Ágnes"},{"lastName":"Hugyák","firstName":"Tamás"}]},"sentenceCased":true},{"key":"vazEmpiricalStudyTask2019","type":"inproceedings","fields":{"author":["Vaz, Luis","Steinmacher, Igor","Marczak, Sabrina"],"booktitle":["2019 ACMIEEE 14th Int. Conf. Glob. Softw. Eng. ICGSE"],"date":["2019-05"],"doi":["10.1109/ICGSE.2019.00041"],"eventtitle":["2019 ACM/IEEE 14th International Conference on Global Software Engineering (ICGSE)"],"isbn":["978-1-5386-9196-0"],"location":["Montreal, QC, Canada"],"pages":["48–57"],"publisher":["IEEE"],"title":["An Empirical Study on Task Documentation in Software Crowdsourcing on TopCoder"]},"creators":{"author":[{"lastName":"Vaz","firstName":"Luis"},{"lastName":"Steinmacher","firstName":"Igor"},{"lastName":"Marczak","firstName":"Sabrina"}]}},{"key":"velazquez-rodriguezUncoveringLibraryFeatures","type":"thesis","fields":{"langid":["english"],"author":["Velázquez-Rodríguez, Camilo"],"keywords":["LOGSEQ"],"note":["<h1>Annotazioni\n (4/3/2024, 15:16:19)</h1> \n\n- \n\n“Camilo Velázquez-Rodríguez” (Velázquez-Rodríguez, p. 1) #66ff66 \n\ni - \n\n“lack of automated tool support.” (Velázquez-Rodríguez, p. i) #ff00ff \n\ni - \n\n“Overview of the Approach” (Velázquez-Rodríguez, p. 4) #ffd400 \n\n<i>By looking at the structure, it seems the thesis is a collection of papers; we are missing a chapter playing the role of glue among all of them... it improves later! </i> - \n\n“This dissertation presents contributions in two main research areas: i) automated library feature uncovering and ii) API type resolution for incomplete code snippets” (Velázquez-Rodríguez, p. 5) #ffd400 \n\n<i>See my previous comment, it is not clear the role of the second part, and how it is linked to the first one. </i> - \n\n“recommendation of multiple tags” (Velázquez-Rodríguez, p. 5) #ffd400 \n\n<i>Existing baselines have not been considered why? See for instance: Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong T. Nguyen, Riccardo Rubei:\n HybridRec: A recommender system for tagging GitHub repositories. Appl. Intell. 53(8): 9708-9730 (2023) </i> - \n\n“In summary, we stress the need for an approach that can extract information from syntactically incorrect code snippets. Such an approach should also resolve missing external API references in incomplete code snippets. The extracted information and the API reference resolution may improve the current SO code processing. Discussed approaches have not addressed these problems commonly found on SO code snippets” (Velázquez-Rodríguez, p. 39) #ffd400 \n\n<i>The goal has been clearly written only at page 39. </i> - \n\n“3.6. Conclusion” (Velázquez-Rodríguez, p. 40) #ffd400 \n\n<i>At the end of chapter 3 the question is: what's the granularity of \"features\"? #question </i> - \n\n“simple names of API type” (Velázquez-Rodríguez, p. 43) #ffd400 \n\n<i>What does it mean simple names? #question </i> - \n\n“alance Datase” (Velázquez-Rodríguez, p. 52) #ffd400 \n\n<i>How have you balanced your dataset? #question </i> - \n\n“ML Classifiers” (Velázquez-Rodríguez, p. 52) #ffd400 \n\n<i>What has been used here? #question </i> - \n\n“Select Best Model” (Velázquez-Rodríguez, p. 52) #ffd400 \n\n<i>Is this done once? #question </i> - \n\n“100 most frequent libraries” (Velázquez-Rodríguez, p. 53) #ffd400 \n\n<i>Have you considered the removal of the most frequent libraries, e.g., log4j #question #popularitybias </i> - \n\n“The FQNs with fewer occurrences than the defined threshold are not considered for the training phase and are therefore excluded.” (Velázquez-Rodríguez, p. 53) #ffd400 \n\n<i>This is a #popularitybias It is a common issue, how to deal with it? </i> - \n\n“External Datasets” (Velázquez-Rodríguez, p. 54) #ffd400 \n\n<i>Are they balanced? </i> - \n\n“The machine learning algorithms employed within RESICO” (Velázquez-Rodríguez, p. 59) #ffd400 \n\n<i>What are the criteria you used to select ML algorithms? #question </i> - \n\n“each of the RESICO classifiers” (Velázquez-Rodríguez, p. 59) #ffd400 \n\n<i>How to decide, which one to be used for the task at hand? </i> - \n\n“We conclude that the best classifier of our approach (i.e., KNN) is more effective than COSTER on this dataset” (Velázquez-Rodríguez, p. 62) #ffd400 \n\n<i>Any qualitative motivation / discussion supporting such conclusions? </i> - \n\n“In the three external datasets considered to evaluate the generalisability of the performance, RESICO-trained models outperform COSTER with a notable difference in some cases.” (Velázquez-Rodríguez, p. 64) #ffd400 \n\n<i>In the case of unbalanced datasets, how do the two approach compare? </i> - \n\n“Our approach is more complex than COSTER since it involves training several machine learning models; hence, it consumes more computational resources during training.” (Velázquez-Rodríguez, p. 73) #ffd400 \n\n<i>From the user perspectives, how is the model selection done / supported? </i> - \n\n“features offered by each library.” (Velázquez-Rodríguez, p. 75) #f0ff00 \n\n<i>it's interesting to see the given definition of features. </i> - \n\n“We adopt their definition in this dissertation so that features comprise the API elements that realise them, as well as their textual description.” (Velázquez-Rodríguez, p. 76) #00b036 \n\ni - \n\n“AutoCat and MUTAMA are not focused on fine-grained features, but target more coarse forms of features such as categories and tags.” (Velázquez-Rodríguez, p. 76) #00b036 \n\ni - \n\n“users could inspect a list of features that are commonly or rarely implemented by the libraries in a selected category.” (Velázquez-Rodríguez, p. 77) #00b036 \n\ni - \n\n“Current tool support does not allow developers to efficiently evaluate and compare candidate libraries with respect to all the desired features.” (Velázquez-Rodríguez, p. 77) #00b036 \n\ni - \n\n“The features, however, can be described at several levels of granularity, from the artifact level to the code level.” (Velázquez-Rodríguez, p. 78) #00b036 \n\n<i>#IMPORTANT Features are given at different level of granularity. </i> - \n\n“AutoCat, automatically categorises a library into one of the top-level library categories used by ecosystem indices.” (Velázquez-Rodríguez, p. 78) #00b036 \n\n<i>autocat </i> - \n\n“LiFUSO, describes a library in terms of features consisting of the API elements that implement them and a natural language description.” (Velázquez-Rodríguez, p. 78) #00b036 \n\n<i>lofuso </i> - \n\n“The proposed approach is based on text classification machine learning algorithms trained and evaluated on a corpus of text extracted from the libraries. We obtain this corpus of text by extracting the identifiers of public classes and methods from a library’s JAR file using the Apache BCEL8 library. For those identifiers following the CamelCase naming convention (e.g., getAccountNumber), we separate the identifier into distinct words (e.g., get, Account, Number)” (Velázquez-Rodríguez, p. 79) #f0ff00 \n\n<i>thus, readme files or alike are not considered right? This could have been useful for the task of categorization..... </i> - \n\n“The generated vectors capture the context around a word (e.g., a window size of five tokens); hence it is possible to relate different words by the surrounding context. Default parameters for the Word2Vec process are selected for its training.” (Velázquez-Rodríguez, p. 79) #f0ff00 \n\n<i>an illustrative example would have been useful here. </i> - \n\n“The task of the machine learning algorithm is to learn and predict a discrete label for each vector that corresponds to the MVNRepository category to which the library belongs. We consider five machine learning algorithms to instantiate our approach: Gaussian Naive Bayes (GNB) as well as Bernoulli Naive Bayes (BNB) [JL95], Support Vector Machines (SVC) [HDO+98], K -Nearest Neighbors (KNN) [Das91] and Random Forest (RF) [Ho95, Bre01] (cf. Section 2.4.2).” (Velázquez-Rodríguez, p. 79) #f0ff00 \n\n<i>I suspect the dataset is not balanced, isn't it? </i> - \n\n“five MVNRepository categories: Collections, Dependency Injection, Http Clients, Compression and JSON libraries.” (Velázquez-Rodríguez, p. 79) #f0ff00 \n\n<i>is there any reason around the selection of such five categories? </i> - \n\n“This small experiment (i.e., only 15 libraries) returns promising results regarding the automatic classification of libraries based on their implementation.” (Velázquez-Rodríguez, p. 79) #f0ff00 \n\n<i>it's a bit obscure without an example </i> - \n\n“Limitations of Category-based Approaches to Feature Uncovering” (Velázquez-Rodríguez, p. 80) #f0ff00 \n\n<i>Why no comparisons have been done with related baseline? </i> - \n\n“An automated approach to suggesting feature tags for a software library could overcome this problem and thereby facilitate ecosystem search.” (Velázquez-Rodríguez, p. 81) #f0ff00 \n\n<i>check if it has been compared with our approach. </i> - \n\n“Table 5.3.: Multi-tag predictions made by the best trained multi-label model.” (Velázquez-Rodríguez, p. 87) #f0ff00 \n\n<i>Also in this case, the dataset can be unbalanced. How have you addressed the problem? </i> - \n\n“Limitations of Tag-based Approaches for Features Discovery” (Velázquez-Rodríguez, p. 88) #f0ff00 \n\n<i>in terms of conveied knowledge, what can we say, given a same project, about the recommended tags and category? Do you think such a cross-cuttings analysis can help or give some more insights? </i> - \n\n“Figure 5.5.:” (Velázquez-Rodríguez, p. 89) #f0ff00 \n\n<i>does the collected features make sense without any initial human intervention? #question </i> - \n\n“example usages of this API from SO snippets (step 3 in Figure 5.5). To collect” (Velázquez-Rodríguez, p. 89) #f0ff00 \n\n<i>this is a bit obscure at this point... </i> - \n\n“we collect all class names that were once considered part of it.” (Velázquez-Rodríguez, p. 89) #f0ff00 \n\n<i>not clear.... </i> - \n\n“has been tagged with the name of the library (e.g., guava, pdfbox).” (Velázquez-Rodríguez, p. 89) #f0ff00 \n\n<i>this limit the applicability of the approach, isn't it? #question </i> - \n\n“its strictness minimises false positives.” (Velázquez-Rodríguez, p. 90) #f0ff00 \n\n<i>but still, in my opinion it limits the applicability of the approach in practice, \n I don't think the are so many tagged answers </i> - \n\n“Parsers generated by an island grammar [Moo01] focus on some constructs of interest (i.e., islands) and consider the remainder of the text to parse as irrelevant (i.e., water). They have been shown well-suited to parsing and lightweight analysis of code that is grammatically incomplete (e.g., a statement without a surrounding method) or that contains syntax errors (e.g., three dots instead of an expression) such as the snippets on SO.” (Velázquez-Rodríguez, p. 90) #00b036 \n\ni - \n\n“clusters with the most frequent name pairs and API references are outputted.” (Velázquez-Rodríguez, p. 94) #f0ff00 \n\n<i>why pairs? </i> - \n\n“Figure 5.11.: Front page of the LiFUSO tool with the Search feature tab activated.” (Velázquez-Rodríguez, p. 97) #f0ff00 \n\n<i>I'm not sure on how significant are the shown features for users in practice. I think a user study would have been needed here. </i> - \n\n“cohesiveness” (Velázquez-Rodríguez, p. 97) #f0ff00 \n\n<i>What does it mean? </i> - \n\n“The evaluation of our approach focuses on the API calls of the generated features.” (Velázquez-Rodríguez, p. 97) #f0ff00 \n\n<i>what does that mean ? </i> - \n\n“research questions:” (Velázquez-Rodríguez, p. 97) #f0ff00 \n\n<i>Without a user study the significance and usefulness of the given features cannot be evaluated properly. A qualitative evaluation is needed. </i> - \n\n“documented tutorial features?” (Velázquez-Rodríguez, p. 98) #f0ff00 \n\n<i>how and when are these uncovered? </i> - \n\n“Tutorial features are compared one by one with all uncovered clusters.” (Velázquez-Rodríguez, p. 101) #f0ff00 \n\n<i>it means that there is a kind of shared / common vocabulary that is manually curated. isn't it? #question </i> - \n\n“When matches occur, we store the uncovered feature identifier (i.e., a number) and the tutorial feature that was matched.” (Velázquez-Rodríguez, p. 101) #f0ff00 \n\n<i>is there a kind of hasmap defined somewhere? #question </i> - \n\n“High relevance scores indicate that uncovered features are highly similar to tutorial features.” (Velázquez-Rodríguez, p. 104) #f0ff00 \n\n<i>there is a bias here, which is related to the process that has been followed to identify tutorial features. What can you say about this? #question </i> - \n\n“Libraries.io to” (Velázquez-Rodríguez, p. 105) #00b036 \n\n<i>this website seems to be interesting for our experiments #ideas </i> - \n\n“Table 5.8.: Newly matched features from GitHub client projects.” (Velázquez-Rodríguez, p. 106) #f0ff00 \n\n<i>there is the usual comment about the not clear definition of what is a feature. Explanatory examples would help here. </i> - \n\n“Another limitation of our approach is that it relies on SO posts being tagged with the name of the library for which features need to be uncovered.” (Velázquez-Rodríguez, p. 109) #f0ff00 \n\n<i>I agree...this has been a limiting decision. </i> - \n\n“Figure 5.12.: Shared features for the studied libraries.” (Velázquez-Rodríguez, p. 111) #f0ff00 \n\n<i>some features are missing context. Create pdf is indeed clear, add page is not. </i> - \n\n“for less popular libraries for which there is little usage in SO answers” (Velázquez-Rodríguez, p. 113) #f0ff00 \n\n<i>this is related to the popularity bias problem mentioned also for the other works. Evaluating the work by filtering out popular libraries would have helped to gain some more insights about the overall accuracy of the work. </i> - \n\n“new GitHub corpus and its application to the whole SO dataset. Additionally, we present the results of our strategies through various evaluation” (Velázquez-Rodríguez, p. 116) #f0ff00 \n\n<i>what are the characteristics of such a new Github datast? #question </i> - \n\n“some manual input is required for parts of the proposed pipeline such as the meta-data of a library (e.g., groupId and artifactId) as well as its corresponding tag name. Additionally, the GitHub repository hosting the library is required as input to the ghtopdep tool, which retrieves the dependent repositories.” (Velázquez-Rodríguez, p. 140) #f0ff00 \n\n<i>This is related to what I was mentioning about the need of having humans in the loop while curatig the creation of the feature taxonomy. </i> - \n\n“LiFUSO-supported libraries” (Velázquez-Rodríguez, p. 140) #f0ff00 \n\n<i>this raises questions about the applicability of the approach in practice #question </i> - \n\n“source of information are unit test cases and their text descriptions, which may scale to many libraries since most of them include a test suite.” (Velázquez-Rodríguez, p. 141) #00b036 \n\n<i>that is very interesting #IMPORTANT </i> - \n\n“Features are defined as API usage patterns with a corresponding description in natural language.” (Velázquez-Rodríguez, p. 143) #f0ff00 \n\n<i>I don't see in the Web based tool such descriptions in natural language. </i> - \n\n“RESICO leverages a dataset of library API usage within complete and correct code to learn word embeddings and the most likely fully qualified name for a simple name in a specific context.” (Velázquez-Rodríguez, p. 144) #f0ff00 \n\n<i>the support for continuous learning is needed in this domain and it is also necessary to address the coldstart problem. What do you think? #question </i> - \n\n“API usage from Stack Overflow” (Velázquez-Rodríguez, p. 146) #f0ff00 \n\n<i>how to deal with ambiguous cases. Add page can be add a pdf page or a page in a Web base system. It is necessary to include the application domain. #question </i> - \n\n“An unsupervised machine learning algorithm is used to form clusters of API usage.” (Velázquez-Rodríguez, p. 149) #f0ff00 \n\n<i>I think this should include supervision. </i> - \n\n“tutorials and cookbooks of the libraries under analysis.” (Velázquez-Rodríguez, p. 149) #f0ff00 \n\n<i>to what extent this is manual / semi-automated? </i> - \n\n“RDSN+20] Riccardo” (Velázquez-Rodríguez, p. 166) #f0ff00 \n\n<i>This is the only one cited? </i>"],"title":["Uncovering Library Features from Incomplete Information on Stack Overflow"]},"creators":{"author":[{"lastName":"Velázquez-Rodríguez","firstName":"Camilo"}]}},{"key":"venChallengesStrategiesUse2008","type":"article","fields":{"langid":["english"],"author":["Ven, Kris","Mannaert, Herwig"],"date":["2008-08"],"doi":["10.1016/j.infsof.2007.09.001"],"issn":["09505849"],"journaltitle":["Inf. Softw. Technol."],"number":["9-10"],"pages":["991–1002"],"title":["Challenges and strategies in the use of Open Source Software by Independent Software Vendors"],"volume":["50"]},"creators":{"author":[{"lastName":"Ven","firstName":"Kris"},{"lastName":"Mannaert","firstName":"Herwig"}]},"sentenceCased":true},{"key":"venkateshScalableApplicationDesignIoT2017","type":"article","fields":{"abstract":["The Internet of Things envisions a web-connected infrastructure of sensing and actuation devices. However, the current state of the art presents another reality: monolithic end-to-end applications tightly coupled to a limited set of sensors and actuators. Growing such applications with new devices or behaviors, or extending the existing infrastructure with new applications, involves redesign and deployment. A proposed approach breaks these applications up into an equivalent set of functional units called context engines, whose I/O transformations are driven by general-purpose machine learning. This approach decreases computational redundancy and complexity with a minimal impact on accuracy. Researchers evaluated this approach's scalability–how the context engines' overhead grows as the input data and number of computational nodes increase. In a large-scale case study of residential smart-grid control, this approach provided better accuracy and scaling than the state-of-the-art single-stage approach."],"author":["Venkatesh, Jagannathan","Aksanli, Baris","Chan, Christine S.","Akyurek, Alper S.","Rosing, Tajana S.","undefined","undefined","undefined","undefined"],"date":["2017"],"entrysubtype":["magazine"],"issn":["0740-7459"],"journaltitle":["IEEE Software"],"keywords":["internet of things","software engineering"],"number":["1"],"pages":["62–70"],"title":["Scalable-Application Design for the IoT"],"volume":["34"]},"creators":{"author":[{"lastName":"Venkatesh","firstName":"Jagannathan"},{"lastName":"Aksanli","firstName":"Baris"},{"lastName":"Chan","firstName":"Christine S."},{"lastName":"Akyurek","firstName":"Alper S."},{"lastName":"Rosing","firstName":"Tajana S."},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"},{"literal":"undefined"}]}},{"key":"verma_fairness_2018","type":"inproceedings","fields":{"abstract":["Algorithm fairness has started to attract the attention of researchers in AI, Software Engineering and Law communities, with more than twenty different notions of fairness proposed in the last few years. Yet, there is no clear agreement on which definition to apply in each situation. Moreover, the detailed differences between multiple definitions are difficult to grasp. To address this issue, this paper collects the most prominent definitions of fairness for the algorithmic classification problem, explains the rationale behind these definitions, and demonstrates each of them on a single unifying case-study. Our analysis intuitively explains why the same case can be considered fair according to some definitions and unfair according to others."],"author":["Verma, Sahil","Rubin, Julia"],"booktitle":["2018 IEEEACM Int. Workshop Softw. Fairness FairWare"],"date":["2018-05"],"doi":["10.1145/3194770.3194776"],"keywords":["Artificial intelligence","Conferences","definitions of fairness","Employment","History","machine learning","Software","Software algorithms","Software engineering","survey"],"note":["TL;DR \n\nThis paper collects the most prominent definitions of fairness for the algorithmic classification problem, explains the rationale behind these definitions, and demonstrates each of them on a single unifying case-study."],"pages":["1–7"],"title":["Fairness Definitions Explained"]},"creators":{"author":[{"lastName":"Verma","firstName":"Sahil"},{"lastName":"Rubin","firstName":"Julia"}]}},{"key":"vermesanInternetThingsApplications2014","type":"book","fields":{"langid":["english"],"author":["Vermesan, Ovidiu"],"date":["2014"],"isbn":["978-87-93102-94-1"],"location":["Place of publication not identified"],"note":["TL;DR \n\nThe chapter describes the Calipso communication architecture for IP connectivity in wireless sensor networks and the Smart Parking application scenario developed within the Project, and shows how the Smart parking application takes advantage of different modules within the architecture."],"publisher":["River Publishers"],"title":["Internet of things applications - from research and innovation to market deployment."]},"creators":{"author":[{"lastName":"Vermesan","firstName":"Ovidiu"}]},"sentenceCased":true},{"key":"vermesanInternetThingsConverging2013","type":"book","fields":{"langid":["english"],"author":["Vermesan, Ovidiu"],"date":["2013"],"publisher":["River Publishers"],"shorttitle":["Internet of Things"],"title":["Internet of Things: Converging Technologies for Smart Environments"]},"creators":{"author":[{"lastName":"Vermesan","firstName":"Ovidiu"}]}},{"key":"vermesanInternetThingsStrategic2011","type":"article","fields":{"author":["Vermesan, Ovidiu","Friess, Peter","Guillemin, Patrick","Gusmeroli, Sergio","Sundmaeker, Harald","Bassi, Alessandro","Jubert, Ignacio Soler","Mazura, Margaretha","Harrison, Mark","Eisenhauer, M.","others"],"date":["2011"],"journaltitle":["Internet Things-Glob. Technol. Soc. Trends"],"pages":["9–52"],"title":["Internet of things strategic research roadmap"],"url":["http://books.google.com/books?hl=en&lr=&id=Eug-RvslW30C&oi=fnd&pg=PA9&dq=%22by+individuals+and+organisations+around+the%22+%22Services+(IoS),+into+a+common+global+IT+platform+of+seamless+networks%22+%22networks+and+Internet.+Research+on+SOA,+Web/enterprise%22+%22interconnects+growing+population+of+users+while+promoting+their%22+&ots=3Tx7vGjxCw&sig=jz8DKE3sstPdA9juWvxatLigzxs"],"urldate":["2016-06-03"]},"creators":{"author":[{"lastName":"Vermesan","firstName":"Ovidiu"},{"lastName":"Friess","firstName":"Peter"},{"lastName":"Guillemin","firstName":"Patrick"},{"lastName":"Gusmeroli","firstName":"Sergio"},{"lastName":"Sundmaeker","firstName":"Harald"},{"lastName":"Bassi","firstName":"Alessandro"},{"lastName":"Jubert","firstName":"Ignacio Soler"},{"lastName":"Mazura","firstName":"Margaretha"},{"lastName":"Harrison","firstName":"Mark"},{"lastName":"Eisenhauer","firstName":"M."},{"lastName":"others"}]},"sentenceCased":true},{"key":"vermolenReconstructingComplexMetamodel2012","type":"incollection","fields":{"author":["Vermolen, Sander D.","Wachsmuth, Guido","Visser, Eelco"],"booktitle":["Software Language Engineering"],"date":["2012"],"pages":["201–221"],"series":["Lecture Notes in Computer Science"],"title":["Reconstructing Complex Metamodel Evolution"],"volume":["6940"]},"creators":{"author":[{"lastName":"Vermolen","firstName":"Sander D."},{"lastName":"Wachsmuth","firstName":"Guido"},{"lastName":"Visser","firstName":"Eelco"}]}},{"key":"vieiraMetricsMeasureChange2014","type":"incollection","fields":{"author":["Vieira, Andreza","Ramalho, Franklin"],"booktitle":["Product-Focused Software Process Improvement"],"date":["2014"],"pages":["254–268"],"series":["Lecture Notes in Computer Science"],"title":["Metrics to Measure the Change Impact in ATL Model Transformations"],"volume":["8892"]},"creators":{"author":[{"lastName":"Vieira","firstName":"Andreza"},{"lastName":"Ramalho","firstName":"Franklin"}]}},{"key":"vignagaTypingArtifactsMegamodeling2011","type":"article","fields":{"author":["Vignaga, Andrés","Jouault, Frédéric","Bastarrica, María Cecilia","Brunelière, Hugo"],"date":["2011"],"doi":["10.1007/s10270-011-0191-2"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nThis paper presents the core elements of a type system for GMM that improves its original typing approach and enables both typechecking and type inference on artifacts within a megamodel, and presents a prototypical implementation of this type system."],"number":["1"],"pages":["105–119"],"title":["Typing artifacts in megamodeling"],"volume":["12"]},"creators":{"author":[{"lastName":"Vignaga","firstName":"Andrés"},{"lastName":"Jouault","firstName":"Frédéric"},{"lastName":"Bastarrica","firstName":"María Cecilia"},{"lastName":"Brunelière","firstName":"Hugo"}]},"sentenceCased":true},{"key":"vignagaTypingModelManagement2009","type":"incollection","fields":{"langid":["english"],"abstract":["Model management is essential for coping with the complexity introduced by the increasing number and varied nature of artifacts involved in MDE-based projects. Global Model Management (GMM) addresses this issue enabling the representation of artifacts, particularly transformation composition and execution, by a model called a megamodel. Typing information about artifacts can be used for preventing type errors during execution. In this work, we present a type system for GMM that improves its current typing approach and enables formal reasoning about the type of artifacts within a megamodel. This type system is able to capture non-trivial situations such as the use of higher order transformations."],"author":["Vignaga, Andrés","Jouault, Frédéric","Bastarrica, María Cecilia","Brunelière, Hugo"],"booktitle":["Theory and Practice of Model Transformations"],"date":["2009"],"editor":["Paige, Richard F."],"isbn":["978-3-642-02407-8 978-3-642-02408-5"],"keywords":["software engineering"],"note":["TL;DR \n\nThis work presents a type system for GMM that improves its current typing approach and enables formal reasoning about the type of artifacts within a megamodel, able to capture non-trivial situations such as the use of higher order transformations."],"number":["5563"],"pages":["197–212"],"publisher":["Springer Berlin Heidelberg"],"series":["Lecture Notes in Computer Science"],"title":["Typing in Model Management"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-02408-5_14"],"urldate":["2015-04-01"]},"creators":{"author":[{"lastName":"Vignaga","firstName":"Andrés"},{"lastName":"Jouault","firstName":"Frédéric"},{"lastName":"Bastarrica","firstName":"María Cecilia"},{"lastName":"Brunelière","firstName":"Hugo"}],"editor":[{"lastName":"Paige","firstName":"Richard F."}]}},{"key":"viroliSASO2014Selected2016","type":"article","fields":{"langid":["english"],"author":["Viroli, Mirko","Diaconescu, Ada","Kandasamy, Nagarajan"],"date":["2016-07-25"],"doi":["10.1145/2939206"],"issn":["15564665"],"journaltitle":["ACM Trans. Auton. Adapt. Syst."],"note":["TL;DR \n\nThis special issue of ACM TAAS champions some of the most solid research results of SASO 2016, presenting selected, revised, and extended best articles."],"number":["2"],"pages":["1–2"],"shorttitle":["SASO 2014"],"title":["SASO 2014: Selected, Revised, and Extended Best Papers"],"volume":["11"]},"creators":{"author":[{"lastName":"Viroli","firstName":"Mirko"},{"lastName":"Diaconescu","firstName":"Ada"},{"lastName":"Kandasamy","firstName":"Nagarajan"}]}},{"key":"virvouHandbookArtificialIntelligenceEmpowered2022","type":"book","fields":{"langid":["english"],"date":["2022"],"doi":["10.1007/978-3-031-08202-3"],"editor":["Virvou, Maria","Tsihrintzis, George A.","Bourbakis, Nikolaos G.","Jain, Lakhmi C."],"isbn":["978-3-031-08201-6 978-3-031-08202-3"],"location":["Cham"],"publisher":["Springer International Publishing"],"series":["Artificial Intelligence-Enhanced Software and Systems Engineering"],"shorttitle":["Handbook on Artificial Intelligence-Empowered Applied Software Engineering"],"title":["Handbook on Artificial Intelligence-Empowered Applied Software Engineering: VOL.1: Novel Methodologies to Engineering Smart Software Systems"],"volume":["2"]},"creators":{"editor":[{"lastName":"Virvou","firstName":"Maria"},{"lastName":"Tsihrintzis","firstName":"George A."},{"lastName":"Bourbakis","firstName":"Nikolaos G."},{"lastName":"Jain","firstName":"Lakhmi C."}]}},{"key":"vladHypersonicModelAnalysis","type":"article","fields":{"author":["Vlad, Acretoaie","Harald, Storrle"],"note":["TL;DR \n\nThis paper investigates the conceptual and technical feasibility of a new software architecture for modeling tools, where certain advanced features are factored out of the client and moved towards the Cloud, by applying standards such as REST and JSON in combination with Prolog as an implementation language."],"title":["Hypersonic: Model Analysis and Checking in the Cloud"]},"creators":{"author":[{"lastName":"Vlad","firstName":"Acretoaie"},{"lastName":"Harald","firstName":"Storrle"}]}},{"key":"vogelsangRequirementsEngineeringMachine2017","type":"inproceedings","fields":{"langid":["english"],"abstract":["Machine learning (ML) is used increasingly in real-world applications. In this paper, we describe our ongoing endeavor to define characteristics and challenges unique to Requirements Engineering (RE) for ML-based systems. As a first step, we interviewed four data scientists to understand how ML experts approach elicitation, specification, and assurance of requirements and expectations. The results show that changes in the development paradigm, i.e., from coding to training, also demands changes in RE. We conclude that development of ML systems demands requirements engineers to: (1) understand ML performance measures to state good functional requirements, (2) be aware of new quality requirements such as explainability, freedom from discrimination, or specific legal requirements, and (3) integrate ML specifics in the RE process. Our study provides a first contribution towards an RE methodology for ML systems."],"author":["Vogelsang, Andreas","Borg, Markus"],"booktitle":["2019 IEEE 27th Int. Requir. Eng. Conf. Workshop REW"],"date":["2017-01"],"doi":["10.1109/REW.2019.00050"],"eprint":["1908.04674"],"eprinttype":["arxiv"],"eventtitle":["2019 IEEE 27th International Requirements Engineering Conference Workshops (REW)"],"isbn":["978-1-72815-165-6"],"location":["Jeju Island, Korea (South)"],"pages":["245–251"],"publisher":["IEEE"],"shorttitle":["Requirements Engineering for Machine Learning"],"title":["Requirements Engineering for Machine Learning: Perspectives from Data Scientists"]},"creators":{"author":[{"lastName":"Vogelsang","firstName":"Andreas"},{"lastName":"Borg","firstName":"Markus"}]}},{"key":"voigtStructuralGraphbasedMetamodel2011","type":"thesis","fields":{"author":["Voigt, Konrad"],"date":["2011"],"ids":["V11"],"title":["Structural Graph-based Metamodel Matching"]},"creators":{"author":[{"lastName":"Voigt","firstName":"Konrad"}]}},{"key":"volter2013model","type":"book","fields":{"author":["Völter, Markus","Stahl, Thomas","Bettin, Jorn","Haase, Arno","Helsen, Simon"],"date":["2013"],"note":["TL;DR \n\nMDSD Tools: Roles, Architecture, SelectionCriteria, Selection Criteria, and Pointers, and MDSD Process Building Blocks and Best Practices."],"publisher":["John Wiley & Sons"],"title":["Model-driven software development: Technology, engineering, management"]},"creators":{"author":[{"lastName":"Völter","firstName":"Markus"},{"lastName":"Stahl","firstName":"Thomas"},{"lastName":"Bettin","firstName":"Jorn"},{"lastName":"Haase","firstName":"Arno"},{"lastName":"Helsen","firstName":"Simon"}]},"sentenceCased":true},{"key":"VWMonDataLogger","type":"online","fields":{"shorttitle":["VWMon"],"title":["VWMon: Data logger and remote control for the Vaillant heat pump | construction blog by Katja & Alexey"],"url":["http://baublog.ozerov.de/waermepumpe/vwmon-datenlogger-fuer-die-vaillant-waermepumpe/"],"urldate":["2015-03-27"]},"creators":{},"sentenceCased":true},{"key":"walensteinSimilarityPrograms2006","type":"inproceedings","fields":{"author":["Walenstein, Andrew","El-Ramly, Mohammad","Cordy, James R.","Evans, William S.","Mahdavi, Kiarash","Pizka, Markus","Ramalingam, Ganesan","family=Gudenberg, given=Jürgen Wolff, prefix=von, useprefix=true"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/conf/dagstuhl/WalensteinECEMPRG06"],"booktitle":["Duplic. Redundancy Similarity Softw. 2307 - 26072006"],"date":["2006"],"note":["TL;DR \n\nThe paper is intended to be a starting point for a more comprehensive analysis of the subject of similarity in programs, which is critical to understand if progress is to be made in fields such as clone detection."],"timestamp":["Thu, 23 Aug 2018 15:56:31 +0200"],"title":["Similarity in programs"],"url":["http://drops.dagstuhl.de/opus/volltexte/2007/968"]},"creators":{"author":[{"lastName":"Walenstein","firstName":"Andrew"},{"lastName":"El-Ramly","firstName":"Mohammad"},{"lastName":"Cordy","firstName":"James R."},{"lastName":"Evans","firstName":"William S."},{"lastName":"Mahdavi","firstName":"Kiarash"},{"lastName":"Pizka","firstName":"Markus"},{"lastName":"Ramalingam","firstName":"Ganesan"},{"lastName":"Gudenberg","firstName":"JürgenWolff","prefix":"von","useprefix":true}]},"sentenceCased":true},{"key":"walter2014ontology","type":"article","fields":{"langid":["english"],"author":["Walter, Tobias","Parreiras, Fernando Silva","Staab, Steffen"],"date":["2014"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nA framework that allows the use of ontology technologies to describe and reason on DSLs and the formal semantics of OWL together with reasoning services allows for addressing constraint definition, progressive evaluation, suggestions, and debugging."],"number":["1"],"pages":["83–108"],"title":["An ontology-based framework for domain-specific modeling"],"volume":["13"]},"creators":{"author":[{"lastName":"Walter","firstName":"Tobias"},{"lastName":"Parreiras","firstName":"Fernando Silva"},{"lastName":"Staab","firstName":"Steffen"}]},"sentenceCased":true},{"key":"Wan2022423","type":"article","fields":{"abstract":["The great success of deep learning (DL) has inspired researchers to develop more accurate and efficient symbol detectors for multi-input multi-output (MIMO) systems. Existing DL-based MIMO detectors, however, suffer several drawbacks. To address these issues, in this paper, we develop a model-driven DL detector based on variational Bayesian inference. Specifically, the proposed unrolled DL architecture is inspired by an inverse-free variational Bayesian learning framework which circumvents matrix inversion via maximizing a relaxed evidence lower bound. Two networks are respectively developed for independent and identically distributed (i.i.d.) Gaussian channels and arbitrarily correlated channels. The proposed networks, referred to as VBINet, have only a few learnable parameters and thus can be efficiently trained with a moderate amount of training samples. The proposed VBINet-based detectors can work in both offline and online training modes. An important advantage of our proposed networks over state-of-the-art MIMO detection networks such as OAMPNet and MMNet is that the VBINet can automatically learn the noise variance from data, thus yielding a significant performance improvement over the OAMPNet and MMNet in the presence of noise variance uncertainty. Simulation results show that the proposed VBINet-based detectors achieve competitive performance for both i.i.d. Gaussian and realistic 3GPP MIMO channels. © 1991-2012 IEEE."],"author":["Wan, Q.","Fang, J.","Huang, Y.","Duan, H.","Li, H."],"coden":["ITPRE"],"date":["2022"],"document_type":["Article"],"doi":["10.1109/TSP.2022.3140926"],"issn":["1053587X"],"journaltitle":["IEEE Trans. Signal Process."],"note":["cited By 0 \n\nTL;DR \n\nThe proposed unrolled DL architecture is inspired by an inverse-free variational Bayesian learning framework which circumvents matrix inversion via maximizing a relaxed evidence lower bound and can automatically learn the noise variance from data, thus yielding a significant performance improvement over the OAMPNet and MMNet in the presence of noise variance uncertainty."],"pages":["423–437"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["A variational bayesian inference-inspired unrolled deep network for MIMO detection"],"volume":["70"]},"creators":{"author":[{"lastName":"Wan","firstName":"Q."},{"lastName":"Fang","firstName":"J."},{"lastName":"Huang","firstName":"Y."},{"lastName":"Duan","firstName":"H."},{"lastName":"Li","firstName":"H."}]},"sentenceCased":true},{"key":"wang_adversarial_2020","type":"article","fields":{"abstract":["Users' feedback information as the ground-truth has attracted a lot of attention in recommender systems. However, the feedback that could be contaminated by users' misoperations or malicious operations is probably not true in real scenarios. This work aims to develop a technique based on an improved Bayesian personalized ranking (BPR), called adversarial training-based mean Bayesian personalized ranking (AT-MBPR). In this method, we divide the feedback information into three categories based on the mean Bayesian personalized ranking (MBPR), then gain the implicit feedback from the mean and non-observed items of each user, following which, adversarial perturbations are added on the embedding vectors of the users and items by playing a minimax game to reduce the noise. The experiments demonstrate in five datasets that our approach outperforms the traditional BPR methods and state-of-the-art methods used for the recommendation. Our implementation is available at: https://github.com/HanXia001/Adversarial-Training-based-Mean-BPR-for-Recommender."],"author":["Wang, Jianfang","Han, Pengfei"],"date":["2020"],"doi":["10.1109/ACCESS.2019.2963316"],"issn":["2169-3536"],"journaltitle":["IEEE Access"],"keywords":["adversarial perturbations","Adversarial training","adversarial training-based mean Bayesian personalized ranking","Bayes methods","BPR","BPR methods","Business process re-engineering","Collaboration","collaborative filtering","embedding vectors","feedback information","game theory","implicit feedback","malicious operations","minimax game","minimax techniques","Negative feedback","recommender system","recommender systems","Recommender systems","Robustness","Training"],"note":["Conference Name: IEEE Access \n\nTL;DR \n\nThis work aims to develop a technique based on an improved Bayesian personalized ranking (BPR), called adversarial training-based mean Bayesian generalized ranking (AT-MBPR), which outperforms the traditional BPR methods and state-of-the-art methods used for the recommendation."],"pages":["7958–7968"],"title":["Adversarial Training-Based Mean Bayesian Personalized Ranking for Recommender System"],"volume":["8"]},"creators":{"author":[{"lastName":"Wang","firstName":"Jianfang"},{"lastName":"Han","firstName":"Pengfei"}]}},{"key":"wang_bridging_2022","type":"inproceedings","fields":{"abstract":["With the great success of pre-trained models, the pretrain-then-finetune paradigm has been widely adopted on downstream tasks for source code understanding. However, compared to costly training a large-scale model from scratch, how to effectively adapt pre-trained models to a new task has not been fully explored. In this paper, we propose an approach to bridge pre-trained models and code-related tasks. We exploit semantic-preserving transformation to enrich downstream data diversity, and help pre-trained models learn semantic features invariant to these semantically equivalent transformations. Further, we introduce curriculum learning to organize the transformed data in an easy-to-hard manner to fine-tune existing pre-trained models. We apply our approach to a range of pre-trained models, and they significantly outperform the state-of-the-art models on tasks for source code understanding, such as algorithm classification, code clone detection, and code search. Our experiments even show that without heavy pre-training on code data, natural language pre-trained model RoBERTa fine-tuned with our lightweight approach could outperform or rival existing code pre-trained models fine-tuned on the above tasks, such as CodeBERT and GraphCodeBERT. This finding suggests that there is still much room for improvement in code pre-trained models."],"author":["Wang, Deze","Jia, Zhouyang","Li, Shanshan","Yu, Yue","Xiong, Yun","Dong, Wei","Liao, Xiangke"],"booktitle":["Proc. 44th Int. Conf. Softw. Eng."],"date":["2022-07"],"doi":["10.1145/3510003.3510062"],"isbn":["978-1-4503-9221-1"],"keywords":["curriculum learning","data augmentation","fine-tuning","test-time augmentation"],"location":["New York, NY, USA"],"note":["TL;DR \n\nThis paper exploits semantic-preserving transformation to enrich downstream data diversity, and helps pre-trained models learn semantic features invariant to these semantically equivalent transformations, and introduces curriculum learning to or-ganize the transformed data in an easy-to-hard manner to fine-tune existing pre- trained models."],"pages":["287–298"],"publisher":["Association for Computing Machinery"],"series":["ICSE '22"],"title":["Bridging pre-trained models and downstream tasks for source code understanding"]},"creators":{"author":[{"lastName":"Wang","firstName":"Deze"},{"lastName":"Jia","firstName":"Zhouyang"},{"lastName":"Li","firstName":"Shanshan"},{"lastName":"Yu","firstName":"Yue"},{"lastName":"Xiong","firstName":"Yun"},{"lastName":"Dong","firstName":"Wei"},{"lastName":"Liao","firstName":"Xiangke"}]},"sentenceCased":true},{"key":"Wang10","type":"article","fields":{"langid":["english"],"author":["Wang, Chao","Li, Hong","Gao, Zhigang","Yao, Min","Yang, Yuhao"],"date":["2010-01"],"doi":["10.1109/ICCET.2010.5485654"],"journaltitle":["Int. Conf. Comput. Eng. Technol. Proc. (ICCET)"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper proposes a new methodology for automatic documentation generation, which is capable of maintaining the consistency between software documentation and the corresponding software system in model-driven development."],"title":["An automatic documentation generator based on model-driven techniques"],"volume":["4"]},"creators":{"author":[{"lastName":"Wang","firstName":"Chao"},{"lastName":"Li","firstName":"Hong"},{"lastName":"Gao","firstName":"Zhigang"},{"lastName":"Yao","firstName":"Min"},{"lastName":"Yang","firstName":"Yuhao"}]},"sentenceCased":true},{"key":"Wang2015689","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Asia South Pac. Des. Autom. Conf., ASP-DAC"],"affiliation":["Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, 100190, China; Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 100190, China"],"art_number":["7059090"],"author":["Wang, H.","Zhu, Z.","Shi, J.","Su, Y."],"date":["2015"],"document_type":["Conference Paper"],"doi":["10.1109/ASPDAC.2015.7059090"],"isbn":["978-1-4799-7792-5"],"note":["cited By 3 \n\nTL;DR \n\nAn accurate and efficient adaptive component selection and smoothing operator (ACOSSO) metamodel assisted NSGA-II (MA-NSGA- II) multi-objective optimization (MOO) technique for processor DSE that achieves higher prediction accuracy and better architecture optimization results."],"pages":["689–694"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["20th Asia and South Pacific Design Automation Conference, ASP-DAC 2015"],"source":["Scopus"],"title":["An accurate ACOSSO metamodeling technique for processor architecture design space exploration"]},"creators":{"author":[{"lastName":"Wang","firstName":"H."},{"lastName":"Zhu","firstName":"Z."},{"lastName":"Shi","firstName":"J."},{"lastName":"Su","firstName":"Y."}]},"sentenceCased":true},{"key":"Wang2019","type":"inproceedings","fields":{"abstract":["Deep neural networks (DNNs) have achieved impressive performance in many difficult tasks. However, DNN models are essentially uninterpretable to humans, and unfortunately prone to adversarial attacks, which hinders their adoption in security and safety-critical scenarios. The robustness of a DNN model, which measures its stableness against adversarial attacks, becomes an important topic in both the machine learning and the software engineering communities. Analytical evaluation of DNN robustness is difficult due to the high-dimensionality of inputs, the huge amount of parameters, and the nonlinear network structure. In practice, the degree of robustness of DNNs is empirically approximated with adversarial searching, which is computationally expensive and cannot be applied in resource constrained settings such as embedded computing. In this paper, we propose to predict the robustness of a DNN model for each input with another DNN model, which takes the output of neurons of the former model as input. We train a regression model to encode the connections between output of the penultimate layer of a DNN model and its robustness. With this trained model, the robustness for an input can be predicted instantaneously. Experiments with MNIST and CIFAR10 datasets and LeNet, VGG and ResNet DNN models were conducted to evaluate the efficacy of the proposed approach. The results indicated that our approach achieved 0.05-0.21 mean absolute errors and significantly outperformed confidence and surprise adequacy-based approaches. © 2019 Association for Computing Machinery."],"art_number":["3361243"],"author":["Wang, Y.","Li, Z.","Xu, J.","Yu, P.","Ma, X."],"author_keywords":["Deep Neural Networks; Prediction; Robustness"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1145/3361242.3361243"],"isbn":["978-1-4503-7701-0"],"keywords":["Analytical evaluation","Deep neural networks","Degree of robustness","Embedded computing","Engineering community","Forecasting","High dimensionality","Mean absolute error","Neural networks","Regression analysis","Regression model","Robustness (control systems)","Safety engineering","Software engineering","Stableness"],"note":["cited By 0 \n\nTL;DR \n\nA regression model is trained to encode the connections between output of the penultimate layer of a DNN model and its robustness and, with this trained model, the robustness for an input can be predicted instantaneously."],"publisher":["Association for Computing Machinery"],"series":["ACM International Conference Proceeding Series"],"source":["Scopus"],"title":["Fast robustness prediction for deep neural network"]},"creators":{"author":[{"lastName":"Wang","firstName":"Y."},{"lastName":"Li","firstName":"Z."},{"lastName":"Xu","firstName":"J."},{"lastName":"Yu","firstName":"P."},{"lastName":"Ma","firstName":"X."}]},"sentenceCased":true},{"key":"Wang2021107","type":"article","fields":{"abstract":["For the task of metal artifact reduction (MAR), although deep learning (DL)-based methods have achieved promising performances, most of them suffer from two problems: 1) the CT imaging geometry constraint is not fully embedded into the network during training, leaving room for further performance improvement; 2) the model interpretability is lack of sufficient consideration. Against these issues, we propose a novel interpretable dual domain network, termed as InDuDoNet, which combines the advantages of model-driven and data-driven methodologies. Specifically, we build a joint spatial and Radon domain reconstruction model and utilize the proximal gradient technique to design an iterative algorithm for solving it. The optimization algorithm only consists of simple computational operators, which facilitate us to correspondingly unfold iterative steps into network modules and thus improve the interpretablility of the framework. Extensive experiments on synthesized and clinical data show the superiority of our InDuDoNet. Code is available in https://github.com/hongwang01/InDuDoNet. © 2021, Springer Nature Switzerland AG."],"author":["Wang, H.","Li, Y.","Zhang, H.","Chen, J.","Ma, K.","Meng, D.","Zheng, Y."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-87231-1_11"],"editor":["family=Bruijne M., de Bruijne M., given=Cattin P.C., suffix=Cotin S., Padoy N., Speidel S., Zheng Y., Essert C., prefix=de, useprefix=true"],"isbn":["9783030872304"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 1 \n\nTL;DR \n\nThis work builds a joint spatial and Radon domain reconstruction model and utilizes the proximal gradient technique to design an iterative algorithm for solving it, which combines the advantages of model-driven and data-driven methodologies and improves the interpretablility of the framework."],"pages":["107–118"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["InDuDoNet: An interpretable dual domain network for CT metal artifact reduction"],"volume":["12906 LNCS"]},"creators":{"author":[{"lastName":"Wang","firstName":"H."},{"lastName":"Li","firstName":"Y."},{"lastName":"Zhang","firstName":"H."},{"lastName":"Chen","firstName":"J."},{"lastName":"Ma","firstName":"K."},{"lastName":"Meng","firstName":"D."},{"lastName":"Zheng","firstName":"Y."}],"editor":[{"lastName":"family=Bruijne M.","suffix":"de Bruijne M.","firstName":"given=Cattin P.C., suffix=Cotin S., Padoy N., Speidel S., Zheng Y., Essert C., prefix=de, useprefix=true"}]},"sentenceCased":true},{"key":"Wang20212270","type":"article","fields":{"abstract":["Deep learning (DL) has dramatically improved the peak-to-average power ratio (PAPR) performance. However, the high computational complexity and excessive training data constitute a significant hurdle. In this letter, a model-driven deep learning algorithm is proposed for PAPR reduction in orthogonal frequency division multiplexing (OFDM) system. Precisely, an iterative peak-canceling signal generation scheme is unfolded as a layer structure of the DL network. The scheme falls into the category of tone reservation technique. A set of trainable parameters, which optimizes the clipping threshold and weights time-domain kernel function, has been designed and introduced into the iterative scheme. Compared with the existing approaches, the simulation results demonstrate that the proposed algorithm achieves comparable PAPR performance with low complexity and training costs. © 2021 IEEE."],"art_number":["9419069"],"author":["Wang, X.","Jin, N.","Wei, J."],"coden":["ICLEF"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/LCOMM.2021.3076605"],"issn":["10897798"],"journaltitle":["IEEE Commun. Lett."],"note":["cited By 2 \n\nTL;DR \n\nA model-driven deep learning algorithm is proposed for PAPR reduction in orthogonal frequency division multiplexing (OFDM) system and simulation results demonstrate that the proposed algorithm achieves comparable P APR performance with low complexity and training costs."],"number":["7"],"pages":["2270–2274"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["A model-driven DL algorithm for PAPR reduction in OFDM system"],"volume":["25"]},"creators":{"author":[{"lastName":"Wang","firstName":"X."},{"lastName":"Jin","firstName":"N."},{"lastName":"Wei","firstName":"J."}]},"sentenceCased":true},{"key":"Wang20212385","type":"article","fields":{"abstract":["In this letter, we propose a pilot-assisted receiver scheme based on learnable successive interference cancellation (PA-LSIC) for uplink single-input multiple-output (SIMO) non-orthogonal multiple access (NOMA) systems. The PA-LSIC combines the successive interference cancellation (SIC) structure with the model-driven deep learning network. Considering the noise impact of channel estimation and the incomplete detection and cancellation in SIC process, we introduce some new parameters, such as noise cancellation factor and interference cancellation factor, which are optimized by using the back-propagation algorithm and random gradient descent algorithm. Numerical results show that the PA-LSIC has superior bit error rate (BER) performance and lower complexity during training and implementation. © 2021 IEEE."],"art_number":["9393981"],"author":["Wang, X.","Zhu, P.","Li, D.","Xu, Y.","You, X."],"coden":["ICLEF"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/LCOMM.2021.3070705"],"issn":["10897798"],"journaltitle":["IEEE Commun. Lett."],"note":["cited By 4 \n\nTL;DR \n\nNumerical results show that the PA-LSIC has superior bit error rate (BER) performance and lower complexity during training and implementation, and introduces some new parameters, such as noise cancellation factor and interference cancellation factor, which are optimized by using the back-propagation algorithm and random gradient descent algorithm."],"number":["7"],"pages":["2385–2389"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Pilot-assisted SIMO-NOMA signal detection with learnable successive interference cancellation"],"volume":["25"]},"creators":{"author":[{"lastName":"Wang","firstName":"X."},{"lastName":"Zhu","firstName":"P."},{"lastName":"Li","firstName":"D."},{"lastName":"Xu","firstName":"Y."},{"lastName":"You","firstName":"X."}]},"sentenceCased":true},{"key":"Wang2021639","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["SoCC - Proc. ACM Symp. Cloud Comput."],"affiliation":["HKUST, Alibaba Group, Hong Kong"],"author":["Wang, L.","Yang, L.","Yu, Y.","Wang, W.","Li, B.","Sun, X.","He, J.","Zhang, L."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1145/3472883.3486987"],"isbn":["978-1-4503-8638-8"],"keywords":["notion"],"note":["cited By 1"],"pages":["639–653"],"publisher":["Association for Computing Machinery, Inc"],"series":["SoCC 2021 - Proceedings of the 2021 ACM Symposium on Cloud Computing"],"source":["Scopus"],"title":["Morphling: Fast, near-Optimal auto-configuration for cloud-native model serving"]},"creators":{"author":[{"lastName":"Wang","firstName":"L."},{"lastName":"Yang","firstName":"L."},{"lastName":"Yu","firstName":"Y."},{"lastName":"Wang","firstName":"W."},{"lastName":"Li","firstName":"B."},{"lastName":"Sun","firstName":"X."},{"lastName":"He","firstName":"J."},{"lastName":"Zhang","firstName":"L."}]},"sentenceCased":true},{"key":"Wang20223440","type":"article","fields":{"abstract":["State-of-the-art adversarial attacks in the text domain have shown their power to induce machine learning models to produce abnormal outputs. The samples generated in these attacks have three important attributes: attack ability, transferability, and imperceptibility. However, compared with the other two attributes, the imperceptibility of adversarial examples has not been well investigated. Unlike the pixel-level perturbations in images, adversarial perturbations in the text are usually traceable, reflecting changes in characters, words, or sentences. The generation of imperceptible samples in texts is more difficult than in images. Therefore, how to constrain adversarial perturbations added in the text is a crucial step to construct more natural adversarial texts. Unfortunately, recent studies merely select measurements to constrain the added adversarial perturbations, but none of them explain where these measurements are suitable, which one is better, and how they perform in different kinds of adversarial attacks. In this paper, we fill this gap by comparing the performance of these metrics in various attacks. Furthermore, we propose a stricter constraint for word-level attacks to obtain more imperceptible samples. It is also helpful to enhance existing word-level attacks for adversarial training. © 2021 Wiley Periodicals LLC."],"author":["Wang, W.","Wang, L.","Wang, R.","Ye, A.","Ke, J."],"author_keywords":["adversarial texts; imperceptibility; measurements; semantic and visual similarity; visual optimization"],"coden":["IJISE"],"date":["2022"],"document_type":["Article"],"doi":["10.1002/int.22696"],"issn":["08848173"],"journaltitle":["Int. J. Intell. Syst."],"keywords":["Adversarial text","Imperceptibility","Machine learning models","Pixel level","Power","Semantic similarity","Semantics","Software engineering","State of the art","Visual optimization","Visual similarity","Word level"],"note":["cited By 2"],"number":["6"],"pages":["3440–3459"],"publisher":["John Wiley and Sons Ltd"],"source":["Scopus"],"title":["Better constraints of imperceptibility, better adversarial examples in the text"],"volume":["37"]},"creators":{"author":[{"lastName":"Wang","firstName":"W."},{"lastName":"Wang","firstName":"L."},{"lastName":"Wang","firstName":"R."},{"lastName":"Ye","firstName":"A."},{"lastName":"Ke","firstName":"J."}]},"sentenceCased":true},{"key":"wangCoCoSumContextualCode2021","type":"article","fields":{"langid":["english"],"abstract":["Source code summaries are short natural language descriptions of code snippets that help developers better understand and maintain source code. There has been a surge of work on automatic code summarization to reduce the burden of writing summaries manually. However, most contemporary approaches mainly leverage the information within the boundary of the method being summarized (i.e., local context), and ignore the broader context that could assist with code summarization. This paper explores two global contexts, namely intra-class and inter-class contexts, and proposes the model CoCoSUM: Contextual Code Summarization with Multi-Relational Graph Neural Networks. CoCoSUM first incorporates class names as the intra-class context to generate the class semantic embeddings. Then, relevant Unified Modeling Language (UML) class diagrams are extracted as inter-class context and are encoded into the class relational embeddings using a novel Multi-Relational Graph Neural Network (MRGNN). Class semantic embeddings and class relational embeddings, together with the outputs from code token encoder and AST encoder, are passed to a decoder armed with a two-level attention mechanism to generate high-quality, context-aware code summaries. We conduct extensive experiments to evaluate our approach and compare it with other automatic code summarization models. The experimental results show that CoCoSUM is effective and outperforms state-of-the-art methods. Our source code and experimental data are available in the supplementary materials and will be made publicly available."],"author":["Wang, Yanlin","Shi, Ensheng","Du, Lun","Yang, Xiaodi","Hu, Yuxuan","Han, Shi","Zhang, Hongyu","Zhang, Dongmei"],"date":["2021-07-05"],"eprint":["2107.01933"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv210701933 Cs"],"keywords":["Computer Science - Software Engineering"],"shorttitle":["CoCoSum"],"title":["CoCoSum: Contextual Code Summarization with Multi-Relational Graph Neural Network"],"url":["http://arxiv.org/abs/2107.01933"],"urldate":["2022-01-28"]},"creators":{"author":[{"lastName":"Wang","firstName":"Yanlin"},{"lastName":"Shi","firstName":"Ensheng"},{"lastName":"Du","firstName":"Lun"},{"lastName":"Yang","firstName":"Xiaodi"},{"lastName":"Hu","firstName":"Yuxuan"},{"lastName":"Han","firstName":"Shi"},{"lastName":"Zhang","firstName":"Hongyu"},{"lastName":"Zhang","firstName":"Dongmei"}]}},{"key":"wangMiningSuccinctHighcoverage2013","type":"inproceedings","fields":{"author":["Wang, J.","Dang, Y.","Zhang, H.","Chen, K.","Xie, T.","Zhang, D."],"booktitle":["10th Work. Conf. Min. Softw. Repos."],"date":["2013"],"ids":["Wang2013Mining"],"issn":["2160-1852"],"keywords":["API usage","application program interfaces","application programming interface","client code mining","Clustering algorithms","Context","data mining","Data mining","high-coverage API usage pattern mining","Indexes","large-scale Microsoft codebase","MAPO","Measurement","mining software repositories","Probabilistic logic","Redundancy","sequence mining","software development","software reusability","software reuse","source code","succinct API usage pattern mining","UP-miner","usage pattern","usage pattern discovery","usage pattern miner"],"location":["Piscataway"],"note":["TL;DR \n\nThis paper proposes two quality metrics (succinctness and coverage) for mined usage patterns, and proposes a novel approach called Usage Pattern Miner (UP-Miner) that mines succinct and high-coverage usage patterns of API methods from source code."],"pages":["319–328"],"publisher":["IEEE"],"title":["Mining succinct and high-coverage API usage patterns from source code"]},"creators":{"author":[{"lastName":"Wang","firstName":"J."},{"lastName":"Dang","firstName":"Y."},{"lastName":"Zhang","firstName":"H."},{"lastName":"Chen","firstName":"K."},{"lastName":"Xie","firstName":"T."},{"lastName":"Zhang","firstName":"D."}]},"sentenceCased":true},{"key":"wangPersonalizingLabelPrediction2022","type":"article","fields":{"langid":["english"],"abstract":["Objective: These factors inspire us to propose a method to identify these synonymous labels automatically and recommend personalized labels for different open-source projects. Method: In this paper, we propose a Personalizing Label Prediction framework for Issues named PLPI. PLPI identifies labels with similar meanings by representing labels as semantic vectors and applying clustering methods. PLPI can predict personalized labels from the existing labels in the open-source project. Result: We conduct a comprehensive study to compare seven commonly adopted labeling models with our approach. The experimental results demonstrate the advantages of our approach. Finally, we show some representative examples and discuss the visualization results of synonyms clustering by dimension reduction. Conclusion: The experimental results show that our method PLPI can improve label prediction performance and provide personalized label recommendation results for different open-source projects."],"author":["Wang, Jun","Zhang, Xiaofang","Chen, Lin","Xie, Xiaoyuan"],"date":["2022-01"],"doi":["10.1016/j.infsof.2022.106845"],"issn":["09505849"],"journaltitle":["Information and Software Technology"],"pages":["106845"],"title":["Personalizing label prediction for GitHub issues"]},"creators":{"author":[{"lastName":"Wang","firstName":"Jun"},{"lastName":"Zhang","firstName":"Xiaofang"},{"lastName":"Chen","firstName":"Lin"},{"lastName":"Xie","firstName":"Xiaoyuan"}]},"sentenceCased":true},{"key":"wangVerifyingMetamodelCoverage2006","type":"inproceedings","fields":{"author":["Wang, J.","Kim, S.-K.","Carrington, D."],"date":["2006"],"doi":["10.1109/ASWEC.2006.55"],"isbn":["978-0-7695-2551-8"],"pages":["10 pp.-282"],"publisher":["IEEE"],"title":["Verifying metamodel coverage of model transformations"]},"creators":{"author":[{"lastName":"Wang","firstName":"J."},{"lastName":"Kim","firstName":"S.-K."},{"lastName":"Carrington","firstName":"D."}]},"sentenceCased":true},{"key":"wangWuKongScalableAccurate2015","type":"inproceedings","fields":{"acmid":["2771795"],"author":["Wang, Haoyu","Guo, Yao","Ma, Ziang","Chen, Xiangqun"],"booktitle":["Proc. 2015 Int. Symp. Softw. Test. Anal."],"date":["2015"],"isbn":["978-1-4503-3620-8"],"keywords":["Android","Clone detection","mobile applications","repackaging","third-party library"],"location":["New York, NY, USA"],"nodoi":["10.1145/2771783.2771795"],"note":["TL;DR \n\nWuKong is proposed, a two-phase detection approach that includes a coarse-grained detection phase to identify suspicious apps by comparing light-weight static semantic features, and a fine- grained phase to compare more detailed features for only those apps found in the first phase."],"numpages":["12"],"pages":["71–82"],"publisher":["ACM"],"series":["ISSTA 2015"],"title":["WuKong: A scalable and accurate two-phase approach to android app clone detection"],"url":["http://doi.acm.org/10.1145/2771783.2771795"]},"creators":{"author":[{"lastName":"Wang","firstName":"Haoyu"},{"lastName":"Guo","firstName":"Yao"},{"lastName":"Ma","firstName":"Ziang"},{"lastName":"Chen","firstName":"Xiangqun"}]},"sentenceCased":true},{"key":"waszkowskiLowcodePlatformAutomating2019","type":"article","fields":{"langid":["english"],"author":["Waszkowski, Robert"],"date":["2019"],"doi":["10.1016/j.ifacol.2019.10.060"],"ids":["WASZKOWSKI2019376"],"issn":["24058963"],"journaltitle":["IFAC-PapersOnLine"],"keywords":["Aurea BPM","business processes","Low-code platform","manufacturing","process automation"],"note":["13th IFAC Workshop on Intelligent Manufacturing Systems IMS 2019 \n\nReferred in <a href=\"zotero://note/u/WN7FRTZI/?ignore=1&line=-1\">PLACEMENT</a>"],"number":["10"],"pages":["376–381"],"title":["Low-code platform for automating business processes in manufacturing"],"volume":["52"]},"creators":{"author":[{"lastName":"Waszkowski","firstName":"Robert"}]},"sentenceCased":true},{"key":"watzoldtModelingCollaborationsSelfadaptive2015","type":"book","fields":{"langid":["english"],"author":["Wätzoldt, Sebastian","Giese, Holger"],"date":["2015"],"editora":["Hasso-Plattner-Institut für Softwaresystemtechnik"],"editoratype":["collaborator"],"isbn":["978-3-86956-324-4"],"location":["Potsdam"],"note":["Literaturverzeichnis S. 62 - 72"],"number":["96"],"pagetotal":["72"],"publisher":["Univ.-Verl"],"series":["Technische Berichte des Hasso-Plattner-Instituts für Softwaresystemtechnik an der Universität Potsdam"],"shorttitle":["Modeling collaborations in self-adaptive systems of systems"],"title":["Modeling collaborations in self-adaptive systems of systems: Terms, characteristics, requirements, and scenarios"]},"creators":{"author":[{"lastName":"Wätzoldt","firstName":"Sebastian"},{"lastName":"Giese","firstName":"Holger"}],"editora":[{"literal":"Hasso-Plattner-Institut für Softwaresystemtechnik"}]},"sentenceCased":true},{"key":"Weber2020403","type":"article","fields":{"abstract":["Industry 4.0 use cases such as predictive maintenance and product quality control make it necessary to create, use and maintain a multitude of different machine learning models. In this setting, model management systems help to organize models. However, concepts for model management systems currently focus on data scientists, but do not support non-expert users such as domain experts and business analysts. Thus, it is difficult for them to reuse existing models for their use cases. In this paper, we address these challenges and present an architecture, a metadata schema and a corresponding model management platform. © Springer Nature Switzerland AG 2020."],"author":["Weber, C.","Hirmer, P.","Reimann, P."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-030-53337-3_30"],"editor":["Abramowicz W., Klein G."],"isbn":["9783030533366"],"issn":["18651348"],"journaltitle":["Lect. Notes Bus. Inf. Process."],"note":["cited By 4 \n\nTL;DR \n\nThis paper presents an architecture, a metadata schema and a corresponding model management platform for non-expert users such as domain experts and business analysts to reuse existing models for their use cases in industry 4.0."],"pages":["403–417"],"publisher":["Springer"],"source":["Scopus"],"title":["A model management platform for industry 4.0 – enabling management of machine learning models in manufacturing environments"],"volume":["389 LNBIP"]},"creators":{"author":[{"lastName":"Weber","firstName":"C."},{"lastName":"Hirmer","firstName":"P."},{"lastName":"Reimann","firstName":"P."}],"editor":[{"lastName":"Abramowicz W.","firstName":"Klein G."}]},"sentenceCased":true},{"key":"Weber202091","type":"inproceedings","fields":{"abstract":["In manufacturing environments, machine learning models are being built for several use cases, such as predictive maintenance and product quality control. In this context, the various manufacturing processes, machines, and product variants make it necessary to create and use lots of different machine learning models. This calls for a software system that is able to manage all these diverse machine learning models and associated metadata. However, current model management systems do not associate models with business and domain context to provide non-expert users with tailored functions for model search and discovery. Moreover, none of the existing systems provides a comprehensive overview of all models within an organization. In our demonstration, we present the MMP, our model management platform that addresses these issues. The MMP provides a model metadata extractor, a model registry, and a context manager to store model metadata in a central metadata store. On top of this, the MMP provides frontend components that offer the above-mentioned functionalities. In our demonstration, we show two scenarios for model management in Industry 4.0 environments that illustrate the novel functionalities of the MMP. We demonstrate to the audience how the platform and its metadata, linking models to their business and domain context, help non-expert users to search and discover models. Furthermore, we show how to use MMP's powerful visualizations for model reporting, such as a dashboard and a model landscape view. © 2020 IEEE."],"art_number":["9233284"],"author":["Weber, C.","Reimann, P."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/EDOCW49879.2020.00025"],"isbn":["978-1-72816-471-7"],"issn":["15417719"],"note":["cited By 1 \n\nTL;DR \n\nThe MMP is presented, the authors' model management platform that addresses issues of model management, and it is demonstrated to the audience how the platform and its metadata, linking models to their business and domain context, help non-expert users to search and discover models."],"pages":["91–94"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - IEEE International Enterprise Distributed Object Computing Workshop, EDOCW"],"source":["Scopus"],"title":["MMP - A platform to manage machine learning models in industry 4.0 environments"],"volume":["2020-October"]},"creators":{"author":[{"lastName":"Weber","firstName":"C."},{"lastName":"Reimann","firstName":"P."}]},"sentenceCased":true},{"key":"Wei2020","type":"inproceedings","fields":{"abstract":["In this work, we consider the use of model-driven deep learning (DL) techniques for signal detection in massive multiple-input multiple-output (MIMO) system. Massive MIMO promises improved spectral efficiency, coverage and reliability, compared to conventional MIMO systems. Unfortunately, these benefits usually come at the cost of significantly increased computational complexity. To address this difficulty, a learned conjugate gradient descent network, referred to as LcgNet, is presented by unfolding the iterative conjugate gradient descent (CG) detector. In the proposed network, instead of calculating the exact values of the scalar step-sizes for every problem instance, we explicitly learn their universal values. We show that the performance of the proposed network can be greatly improved by augmenting the dimensions of these step-sizes. Furthermore, due to the limited learnable parameters to be optimized, the proposed networks are easy and fast to train. Numerical results demonstrate that this approach can achieve superior performance over some state-of-the-art MIMO detectors such as the CG detector, the linear minimum mean squared error (LMMSE) detector etc., with much lower computational complexity. © 2020 IEEE."],"art_number":["9149227"],"author":["Wei, Y.","Zhao, M.-M.","Hong, M.","Zhao, M.-J.","Lei, M."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/ICC40277.2020.9149227"],"isbn":["978-1-72815-089-5"],"issn":["15503607"],"note":["cited By 2 \n\nTL;DR \n\nThis work considers the use of model-driven deep learning techniques for signal detection in massive multiple-input multiple-output (MIMO) system and proposes a learned conjugate gradient descent network, referred to as LcgNet, which can achieve superior performance over some state-of-the-art MIMO detectors with much lower computational complexity."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["IEEE International Conference on Communications"],"source":["Scopus"],"title":["Learned conjugate gradient descent network for massive MIMO detection"],"volume":["2020-June"]},"creators":{"author":[{"lastName":"Wei","firstName":"Y."},{"lastName":"Zhao","firstName":"M.-M."},{"lastName":"Hong","firstName":"M."},{"lastName":"Zhao","firstName":"M.-J."},{"lastName":"Lei","firstName":"M."}]},"sentenceCased":true},{"key":"Wei20206336","type":"article","fields":{"abstract":["In this work, we consider the use of model-driven deep learning techniques for massive multiple-input multiple-output (MIMO) detection. Compared with conventional MIMO systems, massive MIMO promises improved spectral efficiency, coverage and range. Unfortunately, these benefits are at the expense of significantly increased computational complexity. To reduce the complexity of signal detection and guarantee the performance, we present a learned conjugate gradient descent network (LcgNet), which is constructed by unfolding the iterative conjugate gradient descent (CG) detector. In the proposed network, instead of calculating the exact values of the scalar step-sizes, we explicitly learn their universal values. Also, we can enhance the proposed network by augmenting the dimensions of these step-sizes. Furthermore, in order to reduce the memory costs, a novel quantized LcgNet is proposed, where a low-resolution nonuniform quantizer is used to quantize the learned parameters. The quantizer is based on a specially designed soft staircase function with learnable parameters to adjust its shape. Meanwhile, due to fact that the number of learnable parameters is limited, the proposed networks are relatively easy to train. Numerical results demonstrate that the proposed network can achieve promising performance with much lower complexity. © 2020 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission."],"art_number":["3035832"],"author":["Wei, Y.","Zhao, M.-M.","Hong, M.","Zhao, M.-J.","Lei, M."],"coden":["ITPRE"],"date":["2020"],"document_type":["Article"],"doi":["10.1109/TSP.2020.3035832"],"issn":["1053587X"],"journaltitle":["IEEE Trans. Signal Process."],"note":["cited By 16"],"pages":["6336–6349"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Learned conjugate gradient descent network for massive MIMO detection"],"volume":["68"]},"creators":{"author":[{"lastName":"Wei","firstName":"Y."},{"lastName":"Zhao","firstName":"M.-M."},{"lastName":"Hong","firstName":"M."},{"lastName":"Zhao","firstName":"M.-J."},{"lastName":"Lei","firstName":"M."}]},"sentenceCased":true},{"key":"weissModelDrivenDevelopmentSelfDescribing2011","type":"inproceedings","fields":{"author":["Weiss, Gereon","Becker, Klaus","Kamphausen, Benjamin","Radermacher, Ansgar","Gerard, Sebastien"],"date":["2011-08"],"doi":["10.1109/SEAA.2011.78"],"isbn":["978-1-4577-1027-8"],"note":["TL;DR \n\nThis work introduces a novel concept for the model-driven development of self-adaptive embedded systems, and presents a self-x profile, a modeling extension for describing the adaptation, and the respective design flow with built-in transformations."],"pages":["477–484"],"publisher":["IEEE"],"title":["Model-Driven Development of Self-Describing Components for Self-Adaptive Distributed Embedded Systems"]},"creators":{"author":[{"lastName":"Weiss","firstName":"Gereon"},{"lastName":"Becker","firstName":"Klaus"},{"lastName":"Kamphausen","firstName":"Benjamin"},{"lastName":"Radermacher","firstName":"Ansgar"},{"lastName":"Gerard","firstName":"Sebastien"}]}},{"key":"wengLLMPoweredAutonomous2023","type":"online","fields":{"langid":["english"],"abstract":["Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver. Agent System Overview In a LLM-powered autonomous agent system, LLM functions as the agent’s brain, complemented by several key components:"],"author":["Weng, Lilian"],"date":["2023-06-23T00:00:00+00:00"],"title":["LLM Powered Autonomous Agents"],"url":["https://lilianweng.github.io/posts/2023-06-23-agent/"],"urldate":["2024-02-07"]},"creators":{"author":[{"lastName":"Weng","firstName":"Lilian"}]}},{"key":"WenzKT21","type":"inproceedings","fields":{"langid":["english"],"author":["Wenz, Viola","Kesper, Arno","Taentzer, Gabriele"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["ACMIEEE Int. Conf. Model Driven Eng. Lang. Syst. Companion MODELS 2021 Companion Fukuoka Jpn. Oct. 10-15 2021"],"date":["2021"],"doi":["10.1109/MODELS-C53483.2021.00027"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis work proposes a bottom-up approach to detecting quality problems in data models that manifest in heterogeneous data values that supports an explorative analysis of the existing data and can be configured by domain experts according to their domain knowledge."],"pages":["150–159"],"publisher":["IEEE"],"timestamp":["Wed, 23 Feb 2022 12:16:57 +0100"],"title":["Detecting quality problems in data models by clustering heterogeneous data values"]},"creators":{"author":[{"lastName":"Wenz","firstName":"Viola"},{"lastName":"Kesper","firstName":"Arno"},{"lastName":"Taentzer","firstName":"Gabriele"}]},"sentenceCased":true},{"key":"Westfechtel14","type":"article","fields":{"langid":["english"],"author":["Westfechtel, Bernhard"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"date":["2014"],"doi":["10.1007/S10270-012-0279-3"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found"],"number":["2"],"pages":["757–788"],"timestamp":["Fri, 18 Sep 2020 11:19:20 +0200"],"title":["Merging of EMF models - formal foundations"],"volume":["13"]},"creators":{"author":[{"lastName":"Westfechtel","firstName":"Bernhard"}]},"sentenceCased":true},{"key":"weynsApplyingArchitectureBasedAdaptation2018","type":"inproceedings","fields":{"langid":["english"],"abstract":["Architecture-based adaptation equips a software-intensive system with a feedback loop that enables the system to adapt itself at runtime to changes to maintain its required quality goals. To guarantee the required goals, existing adaptation approaches apply exhaustive verification techniques at runtime. However these approaches are restricted to small-scale settings, which often limits their applicability in practice. To tackle this problem, we introduce an innovative architecture-based adaptation approach to solve a concrete practical problem of VersaSense: automating the management of Internet-of-Things (IoT). The approach, called MARTAS, equips a software system with a feedback loop that employs Models At Run Time and Statistical techniques to reason about the system and adapt it to ensure the required goals. We apply MARTAS to a building security case system, which is a representative IoT system deployed by VersaSense. The application comprises a set of IoT devices that communicate sensor data over a time synchronized smart mess network to a central monitoring facility. We demonstrate how MARTAS outperforms a conservative approach that is typically applied in practice and a state-of-the-art adaptation approach for different quality goals, and we report lessons learned from this industrial case."],"author":["Weyns, Danny","Iftikhar, M. Usman","Hughes, Danny","Matthys, Nelson"],"booktitle":["Softw. Archit."],"date":["2018"],"doi":["10.1007/978-3-030-00761-4_4"],"editor":["Cuesta, Carlos E.","Garlan, David","Pérez, Jennifer"],"isbn":["978-3-030-00761-4"],"keywords":["DONE"],"location":["Cham"],"note":["TL;DR \n\nAn innovative architecture-based adaptation approach to solve a concrete practical problem of VersaSense: automating the management of Internet-of-Things (IoT) and demonstrates how MARTAS outperforms a conservative approach that is typically applied in practice and a state- of-the-art adaptation approach for different quality goals."],"pages":["49–67"],"publisher":["Springer International Publishing"],"series":["Lecture Notes in Computer Science"],"title":["Applying Architecture-Based Adaptation to Automate the Management of Internet-of-Things"]},"creators":{"author":[{"lastName":"Weyns","firstName":"Danny"},{"lastName":"Iftikhar","firstName":"M. Usman"},{"lastName":"Hughes","firstName":"Danny"},{"lastName":"Matthys","firstName":"Nelson"}],"editor":[{"lastName":"Cuesta","firstName":"Carlos E."},{"lastName":"Garlan","firstName":"David"},{"lastName":"Pérez","firstName":"Jennifer"}]}},{"key":"Weyssow20221071","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Softw. Syst. Model."],"affiliation":["DIRO, Université de Montréal, Montreal, Canada"],"author":["Weyssow, M.","Sahraoui, H.","Syriani, E."],"correspondence_address1":["Weyssow, M.; DIRO, Canada; email: martin.weyssow@umontreal.ca"],"date":["2022"],"document_type":["Article"],"doi":["10.1007/s10270-022-00975-5"],"ids":["weyssow2022recommending"],"issn":["16191366"],"journaltitle":["Software Syst. Model."],"keywords":["/unread","⛔ No INSPIRE recid found","GOAL_Model-Assistance","notion","TECHNIQUE_LSTM"],"note":["cited By 0 \n\nTL;DR \n\nThe preliminary results show that the trained model is able to provide accurate top 5 lists of relevant recommendations for concept renaming scenarios, and the results are less compelling for the scenario of the iterative construction of the metamodel, in part because of the conservative strategy used to evaluate the recommendations."],"number":["3"],"pages":["1071–1089"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Recommending metamodel concepts during modeling activities with pre-trained language models"],"volume":["21"]},"creators":{"author":[{"lastName":"Weyssow","firstName":"M."},{"lastName":"Sahraoui","firstName":"H."},{"lastName":"Syriani","firstName":"E."}]},"sentenceCased":true},{"key":"weyssow2024codeultrafeedback","type":"article","fields":{"langid":["english"],"author":["Weyssow, Martin","Kamanda, Aton","Sahraoui, Houari"],"date":["2024"],"eprint":["2403.09032"],"eprinttype":["arxiv"],"journaltitle":["arXiv prepr. arXiv:2403,09032"],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nThis paper introduces CodeUltraFeedback, a preference dataset of 10,000 complex instructions to tune and align LLMs to coding preferences through AI feedback, and shows the utility of CodeUltraFeedback for preference tuning."],"title":["CodeUltraFeedback: An LLM-as-a-judge dataset for aligning large language models to coding preferences"]},"creators":{"author":[{"lastName":"Weyssow","firstName":"Martin"},{"lastName":"Kamanda","firstName":"Aton"},{"lastName":"Sahraoui","firstName":"Houari"}]},"sentenceCased":true},{"key":"whalenRequirementsArchitecturesSecure2016","type":"article","fields":{"author":["Whalen, Michael W.","Cofer, Darren","Gacek, Andrew"],"date":["2016"],"journaltitle":["IEEE Softw."],"number":["4"],"pages":["22–25"],"title":["Requirements and Architectures for Secure Vehicles"],"url":["http://ieeexplore.ieee.org/abstract/document/7498541/"],"urldate":["2016-09-28"],"volume":["33"]},"creators":{"author":[{"lastName":"Whalen","firstName":"Michael W."},{"lastName":"Cofer","firstName":"Darren"},{"lastName":"Gacek","firstName":"Andrew"}]}},{"key":"WhatDifferenceAutonomous","type":"online","fields":{"title":["What's the difference between autonomous systems, ISPs and RIRs? - Network Engineering Stack Exchange"],"url":["http://networkengineering.stackexchange.com/questions/25951/whats-the-difference-between-autonomous-systems-isps-and-rirs"],"urldate":["2016-08-26"]},"creators":{},"sentenceCased":true},{"key":"WhatDifferenceEvolution","type":"online","fields":{"title":["What is the difference between evolution and change? | WikiDiff"],"url":["https://wikidiff.com/evolution/change"],"urldate":["2020-02-10"]},"creators":{},"sentenceCased":true},{"key":"WhatLowCode2020","type":"online","fields":{"keywords":["lowcode"],"title":["What Is Low-Code? [2020 Update]"],"url":["https://www.outsystems.com/blog/what-is-low-code.html"],"urldate":["2020-04-08"]},"creators":{}},{"key":"WhenHowUse","type":"misc","fields":{"title":["When and How to Use Multi-Level Modelling.Pdf"]},"creators":{}},{"key":"whitmoreInternetThingsSurvey2015","type":"article","fields":{"langid":["english"],"author":["Whitmore, Andrew","Agarwal, Anurag","Da Xu, Li"],"date":["2015-04"],"doi":["10.1007/s10796-014-9489-2"],"issn":["1387-3326, 1572-9419"],"journaltitle":["Inf. Syst. Front."],"number":["2"],"pages":["261–274"],"title":["The Internet of Things—A survey of topics and trends"],"volume":["17"]},"creators":{"author":[{"lastName":"Whitmore","firstName":"Andrew"},{"lastName":"Agarwal","firstName":"Anurag"},{"lastName":"Da Xu","firstName":"Li"}]},"sentenceCased":true},{"key":"whittleIndustrialAdoptionModeldriven2013","type":"inproceedings","fields":{"author":["Whittle, Jon","Hutchinson, John","Rouncefield, Mark","family=Burden, given=H\\a, prefix=akan, useprefix=false","Heldal, Rogardt"],"booktitle":["Int. Conf. Model Driven Eng. Lang. Syst."],"date":["2013"],"note":["TL;DR \n\nA taxonomy of tool-related considerations is presented, based on industry data, which can be used to reflect on the tooling landscape as well as inform future research on MDE tools."],"pages":["1–17"],"publisher":["Springer"],"shorttitle":["Industrial adoption of model-driven engineering"],"title":["Industrial adoption of model-driven engineering: Are the tools really the problem?"],"url":["http://link.springer.com/chapter/10.1007/978-3-642-41533-3_1"],"urldate":["2017-02-22"]},"creators":{"author":[{"lastName":"Whittle","firstName":"Jon"},{"lastName":"Hutchinson","firstName":"John"},{"lastName":"Rouncefield","firstName":"Mark"},{"lastName":"Burden","firstName":"H\\a","prefix":"akan","useprefix":false},{"lastName":"Heldal","firstName":"Rogardt"}]},"sentenceCased":true},{"key":"Wilcoxon1992","type":"incollection","fields":{"abstract":["The comparison of two treatments generally falls into one of the following two categories: (a) we may have a number of replications for each of the two treatments, which are unpaired, or (b) we may have a number of paired comparisons leading to a series of differences, some of which may be positive and some negative. The appropriate methods for testing the significance of the differences of the means in these two cases are described in most of the textbooks on statistical methods."],"author":["Wilcoxon, Frank"],"booktitle":["Breakthroughs in statistics: Methodology and distribution"],"date":["1992"],"doi":["10.1007/978-1-4612-4380-9₁6"],"editor":["Kotz, Samuel","Johnson, Norman L."],"isbn":["978-1-4612-4380-9"],"location":["New York, NY"],"pages":["196–202"],"publisher":["Springer New York"],"title":["Individual comparisons by ranking methods"]},"creators":{"author":[{"lastName":"Wilcoxon","firstName":"Frank"}],"editor":[{"lastName":"Kotz","firstName":"Samuel"},{"lastName":"Johnson","firstName":"Norman L."}]},"sentenceCased":true},{"key":"WileyAutonomousSystem","type":"online","fields":{"title":["Wiley: The Autonomous System: A Foundational Synthesis of the Sciences of the Mind - Szabolcs Michael de Gyurky, Mark A. Tarbell"],"url":["http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1118294246,subjectCd-EE79.html"],"urldate":["2016-08-22"]},"creators":{}},{"key":"Williams2020","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Des. Eng. Tech. Conf."],"affiliation":["Pennsylvania State University, University Park, PA, United States"],"art_number":["V11AT11A006"],"author":["Williams, G.","Meisel, N.A.","Simpson, T.W.","McComb, C."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1115/DETC2020-22518"],"isbn":["978-0-7918-8400-3"],"note":["cited By 0 \n\nTL;DR \n\nThe results suggest that metamodels predicting the convolutional neural network coefficient of determination, as opposed to computational effort, were most accurate and the size of a design repository, the average complexity of its constituent designs, and the average and spread of design spatial diversity were the best predictors of convolutionic neural network accuracy."],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the ASME Design Engineering Technical Conference"],"source":["Scopus"],"title":["Deriving metamodels to relate machine learning quality to design repository characteristics in the context of additive manufacturing"],"volume":["11A-2020"]},"creators":{"author":[{"lastName":"Williams","firstName":"G."},{"lastName":"Meisel","firstName":"N.A."},{"lastName":"Simpson","firstName":"T.W."},{"lastName":"McComb","firstName":"C."}]},"sentenceCased":true},{"key":"williamsEngineeringSecurityVulnerability2018","type":"article","fields":{"abstract":["Around the turn of the 21st century, practices began to emerge to guide teams toward engineering software to stop attackers and users from utilizing unintended functionality by violating the system designer’s assumptions to cause a security breach. Yet, breaches are reported daily in the news in all domains—from the casual to the critical. The goal of this article is to help software engineers, software engineering educators, and security researchers understand opportunities for education and research through an analysis of current software security practices. The analysis is conducted on data on the use of a subset of 113 software security practices by 109 firms over 42 months, as reported in the Building Security In Maturity Model (BSIMM) Version 8 report. This article is part of a theme issue on software engineering’s 50th anniversary."],"author":["Williams, L.","McGraw, G.","Migues, S."],"date":["2018-09"],"doi":["10.1109/MS.2018.290110854"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"keywords":["software engineering"],"note":["TL;DR \n\nThe goal of this article is to help software engineers, software engineering educators, and security researchers understand opportunities for education and research through an analysis of current software security practices."],"number":["5"],"pages":["76–80"],"title":["Engineering Security Vulnerability Prevention, Detection, and Response"],"volume":["35"]},"creators":{"author":[{"lastName":"Williams","firstName":"L."},{"lastName":"McGraw","firstName":"G."},{"lastName":"Migues","firstName":"S."}]}},{"key":"williamsModelBasedAutonomousSystems1996","type":"inproceedings","fields":{"author":["Williams, Brian C."],"booktitle":["AIPS"],"date":["1996"],"note":["TL;DR \n\nSelf modeling, self configuration, deliberated reactions and compositional, model-based programming are the four key elements of a model- based autonomous systems architecture that is taking us into the New Millenium."],"pages":["275–282"],"title":["Model-Based Autonomous Systems in the New Millenium."],"url":["http://www.aaai.org/Papers/AIPS/1996/AIPS96-035.pdf"],"urldate":["2016-08-21"]},"creators":{"author":[{"lastName":"Williams","firstName":"Brian C."}]}},{"key":"Wills06googlespagerank","type":"article","fields":{"author":["Wills, Rebecca S."],"date":["2006"],"journaltitle":["Math. Intelligencer"],"pages":["6–10"],"title":["Google's PageRank: The math behind the search engine"]},"creators":{"author":[{"lastName":"Wills","firstName":"Rebecca S."}]},"sentenceCased":true},{"key":"WimmerB13","type":"inproceedings","fields":{"langid":["english"],"author":["Wimmer, Manuel","Burgueño, Loli"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"booktitle":["Model-Driven Eng. Lang. Syst. - 16th Int. Conf. MODELS 2013 Miami FL USA Sept. 29 - Oct. 4 2013 Proc."],"date":["2013"],"doi":["10.1007/978-3-642-41533-3\\_13"],"editor":["Moreira, Ana","Schätz, Bernhard","Gray, Jeff","Vallecillo, Antonio","Clarke, Peter J."],"keywords":["/unread","⛔ No INSPIRE recid found"],"note":["TL;DR \n\nTracts, a M2M transformation testing approach, is extended, to represent text within a generic metamodel, and applied to evaluate code generation capabilities of several existing UML tools."],"pages":["203–219"],"publisher":["Springer"],"series":["Lecture notes in computer science"],"timestamp":["Mon, 21 Jun 2021 12:26:18 +0200"],"title":["Testing M2T/T2M transformations"],"volume":["8107"]},"creators":{"author":[{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Burgueño","firstName":"Loli"}],"editor":[{"lastName":"Moreira","firstName":"Ana"},{"lastName":"Schätz","firstName":"Bernhard"},{"lastName":"Gray","firstName":"Jeff"},{"lastName":"Vallecillo","firstName":"Antonio"},{"lastName":"Clarke","firstName":"Peter J."}]},"sentenceCased":true},{"key":"wimmerCatalogueRefactoringsModeltoModel2012","type":"article","fields":{"author":["Wimmer, Manuel","Martínez, Salvador","Jouault, Frédéric","Cabot, Jordi"],"date":["2012"],"doi":["10.5381/jot.2012.11.2.a2"],"journaltitle":["J. Object Technol."],"note":["TL;DR \n\nA dedicated catalogue of refactorings for improving the quality of model transformations in model-to-model (M2M) transfor- mations and applicable also to other M2M transformation languages."],"number":["2"],"pages":["2:1"],"title":["A Catalogue of Refactorings for Model-to-Model Transformations."],"volume":["11"]},"creators":{"author":[{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Martínez","firstName":"Salvador"},{"lastName":"Jouault","firstName":"Frédéric"},{"lastName":"Cabot","firstName":"Jordi"}]}},{"key":"wimmerHowWebCan2008","type":"article","fields":{"author":["Wimmer, Manuel","Schauerhuber, Andrea","Michael, Strommer","Jürgen, Flandorfer","Gerti, Kappel"],"date":["2008"],"journaltitle":["Workshop Domänspezifische Modellier."],"title":["How Web 2.0 can leverage Model Engineering in Practice"]},"creators":{"author":[{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Schauerhuber","firstName":"Andrea"},{"lastName":"Michael","firstName":"Strommer"},{"lastName":"Jürgen","firstName":"Flandorfer"},{"lastName":"Gerti","firstName":"Kappel"}]},"sentenceCased":true},{"key":"wimmerPlugPlayModel2010","type":"inproceedings","fields":{"author":["Wimmer, Manuel","Retschitzegger, W.","Kappel, G.","Schoenboeck, J.","Kusel, A.","Schwinger, Wieland"],"booktitle":["Proc. 10th Workshop Domain-Specif. Model."],"date":["2010"],"pages":["7"],"publisher":["ACM"],"shorttitle":["Plug & play model transformations"],"title":["Plug & play model transformations: A DSL for resolving structural metamodel heterogeneities"],"url":["http://dl.acm.org/citation.cfm?id=2060348"],"urldate":["2015-06-24"]},"creators":{"author":[{"lastName":"Wimmer","firstName":"Manuel"},{"lastName":"Retschitzegger","firstName":"W."},{"lastName":"Kappel","firstName":"G."},{"lastName":"Schoenboeck","firstName":"J."},{"lastName":"Kusel","firstName":"A."},{"lastName":"Schwinger","firstName":"Wieland"}]},"sentenceCased":true},{"key":"wimmerReusingModelTransformations2011","type":"article","fields":{"author":["Wimmer, Manuel"],"date":["2011"],"title":["Reusing Model Transformations across Heterogeneous Metamodels"]},"creators":{"author":[{"lastName":"Wimmer","firstName":"Manuel"}]}},{"key":"winterMonitoringawareIDEs2019","type":"inproceedings","fields":{"langid":["english"],"author":["Winter, Jos","Aniche, Maurício","Cito, Jürgen","family=Deursen, given=Arie, prefix=van, useprefix=false"],"booktitle":["Proc. 2019 27th ACM Jt. Meet. Eur. Softw. Eng. Conf. Symp. Found. Softw. Eng."],"date":["2019-08-12"],"doi":["10.1145/3338906.3338926"],"eventtitle":["ESEC/FSE '19: 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering"],"ids":["winterMonitoringawareIDEs2019a"],"isbn":["978-1-4503-5572-8"],"keywords":["devops","IDE","Integrated Development Environment","runtime monitoring","software engineering","systems monitoring"],"location":["Tallinn Estonia"],"note":["<b>Contents</b> \n\n<ul> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/2\">Abstract</a> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/2\">1 Introduction</a> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/3\">2 Background</a> <ul> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/3\">2.1 Related Work</a> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/4\">2.2 Monitoring and DevOps</a> </ul> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/5\">3 Monitoring-Aware IDEs</a> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/5\">4 Monitoring-aware IDE prototype</a> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/6\">5 Field Experiment</a> <ul> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/6\">5.1 Methodology</a> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/7\">5.2 Participants</a> </ul> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/7\">6 Results</a> <ul> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/7\">6.1 RQ1: How do developers interact with a Monitoring-Aware IDE?</a> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/8\">6.2 RQ2: What impact does a Monitoring-Aware IDE bring to software development teams?</a> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/9\">6.3 RQ3: What are the developers' perceptions about the usefulness of a Monitoring-Aware IDE to support their monitoring practices?</a> </ul> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/10\">7 Discussion</a> <ul> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/10\">7.1 Building Monitoring-Aware IDEs</a> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/11\">7.2 Threats to Validity</a> </ul> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/11\">8 Conclusions</a> <li><a href=\"zotero://open-pdf/0_IL3NR2SD/12\">References</a> </ul> \n\nTL;DR \n\nThis paper implemented a prototype of a Monitoring-Aware IDE, connected to the monitoring systems of Adyen, a large-scale payment company that performs intense monitoring in their software systems, and concluded that monitoring-aware IDEs can play an essential role in improving how developers perform monitoring."],"pages":["420–431"],"publisher":["ACM"],"title":["Monitoring-aware IDEs"]},"creators":{"author":[{"lastName":"Winter","firstName":"Jos"},{"lastName":"Aniche","firstName":"Maurício"},{"lastName":"Cito","firstName":"Jürgen"},{"lastName":"Deursen","firstName":"Arie","prefix":"van","useprefix":false}]},"sentenceCased":true},{"key":"wintersSoftwareEngineeringGoogle","type":"article","fields":{"langid":["english"],"author":["Winters, Titus","Manschreck, Tom","Wright, Hyrum"],"note":["TL;DR \n\nThe authors catalog and describe Google’s key software engineering practices, which include the server-side software behind speech recognition and voice actions, and speech synthesis."],"pages":["602"],"title":["Software Engineering at Google"]},"creators":{"author":[{"lastName":"Winters","firstName":"Titus"},{"lastName":"Manschreck","firstName":"Tom"},{"lastName":"Wright","firstName":"Hyrum"}]}},{"key":"Wollstadt2022","type":"article","fields":{"langid":["english"],"abbrev_source_title":["IEEE Trans Evol Comput"],"affiliation":["Honda Research Institute Europe, Offenbach/Main, Germany. (e-mail: patricia.wollstadt@honda-ri.de); Honda Research Institute Europe, Offenbach/Main, Germany.; Simulation Innovation &#x0026; Modeling Center, The Ohio State University Columbus, Ohio, USA.; Digital Design &#x0026; Manufacturing Lab, The Ohio State University Columbus, Ohio, USA.; Honda Development &#x0026; Manufacturing of America, Raymond, Ohio, USA."],"author":["Wollstadt, P.","Bujny, M.","Ramnath, S.","Shah, J.J.","Detwiler, D.","Menzel, S."],"coden":["ITEVF"],"date":["2022"],"document_type":["Article"],"doi":["10.1109/TEVC.2022.3147013"],"issn":["1089778X"],"journaltitle":["IEEE Trans. Evol. Comput."],"note":["cited By 0 \n\nTL;DR \n\nThe OSU-Honda Automobile Hood Dataset (CarHoods10k), an industry-grade 3-D vehicle hood data set of over 10 000 shapes along with mechanical performance data that were validated against real-world hood designs by industry experts, is introduced."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["CarHoods10k: An industry-grade data set for representation learning and design optimization in engineering applications"]},"creators":{"author":[{"lastName":"Wollstadt","firstName":"P."},{"lastName":"Bujny","firstName":"M."},{"lastName":"Ramnath","firstName":"S."},{"lastName":"Shah","firstName":"J.J."},{"lastName":"Detwiler","firstName":"D."},{"lastName":"Menzel","firstName":"S."}]},"sentenceCased":true},{"key":"wongPerformanceEvaluationClassification2015","type":"article","fields":{"address":["New York"],"author":["Wong, Tzu-Tsung"],"date":["2015"],"issn":["0031-3203"],"journaltitle":["Pattern Recognit."],"nodoi":["10.1016/j.patcog.2015.03.009"],"number":["9"],"numpages":["8"],"pages":["2839–2846"],"publisher":["Elsevier"],"title":["Performance evaluation of classification algorithms by K-fold and leave-one-out cross validation"],"volume":["48"]},"creators":{"author":[{"lastName":"Wong","firstName":"Tzu-Tsung"}]},"sentenceCased":true},{"key":"Worsey2021265","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - IEEE 5G World Forum, 5GWF"],"affiliation":["University of Bristol, Department of Electrical And Electronic Engineering, Bristol, United Kingdom"],"author":["Worsey, J.","Hindmarch, I.","Armour, S.","Bull, D."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/5GWF52925.2021.00053"],"isbn":["978-1-66544-308-1"],"note":["cited By 0"],"pages":["265–268"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2021 IEEE 4th 5G World Forum, 5GWF 2021"],"source":["Scopus"],"title":["Observations from using a portable LIDAR scanner to capture RF propagation modelling environments"]},"creators":{"author":[{"lastName":"Worsey","firstName":"J."},{"lastName":"Hindmarch","firstName":"I."},{"lastName":"Armour","firstName":"S."},{"lastName":"Bull","firstName":"D."}]},"sentenceCased":true},{"key":"wortmannModelingLanguagesIndustry2019","type":"article","fields":{"langid":["english"],"abstract":["Industry 4.0 integrates cyber-physical systems with the Internet of Things to optimize the complete value-added chain. Successfully applying Industry 4.0 requires the cooperation of various stakeholders from different domains. Domain-specific modeling languages promise to facilitate their involvement through leveraging (domain-specific) models to primary development artifacts. We aim to assess the use of modeling in Industry 4.0 through the lens of modeling languages in a broad sense. Based on an extensive literature review, we updated our systematic mapping study on modeling languages and modeling techniques used in Industry 4.0 (Wortmann et al., Conference on model-driven engineering languages and systems (MODELS’17), IEEE, pp 281–291, 2017) to include publications until February 2018. Overall, the updated study considers 3344 candidate publications that were systematically investigated until 408 relevant publications were identified. Based on these, we developed an updated map of the research landscape on modeling languages and techniques for Industry 4.0. Research on modeling languages in Industry 4.0 focuses on contributing methods to solve the challenges of digital representation and integration. To this end, languages from systems engineering and knowledge representation are applied most often but rarely combined. There also is a gap between the communities researching and applying modeling languages for Industry 4.0 that originates from different perspectives on modeling and related standards. From the vantage point of modeling, Industry 4.0 is the combination of systems engineering, with cyber-physical systems, and knowledge engineering. Research currently is splintered along topics and communities and accelerating progress demands for multi-disciplinary, integrated research efforts."],"author":["Wortmann, Andreas","Barais, Olivier","Combemale, Benoit","Wimmer, Manuel"],"date":["2019-09-20"],"doi":["10.1007/s10270-019-00757-6"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw Syst Model"],"shorttitle":["Modeling languages in Industry 4.0"],"title":["Modeling languages in Industry 4.0: An extended systematic mapping study"]},"creators":{"author":[{"lastName":"Wortmann","firstName":"Andreas"},{"lastName":"Barais","firstName":"Olivier"},{"lastName":"Combemale","firstName":"Benoit"},{"lastName":"Wimmer","firstName":"Manuel"}]},"sentenceCased":true},{"key":"wu_effective_2016","type":"article","fields":{"langid":["english"],"abstract":["Objective. This study proposes an Android malware detecting system that provides highly accurate classification and efficient sensitive data transmission analysis. Method. The study adopts a machine learning approach that leverages the use of dataflow application program interfaces (APIs) as classification features to detect Android malware. We conduct a thorough analysis to extract dataflow-related API-level features and improve the k-nearest neighbour classification model. The dataflow-related API list is further optimized through machine learning, which enables us to improve considerably the efficiency of sensitive data transmission analysis, whereas analytical accuracy is approximated to that of the experiment using a full dataflow-related API list. Results. The proposed scheme is evaluated using 1160 benign and 1050 malicious samples. Results show that the system can achieve an accuracy rate of as high as 97.66% in detecting unknown Android malware. Our experiment of static dataflow analysis shows that more than 85% of sensitive data transmission paths can be determined using the refined API subset, whereas time of analysis decreases by nearly 40%. Conclusion. The usage of dataflow-related APIs is a valid feature for identifying Android malware. The proposed scheme provides an efficient approach to detecting Android malware and investigating privacy violations in malicious apps."],"author":["Wu, Songyang","Wang, Pan","Li, Xun","Zhang, Yong"],"date":["2016-07"],"doi":["10.1016/j.infsof.2016.03.004"],"issn":["09505849"],"journaltitle":["Inf. Softw. Technol."],"pages":["17–25"],"title":["Effective detection of android malware based on the usage of data flow APIs and machine learning"],"volume":["75"]},"creators":{"author":[{"lastName":"Wu","firstName":"Songyang"},{"lastName":"Wang","firstName":"Pan"},{"lastName":"Li","firstName":"Xun"},{"lastName":"Zhang","firstName":"Yong"}]},"sentenceCased":true},{"key":"Wu201911899","type":"inproceedings","fields":{"abstract":["Domain adaptation addresses the common situation in which the target distribution generating our test data differs from the source distribution generating our training data. While absent assumptions, domain adaptation is impossible, strict conditions, e.g. covariate or label shift, enable principled algorithms. Recently-proposed domain-adversarial approaches consist of aligning source and target encodings, an approach often motivated as minimizing two (of three) terms in a theoretical bound on target error. Unfortunately, this minimization can cause arbitrary increases in the third term, a problem guaranteed to arise under shifting label distributions. We propose asymmetrically-relaxed distribution alignment, a new approach that overcomes some limitations of standard domain-adversarial algorithms. Moreover, we characterize precise assumptions under which our algorithm is theoretically principled and demonstrate empirical benefits on both synthetic and real datasets. Copyright © 2019 ASME"],"author":["Wu, Y.","Winston, E.","Kaushik, D.","Lipton, Z.C."],"date":["2019"],"document_type":["Conference Paper"],"isbn":["978-1-5108-8698-8"],"keywords":["Artificial intelligence","Domain adaptation","Label distribution","Machine learning","New approaches","Real data sets","Software engineering","Source distribution","Standard domains","Theoretical bounds","Training data"],"note":["cited By 24 \n\nTL;DR \n\nAsymmetrically-relaxed distribution alignment is proposed, a new approach that overcomes some limitations of standard domain-adversarial algorithms and characterize precise assumptions under which the algorithm is theoretically principled and demonstrate empirical benefits on both synthetic and real datasets."],"pages":["11899–11914"],"publisher":["International Machine Learning Society (IMLS)"],"series":["36th International Conference on Machine Learning, ICML 2019"],"source":["Scopus"],"title":["Domain adaptation with asymmetrically-relaxed distribution alignment"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078282922&partnerID=40&md5=f9cb636540ab2ed0339cb1978717dd35"],"volume":["2019-June"]},"creators":{"author":[{"lastName":"Wu","firstName":"Y."},{"lastName":"Winston","firstName":"E."},{"lastName":"Kaushik","firstName":"D."},{"lastName":"Lipton","firstName":"Z.C."}]},"sentenceCased":true},{"key":"Wu20202230","type":"article","fields":{"langid":["english"],"abbrev_source_title":["IEEE ASME Trans Mechatron"],"affiliation":["School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China; School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China; College of Electrical Engineering, Henan University of Technology, Zhengzhou, 450001, China"],"art_number":["9141518"],"author":["Wu, J.","Guo, P.","Cheng, Y.","Zhu, H.","Wang, X.-B.","Shao, X."],"coden":["IATEF"],"correspondence_address1":["Wang, X.-B.; College of Electrical Engineering, China; email: xb<sub>w</sub>ang@live.com"],"date":["2020"],"document_type":["Article"],"doi":["10.1109/TMECH.2020.3009449"],"issn":["10834435"],"journaltitle":["IEEEASME Trans. Mechatron."],"note":["cited By 22"],"number":["5"],"pages":["2230–2240"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Ensemble generalized multiclass support-vector-machine-based health evaluation of complex degradation systems"],"volume":["25"]},"creators":{"author":[{"lastName":"Wu","firstName":"J."},{"lastName":"Guo","firstName":"P."},{"lastName":"Cheng","firstName":"Y."},{"lastName":"Zhu","firstName":"H."},{"lastName":"Wang","firstName":"X.-B."},{"lastName":"Shao","firstName":"X."}]},"sentenceCased":true},{"key":"Wu2021","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Eng Appl Artif Intell"],"affiliation":["Product Design and Optimization Laboratory, Mechatronic System Engineering Department, Simon Fraser University, Surrey, BCV3T 0A3, Canada"],"art_number":["104089"],"author":["Wu, D.","Wang, G.G."],"coden":["EAAIE"],"correspondence_address1":["Wu, D.; Product Design and Optimization Laboratory, Surrey, BC, Canada; email: dwa88@sfu.ca"],"date":["2021"],"document_type":["Article"],"doi":["10.1016/j.engappai.2020.104089"],"issn":["09521976"],"journaltitle":["Eng. Appl. Artif. Intell."],"note":["cited By 4"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Causal artificial neural network and its applications in engineering design"],"volume":["97"]},"creators":{"author":[{"lastName":"Wu","firstName":"D."},{"lastName":"Wang","firstName":"G.G."}]},"sentenceCased":true},{"key":"Wu20211915","type":"article","fields":{"abstract":["While massive multiple-input multiple-output (MIMO) has achieved tremendous success in both theory and practice, it faces a crisis of sharp performance degradation in moderate or high-mobility scenarios (e.g., 30 km/h), due to the breach of uplink-downlink channel duality. Such a 'curse of mobility' has spurred the research on channel prediction in high-mobility scenarios. Instead of predicting channel response matrix in the space-frequency domain, we investigate it in the angle-delay domain by utilizing the high angle-delay resolution of wideband massive MIMO systems. Specifically, we study the general angle-delay domain channel characterization and obtain that: 1) the correlations between the angle-delay domain channel response matrix (ADCRM) elements are decoupled significantly; 2) when the number of antennas and bandwidth are limited, the decoupling is insufficient and residual correlations between the neighboring ADCRM elements exist. Then focusing on the ADCRM, we propose two channel prediction methods: a spatio-temporal autoregressive (ST-AR) model-driven unsupervised-learning method and a deep learning (DL) based data-driven supervised-learning method. While the model-driven method provides a principled way for channel prediction, the data-driven method is generalizable to various channel scenarios. In particular, ST-AR exploits the residual spatio-temporal correlations of the channel element with its most neighboring elements, and DL realizes element-wise angle-delay domain channel prediction utilizing a complex-valued neural network (CVNN). Simulation results under the 3GPP non-line-of-sight (NLOS) scenarios indicate that, compared to the state-of-the-art Prony-based angular-delay domain (PAD) prediction method, both the proposed ST-AR and the CVNN-based channel prediction methods can enhance the channel prediction accuracy. © 1983-2012 IEEE."],"art_number":["9427230"],"author":["Wu, C.","Yi, X.","Zhu, Y.","Wang, W.","You, L.","Gao, X."],"coden":["ISACE"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/JSAC.2021.3078503"],"issn":["07338716"],"journaltitle":["IEEE J. Sel. Areas Commun."],"note":["cited By 2 \n\nTL;DR \n\nSimulation results under the 3GPP non-line- of-sight (NLOS) scenarios indicate that, compared to the state-of-the-art Prony-based angular-delay domain (PAD) prediction method, both the proposed ST-AR and the CVNN-based channel prediction methods can enhance the channel prediction accuracy."],"number":["7"],"pages":["1915–1930"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Channel prediction in high-mobility massive MIMO: From spatio-temporal autoregression to deep learning"],"volume":["39"]},"creators":{"author":[{"lastName":"Wu","firstName":"C."},{"lastName":"Yi","firstName":"X."},{"lastName":"Zhu","firstName":"Y."},{"lastName":"Wang","firstName":"W."},{"lastName":"You","firstName":"L."},{"lastName":"Gao","firstName":"X."}]},"sentenceCased":true},{"key":"wuAutoGenEnablingNextGen2023","type":"online","fields":{"abstract":["AutoGen is an open-source framework that allows developers to build LLM applications via multiple agents that can converse with each other to accomplish tasks. AutoGen agents are customizable, conversable, and can operate in various modes that employ combinations of LLMs, human inputs, and tools. Using AutoGen, developers can also flexibly define agent interaction behaviors. Both natural language and computer code can be used to program flexible conversation patterns for different applications. AutoGen serves as a generic infrastructure to build diverse applications of various complexities and LLM capacities. Empirical studies demonstrate the effectiveness of the framework in many example applications, with domains ranging from mathematics, coding, question answering, operations research, online decision-making, entertainment, etc."],"author":["Wu, Qingyun","Bansal, Gagan","Zhang, Jieyu","Wu, Yiran","Li, Beibin","Zhu, Erkang","Jiang, Li","Zhang, Xiaoyun","Zhang, Shaokun","Liu, Jiale","Awadallah, Ahmed Hassan","White, Ryen W.","Burger, Doug","Wang, Chi"],"date":["2023-10-03"],"eprint":["2308.08155"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Computation and Language"],"note":["Comment: 43 pages (10 pages for the main text, 3 pages for references, and 30 pages for appendices)"],"pubstate":["preprint"],"shorttitle":["AutoGen"],"title":["AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation"],"url":["http://arxiv.org/abs/2308.08155"],"urldate":["2024-01-26"]},"creators":{"author":[{"lastName":"Wu","firstName":"Qingyun"},{"lastName":"Bansal","firstName":"Gagan"},{"lastName":"Zhang","firstName":"Jieyu"},{"lastName":"Wu","firstName":"Yiran"},{"lastName":"Li","firstName":"Beibin"},{"lastName":"Zhu","firstName":"Erkang"},{"lastName":"Jiang","firstName":"Li"},{"lastName":"Zhang","firstName":"Xiaoyun"},{"lastName":"Zhang","firstName":"Shaokun"},{"lastName":"Liu","firstName":"Jiale"},{"lastName":"Awadallah","firstName":"Ahmed Hassan"},{"lastName":"White","firstName":"Ryen W."},{"lastName":"Burger","firstName":"Doug"},{"lastName":"Wang","firstName":"Chi"}]}},{"key":"wuGraphNeuralNetworks2021","type":"article","fields":{"abstract":["Owing to the superiority of GNN in learning on graph data and its efficacy in capturing collaborative signals and sequential patterns, utilizing GNN techniques in recommender systems has gain increasing interests in academia and industry. In this survey, we provide a comprehensive review of the most recent works on GNN-based recommender systems. We proposed a classification scheme for organizing existing works. For each category, we briefly clarify the main issues, and detail the corresponding strategies adopted by the representative models. We also discuss the advantages and limitations of the existing strategies. Furthermore, we suggest several promising directions for future researches. We hope this survey can provide readers with a general understanding of the recent progress in this field, and shed some light on future developments."],"author":["Wu, Shiwen","Sun, Fei","Zhang, Wentao","Cui, Bin"],"date":["2021-04-19"],"eprint":["2011.02260"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv201102260 Cs"],"keywords":["Computer Science - Information Retrieval","Computer Science - Machine Learning"],"note":["TL;DR \n\nThis article provides a taxonomy of GNN-based recommendation models according to the types of information used and recommendation tasks and systematically analyze the challenges of applying GNN on different types of data."],"shorttitle":["Graph Neural Networks in Recommender Systems"],"title":["Graph Neural Networks in Recommender Systems: A Survey"],"url":["http://arxiv.org/abs/2011.02260"],"urldate":["2021-10-19"]},"creators":{"author":[{"lastName":"Wu","firstName":"Shiwen"},{"lastName":"Sun","firstName":"Fei"},{"lastName":"Zhang","firstName":"Wentao"},{"lastName":"Cui","firstName":"Bin"}]}},{"key":"wuLowComplexityModelDriven2021","type":"inproceedings","fields":{"abstract":["A novel Neural Offset Min-Sum(NOMS) Belief Propagation(BP) decoding algorithm based on model-driven is proposed which applied to LDPC decoding. NOMS is improved multiplication in Neural Normalized Min-Sum(NNMS) into addition operation to reduce the complexity of calculation., a better Bit Error Rate (BER) performance is simultaneously achieved in the same condition. Secondly, considering that there are still many multiplication operations in NOMS, we propose a novel Shared Offset Min-Sum(SNOMS) to reduce the number of weights in the network by sharing parameters. Finally, codebook-based quantization is used to further reduce the memory consumption. Simulation experimental results show that the proposed method has a better BER performance, and the decoding accuracy of the decoder is 0.65dB higher than that of the NNMS after 5 iterations. In addition, SNOMS decoding method achieves almost the same decoding performance comparable to that of NOMS, but requires less complex calculation. Proposed quantization of code-book method reduces memory requirement significantly with slight performance loss. © 2021 IEEE."],"author":["Wu, Q.","Tang, S.-K.","Liang, Y.","Lam, C.T.","Ma, Y."],"booktitle":["2021 IEEE 6th Int. Conf. Comput. Commun. Syst. ICCCS 2021"],"date":["2021"],"doi":["10.1109/ICCCS52626.2021.9449266"],"isbn":["978-0-7381-2604-3"],"keywords":["Belief propagation decoding algorithms","Bit error rate","Bit error rate (BER) performance","Complex networks","Complexity modeling","Decoding performance","Deep learning","Iterative decoding","Memory consumption","Memory requirements","Multiplication operations","Performance loss"],"note":["cited By 0 \n\nTL;DR \n\nA novel Neural Offset Min-Sum (NOMS) Belief Propagation (BP) decoding algorithm based on model-driven is proposed which applied to LDPC decoding, and proposed quantization of codebook-based quantization is used to further reduce the memory consumption."],"pages":["558–563"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["A Low Complexity Model-Driven Deep Learning LDPC Decoding Algorithm"]},"creators":{"author":[{"lastName":"Wu","firstName":"Q."},{"lastName":"Tang","firstName":"S.-K."},{"lastName":"Liang","firstName":"Y."},{"lastName":"Lam","firstName":"C.T."},{"lastName":"Ma","firstName":"Y."}]}},{"key":"Xanthopoulos201869","type":"article","fields":{"langid":["english"],"abbrev_source_title":["J Intell Manuf"],"affiliation":["Department of Production and Management Engineering, Democritus University of Thrace, V. Sofias 12, Xanthi, 67100, Greece"],"author":["Xanthopoulos, A.S.","Koulouriotis, D.E."],"coden":["JIMNE"],"correspondence_address1":["Xanthopoulos, A.S.; Department of Production and Management Engineering, V. Sofias 12, Greece; email: axanthop@pme.duth.gr"],"date":["2018"],"document_type":["Article"],"doi":["10.1007/s10845-015-1090-0"],"issn":["09565515"],"journaltitle":["J. Intell. Manuf."],"note":["cited By 4 \n\nTL;DR \n\nThe results of this article can be used as a component for prediction systems of dispatching rule output, as a guideline for building new dispatching heuristic with entirely different characteristics than existing ones, and to significantly decrease the length of what-if simulation studies."],"number":["1"],"pages":["69–91"],"publisher":["Springer New York LLC"],"source":["Scopus"],"title":["Cluster analysis and neural network-based metamodeling of priority rules for dynamic sequencing"],"volume":["29"]},"creators":{"author":[{"lastName":"Xanthopoulos","firstName":"A.S."},{"lastName":"Koulouriotis","firstName":"D.E."}]},"sentenceCased":true},{"key":"xhafaInternetThingsEngineering2018","type":"article","fields":{"langid":["english"],"author":["Xhafa, Fatos"],"date":["2018-09"],"doi":["10.1016/S2542-6605(18)30099-4"],"issn":["25426605"],"journaltitle":["Internet Things"],"pages":["iii"],"shorttitle":["Internet of Things"],"title":["Internet of Things: Engineering Cyber Physical Human Systems"],"volume":["1–2"]},"creators":{"author":[{"lastName":"Xhafa","firstName":"Fatos"}]}},{"key":"xia:tag:2013","type":"inproceedings","fields":{"author":["Xia, Xin","Lo, David","Wang, Xinyu","Zhou, Bo"],"booktitle":["Proc. 10th Work. Conf. Min. Softw. Repos."],"date":["2013"],"isbn":["978-1-4673-2936-1"],"location":["Piscataway, NJ, USA"],"note":["TL;DR \n\nThis paper proposes TagCombine, an automatic tag recommendation method which analyzes objects in software information sites and recommends tags after analyzing the terms in the objects."],"pages":["287–296"],"publisher":["IEEE Press"],"series":["MSR '13"],"title":["Tag recommendation in software information sites"],"url":["http://dl.acm.org/citation.cfm?id=2487085.2487140"]},"creators":{"author":[{"lastName":"Xia","firstName":"Xin"},{"lastName":"Lo","firstName":"David"},{"lastName":"Wang","firstName":"Xinyu"},{"lastName":"Zhou","firstName":"Bo"}]},"sentenceCased":true},{"key":"xieSystematicMappingStudy2021","type":"article","fields":{"abstract":["The development of artificial intelligence (AI) has made various industries eager to explore the benefits of AI. There is an increasing amount of research surrounding AI, most of which is centred on the development of new AI algorithms and techniques. However, the advent of AI is bringing an increasing set of practical problems related to AI model lifecycle management that need to be investigated. We address this gap by conducting a systematic mapping study on the lifecycle of AI model. Through quantitative research, we provide an overview of the field, identify research opportunities, and provide suggestions for future research. Our study yields 405 publications published from 2005 to 2020, mapped in 5 different main research topics, and 31 sub-topics. We observe that only a minority of publications focus on data management and model production problems, and that more studies should address the AI lifecycle from a holistic perspective."],"author":["Xie, Yuanhao","Cruz, Luís","Heck, Petra","Rellermeyer, Jan S."],"date":["2021-03-11"],"eprint":["2103.10248"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv210310248 Cs"],"keywords":["68T01 (Primary)","Computer Science - Artificial Intelligence","Computer Science - Machine Learning","Computer Science - Software Engineering","D.2.9","I.2.5"],"note":["Comment: Accepted at WAIN21: 1st Workshop on AI Engineering - Software Engineering for AI \n\nTL;DR \n\nA systematic mapping study on the lifecycle of AI model management, observing that only a minority of publications focus on data management and model production problems, and that more studies should address the AI lifecycle from a holistic perspective."],"title":["Systematic Mapping Study on the Machine Learning Lifecycle"],"url":["http://arxiv.org/abs/2103.10248"],"urldate":["2021-03-23"]},"creators":{"author":[{"lastName":"Xie","firstName":"Yuanhao"},{"lastName":"Cruz","firstName":"Luís"},{"lastName":"Heck","firstName":"Petra"},{"lastName":"Rellermeyer","firstName":"Jan S."}]}},{"key":"xing_api-evolution_2007","type":"article","fields":{"abstract":["Applications built on reusable component frameworks are subject to two independent, and potentially conflicting, evolution processes. The application evolves in response to the specific requirements and desired qualities of the application's stakeholders. On the other hand, the evolution of the component framework is driven by the need to improve the framework functionality and quality while maintaining its generality. Thus, changes to the component framework frequently change its API on which its client applications rely and, as a result, these applications break. To date, there has been some work aimed at supporting the migration of client applications to newer versions of their underlying frameworks, but it usually requires that the framework developers do additional work for that purpose or that the application developers use the same tools as the framework developers. In this paper, we discuss our approach to tackle the API-evolution problem in the context of reuse-based software development, which automatically recognizes the API changes of the reused framework and proposes plausible replacements to the \"obsolete\" API based on working examples of the framework code base. This approach has been implemented in the Diff-CatchUp tool. We report on two case studies that we have conducted to evaluate the effectiveness of our approach with its Diff-CatchUp prototype."],"author":["Xing, Zhenchang","Stroulia, Eleni"],"date":["2007-12"],"doi":["10.1109/TSE.2007.70747"],"journaltitle":["IEEE Trans. Softw. Eng."],"keywords":["API-evolution support","application program interfaces","Application software","client application migration","component framework functionality","component framework maintenance","component framework quality","Costs","D.2.10.g Object-oriented design methods","D.2.2.eProgrammer workbench","D.2.3.aObject-oriented programming","D.2.3Coding Tools and Techniques","Diff-CatchUp tool","Documentation","object-oriented programming","Programming","Prototypes","reusable component framework evolution","reuse-based software development","Software engineering","software maintenance","software prototyping","Software prototyping","software quality","software reusability","software tools","Software tools"],"number":["12"],"pages":["818–836"],"title":["API-Evolution Support with Diff-CatchUp"],"volume":["33"]},"creators":{"author":[{"lastName":"Xing","firstName":"Zhenchang"},{"lastName":"Stroulia","firstName":"Eleni"}]}},{"key":"Xiong2022","type":"article","fields":{"abstract":["While Machine Learning (ML) technologies are widely adopted in many mission critical fields to support intelligent decision-making, concerns remain about system resilience against ML-specific security attacks and privacy breaches as well as the trust that users have in these systems. In this article, we present our recent systematic and comprehensive survey on the state-of-the-art ML robustness and trustworthiness from a security engineering perspective, focusing on the problems in system threat analysis, design and evaluation faced in developing practical machine learning applications, in terms of robustness and user trust. Accordingly, we organize the presentation of this survey intended to facilitate the convey of the body of knowledge from this angle. We then describe a metamodel we created that represents the body of knowledge in a standard and visualized way. We further illustrate how to leverage the metamodel to guide a systematic threat analysis and security design process which extends and scales up the classic process. Finally, we propose the future research directions motivated by our findings. Our work differs itself from the existing surveys by (i) exploring the fundamental principles and best practices to support robust and trustworthy ML system development, and (ii) studying the interplay of robustness and user trust in the context of ML systems. We expect this survey provides a big picture for machine learning security practitioners. © 2022"],"art_number":["103121"],"author":["Xiong, P.","Buffett, S.","Iqbal, S.","Lamontagne, P.","Mamun, M.","Molyneaux, H."],"date":["2022"],"document_type":["Article"],"doi":["10.1016/j.jisa.2022.103121"],"issn":["22142134"],"journaltitle":["J. Inf. Secur. Appl."],"keywords":["GOAL_ML-System-Development"],"note":["cited By 0"],"publisher":["Elsevier Ltd"],"source":["Scopus"],"title":["Towards a robust and trustworthy machine learning system development: An engineering perspective"],"volume":["65"]},"creators":{"author":[{"lastName":"Xiong","firstName":"P."},{"lastName":"Buffett","firstName":"S."},{"lastName":"Iqbal","firstName":"S."},{"lastName":"Lamontagne","firstName":"P."},{"lastName":"Mamun","firstName":"M."},{"lastName":"Molyneaux","firstName":"H."}]},"sentenceCased":true},{"key":"xiuExploratoryStudyMachine2021","type":"article","fields":{"author":["Xiu, Minke","Jiang, Zhen Ming Jack","Adams, Bram"],"date":["2021-01"],"doi":["10.1109/MS.2020.2975159"],"issn":["0740-7459, 1937-4194"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nThree stores that provide public access to pretrained machine learning models and infrastructure are examined and the information they provide is compared against two mobileapp stores and among themselves."],"number":["1"],"pages":["114–122"],"title":["An Exploratory Study of Machine Learning Model Stores"],"volume":["38"]},"creators":{"author":[{"lastName":"Xiu","firstName":"Minke"},{"lastName":"Jiang","firstName":"Zhen Ming Jack"},{"lastName":"Adams","firstName":"Bram"}]}},{"key":"xu_meditor_2019","type":"inproceedings","fields":{"abstract":["Developers build programs based on software libraries. When a library evolves, programmers need to migrate their client code from the library's old release(s) to new release(s). Due to the API backwards incompatibility issues, such code migration may require developers to replace API usage and apply extra edits (e.g., statement insertions or deletions) to ensure the syntactic or semantic correctness of migrated code. Existing tools extract API replacement rules without handling the additional edits necessary to fulfill a migration task. This paper presents our novel approach, Meditor, which extracts and applies the necessary edits together with API replacement changes. Meditor has two phases: inference and application of migration edits. For edit inference, Meditor mines open source repositories for migration-related (MR) commits, and conducts program dependency analysis on changed Java files to locate and cluster MR code changes. From these changes, Meditor further generalizes API migration edits by abstracting away unimportant details (e.g., concrete variable identifiers). For edit application, Meditor matches a given program with inferred edits to decide which edit is applicable, customizes each applicable edit, and produces a migrated version for developers to review. We applied Meditor to four popular libraries: Lucene, CraftBukkit, Android SDK, and Commons IO. By searching among 602,249 open source projects on GitHub, Meditor identified 1,368 unique migration edits. Among these edits, 885 edits were extracted from single updated statements, while the other 483 more complex edits were from multiple co-changed statements. We sampled 937 inferred edits for manual inspection and found all of them to be correct. Our evaluation shows that Meditor correctly applied code migrations in 218 out of 225 cases. This research will help developers automatically adapt client code to different library versions."],"author":["Xu, Shengzhe","Dong, Ziqi","Meng, Na"],"booktitle":["2019 IEEEACM 27th Int Conf Program Comprehension ICPC"],"date":["2019-05"],"doi":["10.1109/ICPC.2019.00052"],"keywords":["Android SDK","API backwards incompatibility issues","API migration edits","API replacement rules","API usage","application program interfaces","automatic program transformation","client code","cluster MR code changes","code migration","Commons IO","CraftBukkit","data mining","edit inference","Java","library","Lucene","Meditor","migrated code","migrated version","migration task","migration-related commits","open source repository mining","program dependency analysis","public domain software","software libraries"],"pages":["335–346"],"shorttitle":["Meditor"],"title":["Meditor: Inference and Application of API Migration Edits"]},"creators":{"author":[{"lastName":"Xu","firstName":"Shengzhe"},{"lastName":"Dong","firstName":"Ziqi"},{"lastName":"Meng","firstName":"Na"}]}},{"key":"Xu2013653","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Struct. Mutltidiscip. Opt."],"affiliation":["State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China; Key Laboratory of Manufacture and Test Techniques for Automobile Parts, Ministry of Education, Chongqing 400054, China; School of Aerospace, Mechanical and Mechatronic Engineering, University of Sydney, Sydney NSW 2006, Australia"],"author":["Xu, F.","Sun, G.","Li, G.","Li, Q."],"coden":["SMOTB"],"correspondence_address1":["Li, G.; State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, , Changsha 410082, China; email: gyli@hnu.edu.cn"],"date":["2013"],"document_type":["Article"],"doi":["10.1007/s00158-013-0916-7"],"issn":["1615147X"],"journaltitle":["Struct. Multidiscip. Optim."],"note":["cited By 59"],"number":["3"],"pages":["653–667"],"publisher":["Springer Verlag"],"source":["Scopus"],"title":["Crashworthiness design of multi-component tailor-welded blank (TWB) structures"],"volume":["48"]},"creators":{"author":[{"lastName":"Xu","firstName":"F."},{"lastName":"Sun","firstName":"G."},{"lastName":"Li","firstName":"G."},{"lastName":"Li","firstName":"Q."}]},"sentenceCased":true},{"key":"Xu2015","type":"article","fields":{"abstract":["Data analysis is used as a common method in modern science research, which is across communication science, computer science and biology science. Clustering, as the basic composition of data analysis, plays a significant role. On one hand, many tools for cluster analysis have been created, along with the information increase and subject intersection. On the other hand, each clustering algorithm has its own strengths and weaknesses, due to the complexity of information. In this review paper, we begin at the definition of clustering, take the basic elements involved in the clustering process, such as the distance or similarity measurement and evaluation indicators, into consideration, and analyze the clustering algorithms from two perspectives, the traditional ones and the modern ones. All the discussed clustering algorithms will be compared in detail and comprehensively shown in Appendix Table 22."],"author":["Xu, Dongkuan","Tian, Yingjie"],"date":["2015-06-01"],"doi":["10.1007/s40745-015-0040-1"],"issn":["2198-5812"],"journaltitle":["Ann. Data Sci."],"note":["TL;DR \n\nThis review paper begins at the definition of clustering, takes the basic elements involved in the clustering process, such as the distance or similarity measurement and evaluation indicators, into consideration, and analyzes the clustered algorithms from two perspectives, the traditional ones and the modern ones."],"number":["2"],"pages":["165–193"],"title":["A comprehensive survey of clustering algorithms"],"volume":["2"]},"creators":{"author":[{"lastName":"Xu","firstName":"Dongkuan"},{"lastName":"Tian","firstName":"Yingjie"}]},"sentenceCased":true},{"key":"Xu2016","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Des. Eng. Tech. Conf."],"affiliation":["Research and Advanced Engineering, Ford Motor Company, Dearborn, MI, United States"],"author":["Xu, H.","Chuang, C.-H.","Yang, R.-J."],"correspondence_address1":["Xu, H.; Research and Advanced Engineering, United States; email: hxu41@ford.com"],"date":["2016"],"document_type":["Conference Paper"],"doi":["10.1115/DETC2016-59176"],"isbn":["978-0-7918-5011-4"],"note":["cited By 7"],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the ASME Design Engineering Technical Conference"],"source":["Scopus"],"title":["Mixed-variable metamodeling methods for designing multimaterial structures"],"volume":["2B-2016"]},"creators":{"author":[{"lastName":"Xu","firstName":"H."},{"lastName":"Chuang","firstName":"C.-H."},{"lastName":"Yang","firstName":"R.-J."}]},"sentenceCased":true},{"key":"Xu2021160","type":"inproceedings","fields":{"abstract":["In recent years, machine learning has demonstrated impressive performance in many real-world tasks, especially in computer vision and natural language processing. However, to apply them in safety-critical systems one needs formal guarantees on the neural network outputs. The Reluplex tool is proposed to verify the safety of deep neural networks (DNNs), and in case the DNN fails to give a correct output, can generate adversarial examples. Since the tool can only handle DNNs, it is necessary to extend the tool to process image data. Therefore, in this paper, we propose the Conv-Reluplex framework, which is designed to verify the convolutional layer and pooling layer in convolutional neural networks(CNNs), and generate adversarial examples when classification is misguided. We conduct several experiments on MNIST to evaluate our approaches. The results show that the original CNN is improved using the adversarial examples generated by our tool, and the precision of classification can be increased significantly. © 2021 Knowledge Systems Institute Graduate School. All rights reserved."],"author":["Xu, J.","Li, Z.","Zhang, M.","Du, B."],"author_keywords":["Adversarial robustness; Reluplex algorithm; Verification framework"],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.18293/SEKE2021-085"],"isbn":["1-891706-52-7"],"issn":["23259000"],"keywords":["Convolution","Convolution neural network","Convolutional neural networks","Deep neural networks","Image data","Multilayer neural networks","NAtural language processing","Natural language processing systems","Real-world task","Safety critical systems","Safety engineering","Software engineering","Verification framework"],"note":["cited By 2"],"pages":["160–165"],"publisher":["Knowledge Systems Institute Graduate School"],"series":["Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE"],"source":["Scopus"],"title":["Conv-Reluplex: A verification framework for convolution neural networks"],"volume":["2021-July"]},"creators":{"author":[{"lastName":"Xu","firstName":"J."},{"lastName":"Li","firstName":"Z."},{"lastName":"Zhang","firstName":"M."},{"lastName":"Du","firstName":"B."}]},"sentenceCased":true},{"key":"xuREPERSPRecommendingPersonalized2017","type":"inproceedings","fields":{"author":["Xu, Wenyuan","Sun, Xiaobing","Hu, Jiajun","Li, Bin"],"date":["2017-09"],"doi":["10.1109/ICSME.2017.20"],"isbn":["978-1-5386-0992-7"],"pages":["648–652"],"publisher":["IEEE"],"shorttitle":["REPERSP"],"title":["REPERSP: Recommending Personalized Software Projects on GitHub"]},"creators":{"author":[{"lastName":"Xu","firstName":"Wenyuan"},{"lastName":"Sun","firstName":"Xiaobing"},{"lastName":"Hu","firstName":"Jiajun"},{"lastName":"Li","firstName":"Bin"}]}},{"key":"Yan2018343","type":"article","fields":{"langid":["english"],"abbrev_source_title":["CMES Comput. Model. Eng. Sci."],"affiliation":["Department of Materials Science and Engineering, Northwestern University, 2220 Campus Dr, Evanston, IL 60208, United States; Department of Mechanical Engineering, Northwestern University, 2145 Sheridan Rd, Evanston, IL 60208, United States; QuesTek Innovations LLC, 1820 Ridge Ave, Evanston, IL 60201, United States; Product Development and Analysis LLC, 1776 Legacy Circle, Suite #115, Naperville, IL 60563, United States"],"author":["Yan, F.","Chan, Y.-C.","Saboo, A.","Shah, J.","Olson, G.B.","Chen, W."],"correspondence_address1":["Chen, W.; Department of Mechanical Engineering, 2145 Sheridan Rd, United States; email: weichen@northwestern.edu"],"date":["2018"],"document_type":["Article"],"doi":["10.31614/cmes.2018.04452"],"issn":["15261492"],"journaltitle":["CMES - Comput. Model. Eng. Sci."],"note":["cited By 10 \n\nTL;DR \n\nA rapid prediction framework that replaces the physics-based mechanistic models with Gaussian process (GP) metamodels, a type of machine learning model for limited data and statistical inference, that can predict the varying properties in an entire part in a fraction of the time is proposed."],"number":["3"],"pages":["343–366"],"publisher":["Tech Science Press"],"source":["Scopus"],"title":["Data-driven prediction of mechanical properties in support of rapid certification of additively manufactured alloys"],"volume":["117"]},"creators":{"author":[{"lastName":"Yan","firstName":"F."},{"lastName":"Chan","firstName":"Y.-C."},{"lastName":"Saboo","firstName":"A."},{"lastName":"Shah","firstName":"J."},{"lastName":"Olson","firstName":"G.B."},{"lastName":"Chen","firstName":"W."}]},"sentenceCased":true},{"key":"Yang2017","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Des. Eng. Tech. Conf."],"affiliation":["Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003, United States; Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, United States"],"art_number":["67807"],"author":["Yang, Z.","Hagedorn, T.","Eddy, D.","Krishnamurty, S.","Grosse, I.","Denno, P.","Lu, Y.","Witherell, P."],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.1115/DETC2017-67807"],"isbn":["978-0-7918-5811-0"],"note":["cited By 6"],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the ASME Design Engineering Technical Conference"],"source":["Scopus"],"title":["A domain-driven approach to metamodeling in additive manufacturing"],"volume":["1"]},"creators":{"author":[{"lastName":"Yang","firstName":"Z."},{"lastName":"Hagedorn","firstName":"T."},{"lastName":"Eddy","firstName":"D."},{"lastName":"Krishnamurty","firstName":"S."},{"lastName":"Grosse","firstName":"I."},{"lastName":"Denno","firstName":"P."},{"lastName":"Lu","firstName":"Y."},{"lastName":"Witherell","firstName":"P."}]},"sentenceCased":true},{"key":"Yang2018","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. ASME Des. Eng. Tech. Conf."],"affiliation":["University of Massachusetts Amherst, Department of Mechanical and Industrial Engineering, Amherst, MA 01003, United States; National Institute of Standards and Technology Engineering Laboratory, Gaithersburg, MD 20899, United States"],"author":["Yang, Z.","Eddy, D.","Krishnamurty, S.","Grosse, I.","Lu, Y."],"correspondence_address1":["Eddy, D.; University of Massachusetts Amherst, United States; email: dceddy@engin.umass.edu"],"date":["2018"],"document_type":["Conference Paper"],"doi":["10.1115/DETC201886055"],"isbn":["978-0-7918-5172-2"],"note":["cited By 7 \n\nTL;DR \n\nThis paper introduces a super-metamodel optimization framework (SMOF) to improve overall prediction accuracy by integrating different metamodeling techniques without a need for additional data."],"publisher":["American Society of Mechanical Engineers (ASME)"],"series":["Proceedings of the ASME Design Engineering Technical Conference"],"source":["Scopus"],"title":["A super-metamodeling framework to optimize system predictability"],"volume":["1A-2018"]},"creators":{"author":[{"lastName":"Yang","firstName":"Z."},{"lastName":"Eddy","firstName":"D."},{"lastName":"Krishnamurty","firstName":"S."},{"lastName":"Grosse","firstName":"I."},{"lastName":"Lu","firstName":"Y."}]},"sentenceCased":true},{"key":"Yang2021","type":"inproceedings","fields":{"abstract":["We present a deep learning based joint source channel coding (JSCC) scheme for wireless image transmission over multipath fading channels with non-linear signal clipping. The proposed encoder and decoder use convolutional neural networks (CNN) and directly map the source images to complex-valued baseband samples for orthogonal frequency division multiplexing (OFDM) transmission. The proposed model-driven machine learning approach eliminates the need for separate source and channel coding while integrating an OFDM datapath to cope with multipath fading channels. The end-to-end JSCC communication system combines trainable CNN layers with non-trainable but differentiable layers representing the multipath channel model and OFDM signal processing blocks. Our results show that injecting domain expert knowledge by incorporating OFDM baseband processing blocks into the machine learning framework significantly enhances the overall performance compared to an unstructured CNN. Our method outperforms conventional schemes that employ state-of-the-art but separate source and channel coding such as BPG and LDPC with OFDM. Moreover, our method is shown to be robust against non-linear signal clipping in OFDM for various channel conditions that do not match the model parameter used during the training. © 2021 IEEE."],"author":["Yang, M.","Bian, C.","Kim, H.-S."],"date":["2021"],"document_type":["Conference Paper"],"doi":["10.1109/ICC42927.2021.9500996"],"isbn":["978-1-72817-122-7"],"issn":["15503607"],"note":["cited By 2 \n\nTL;DR \n\nThe results show that injecting domain expert knowledge by incorporating OFDM baseband processing blocks into the machine learning framework significantly enhances the overall performance compared to an unstructured CNN."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["IEEE International Conference on Communications"],"source":["Scopus"],"title":["Deep joint source channel coding for wireless image transmission with OFDM"]},"creators":{"author":[{"lastName":"Yang","firstName":"M."},{"lastName":"Bian","firstName":"C."},{"lastName":"Kim","firstName":"H.-S."}]},"sentenceCased":true},{"key":"yangActionableAnalyticsSoftware2018","type":"article","fields":{"author":["Yang, Ye","Falessi, Davide","Menzies, Tim","Hihn, Jairus"],"date":["2018"],"journaltitle":["IEEE Softw."],"note":["TL;DR \n\nThis theme issue aims to reflect on actionable analytics for software engineering and to document a catalog of success stories in which analytics has been proven actionable and useful, in some significant way, in an organization."],"number":["1"],"pages":["51–53"],"title":["Actionable Analytics for Software Engineering"],"volume":["35"]},"creators":{"author":[{"lastName":"Yang","firstName":"Ye"},{"lastName":"Falessi","firstName":"Davide"},{"lastName":"Menzies","firstName":"Tim"},{"lastName":"Hihn","firstName":"Jairus"}]}},{"key":"yangIoTStreamProcessing2017","type":"article","fields":{"author":["Yang, Shusen"],"date":["2017-08"],"doi":["10.1109/MCOM.2017.1600840"],"issn":["0163-6804, 1558-1896"],"journaltitle":["IEEE Commun. Mag."],"keywords":["Data analysis","DONE","internet of things"],"note":["TL;DR \n\nThe general models and architecture of fog data streaming are presented, by analyzing the common properties of several typical applications, and the design space of fog streaming is analyzed with the consideration of four essential dimensions (system, data, human, and optimization)."],"number":["8"],"pages":["21–27"],"title":["IoT Stream Processing and Analytics in the Fog"],"volume":["55"]},"creators":{"author":[{"lastName":"Yang","firstName":"Shusen"}]}},{"key":"yangNaturalAttackPretrained2022","type":"article","fields":{"langid":["english"],"abstract":["Pre-trained models of code have achieved success in many important software engineering tasks. However, these powerful models are vulnerable to adversarial attacks that slightly perturb model inputs to make a victim model produce wrong outputs. Current works mainly attack models of code with examples that preserve operational program semantics but ignore a fundamental requirement for adversarial example generation: perturbations should be natural to human judges, which we refer to as naturalness requirement."],"author":["Yang, Zhou","Shi, Jieke","He, Junda","Lo, David"],"date":["2022-01-21"],"doi":["10.1145/3510003.3510146"],"eprint":["2201.08698"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv220108698 Cs"],"keywords":["Computer Science - Software Engineering"],"note":["Comment: Accepted to the Technical Track of ICSE 2022 \n\nTL;DR \n\nThis paper proposes ALERT (Naturalness Aware Attack), a black-box attack that adversarially transforms inputs to make victim models produce wrong outputs and investigates the value of the generated adversarial examples to harden victim models through an adversarial fine-tuning procedure."],"title":["Natural Attack for Pre-trained Models of Code"]},"creators":{"author":[{"lastName":"Yang","firstName":"Zhou"},{"lastName":"Shi","firstName":"Jieke"},{"lastName":"He","firstName":"Junda"},{"lastName":"Lo","firstName":"David"}]}},{"key":"yangStackOverflowGithub2017","type":"inproceedings","fields":{"author":["Yang, Di","Martins, Pedro","Saini, Vaibhav","Lopes, Cristina"],"booktitle":["Min. Softw. Repos. MSR 2017 IEEEACM 14th Int. Conf. On"],"date":["2017"],"pages":["280–290"],"publisher":["IEEE"],"shorttitle":["Stack overflow in github"],"title":["Stack overflow in github: Any snippets there?"]},"creators":{"author":[{"lastName":"Yang","firstName":"Di"},{"lastName":"Martins","firstName":"Pedro"},{"lastName":"Saini","firstName":"Vaibhav"},{"lastName":"Lopes","firstName":"Cristina"}]},"sentenceCased":true},{"key":"yanPopularityBiasCorrelation2024","type":"article","fields":{"abstract":["The explosive growth of the API economy in recent years has led to a dramatic increase in available APIs. Mashup development, a dominant approach for creating data-centric applications based on APIs, has experienced a surge in popularity. However, the vast array of choices poses a challenge for mashup developers when selecting appropriate API compositions to meet specific business requirements. Correlation graph-based recommendation approaches have been designed to assist developers in discovering related and compatible API compositions for mashup creation. Unfortunately, these approaches often suffer from popularity bias issues, leading to an inequality in API usage and potential disruptions to the entire API ecosystem. To address these challenges, our research begins with a theoretical analysis of the popularity bias introduced by correlation graph-based API recommendation approaches. Subsequently, we empirically validate the presence of popularity bias in API recommendations through a data-driven study. Finally, we introduce the popularity bias aware web API recommendation (PB-WAR) approach to mitigate popularity bias in correlation graph-based API recommendations. Experimental results over a real world dataset demonstrate that PB-WAR offers the optimal trade-off between accuracy and debiasing performance compared to other competitive methods."],"author":["Yan, Chao","Zhong, Weiyi","Zhai, Dengshuai","Khan, Arif Ali","Gong, Wenwen","Xu, Yanwei","Xin, Baogui"],"date":["2024-04-02"],"doi":["10.1145/3654445"],"issn":["2157-6904"],"journaltitle":["ACM Trans. Intell. Syst. Technol."],"keywords":["⛔ No INSPIRE recid found","API recommendation","correlation graph","mashup","popularity bias"],"title":["Popularity Bias in Correlation Graph based API Recommendation for Mashup Creation"]},"creators":{"author":[{"lastName":"Yan","firstName":"Chao"},{"lastName":"Zhong","firstName":"Weiyi"},{"lastName":"Zhai","firstName":"Dengshuai"},{"lastName":"Khan","firstName":"Arif Ali"},{"lastName":"Gong","firstName":"Wenwen"},{"lastName":"Xu","firstName":"Yanwei"},{"lastName":"Xin","firstName":"Baogui"}]},"sentenceCased":true},{"key":"yaoIntelligentManufacturingSmart2017","type":"inproceedings","fields":{"langid":["english"],"abstract":["Smart manufacturing (SM) is emerging as a new version of intelligent manufacturing (IM), reflecting the magnitude and impact of smart technologies such the Internet of Things, Cloud Computing, Cyber-Physical Systems and Big Data on Industry 4.0. This paper addresses how IM evolves to SM along with artificial intelligence (AI) evolution. To this end, this study first summarizes how the symbolic AI (called AI 1.0) characterized by structured contents and centralized control structures evolves into the next-generation AI (called AI 2.0) characterized by unstructured contents, decentralized control structures and machine learning (especially deep learning), and explain show IM enabled by AI 1.0 evolves into SM by AI 2.0 accordingly. Then, the comparison of IM and SM is discussed in detail. Finally, the further development of smart manufacturing for Industry 4.0 is given."],"author":["Yao, Xifan","Zhou, Jiajun","Zhang, Jiangming","Boer, Claudio R."],"booktitle":["2017 5th Int. Conf. Enterp. Syst. ES"],"date":["2017-09"],"doi":["10.1109/ES.2017.58"],"eventtitle":["2017 5th International Conference on Enterprise Systems (ES)"],"isbn":["978-1-5386-0936-1"],"location":["Beijing"],"note":["TL;DR \n\nThis study summarizes how the symbolic AI characterized by structured contents and centralized control structures evolves into the next-generation AI (called AI 2.0) characterized by unstructured contents, decentralized control structures and machine learning (especially deep learning)."],"pages":["311–318"],"publisher":["IEEE"],"title":["From Intelligent Manufacturing to Smart Manufacturing for Industry 4.0 Driven by Next Generation Artificial Intelligence and Further On"]},"creators":{"author":[{"lastName":"Yao","firstName":"Xifan"},{"lastName":"Zhou","firstName":"Jiajun"},{"lastName":"Zhang","firstName":"Jiangming"},{"lastName":"Boer","firstName":"Claudio R."}]}},{"key":"Yarom2020725","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["ICAART - Proc. Int. Conf. Agents Artif. Intell."],"affiliation":["Ostfalia University of Applied Sciences, Salzdahulmer Str. 46/48, Wolfenbuettel, 38302, Germany"],"author":["Yarom, O.A.","Scherler, S.","Goellner, M.","Liu-Henke, X."],"date":["2020"],"document_type":["Conference Paper"],"editor":["Rocha A., Steels L., van den Herik J."],"isbn":["978-989-758-395-7"],"keywords":["GOAL_Model-Assistance","notion"],"note":["cited By 4 \n\nTL;DR \n\nThe model-based development of a function for lateral control of an automated vehicle using Artificial Neural Networks (ANN) and Genetic Algorithms (GA) is presented and the driving function is designed in the form of a functional structure."],"pages":["725–733"],"publisher":["SciTePress"],"series":["ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence"],"source":["Scopus"],"title":["Artificial neural networks and reinforcement learning for model-based design of an automated vehicle guidance system"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083099118&partnerID=40&md5=7022f6c914439fde6f66fb48b414ff4f"],"volume":["2"]},"creators":{"author":[{"lastName":"Yarom","firstName":"O.A."},{"lastName":"Scherler","firstName":"S."},{"lastName":"Goellner","firstName":"M."},{"lastName":"Liu-Henke","firstName":"X."}],"editor":[{"lastName":"Rocha A.","suffix":"Steels L.","firstName":"van den Herik J."}]},"sentenceCased":true},{"key":"Yavanoglu20172186","type":"inproceedings","fields":{"abstract":["It is an undeniable fact that currently information is a pretty significant presence for all companies or organizations. Therefore protecting its security is crucial and the security models driven by real datasets has become quite important. The operations based on military, government, commercial and civilians are linked to the security and availability of computer systems and network. From this point of security, the network security is a significant issue because the capacity of attacks is unceasingly rising over the years and they turn into be more sophisticated and distributed. The objective of this review is to explain and compare the most commonly used datasets. This paper focuses on the datasets used in artificial intelligent and machine learning techniques, which are the primary tools for analyzing network traffic and detecting abnormalities. © 2017 IEEE."],"author":["Yavanoglu, O.","Aydos, M."],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.1109/BigData.2017.8258167"],"editor":["Nie J.-Y., Obradovic Z., Ghosh R., Nambiar R., Wang C., Zang H., Baeza-Yates R., Baeza-Yates R., Hu X., Kepner J., Cuzzocrea A., Tang J., Toyoda M., Suzumura T."],"isbn":["978-1-5386-2714-3"],"note":["cited By 51 \n\nTL;DR \n\nThe objective of this review is to explain and compare the most commonly used datasets used in artificial intelligent and machine learning techniques, which are the primary tools for analyzing network traffic and detecting abnormalities."],"pages":["2186–2193"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017"],"source":["Scopus"],"title":["A review on cyber security datasets for machine learning algorithms"],"volume":["2018-January"]},"creators":{"author":[{"lastName":"Yavanoglu","firstName":"O."},{"lastName":"Aydos","firstName":"M."}],"editor":[{"lastName":"Nie J.-Y.","suffix":"Obradovic Z.","firstName":"Ghosh R., Nambiar R., Wang C., Zang H., Baeza-Yates R., Baeza-Yates R., Hu X., Kepner J., Cuzzocrea A., Tang J., Toyoda M., Suzumura T."}]},"sentenceCased":true},{"key":"ye_misim_nodate","type":"article","fields":{"langid":["english"],"abstract":["Code similarity systems are integral to a range of applications from code recommendation to automated software defect correction. We argue that code similarity is now a first-order problem that must be solved. To begin to address this, we present machine Inferred Code Similarity (MISIM), a novel end-to-end code similarity system that consists of two core components. First, MISIM uses a novel context-aware semantic structure, which is designed to aid in lifting semantic meaning from code syntax. Second, MISIM provides a neural-based code similarity scoring algorithm, which can be implemented with various neural network architectures with learned parameters. We compare MISIM to three state-of-the-art code similarity systems: (i) code2vec, (ii) Neural Code Comprehension, and (iii) Aroma. In our experimental evaluation across 328,155 programs (over 18 million lines of code), MISIM has 1.5x to 43.4x better accuracy than all three systems."],"author":["Ye, Fangke","Zhou, Shengtian","Venkat, Anand","Marcus, Ryan","Tatbul, Nesime","Tithi, Jesmin J","Hasabnis, Niranjan","Petersen, Paul","Mattson, Timothy","Kraska, Tim","Dubey, Pradeep","Sarkar, Vivek","Gottschlich, Justin E"],"note":["TL;DR \n\nThis work presents machine Inferred Code Similarity (MISIM), a novel end-to-end code similarity system that consists of two core components: a novel context-aware semantic structure and a neural-based code similarity scoring algorithm that can be implemented with various neural network architectures with learned parameters."],"pages":["22"],"title":["MISIM: A Novel Code Similarity System"]},"creators":{"author":[{"lastName":"Ye","firstName":"Fangke"},{"lastName":"Zhou","firstName":"Shengtian"},{"lastName":"Venkat","firstName":"Anand"},{"lastName":"Marcus","firstName":"Ryan"},{"lastName":"Tatbul","firstName":"Nesime"},{"lastName":"Tithi","firstName":"Jesmin J"},{"lastName":"Hasabnis","firstName":"Niranjan"},{"lastName":"Petersen","firstName":"Paul"},{"lastName":"Mattson","firstName":"Timothy"},{"lastName":"Kraska","firstName":"Tim"},{"lastName":"Dubey","firstName":"Pradeep"},{"lastName":"Sarkar","firstName":"Vivek"},{"lastName":"Gottschlich","firstName":"Justin E"}]}},{"key":"Ye202166","type":"article","fields":{"abstract":["Non-orthogonal multiple access (NOMA) is a promising evolution path to meet the requirements of massive machine type communications (mMTC) in 5G and beyond. However, the deployment of NOMA is hindered by the non-unified signal processing architectures of various NOMA schemes and the inflexibility resulting from the offline design paradigm. The block-wise optimized transceivers make its performance far from the limit. The recent breakthrough of deep learning and its positive applications to wireless communications have paved the way to tackle these challenges. This article studies the effectiveness and efficiency of deep learning in enhancing NOMA performance. Specifically, we first present the deep neural network (DNN), which is constructed via a uniform signal processing architecture, and use it as the unified multiuser receiver in both data and model-driven approaches. This enables the end-to-end optimization of NOMA transceivers due to the universal function approximation property of DNN. On the other hand, with DNN we can automatically extract the user access behaviors out of the time-series signals and optimize the transceivers to match these cross-lay-er behaviors. We further analyze the integration of non-orthogonal communication and neural computation to accomplish high-efficiency data transmission at low cost. Finally, we identify some essential future directions of deep-learning-en-hanced NOMA from the perspectives of online reconfigurability and adaptability toward the ever changing environment in future mMTC. © 2002-2012 IEEE."],"art_number":["9535455"],"author":["Ye, N.","An, J.","Yu, J."],"coden":["IWCEA"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/MWC.001.2000472"],"issn":["15361284"],"journaltitle":["IEEE Wirel. Commun."],"note":["cited By 1"],"number":["4"],"pages":["66–73"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Deep-learning-enhanced NOMA transceiver design for massive MTC: Challenges, state of the art, and future directions"],"volume":["28"]},"creators":{"author":[{"lastName":"Ye","firstName":"N."},{"lastName":"An","firstName":"J."},{"lastName":"Yu","firstName":"J."}]},"sentenceCased":true},{"key":"yeSupportingReuseDelivering2002","type":"inproceedings","fields":{"acmid":["581402"],"author":["Ye, Yunwen","Fischer, Gerhard"],"booktitle":["Proc. 24th Int. Conf. Softw. Eng."],"date":["2002"],"isbn":["1-58113-472-X"],"location":["New York, NY, USA"],"nodoi":["10.1145/581339.581402"],"note":["TL;DR \n\nThis research has explored a new interaction style between software developers and reuse repository systems enabled by information delivery mechanisms, where information delivery autonomously locates and presents components by using the developers' partially written programs as implicit queries."],"numpages":["11"],"pages":["513–523"],"publisher":["ACM"],"series":["ICSE '02"],"title":["Supporting reuse by delivering task-relevant and personalized information"],"url":["http://doi.acm.org/10.1145/581339.581402"]},"creators":{"author":[{"lastName":"Ye","firstName":"Yunwen"},{"lastName":"Fischer","firstName":"Gerhard"}]},"sentenceCased":true},{"key":"Yin2022","type":"article","fields":{"abstract":["In order to fully exploit the advantages of massive multiple-input multiple-output (mMIMO), it is critical for the transmitter to accurately acquire the channel state information (CSI). Deep learning (DL)-based methods have been proposed for CSI compression and feedback to the transmitter. Although most existing DL-based methods consider the CSI matrix as an image, structural features of the CSI image are rarely exploited in neural network design. As such, we propose a model of self-information that dynamically measures the amount of information contained in each patch of a CSI image from the perspective of structural features. Then, by applying the self-information model, we propose a model-and-data-driven network for CSI compression and feedback, namely IdasNet. The IdasNet includes the design of a module of self-information deletion and selection (IDAS), an encoder of informative feature compression (IFC), and a decoder of informative feature recovery (IFR). In particular, the model-driven module of IDAS pre-compresses the CSI image by removing informative redundancy in terms of the self-information. The encoder of IFC then conducts feature compression to the pre-compressed CSI image and generates a feature codeword which contains two components, i.e., codeword values and position indices of the codeword values. Subsequently, the IFR decoder decouples the codeword values as well as position indices to recover the CSI image. Experimental results verify that the proposed IdasNet noticeably outperforms existing DL-based networks under various compression ratios while it has the number of network parameters reduced by orders-of-magnitude compared with various existing methods. IEEE"],"author":["Yin, Z.","Xu, W.","Xie, R.","Zhang, S.","Ng, D.W.K.","You, X."],"date":["2022"],"document_type":["Article"],"doi":["10.1109/TWC.2022.3170576"],"issn":["15361276"],"journaltitle":["IEEE Trans. Wirel. Commun."],"note":["cited By 0 \n\nTL;DR \n\nExperimental results verify that the proposed IdasNet noticeably outperforms existing DL-based networks under various compression ratios while it has the number of network parameters reduced by orders-of-magnitude compared with various existing methods."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Deep CSI compression for massive MIMO: A self-information model-driven neural network"]},"creators":{"author":[{"lastName":"Yin","firstName":"Z."},{"lastName":"Xu","firstName":"W."},{"lastName":"Xie","firstName":"R."},{"lastName":"Zhang","firstName":"S."},{"lastName":"Ng","firstName":"D.W.K."},{"lastName":"You","firstName":"X."}]},"sentenceCased":true},{"key":"yinDynamicDataMining2020","type":"article","fields":{"langid":["english"],"abstract":["The research of data mining has aroused widespread concern in academia and industry. However, an important mark of the Internet of Things era is that sensor data replaces artificially compiled data. How to extract valuable knowledge and patterns from a large amount of data generated by sensors is a meaningful research topic. This paper proposes a dynamic data mining framework for processing sensor data. A sensor data mining model which can be used in the process of dynamic change is constructed. In this model, different sensor network environments are considered as different physical systems. The physical system and its parameters are trained by collecting and mining historical changes in sensor data; the associations between different sensor network environments are discovered by mining the associations between the parameters of different physical systems. In our limited experimental environment, the physical quantities considered included transmission distance, transmission delay, sensor data, data changes, and so on. Experiments were carried out on the designated experimental platform, and the results showed that the model could mine the dynamic data and find stable patterns. Through the analysis of the experimental results, it was found that the model had reference value for the dynamic mining of sensor data, and was expected to construct new methods for industrial big data analysis."],"author":["Yin, Yunfei","Long, Lianjie","Deng, Xiyu"],"date":["2020"],"doi":["10.1109/ACCESS.2020.2976699"],"issn":["2169-3536"],"journaltitle":["IEEE Access"],"note":["TL;DR \n\nA dynamic data mining framework for processing sensor data is proposed and a model which can be used in the process of dynamic change is constructed, finding that the model had reference value for the dynamic mining of sensor data, and was expected to construct new methods for industrial big data analysis."],"pages":["41637–41648"],"title":["Dynamic Data Mining of Sensor Data"],"volume":["8"]},"creators":{"author":[{"lastName":"Yin","firstName":"Yunfei"},{"lastName":"Long","firstName":"Lianjie"},{"lastName":"Deng","firstName":"Xiyu"}]}},{"key":"yingSelectionPresentationPractices","type":"article","fields":{"langid":["english"],"abstract":["Code examples are an important source for answering questions about software libraries and applications. Many usage contexts for code examples require them to be distilled to their essence: e.g., when serving as cues to longer documents, or for reminding developers of a previously known idiom. We conducted a study to discover how code can be summarized and why. As part of the study, we collected 156 pairs of code examples and their summaries from 16 participants, along with over 26 hours of think-aloud verbalizations detailing the decisions of the participants during their summarization activities. Based on a qualitative analysis of this data we elicited a list of practices followed by the participants to summarize code examples and propose empirically-supported hypotheses justifying the use of specific practices. One main finding was that none of the participants exclusively extracted code verbatim for the summaries, motivating abstractive summarization. The results provide a grounded basis for the development of code example summarization and presentation technology."],"author":["Ying, Annie T T","Robillard, Martin P"],"pages":["12"],"title":["Selection and Presentation Practices for Code Example Summarization"]},"creators":{"author":[{"lastName":"Ying","firstName":"Annie T T"},{"lastName":"Robillard","firstName":"Martin P"}]}},{"key":"Yılmaz20214305","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Struct. Mutltidiscip. Opt."],"affiliation":["Borçelik Çelik San. ve Tic. A.Ş., Ata Mh. 125. Sk. No:1, Gemlik, Bursa, 16601, Turkey; Department of Civil Engineering, Sirnak University, M. Emin Acar Campus, Sirnak, 73000, Turkey; Department of Civil Engineering, İstanbul Technical University, Ayazağa Campus, İstanbul, 34469, Turkey; Pass+Co Road Restraint Systems, Seigen, Germany"],"author":["Yılmaz, İ.","Yelek, İ.","Özcanan, S.","Atahan, A.O.","Hiekmann, J.M."],"coden":["SMOTB"],"correspondence_address1":["Yılmaz, İ.; Borçelik Çelik San. ve Tic. A.Ş., Ata Mh. 125. Sk. No:1, Gemlik, Turkey; email: ilyilmaz@borcelik.com"],"date":["2021"],"document_type":["Article"],"doi":["10.1007/s00158-021-03080-1"],"issn":["1615147X"],"journaltitle":["Struct. Multidiscip. Optim."],"note":["cited By 1"],"number":["6"],"pages":["4305–4323"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Artificial neural network metamodeling-based design optimization of a continuous motorcyclists protection barrier system"],"volume":["64"]},"creators":{"author":[{"lastName":"Yılmaz","firstName":"İ."},{"lastName":"Yelek","firstName":"İ."},{"lastName":"Özcanan","firstName":"S."},{"lastName":"Atahan","firstName":"A.O."},{"lastName":"Hiekmann","firstName":"J.M."}]},"sentenceCased":true},{"key":"yohannisModelbasedBiasMitigation2022","type":"inproceedings","fields":{"langid":["english"],"abstract":["Models produced by machine learning are not guaranteed to be free from bias, particularly when trained and tested with data produced in discriminatory environments. The bias can be unethical, mainly when the data contains sensitive attributes, such as sex, race, age, etc. Some approaches have contributed to mitigating such biases by providing bias metrics and mitigation algorithms. The challenge is users have to implement their code in general/statistical programming languages, which can be demanding for users with little programming and fairness in machine learning experience. We present FairML, a model-based approach to facilitate bias measurement and mitigation with reduced software development effort. Our evaluation shows that FairML requires fewer lines of code to produce comparable measurement values to the ones produced by the baseline code."],"author":["Yohannis, Alfa","Kolovos, Dimitris"],"booktitle":["Proc. 25th Int. Conf. Model Driven Eng. Lang. Syst."],"date":["2022-10-23"],"doi":["10.1145/3550355.3552401"],"eventtitle":["MODELS '22: ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems"],"isbn":["978-1-4503-9466-6"],"keywords":["LOGSEQ"],"location":["Montreal Quebec Canada"],"note":["TL;DR \n\nThis work presents FairML, a model-based approach to facilitate bias measurement and mitigation with reduced software development effort, and shows that FairML requires fewer lines of code to produce comparable measurement values to the ones produced by the baseline code."],"pages":["143–153"],"publisher":["ACM"],"title":["Towards model-based bias mitigation in machine learning"]},"creators":{"author":[{"lastName":"Yohannis","firstName":"Alfa"},{"lastName":"Kolovos","firstName":"Dimitris"}]},"sentenceCased":true},{"key":"Yoo2022","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Struct. Mutltidiscip. Opt."],"affiliation":["School of Mechanical Engineering, Yonsei University, Seoul, 03722, South Korea; Department of Automotive Engineering, Gwangju University, Gwangju, 61743, South Korea"],"art_number":["189"],"author":["Yoo, Y.","Park, C.-K.","Lee, J."],"coden":["SMOTB"],"correspondence_address1":["Lee, J.; School of Mechanical Engineering, South Korea; email: jleej@yonsei.ac.kr"],"date":["2022"],"document_type":["Article"],"doi":["10.1007/s00158-022-03290-1"],"issn":["1615147X"],"journaltitle":["Struct. Multidiscip. Optim."],"note":["cited By 0 \n\nTL;DR \n\nThis study proposes a deep learning-based efficient metamodeling method called domain knowledge-integrated designable data augmentation (DDA) with transfer learning for engineering design that was applied to the design of a bumper considering vehicle crash safety."],"number":["7"],"publisher":["Springer Science and Business Media Deutschland GmbH"],"source":["Scopus"],"title":["Deep learning-based efficient metamodeling via domain knowledge-integrated designable data augmentation with transfer learning: Application to vehicle crash safety"],"volume":["65"]},"creators":{"author":[{"lastName":"Yoo","firstName":"Y."},{"lastName":"Park","firstName":"C.-K."},{"lastName":"Lee","firstName":"J."}]},"sentenceCased":true},{"key":"Yoon202010468","type":"inproceedings","fields":{"abstract":["Estimating a dense and accurate depth map is the key requirement for autonomous driving and robotics. Recent advances in deep learning have allowed depth estimation in full resolution from a single image. Despite this impressive result, many deep-learning-based monocular depth estimation (MDE) algorithms have failed to keep their accuracy yielding a meter-level estimation error. In many robotics applications, accurate but sparse measurements are readily available from Light Detection and Ranging (LiDAR). Although they are highly accurate, the sparsity limits full resolution depth map reconstruction. Targeting the problem of dense and accurate depth map recovery, this paper introduces the fusion of these two modalities as a depth completion (DC) problem by dividing the role of depth inference and depth regression. Utilizing the state-of-the-art MDE and our Gaussian process (GP) based depth-regression method, we propose a general solution that can flexibly work with various MDE modules by enhancing its depth with sparse range measurements. To overcome the major limitation of GP, we adopt Kernel Interpolation for Scalable Structured (KISS)-GP and mitigate the computational complexity from O(N3) to O(N). Our experiments demonstrate that the accuracy and robustness of our method outperform state-of-the-art unsupervised methods for sparse and biased measurements. © 2020 IEEE."],"art_number":["9341769"],"author":["Yoon, S.","Kim, A."],"coden":["85RBA"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/IROS45743.2020.9341769"],"isbn":["978-1-72816-212-6"],"issn":["21530858"],"note":["cited By 2"],"pages":["10468–10475"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["IEEE International Conference on Intelligent Robots and Systems"],"source":["Scopus"],"title":["Balanced depth completion between dense depth inference and sparse range measurements via KISS-GP"]},"creators":{"author":[{"lastName":"Yoon","firstName":"S."},{"lastName":"Kim","firstName":"A."}]},"sentenceCased":true},{"key":"Yu2020310","type":"inproceedings","fields":{"abstract":["With the development of artificial intelligence technology, the ideas of machine learning have been introduced into the field of design in recent years. The research methods of 'AI + Architecture' have brought new ideas for solving traditional problems. Generative Adversarial Network (GAN) is a machine learning model for image generation. Pix2pix is an improved version of GAN, which is specially designed to learn and generate pairs of image data with similar characteristics. In this study, Pix2pix is applied to the recognition and generation of building facade. The purpose is to explore the feasibility of using image generation technology to achieve rapid recognition and generation of building facade based on pix2pix. This paper also discusses the application scenarios of this technology. The existing building façade datasets and the self-made Chinese traditional building datasets are used to test and verify that pix2pix under different types of datasets can nicely identify and generate facade images. Then we summarize a set of working methods based on GAN to realize the overall or local reconstruction design of the facade, so as to provide new ideas for the improvement of the efficiency of related industries and the expansion of teaching tools. © 2020 IEEE."],"art_number":["9403820"],"author":["Yu, Q.","Malaeb, J.","Ma, W."],"author_keywords":["facade; GAN; image generation; image recognition"],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/ICBASE51474.2020.00072"],"isbn":["978-1-72819-619-0"],"keywords":["Adversarial networks","Application scenario","Architectural facades","Artificial intelligence technologies","Big data","Building facades","Chinese traditional buildings","Facades","Image enhancement","Image generations","Machine learning","Machine learning models","Software engineering","Turing machines"],"note":["cited By 2"],"pages":["310–316"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2020 International Conference on Big Data and Artificial Intelligence and Software Engineering, ICBASE 2020"],"source":["Scopus"],"title":["Architectural facade recognition and generation through generative adversarial networks"]},"creators":{"author":[{"lastName":"Yu","firstName":"Q."},{"lastName":"Malaeb","firstName":"J."},{"lastName":"Ma","firstName":"W."}]},"sentenceCased":true},{"key":"yuAPIBookEffectiveApproach2016","type":"inproceedings","fields":{"langid":["english"],"author":["Yu, Haibo","Song, Wenhao","Mine, Tsunenori"],"date":["2016"],"doi":["10.1145/2993717.2993727"],"isbn":["978-1-4503-4829-4"],"note":["TL;DR \n\nA search-based recommendation algorithm on API methods is proposed that combines semantic relevance, type relevance and the extent of degree that API method is used to sort these API methods and rank those that are highly relevant and widely used in the top positions."],"pages":["45–53"],"publisher":["ACM Press"],"shorttitle":["APIBook"],"title":["APIBook: An effective approach for finding APIs"]},"creators":{"author":[{"lastName":"Yu","firstName":"Haibo"},{"lastName":"Song","firstName":"Wenhao"},{"lastName":"Mine","firstName":"Tsunenori"}]},"sentenceCased":true},{"key":"yuEfficientSimRankComputation2013","type":"inproceedings","fields":{"added-at":["2013-06-27T00:00:00.000+0200"],"author":["Yu, Weiren","Lin, Xuemin","Zhang, Wenjie"],"biburl":["http://www.bibsonomy.org/bibtex/2026a998396ad1c9c6555439949e04747/dblp"],"booktitle":["ICDE"],"date":["2013"],"editor":["Jensen, Christian S.","Jermaine, Christopher M.","Zhou, Xiaofang"],"ee":["http://doi.ieeecomputersociety.org/10.1109/ICDE.2013.6544859"],"interhash":["22d1f058c9d3b87edb546d64328413e8"],"intrahash":["026a998396ad1c9c6555439949e04747"],"isbn":["978-1-4673-4909-3"],"keywords":["dblp"],"pages":["601–612"],"publisher":["IEEE Computer Society"],"timestamp":["2013-06-27T00:00:00.000+0200"],"title":["Towards efficient SimRank computation on large networks."],"url":["http://dblp.uni-trier.de/db/conf/icde/icde2013.html#YuLZ13"]},"creators":{"author":[{"lastName":"Yu","firstName":"Weiren"},{"lastName":"Lin","firstName":"Xuemin"},{"lastName":"Zhang","firstName":"Wenjie"}],"editor":[{"lastName":"Jensen","firstName":"Christian S."},{"lastName":"Jermaine","firstName":"Christopher M."},{"lastName":"Zhou","firstName":"Xiaofang"}]},"sentenceCased":true},{"key":"yuRapidApplicationDevelopment2011","type":"article","fields":{"langid":["english"],"abstract":["The development of large or medium-sized domain application systems usually involves intensive workforce due to its complexity. Reuse of existing components, especially those architectural ones, could dramatically reduce the production cost and improve the quality. However, the problems related with making and adapting reusable components among different systems often inhibit the introduction of reuse. Fortunately, domainoriented application systems, especially those data-centric ones, usually share similar behaviors no matter what they server for. This paper extracts the common behaviors existing in different domains and introduces the templates based application framework, called RADF. RADF provides application skeletons and confines domain specific coding in predefined templates of classes and configuration files. The proprietary behavior of domain specific applications could be realized via simply filling codes in these templates. RADF not only consolidates the programming paradigm and provides the supporting classes for default behaviors expected in different domains, but also allows manually extending and reassembling these supporting classes. Four cases of RADF-based development have proved that RADF helps rapid application development with significantly reduced number of manually-coded source lines."],"author":["Yu, Dongjin"],"date":["2011-08-01"],"doi":["10.4304/jsw.6.9.1795-1804"],"issn":["1796-217X"],"journaltitle":["JSW"],"number":["9"],"pages":["1795–1804"],"title":["Towards the Rapid Application Development Based on Predefined Frameworks"],"volume":["6"]},"creators":{"author":[{"lastName":"Yu","firstName":"Dongjin"}]}},{"key":"Zahoor2020198","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["ACM Int. Conf. Proc. Ser."],"affiliation":["Department of Computer and Software Engineering, College of EandME, National University of Sciences and Technology (NUST), H-12 Islamabad, Pakistan"],"author":["Zahoor, T.","Azam, F.","Anwar, M.W.","Tariq, A.","Javaid, H.A."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1145/3436829.3436851"],"isbn":["978-1-4503-7721-8"],"note":["cited By 0 \n\nTL;DR \n\nThe key tools, techniques &amp; challenges proposed in the recent research studies in smart parking systems are investigated and will definitely assist the practitioners while deciding the appropriate selections."],"pages":["198–203"],"publisher":["Association for Computing Machinery"],"series":["ACM International Conference Proceeding Series"],"source":["Scopus"],"title":["An investigation of smart parking tools, technologies, & challenges"]},"creators":{"author":[{"lastName":"Zahoor","firstName":"T."},{"lastName":"Azam","firstName":"F."},{"lastName":"Anwar","firstName":"M.W."},{"lastName":"Tariq","firstName":"A."},{"lastName":"Javaid","firstName":"H.A."}]},"sentenceCased":true},{"key":"zambonelliKeyAbstractionsIoTOriented2017","type":"article","fields":{"langid":["english"],"author":["Zambonelli, Franco"],"date":["2017-01"],"doi":["10.1109/MS.2017.3"],"issn":["0740-7459"],"journaltitle":["IEEE Softw."],"number":["1"],"pages":["38–45"],"title":["Key Abstractions for IoT-Oriented Software Engineering"],"volume":["34"]},"creators":{"author":[{"lastName":"Zambonelli","firstName":"Franco"}]}},{"key":"zambonelliSelfAdaptationSelfExpressionSelfAwareness2011","type":"inproceedings","fields":{"author":["Zambonelli, Franco","Bicocchi, Nicola","Cabri, Giacomo","Leonardi, Letizia","Puviani, Mariachiara"],"date":["2011-10"],"doi":["10.1109/SASOW.2011.24"],"isbn":["978-1-4577-2029-1 978-0-7695-4545-5"],"note":["TL;DR \n\nThis position paper frame and discuss the above issues, survey the state of the art in the area, and sketch the main research challenges that will be faced in the ASCENS project towards the definition of a fully-fledged framework for autonomic services."],"pages":["108–113"],"publisher":["IEEE"],"title":["On Self-Adaptation, Self-Expression, and Self-Awareness in Autonomic Service Component Ensembles"]},"creators":{"author":[{"lastName":"Zambonelli","firstName":"Franco"},{"lastName":"Bicocchi","firstName":"Nicola"},{"lastName":"Cabri","firstName":"Giacomo"},{"lastName":"Leonardi","firstName":"Letizia"},{"lastName":"Puviani","firstName":"Mariachiara"}]}},{"key":"zampettiHowOpenSource2017","type":"inproceedings","fields":{"author":["Zampetti, Fiorella","Scalabrino, Simone","Oliveto, Rocco","Canfora, Gerardo","Di Penta, Massimiliano"],"date":["2017-05"],"doi":["10.1109/MSR.2017.2"],"isbn":["978-1-5386-1544-7"],"note":["TL;DR \n\nStudy of the usage of static analysis tools in 20 Java open source projects hosted on GitHub and using Travis CI as continuous integration infrastructure reveals that build breakages are quickly fixed by actually solving the problem, rather than by disabling the warning, and are often properly documented."],"pages":["334–344"],"publisher":["IEEE"],"title":["How Open Source Projects Use Static Code Analysis Tools in Continuous Integration Pipelines"]},"creators":{"author":[{"lastName":"Zampetti","firstName":"Fiorella"},{"lastName":"Scalabrino","firstName":"Simone"},{"lastName":"Oliveto","firstName":"Rocco"},{"lastName":"Canfora","firstName":"Gerardo"},{"lastName":"Di Penta","firstName":"Massimiliano"}]}},{"key":"zayanEffectsUsingExamples2014","type":"inproceedings","fields":{"author":["Zayan, Dina","Antkiewicz, Micha\\l","Czarnecki, Krzysztof"],"booktitle":["Proc. 36th Int. Conf. Softw. Eng."],"date":["2014"],"pages":["955–966"],"publisher":["ACM"],"shorttitle":["Effects of using examples on structural model comprehension"],"title":["Effects of using examples on structural model comprehension: A controlled experiment"],"url":["http://dl.acm.org/citation.cfm?id=2568270"],"urldate":["2015-05-17"]},"creators":{"author":[{"lastName":"Zayan","firstName":"Dina"},{"lastName":"Antkiewicz","firstName":"Micha\\l"},{"lastName":"Czarnecki","firstName":"Krzysztof"}]},"sentenceCased":true},{"key":"zelkowitzExperimentalModelsValidating1998","type":"article","fields":{"langid":["english"],"author":["Zelkowitz, M.V.","Wallace, D.R."],"date":["1998-05"],"doi":["10.1109/2.675630"],"issn":["00189162"],"journaltitle":["Computer"],"number":["5"],"pages":["23–31"],"title":["Experimental models for validating technology"],"volume":["31"]},"creators":{"author":[{"lastName":"Zelkowitz","firstName":"M.V."},{"lastName":"Wallace","firstName":"D.R."}]},"sentenceCased":true},{"key":"Zeng2017982","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc. - Chin. Autom. Congr., CAC"],"affiliation":["College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha, China"],"author":["Zeng, S.","Liu, Y.","Li, J.","Zhou, S."],"date":["2017"],"document_type":["Conference Paper"],"doi":["10.1109/CAC.2017.8242909"],"isbn":["978-1-5386-3524-7"],"keywords":["notion"],"note":["cited By 1"],"pages":["982–987"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["Proceedings - 2017 Chinese Automation Congress, CAC 2017"],"source":["Scopus"],"title":["Metamodel of the two-dimensional magnet-rail relationship based on a BP neural network"],"volume":["2017-January"]},"creators":{"author":[{"lastName":"Zeng","firstName":"S."},{"lastName":"Liu","firstName":"Y."},{"lastName":"Li","firstName":"J."},{"lastName":"Zhou","firstName":"S."}]},"sentenceCased":true},{"key":"zennaroMachineLearningApproach2018","type":"inproceedings","fields":{"abstract":["Advancements of Machine Learning (ML) in the field of computer vision have paved the way for its potential application in many other fields. Researchers and hardware domain experts are exploring possible applications of Machine Learning in optimizing many aspects of hardware development process. In this paper, we propose a novel approach for predicting the area of hardware components from specifications. The flow uses an existing RTL generation framework, for generating valid data samples that enable ML algorithms to train the learning models. The approach has been successfully employed to predict the area of real-life hardware components such as Control and Status Register (CSR) interfaces that are ubiquitous in embedded systems. With this approach we are able to predict the area with more than 98% accuracy and 600x faster than the existing methods. In addition, we are able to rank the features according to their importance in final area estimations. © 2018 IEEE."],"author":["Zennaro, E.","Servadei, L.","Devarajegowda, K.","Ecker, W."],"booktitle":["Proc. - 21st Euromicro Conf. Digit. Syst. Des. DSD 2018"],"date":["2018"],"doi":["10.1109/DSD.2018.00076"],"editor":["Konofaos N., Novotny M., Skavhaug A."],"isbn":["978-1-5386-7376-8"],"keywords":["Area estimation","Artificial intelligence","Code Generation","Computer hardware","Design productivity","Embedded systems","Forecasting","Hardware","Learning systems","Meta model","Model driven architectures","Software architecture","Software design","Specifications","Systems analysis"],"note":["cited By 11"],"pages":["413–420"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"title":["A machine learning approach for area prediction of hardware designs from abstract specifications"]},"creators":{"author":[{"lastName":"Zennaro","firstName":"E."},{"lastName":"Servadei","firstName":"L."},{"lastName":"Devarajegowda","firstName":"K."},{"lastName":"Ecker","firstName":"W."}],"editor":[{"lastName":"Konofaos N.","suffix":"Novotny M.","firstName":"Skavhaug A."}]},"sentenceCased":true},{"key":"zeshanPromptInjectionBasedAdversarial","type":"misc","fields":{"langid":["english"],"author":["Zeshan, Muhammad Umar"],"keywords":["LOGSEQ","Mentoring","people/Umar"],"note":["<h1>Annotazioni\n (19/1/2024, 16:08:19)</h1> \n\n“trendy” (Zeshan, p. 1) #ff6666 \n\n“prompt attacks in Large Language Models” (Zeshan, p. 1) #a28ae5 \n\n“LLMs” (Zeshan, p. 1) #ff6666 \n\n“better” (Zeshan, p. 1) #ffd400 \n <i>Nothing has been said so far. Better than that?</i> \n\n“ethical issues, bias, and responsible use become crucial factors to take into account” (Zeshan, p. 1) #ffd400 \n <i>These are critical points. Are you mentioning them because you want to plan to deal with them? If not, why are you mentioning them?</i> \n\n“insufficient safety assessments and guardrails are accompanying this drive toward AI integration” (Zeshan, p. 1) #5fb236 \n\n“A prompt should ideally generate an answer that is accurate, sufficient in both form and content, and of the appropriate length” (Zeshan, p. 2) #5fb236 \n\n“several human feedback-incorporating fine-tuning procedures have been developed to guarantee that LLM outputs are both safe and consistent with human values.” (Zeshan, p. 2) #5fb236 \n\n“around the security.” (Zeshan, p. 2) #ffd400 \n <i>Some more details about security issues one can have with LLMs are needed.</i> \n\n“According to Zou et al.’s research from 2023, adversarial sequence creation can be automated, producing an infinite number of these attacks. Furthermore, they demonstrate how safety precautions can be circumvented by appending a single adversarial sequence to several damaging prompts” (Zeshan, p. 2) #ffd400 \n <i>Some illustrative examples are needed here!</i> \n\n“Adversarial attacks detection in RSSE” (Zeshan, p. 2) #ffd400 \n <i>This section should be on presenting Rec Systems in Software Engineering. Thus the title should be changed and the content should be expanded with the aim of presenting a quick overview on RSSE.</i> \n\n“Adversarial attempts produce perturbations to trick and confuse systems by breaking them down, impairing their ability to provide recommendations. For instance, an adversarial attack on recommender systems may support or disparage a product, depending on the intent, which would have a detrimental effect on the final recommendations. Similarly, malicious users may expose recommender systems to hazardous artifacts by altering training data that is accessible through OSS platforms. Software system disruptions may arise if a recommender is trained to deliver harmful outcomes based on Adversaries. For instance, a recent study reveals that there have been attempts to force Android apps to open ports covertly, enabling unwanted access. Security concerns in machine learning systems and all-purpose recommender systems are investigated via research on adversarial machine learning (AML)” (Zeshan, p. 3) #ffd400 \n <i>I would show some technical details that will be used later in the text.</i> \n\n“Adversarial Attacks in Promptbased Learning” (Zeshan, p. 4) #ffd400 \n <i>All the different approaches that are overviewed in this section need to be expanded with concrete examples. It is essential to expand because, as far as I understood, this will underpin and motivate the planned work.</i> \n\n“trendy” (Zeshan, p. 4) #ff6666 \n <i>I don't like it; it is not for scientific documents.</i> \n\n“backdoor attacks” (Zeshan, p. 4) #5fb236 \n\n“Our Methodology” (Zeshan, p. 5) #ffd400 \n <i>For what? It is necessary to conclude the previous section by listing the challenges you plan to address! By clearly listing the challenges at the end of the previous section, in this section you can discuss how you plant to deal with them.</i> \n\n“Limitations in previous methods” (Zeshan, p. 6) #ffd400 \n <i>This must be moved to the previous section before listing the challenges that you plan to address.</i> \n\n“The main drawback of previous research is that it is case study oriented; for example, it did not define the attacker’s objective in rapid injection assaults in terms of the type of the attack, attacker wants to carry.” (Zeshan, p. 6) #ffd400 \n <i>The document is plenty of sentences like this one, we are missing concreteness, you have to provide explanatory examples to help reader understand what's the problem by referring to real cases.</i> \n\n“Rather than simply translating a text into English, they demonstrated how an assailant may lead an LLM astray and have them compose a sonnet about pandas. The main drawback of this kind of caseby-case research is how difficult it is to come up with novel prompt injection attacks or carry out a thorough analysis and comparison of other prompt injection assaults. Even the latest studies are focusing on some particular type of prompt injections, which also allow for enhancing the attack by combining all the possible attack scenarios.” (Zeshan, p. 6) #ffd400 \n <i>Suddenly, we lost the reference to RSSE!</i> \n\n“Research Questions” (Zeshan, p. 6) #ffd400 \n <i>Are you still interested in RSSE? The research questions you defined are not related to RSSE.</i> \n\n“ll kinds of adversarial attacks defined in literature are discussed which are relevant in this new trendy topic of prompt learning attacks.” (Zeshan, p. 6) #ffd400 \n <i>Thus, what's the plan? Are you planning to work on a survey work? What do you expect to do further than expanding what you have listed in 3.2?</i> \n\n“threat model is proposed, in which a combined attack model is applied which concatenates all the possible types of attacks in prompts by the attacker.” (Zeshan, p. 6) #ffd400 \n <i>I don't see it in Section 3.2</i> \n\n“Prompt Injection Attacks” (Zeshan, p. 8) #ffd400 \n <i>Is this supposed to be a new type of attack? But it is not new, isn't it?</i>"],"title":["Prompt-Injection based Adversarial Attacks in Large Language Models"]},"creators":{"author":[{"lastName":"Zeshan","firstName":"Muhammad Umar"}]},"sentenceCased":true},{"key":"zhang_automatic_2012","type":"inproceedings","fields":{"abstract":["Programmers extensively use application programming interfaces (APIs) to leverage existing libraries and frameworks. However, correctly and efficiently choosing and using APIs from unfamiliar libraries and frameworks is still a non-trivial task. Programmers often need to ruminate on API documentations (that are often incomplete) or inspect code examples (that are often absent) to learn API usage patterns. Recently, various techniques have been proposed to alleviate this problem by creating API summarizations, mining code examples, or showing common API call sequences. However, few techniques focus on recommending API parameters. In this paper, we propose an automated technique, called Precise, to address this problem. Differing from common code completion systems, Precise mines existing code bases, uses an abstract usage instance representation for each API usage example, and then builds a parameter usage database. Upon a request, Precise queries the database for abstract usage instances in similar contexts and generates parameter candidates by concretizing the instances adaptively. The experimental results show that our technique is more general and applicable than existing code completion systems, specially, 64% of the parameter recommendations are useful and 53% of the recommendations are exactly the same as the actual parameters needed. We have also performed a user study to show our technique is useful in practice."],"author":["Zhang, Cheng","Yang, Juyuan","Zhang, Yi","Fan, Jing","Zhang, Xin","Zhao, Jianjun","Ou, Peizhao"],"booktitle":["2012 34th Int. Conf. Softw. Eng. ICSE"],"date":["2012-06"],"doi":["10.1109/ICSE.2012.6227136"],"keywords":["abstract usage instance representation","Abstracts","API","API call sequences","API documentations","API summarizations","API usage pattern learning","application program interfaces","application programming interfaces","argument","Arrays","automatic parameter recommendation","code base mining","code completion","code completion systems","code example mining","Complexity theory","Context","data mining","database querying","Documentation","Indexes","inspect code examples","learning (artificial intelligence)","parameter","parameter usage database","practical API usage","Precise","query processing","recommendation","recommender systems"],"note":["ISSN: 1558-1225 \n\nTL;DR \n\nAn automated technique, called Precise, is proposed, which mines existing code bases, uses an abstract usage instance representation for each API usage example, and then builds a parameter usage database and generates parameter candidates by concretizing the instances adaptively."],"pages":["826–836"],"title":["Automatic parameter recommendation for practical API usage"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Cheng"},{"lastName":"Yang","firstName":"Juyuan"},{"lastName":"Zhang","firstName":"Yi"},{"lastName":"Fan","firstName":"Jing"},{"lastName":"Zhang","firstName":"Xin"},{"lastName":"Zhao","firstName":"Jianjun"},{"lastName":"Ou","firstName":"Peizhao"}]},"sentenceCased":true},{"key":"zhang_cyber-guided_2020","type":"inproceedings","fields":{"abstract":["As the largest source code repository, GitHub has played a vital role in modern social coding ecosystem to generate production software. Despite the apparent benefits of such social coding paradigm, its potential security risks have been largely overlooked (e.g., malicious codes or repositories could be easily embedded and distributed). To address this imminent issue, in this paper, we propose a novel framework (named GitCyber) to automate malicious repository detection in GitHub at the first attempt. In GitCyber, we first extract code contents from the repositories hosted in GitHub as the inputs for deep neural network (DNN), and then we incorporate cybersecurity domain knowledge modeled by heterogeneous information network (HIN) to design cyber-guided loss function in the learning objective of the DNN to assure the classification performance while preserving consistency with the observational domain knowledge. Comprehensive experiments based on the large-scale data collected from GitHub demonstrate that our proposed GitCyber outperforms the state-of-the-arts in malicious repository detection."],"author":["Zhang, Yiming","Fan, Yujie","Hou, Shifu","Ye, Yanfang","Xiao, Xusheng","Li, Pan","Shi, Chuan","Zhao, Liang","Xu, Shouhuai"],"booktitle":["2020 IEEE Int. Conf. Knowl. Graph ICKG"],"date":["2020-08"],"doi":["10.1109/ICBK50248.2020.00071"],"keywords":["Cyber-guided DNN","Data mining","Encoding","Feature extraction","heterogeneous information network","Knowledge engineering","malicious repository detection","Neural networks","Security","Software"],"note":["TL;DR \n\nComprehensive experiments based on the large-scale data collected from GitHub demonstrate that the proposed GitCyber outperforms the state-of-the-arts in malicious repository detection."],"pages":["458–465"],"title":["Cyber-guided Deep Neural Network for Malicious Repository Detection in GitHub"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Yiming"},{"lastName":"Fan","firstName":"Yujie"},{"lastName":"Hou","firstName":"Shifu"},{"lastName":"Ye","firstName":"Yanfang"},{"lastName":"Xiao","firstName":"Xusheng"},{"lastName":"Li","firstName":"Pan"},{"lastName":"Shi","firstName":"Chuan"},{"lastName":"Zhao","firstName":"Liang"},{"lastName":"Xu","firstName":"Shouhuai"}]},"sentenceCased":true},{"key":"Zhang:1997:BND:593415.593443","type":"article","fields":{"acmid":["593443"],"address":["Hingham, MA, USA"],"author":["Zhang, Tian","Ramakrishnan, Raghu","Livny, Miron"],"date":["1997-01"],"issn":["1384-5810"],"issue_date":["1997"],"journaltitle":["Data Min. Knowl. Discov."],"keywords":["Data Classification and Compression","Data Clustering","Incremental Algorithm","Very Large Databases"],"nodoi":["10.1023/A:1009783824328"],"number":["2"],"numpages":["42"],"pages":["141–182"],"publisher":["Kluwer Academic Publishers"],"title":["BIRCH: A new data clustering algorithm and its applications"],"url":["https://doi.org/10.1023/A:1009783824328"],"volume":["1"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Tian"},{"lastName":"Ramakrishnan","firstName":"Raghu"},{"lastName":"Livny","firstName":"Miron"}]},"sentenceCased":true},{"key":"ZHANG2011625","type":"article","fields":{"abstract":["Context Systematic literature review (SLR) has become an important research methodology in software engineering since the introduction of evidence-based software engineering (EBSE) in 2004. One critical step in applying this methodology is to design and execute appropriate and effective search strategy. This is a time-consuming and error-prone step, which needs to be carefully planned and implemented. There is an apparent need for a systematic approach to designing, executing, and evaluating a suitable search strategy for optimally retrieving the target literature from digital libraries. Objective The main objective of the research reported in this paper is to improve the search step of undertaking SLRs in software engineering (SE) by devising and evaluating systematic and practical approaches to identifying relevant studies in SE. Method We have systematically selected and analytically studied a large number of papers (SLRs) to understand the state-of-the-practice of search strategies in EBSE. Having identified the limitations of the current ad-hoc nature of search strategies used by SE researchers for SLRs, we have devised a systematic and evidence-based approach to developing and executing optimal search strategies in SLRs. The proposed approach incorporates the concept of ‘quasi-gold standard’ (QGS), which consists of collection of known studies, and corresponding ‘quasi-sensitivity’ into the search process for evaluating search performance. Results We conducted two participant–observer case studies to demonstrate and evaluate the adoption of the proposed QGS-based systematic search approach in support of SLRs in SE research. Conclusion We report their findings based on the case studies that the approach is able to improve the rigor of search process in an SLR, as well as it can serve as a supplement to the guidelines for SLRs in EBSE. We plan to further evaluate the proposed approach using a series of case studies on varying research topics in SE."],"author":["Zhang, He","Babar, Muhammad Ali","Tell, Paolo"],"date":["2011"],"doi":["10.1016/j.infsof.2010.12.010"],"ids":["zhang2011identifying"],"issn":["0950-5849"],"journaltitle":["Inf. Softw. Technol."],"keywords":["Evidence-based software engineering","Quasi-gold standard","Search strategy","Systematic literature review"],"note":["Special Section: Best papers from the APSEC"],"number":["6"],"pages":["625–637"],"publisher":["Elsevier"],"title":["Identifying relevant studies in software engineering"],"volume":["53"]},"creators":{"author":[{"lastName":"Zhang","firstName":"He"},{"lastName":"Babar","firstName":"Muhammad Ali"},{"lastName":"Tell","firstName":"Paolo"}]},"sentenceCased":true},{"key":"Zhang2017","type":"article","fields":{"langid":["english"],"abbrev_source_title":["J. Comput. Civ. Eng."],"affiliation":["College of Design, School of Building Construction, Georgia Institute of Technology, 280 Ferst Dr., Atlanta, GA 30332-0680, United States; School of Civil Engineering and Mechanics, Huazhong Univ. of Science and Technology, Wuhan, Hubei, 430074, China; Dept. of Civil and Environmental Engineering, Hole School of Construction Engineering, Univ. of Alberta, 5-047 Markin/Canadian Natural Resources Limited, Natural Resources Engineering Facility, Edmonton, AB T6G 2W2, Canada"],"art_number":["04017065"],"author":["Zhang, L.","Wu, X.","Zhu, H.","Abourizk, S.M."],"coden":["JCCEE"],"correspondence_address1":["Zhu, H.; School of Civil Engineering and Mechanics, China; email: hpzhu@mail.hust.edu.cn"],"date":["2017"],"document_type":["Article"],"doi":["10.1061/(ASCE)CP.1943-5487.0000714"],"issn":["08873801"],"journaltitle":["J. Comput. Civ. Eng."],"note":["cited By 31"],"number":["6"],"publisher":["American Society of Civil Engineers (ASCE)"],"source":["Scopus"],"title":["Performing global uncertainty and sensitivity analysis from given data in tunnel construction"],"volume":["31"]},"creators":{"author":[{"lastName":"Zhang","firstName":"L."},{"lastName":"Wu","firstName":"X."},{"lastName":"Zhu","firstName":"H."},{"lastName":"Abourizk","firstName":"S.M."}]},"sentenceCased":true},{"key":"Zhang2019","type":"inproceedings","fields":{"abstract":["Wireless localization for mobile device has attracted more and more interests by increasing the demand for location based services. Fingerprint-based localization is promising, especially in non-Line-of-Sight (NLoS) or rich scattering environments, such as urban areas and indoor scenarios. In this paper, we propose a novel fingerprint-based localization technique based on deep learning framework under commercial long term evolution (LTE) systems. Specifically, we develop a software defined user equipment to collect the real time channel state information (CSI) knowledge from LTE base stations and extract the intrinsic features among CSI observations. On top of that, we propose a time domain fusion approach to assemble multiple positioning estimations. Experimental results demonstrated that the proposed localization technique can significantly improve the localization accuracy and robustness, e.g. achieves Mean Distance Error (MDE) of 0.47 meters for indoor and of 19.9 meters for outdoor scenarios, respectively. © 2019 IEEE."],"art_number":["8891257"],"author":["Zhang, H.","Zhang, Z.","Zhang, S.","Xu, S.","Cao, S."],"coden":["IVTCD"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1109/VTCFall.2019.8891257"],"isbn":["978-1-72811-220-6"],"issn":["15502252"],"note":["cited By 14 \n\nTL;DR \n\nA novel fingerprint-based localization technique based on deep learning framework under commercial long term evolution (LTE) systems is proposed, which develops a software defined user equipment to collect the real time channel state information (CSI) knowledge from LTE base stations and extract the intrinsic features among CSI observations."],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["IEEE Vehicular Technology Conference"],"source":["Scopus"],"title":["Fingerprint-based localization using commercial LTE signals: A field-trial study"],"volume":["2019-September"]},"creators":{"author":[{"lastName":"Zhang","firstName":"H."},{"lastName":"Zhang","firstName":"Z."},{"lastName":"Zhang","firstName":"S."},{"lastName":"Xu","firstName":"S."},{"lastName":"Cao","firstName":"S."}]},"sentenceCased":true},{"key":"Zhang201912744","type":"inproceedings","fields":{"abstract":["In this paper, we propose the Self-Attention Generative Adversarial Network (SAGAN) which allows attention-driven, long-range dependency modeling for image generation tasks. Traditional convolutional GAXs generate high-resolution details as a function of only spatially local points in lower-resolution feature maps. In SAGAN, details can be generated using cues from all feature locations. Moreover, the discriminator can check that highly detailed features in distant portions of the image are consistent with each other. Furthermore, recent work has shown that generator conditioning affects GAN performance. Leveraging this insight, we apply spectral normalization to the GAN generator and find that this improves training dynamics. The proposed SAGAN performs better than prior work1, boosting the best published Inception score from 36.8 to 52.52 and reducing Fréhet Inception distance from 27.62 to 18.65 on the challenging ImageNet dataset. Visualization of the attention layers shows that the generator leverages neighborhoods that correspond to object shapes rather than local regions of fixed shape. © 36th International Conference on Machine Learning, ICML 2019. All rights reserved."],"author":["Zhang, H.","Goodfellow, I.","Metaxas, D.","Odena, A."],"date":["2019"],"document_type":["Conference Paper"],"isbn":["978-1-5108-8698-8"],"keywords":["Adversarial networks","Artificial intelligence","Feature location","High-Resolution Details","Image generations","Local region","Long-range dependencies","Lower resolution","Machine learning","Software engineering","Spectral normalization"],"note":["cited By 1392 \n\nTL;DR \n\nThe proposed SAGAN achieves the state-of-the-art results, boosting the best published Inception score from 36.8 to 52.52 and reducing Frechet Inception distance from 27.62 to 18.65 on the challenging ImageNet dataset."],"pages":["12744–12753"],"publisher":["International Machine Learning Society (IMLS)"],"series":["36th International Conference on Machine Learning, ICML 2019"],"source":["Scopus"],"title":["Self-attention generative adversarial networks"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078069179&partnerID=40&md5=5849359dc99edfeab0013f81d7c62855"],"volume":["2019-June"]},"creators":{"author":[{"lastName":"Zhang","firstName":"H."},{"lastName":"Goodfellow","firstName":"I."},{"lastName":"Metaxas","firstName":"D."},{"lastName":"Odena","firstName":"A."}]},"sentenceCased":true},{"key":"Zhang2019376","type":"inproceedings","fields":{"abstract":["Most of the data is extracted and processed by Spark in Tencent Machine Learning Platform. However, seldom of them use Spark MLlib, an official machine learning (ML) library on top of Spark due to its inefficiency. In contrast, systems like parameter servers, XGBoost and TensorFlow are more used, which incur expensive cost of transferring data in and out of Spark ecosystem. In this paper, we identify the causes of inefficiency in Spark MLlib and solve the problem by building parameter servers on top of Spark. We propose PS2, a parameter server architecture that integrates Spark without hacking the core of Spark. With PS2, we leverage the power of Spark for data processing and ML training, and parameter servers for maintaining ML models. By carefully analyzing Tencent ML workloads, we figure out a widely existing computation pattern for ML models-element-wise operations among multiple high dimensional vectors. Based on this observation, we propose a new data abstraction, called Dimension Co-located Vector (DCV) for efficient model management in PS2. A DCV is a distributed vector that considers locality in parameter servers and enables efficient computation with multiple co-located distributed vectors. For ease-of-use, we also design a wide variety of advanced operators for operating DCVs. Finally, we carefully implement the PS2 system and evaluate it against existing systems on both public and Tencent workloads. Empirical results demonstrate that PS2 can outperform Spark MLlib by up to 55.6× and specialized ML systems like Petuum by up to 3.7×. © 2019 Association for Computing Machinery."],"author":["Zhang, Z.","Cui, B.","Shao, Y.","Yu, L.","Jiang, J.","Miao, X."],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.1145/3299869.3314038"],"isbn":["978-1-4503-5643-5"],"issn":["07308078"],"note":["cited By 12"],"pages":["376–388"],"publisher":["Association for Computing Machinery"],"series":["Proceedings of the ACM SIGMOD International Conference on Management of Data"],"source":["Scopus"],"title":["PS2: Parameter server on spark"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Z."},{"lastName":"Cui","firstName":"B."},{"lastName":"Shao","firstName":"Y."},{"lastName":"Yu","firstName":"L."},{"lastName":"Jiang","firstName":"J."},{"lastName":"Miao","firstName":"X."}]},"sentenceCased":true},{"key":"Zhang20201513","type":"inproceedings","fields":{"abstract":["Distributed machine learning (ML) has triggered tremendous research interest in recent years. Stochastic gradient descent (SGD) is one of the most popular algorithms for training ML models, and has been implemented in almost all distributed ML systems, such as Spark MLlib, Petuum, MXNet, and TensorFlow. However, current implementations often incur huge communication and memory overheads when it comes to large models. One important reason for this inefficiency is the row-oriented scheme (RowSGD) that existing systems use to partition the training data, which forces them to adopt a centralized model management strategy that leads to vast amount of data exchange over the network.We propose a novel, column-oriented scheme (ColumnSGD) that partitions training data by columns rather than by rows. As a result, ML model can be partitioned by columns as well, leading to a distributed configuration where individual data and model partitions can be collocated on the same machine. Following this locality property, we develop a simple yet powerful computation framework that significantly reduces communication overheads and memory footprints compared to RowSGD, for large-scale ML models such as generalized linear models (GLMs) and factorization machines (FMs). We implement ColumnSGD on top of Apache Spark, and study its performance both analytically and experimentally. Experimental results on both public and real-world datasets show that ColumnSGD is up to 930 x faster than MLlib, 63 x faster than Petuum, and 14 x faster than MXNet. © 2020 IEEE."],"art_number":["9101731"],"author":["Zhang, Z.","Wu, W.","Jiang, J.","Yu, L.","Cui, B.","Zhang, C."],"date":["2020"],"document_type":["Conference Paper"],"doi":["10.1109/ICDE48307.2020.00134"],"isbn":["978-1-72812-903-7"],"issn":["10844627"],"note":["cited By 1 \n\nTL;DR \n\nA novel, column-oriented scheme (ColumnSGD) that partitions training data by columns rather than by rows, leading to a distributed configuration where individual data and model partitions can be collocated on the same machine."],"pages":["1513–1524"],"publisher":["IEEE Computer Society"],"series":["Proceedings - International Conference on Data Engineering"],"source":["Scopus"],"title":["ColumnSGD: A column-oriented framework for distributed stochastic gradient descent"],"volume":["2020-April"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Z."},{"lastName":"Wu","firstName":"W."},{"lastName":"Jiang","firstName":"J."},{"lastName":"Yu","firstName":"L."},{"lastName":"Cui","firstName":"B."},{"lastName":"Zhang","firstName":"C."}]},"sentenceCased":true},{"key":"Zhang2020903","type":"article","fields":{"abstract":["Traditional compressed sensing MRI methods that focus on constructing better prior regularizations or numerical iterative optimizations usually suffer from heavy computational burden. Recently developed deep learning based approaches rely too much on the selection of training data and deep architecture, thus have poor abilities of generalization. To address these issues, we propose an efficient and robust algorithm to achieve the balance between reconstruction accuracy and efficiency. We construct a model-driven priori expression process and a data-driven prediction process for details restoration and artifacts correction, in a complementary perspective, realizing an integration of domain knowledge and deep representation. Further, the iteratively alternating mechanism ensures that the output propagation can be corrected in time and guided towards the desired solution in expected direction. Detailed experiments on T1 and T2 weighted data demonstrate that compared with the state-of-the-art, our method achieves higher reconstruction accuracy for all three kinds of sampling patterns and five sampling ratios, as well as higher computation efficiency on both GPU and CPU. Further experiments show that our method provides stronger robustness to data variations and noise pollution. © 2020, Beijing China Science Journal Publishing Co. Ltd. All right reserved."],"author":["Zhang, Y.","Ma, L.","Liu, R.","Cheng, S.","Fan, X.","Luo, Z."],"coden":["JFTXF"],"date":["2020"],"document_type":["Article"],"doi":["10.3724/SP.J.1089.2020.17999"],"issn":["10039775"],"journaltitle":["Jisuanji Fuzhu Sheji Yu Tuxingxue XuebaoJournal Comput.-Aided Des. Comput. Graph."],"note":["cited By 1"],"number":["6"],"pages":["903–910"],"publisher":["Institute of Computing Technology"],"source":["Scopus"],"title":["An efficient data-model dual-drive algorithm for compressed sensing MRI [数据与模型双驱动的高效压缩感知磁共振成像重构算法]"],"volume":["32"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Y."},{"lastName":"Ma","firstName":"L."},{"lastName":"Liu","firstName":"R."},{"lastName":"Cheng","firstName":"S."},{"lastName":"Fan","firstName":"X."},{"lastName":"Luo","firstName":"Z."}]},"sentenceCased":true},{"key":"Zhang2021141","type":"article","fields":{"abstract":["As current 5G communication systems cannot fulfill the stringent requirements brought by emerging applications, 6G will innovatively employ deep learning (DL) techniques to fundamentally rethink the communication systems design problem from the bottom to top layers. Although recent evidence has shown the power of DL techniques in the communication domain, the exploration and utilization of DL techniques in communication systems is still in its infancy and should come in a progressive manner. To effectively and efficiently implement DL techniques in future 6G communications in the physical layer, we give some potential deployment strategies and key enabling technologies that relate to 6G in terms of joint design of block-structured and end-to-end DL, integration of model-driven and data-driven DL, combination of online and offline training, ubiquitous learning and explainable DL techniques. © 2021 IEEE."],"author":["Zhang, S.","Liu, J.","Rodrigues, T.K.","Kato, N."],"coden":["IWCEA"],"date":["2021"],"document_type":["Article"],"doi":["10.1109/MWC.001.2000516"],"issn":["15361284"],"journaltitle":["IEEE Wirel. Commun."],"note":["cited By 0 \n\nTL;DR \n\nSome potential deployment strategies and key enabling technologies that relate to 6G in terms of joint design of block-structured and end-to-end DL, integration of model-driven and data-driven DL, combination of online and offline training, ubiquitous learning and explainable DL techniques are given."],"number":["5"],"pages":["141–147"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Deep learning techniques for advancing 6G communications in the physical layer"],"volume":["28"]},"creators":{"author":[{"lastName":"Zhang","firstName":"S."},{"lastName":"Liu","firstName":"J."},{"lastName":"Rodrigues","firstName":"T.K."},{"lastName":"Kato","firstName":"N."}]},"sentenceCased":true},{"key":"Zhang2022","type":"article","fields":{"langid":["english"],"abbrev_source_title":["J Mech Des, Trans ASME"],"affiliation":["National CAD Supported Software Engineering Centre, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China"],"art_number":["081701"],"author":["Zhang, Q.","Wu, Y.","Lu, L.","Qiao, P."],"coden":["JMDEE"],"correspondence_address1":["Wu, Y.; National CAD Supported Software Engineering Centre, China; email: cad.wyz@hust.edu.cn"],"date":["2022"],"document_type":["Article"],"doi":["10.1115/1.4053526"],"issn":["10500472"],"journaltitle":["J. Mech. Des. Trans. ASME"],"note":["cited By 0"],"number":["8"],"publisher":["American Society of Mechanical Engineers (ASME)"],"source":["Scopus"],"title":["An adaptive dendrite-HDMR metamodeling technique for high-dimensional problems"],"volume":["144"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Q."},{"lastName":"Wu","firstName":"Y."},{"lastName":"Lu","firstName":"L."},{"lastName":"Qiao","firstName":"P."}]},"sentenceCased":true},{"key":"Zhang20221037","type":"article","fields":{"abstract":["Precoding design exploiting deep learning methods has been widely studied for multiuser multiple-input multiple-output (MU-MIMO) systems. However, conventional neural precoding design applies black-box-based neural networks which are less interpretable. In this letter, we propose a deep learning-based precoding method based on an interpretable design of a neural precoding network, namely iPNet. In particular, the iPNet mimics the classic minimum mean-squared error (MMSE) precoding and approximates the matrix inversion in the design of the neural network architecture. Specifically, the proposed iPNet consists of a model-driven component network, responsible for augmenting the input channel state information (CSI), and a data-driven sub-network, responsible for precoding calculation from this augmented CSI. The latter data-driven module is explicitly interpreted as an unsupervised learner of the MMSE precoder. Simulation results show that by exploiting the augmented CSI, the proposed iPNet achieves noticeable performance gain over existing black-box designs and also exhibits enhanced generalizability against CSI mismatches. © 1997-2012 IEEE."],"author":["Zhang, S.","Xu, J.","Xu, W.","Wang, N.","Ng, D.W.K.","You, X."],"coden":["ICLEF"],"date":["2022"],"document_type":["Article"],"doi":["10.1109/LCOMM.2022.3156946"],"issn":["10897798"],"journaltitle":["IEEE Commun. Lett."],"note":["cited By 0 \n\nTL;DR \n\nA deep learning-based precoding method based on an interpretable design of a neural precoding network, namely iPNet, which mimics the classic minimum mean-squared error (MMSE) precoding and approximates the matrix inversion in the design of the neural network architecture."],"number":["5"],"pages":["1037–1041"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Data augmentation empowered neural precoding for multiuser MIMO with MMSE model"],"volume":["26"]},"creators":{"author":[{"lastName":"Zhang","firstName":"S."},{"lastName":"Xu","firstName":"J."},{"lastName":"Xu","firstName":"W."},{"lastName":"Wang","firstName":"N."},{"lastName":"Ng","firstName":"D.W.K."},{"lastName":"You","firstName":"X."}]},"sentenceCased":true},{"key":"ZHANG2022106922","type":"article","fields":{"abstract":["Context: Stack Overflow is very helpful for software developers who are seeking answers to programming problems. Previous studies have shown that a growing number of questions are of low quality and thus obtain less attention from potential answerers. Gao et al. proposed an LSTM-based model (i.e., BiLSTM-CC) to automatically generate question titles from the code snippets to improve the question quality. However, only using the code snippets in the question body cannot provide sufficient information for title generation, and LSTMs cannot capture the long-range dependencies between tokens. Objective: This paper proposes CCBERT, a deep learning based novel model to enhance the performance of question title generation by making full use of the bi-modal information of the entire question body. Method: CCBERT follows the encoder–decoder paradigm and uses CodeBERT to encode the question body into hidden representations, a stacked Transformer decoder to generate predicted tokens, and an additional copy attention layer to refine the output distribution. Both the encoder and decoder perform the multi-head self-attention operation to better capture the long-range dependencies. This paper builds a dataset containing around 200,000 high-quality questions filtered from the data officially published by Stack Overflow to verify the effectiveness of the CCBERT model. Results: CCBERT outperforms all the baseline models on the dataset. Experiments on both code-only and low-resource datasets show the superiority of CCBERT with less performance degradation. The human evaluation also shows the excellent performance of CCBERT concerning both readability and correlation criteria. Conclusion: CCBERT is capable of automatically capturing the bi-modal semantic information from the entire question body and parsing the long-range dependencies to achieve better performance. Therefore, CCBERT is an effective approach for generating Stack Overflow question titles."],"author":["Zhang, Fengji","Yu, Xiao","Keung, Jacky","Li, Fuyang","Xie, Zhiwen","Yang, Zhen","Ma, Caoyuan","Zhang, Zhimin"],"date":["2022"],"doi":["10.1016/j.infsof.2022.106922"],"issn":["0950-5849"],"journaltitle":["Inf. Softw. Technol."],"keywords":["CodeBERT","Copy mechanism","Stack Overflow","Title generation"],"pages":["106922"],"title":["Improving Stack Overflow question title generation with copying enhanced CodeBERT model and bi-modal information"],"volume":["148"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Fengji"},{"lastName":"Yu","firstName":"Xiao"},{"lastName":"Keung","firstName":"Jacky"},{"lastName":"Li","firstName":"Fuyang"},{"lastName":"Xie","firstName":"Zhiwen"},{"lastName":"Yang","firstName":"Zhen"},{"lastName":"Ma","firstName":"Caoyuan"},{"lastName":"Zhang","firstName":"Zhimin"}]},"sentenceCased":true},{"key":"Zhang2022190","type":"article","fields":{"langid":["chinese"],"abbrev_source_title":["Jixie Gongcheng Xuebao"],"affiliation":["School of Astronautics, Beijing Institute of Technology, Beijing, 100081, China; China Aerodynamic Research and Development Center, Mianyang, 621000, China"],"author":["Zhang, L.","Chen, J.","Xiong, F.","Ren, C.","Li, C."],"coden":["CHHKA"],"correspondence_address1":["Xiong, F.; School of Astronautics, China; email: fenfenx@bit.edu.cn"],"date":["2022"],"document_type":["Article"],"doi":["10.3901/JME.2022.01.190"],"issn":["05776686"],"journaltitle":["Jixie Gongcheng XuebaoJournal Mech. Eng."],"note":["cited By 0"],"number":["1"],"pages":["190–200"],"publisher":["Chinese Mechanical Engineering Society"],"source":["Scopus"],"title":["Meta-Learning Based Multi-Fidelity Deep Neural Networks Metamodel Method [基于元学习的多可信度深度神经网络代理模型]"],"volume":["58"]},"creators":{"author":[{"lastName":"Zhang","firstName":"L."},{"lastName":"Chen","firstName":"J."},{"lastName":"Xiong","firstName":"F."},{"lastName":"Ren","firstName":"C."},{"lastName":"Li","firstName":"C."}]}},{"key":"Zhang20222368","type":"article","fields":{"abstract":["Accurate downlink channel information is crucial to the beamforming design, but it is difficult to obtain in practice. This paper investigates a deep learning-based optimization approach of the downlink beamforming to maximize the system sum rate, when only the uplink channel information is available. Our main contribution is to propose a model-driven learning technique that exploits the structure of the optimal downlink beamforming to design an effective hybrid learning strategy with the aim to maximize the sum rate performance. This is achieved by jointly considering the learning performance of the downlink channel, the power and the sum rate in the training stage. The proposed approach applies to generic cases in which the uplink channel information is available, but its relation to the downlink channel is unknown and does not require an explicit downlink channel estimation. We further extend the developed technique to massive multiple-input multiple-output scenarios and achieve a distributed learning strategy for multicell systems without an inter-cell signalling overhead. Simulation results verify that our proposed method provides the performance close to the state of the art numerical algorithms with perfect downlink channel information and significantly outperforms existing data-driven methods in terms of the sum rate. © 2002-2012 IEEE."],"author":["Zhang, J.","You, M.","Zheng, G.","Krikidis, I.","Zhao, L."],"date":["2022"],"document_type":["Article"],"doi":["10.1109/TWC.2021.3111843"],"issn":["15361276"],"journaltitle":["IEEE Trans. Wirel. Commun."],"note":["cited By 0 \n\nTL;DR \n\nThis paper investigates a deep learning-based optimization approach of the downlink beamforming to maximize the system sum rate, when only the uplink channel information is available and significantly outperforms existing data-driven methods in terms of the sum rate."],"number":["4"],"pages":["2368–2382"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Model-driven learning for generic MIMO downlink beamforming with uplink channel information"],"volume":["21"]},"creators":{"author":[{"lastName":"Zhang","firstName":"J."},{"lastName":"You","firstName":"M."},{"lastName":"Zheng","firstName":"G."},{"lastName":"Krikidis","firstName":"I."},{"lastName":"Zhao","firstName":"L."}]},"sentenceCased":true},{"key":"zhangCodeBERTAttackAdversarial2023","type":"article","fields":{"langid":["english"],"author":["Zhang, Huangzhao","Lu, Shuai","Li, Zhuo","Jin, Zhi","Ma, Lei","Liu, Yang","Li, Ge"],"date":["2023-05-15"],"doi":["10.1002/smr.2571"],"issn":["2047-7473, 2047-7481"],"journaltitle":["J Software Evolu Process"],"pages":["e2571"],"shorttitle":["CodeBERT‐Attack"],"title":["CodeBERT‐Attack: Adversarial attack against source code deep learning models via Pre‐trained model"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Huangzhao"},{"lastName":"Lu","firstName":"Shuai"},{"lastName":"Li","firstName":"Zhuo"},{"lastName":"Jin","firstName":"Zhi"},{"lastName":"Ma","firstName":"Lei"},{"lastName":"Liu","firstName":"Yang"},{"lastName":"Li","firstName":"Ge"}]},"sentenceCased":true},{"key":"zhangOptimalityNaiveBayes2004","type":"inproceedings","fields":{"abstract":["Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surprising, because the conditional independence assumption on which it is based, is rarely true in realworld applications. An open question is: what is the true reason for the surprisingly good performance of naive Bayes in classification? In this paper, we propose a novel explanation on the superb classification performance of naive Bayes. We show that, essentially, the dependence distribution; i.e., how the local dependence of a node distributes in each class, evenly or unevenly, and how the local dependencies of all nodes work together, consistently (supporting a certain classification) or inconsistently (canceling each other out), plays a crucial role. Therefore, no matter how strong the dependences among attributes are, naive Bayes can still be optimal if the dependences distribute evenly in classes, or if the dependences cancel each other out. We propose and prove a sufficient and necessary conditions for the optimality of naive Bayes. Further, we investigate the optimality of naive Bayes under the Gaussian distribution. We present and prove a sufficient condition for the optimality of naive Bayes, in which the dependence between attributes do exist. This provides evidence that dependence among attributes may cancel out each other. In addition, we explore when naive Bayes works well."],"added-at":["2011-03-27T19:35:34.000+0200"],"author":["Zhang, Harry"],"biburl":["https://www.bibsonomy.org/bibtex/29288cd3adf6e5273ce7f8b74beb4c6e2/cocus"],"booktitle":["Proc. Seventeenth Int. Fla. Artif. Intell. Res. Soc. Conf. FLAIRS 2004"],"booktitleaddon":["May 17-19, 2004"],"date":["2004"],"editor":["Barr, Valerie","Markov, Zdravko"],"interhash":["a8e31b4197a90abcb0bdb2b93504acda"],"intrahash":["9288cd3adf6e5273ce7f8b74beb4c6e2"],"keywords":["bayesian","naive-bayes"],"owner":["CK"],"publisher":["AAAI Press"],"timestamp":["2011-03-27T19:35:45.000+0200"],"title":["The optimality of naive bayes"],"venue":["Miami Beach, Florida, USA"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Harry"}],"editor":[{"lastName":"Barr","firstName":"Valerie"},{"lastName":"Markov","firstName":"Zdravko"}]},"sentenceCased":true},{"key":"zhangTPPFAMUseThreshold2014","type":"article","fields":{"abstract":["The issue of category proliferation caused by the overlapping classes in fuzzy ARTMAP (FAM) is addressed in this paper. A new FAM-based neural architecture called TTPFAM is proposed, which can reduce category proliferation by performing a threshold filtering mechanism before a new category created during training, and improve the classification accuracy by combining prediction distributed by the dynamic Q-max rule and posterior probability estimated during testing. The TPPFAM can produce a small size of neural network architecture without degradation of the classification accuracy. The algorithm is evaluated in terms of the classification accuracy and the number of categories by experiments on both artificial and real data, and the results show that the performance of TPPFAM is better than that of the other models."],"author":["Zhang, Yongquan","Ji, Hongbing","Zhang, Wenbo"],"date":["2014"],"issn":["0925-2312"],"journaltitle":["Neurocomputing"],"keywords":["Category proliferation","Fuzzy ARTMAP (FAM)","Overlapping classes","Posterior probability","Threshold adjustment parameter"],"nodoi":["https://doi.org/10.1016/j.neucom.2013.07.042"],"pages":["63–71"],"title":["TPPFAM: Use of threshold and posterior probability for category reduction in fuzzy ARTMAP"],"url":["http://www.sciencedirect.com/science/article/pii/S0925231213008151"],"volume":["124"]},"creators":{"author":[{"lastName":"Zhang","firstName":"Yongquan"},{"lastName":"Ji","firstName":"Hongbing"},{"lastName":"Zhang","firstName":"Wenbo"}]},"sentenceCased":true},{"key":"zhao2005","type":"article","fields":{"abstract":["Fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. In particular, clustering algorithms that build meaningful hierarchies out of large document collections are ideal tools for their interactive visualization and exploration as they provide data-views that are consistent, predictable, and at different levels of granularity. This paper focuses on document clustering algorithms that build such hierarchical solutions and (i) presents a comprehensive study of partitional and agglomerative algorithms that use different criterion functions and merging schemes, and (ii) presents a new class of clustering algorithms called constrained agglomerative algorithms, which combine features from both partitional and agglomerative approaches that allows them to reduce the early-stage errors made by agglomerative methods and hence improve the quality of clustering solutions. The experimental evaluation shows that, contrary to the common belief, partitional algorithms always lead to better solutions than agglomerative algorithms; making them ideal for clustering large document collections due to not only their relatively low computational requirements, but also higher clustering quality. Furthermore, the constrained agglomerative methods consistently lead to better solutions than agglomerative methods alone and for many cases they outperform partitional methods, as well."],"acmid":["1061908"],"added-at":["2011-09-18T22:25:48.000+0200"],"address":["Hingham, MA, USA"],"author":["Zhao, Ying","Karypis, George","Fayyad, Usama"],"biburl":["http://www.bibsonomy.org/bibtex/21afe6065cc536f52534a7c15eed599c3/jil"],"date":["2005-03"],"interhash":["fdb19684fd849b0c44ac0fb996b7888e"],"intrahash":["1afe6065cc536f52534a7c15eed599c3"],"issn":["1384-5810"],"journaltitle":["Data Min. Knowl. Discov."],"keywords":["cluster clustering entropy evaluation f-score fscore measure measures purity"],"nodoi":["10.1007/s10618-005-0361-3"],"note":["TL;DR \n\nThe experimental evaluation shows that, contrary to the common belief, partitional algorithms always lead to better solutions than agglomerative algorithms; making them ideal for clustering large document collections due to not only their relatively low computational requirements, but also higher clustering quality."],"number":["2"],"numpages":["28"],"pages":["141–168"],"publisher":["Kluwer Academic Publishers"],"timestamp":["2013-11-23T20:11:51.000+0100"],"title":["Hierarchical clustering algorithms for document datasets"],"url":["http://dl.acm.org/citation.cfm?id=1061897.1061908"],"volume":["10"]},"creators":{"author":[{"lastName":"Zhao","firstName":"Ying"},{"lastName":"Karypis","firstName":"George"},{"lastName":"Fayyad","firstName":"Usama"}]},"sentenceCased":true},{"key":"ZHAO20192018EDP7227","type":"article","fields":{"author":["Zhao, Xiaoqiong","Li, Shanping","Yu, Huan","Wang, Ye","Qiu, Weiwei"],"date":["2019"],"doi":["10.1587/transinf.2018EDP7227"],"journaltitle":["IEICE Trans. Inf. Syst."],"number":["3"],"pages":["522–536"],"title":["Accurate library recommendation using combining collaborative filtering and topic model for mobile development"],"volume":["E102.D"]},"creators":{"author":[{"lastName":"Zhao","firstName":"Xiaoqiong"},{"lastName":"Li","firstName":"Shanping"},{"lastName":"Yu","firstName":"Huan"},{"lastName":"Wang","firstName":"Ye"},{"lastName":"Qiu","firstName":"Weiwei"}]},"sentenceCased":true},{"key":"Zhao2022","type":"article","fields":{"langid":["english"],"abbrev_source_title":["Mob. Inf. Sys."],"affiliation":["Department of Art and Design, Shijiazhuang University of Applied Technology, Shijiazhuang, 050081, China"],"art_number":["3534167"],"author":["Zhao, Y."],"correspondence_address1":["Zhao, Y.; Department of Art and Design, China; email: 2013010678@sjzpt.edu.cn"],"date":["2022"],"document_type":["Article"],"doi":["10.1155/2022/3534167"],"issn":["1574017X"],"journaltitle":["Mob. Inf. Syst."],"note":["cited By 0 \n\nTL;DR \n\nThis research creates a user interface framework based on interaction behavior from the user’s perspective and incorporates user requirements and provides a scientific reference for the development and design of user interfaces."],"publisher":["Hindawi Limited"],"source":["Scopus"],"title":["Interaction design system for artificial intelligence user interfaces based on UML extension mechanisms"],"volume":["2022"]},"creators":{"author":[{"lastName":"Zhao","firstName":"Y."}]},"sentenceCased":true},{"key":"zhaoAutomaticModelSelection2023","type":"online","fields":{"abstract":["Chain-of-Thought (CoT) and Program-Aided Language Models (PAL) represent two distinct reasoning methods, each with its own strengths. CoT employs natural language, offering flexibility and interpretability, while PAL utilizes programming language, yielding more structured and rigorous logic. We introduce a model selection method to combine the best of both worlds by employing a large language model (LLM) to dynamically select between them. Our theoretical analysis underscores the feasibility of this method, which is further corroborated by empirical results. Our proposed method demonstrates significant performance improvements across eight reasoning datasets with Codex, ChatGPT, and GPT-4. Additionally, our method is complementary to self-consistency; when integrated, it can further enhance performance while significantly reducing computation costs. Moreover, we achieve new state-of-the-art results on GSM8K and SVAMP, with respective accuracies of 96.8% and 93.7%. Our code, data and prompts are available at https://github.com/XuZhao0/Model-Selection-Reasoning"],"author":["Zhao, James Xu","Xie, Yuxi","Kawaguchi, Kenji","He, Junxian","Xie, Michael Qizhe"],"date":["2023-10-23"],"doi":["10.48550/arXiv.2305.14333"],"eprint":["2305.14333"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Computation and Language"],"note":["Comment: EMNLP 2023 Findings \n\nTL;DR \n\nThis work introduces a model selection method to combine the best of both worlds by employing a large language model (LLM) to dynamically select between them, and demonstrates significant performance improvements across eight reasoning datasets with Codex, ChatGPT, and GPT-4."],"pubstate":["preprint"],"title":["Automatic Model Selection with Large Language Models for Reasoning"]},"creators":{"author":[{"lastName":"Zhao","firstName":"James Xu"},{"lastName":"Xie","firstName":"Yuxi"},{"lastName":"Kawaguchi","firstName":"Kenji"},{"lastName":"He","firstName":"Junxian"},{"lastName":"Xie","firstName":"Michael Qizhe"}]}},{"key":"zhaoOndemandServiceAggregation2019","type":"article","fields":{"abbrev_source_title":["Intell. Data Anal."],"abstract":["'Internet plus' application service recommendation is challenged by two issues: One is the increase in service volume and the disorderliness of the service organizations. A second is the diversification of user requirements. The research focus of this study was to investigate how to achieve more ordered aggregation and recommend services that meet the individualized requirements of users. This paper addresses the disorderliness of conventional service aggregation and considers the aggregation requirements of QoS weights with non-functional targets. Based on semantic relevance using the role (R), goal (G), process (P), service (S) demand metamodel, an RGPS association is proposed that is a weighted network for ordered QoS service aggregation. An individualized service recommendation method then is provided, based on an LSTM neural network with role and target backstepping using RGPS association network, that can achieve a high-quality precision service. Finally, a simulation experiment was carried out on service recommendations in the tourism domain, which verified the precision, effectiveness and application value of the service recommendation method. © 2019 - IOS Press and the authors. All rights reserved."],"affiliation":["Department School of Computer Science, Wuhan University, Wuhan, China; Department School of Data Science and Software Engineering, Qingdao University, Qingdao, China"],"author":["Zhao, Y.","Guo, J.","He, K."],"correspondence_address1":["Zhao, Y.; Department School of Computer Science, China; email: ivwepriu@sina.com"],"date":["2019"],"document_type":["Conference Paper"],"doi":["10.3233/IDA-192628"],"ids":["Zhao2019S3"],"issn":["1088467X"],"journaltitle":["Intell. Data Anal."],"keywords":["Application services","Conventional services","Long short-term memory","Meta model","nonfunctional target requirement","On-demand services","Semantic relevance","Semantics","Service organizations","Service recommendations"],"note":["cited By 0 \n\ncited By 0"],"number":["S1"],"pages":["S3-S23"],"publisher":["IOS Press"],"source":["Scopus"],"title":["An on-demand service aggregation and service recommendation method based on RGPS"],"volume":["23"]},"creators":{"author":[{"lastName":"Zhao","firstName":"Y."},{"lastName":"Guo","firstName":"J."},{"lastName":"He","firstName":"K."}]},"sentenceCased":true},{"key":"zhaoUserbasedCollaborativefilteringRecommendation2010","type":"inproceedings","fields":{"acmid":["1749278"],"author":["Zhao, Zhi-Dan","Shang, Ming-sheng"],"booktitle":["Proc. 2010 Third Int. Conf. Knowl. Discov. Data Min."],"date":["2010"],"isbn":["978-0-7695-3923-2"],"keywords":["cloud computing","collaborative filtering","hadoop","Map-Reduce","recommender systems"],"location":["Washington, DC, USA"],"nodoi":["10.1109/WKDD.2010.54"],"note":["TL;DR \n\nThis paper implements user-based CF algorithm on a cloud computing platform, namely Hadoop, to solve the scalability problem of CF."],"numpages":["4"],"pages":["478–481"],"publisher":["IEEE Computer Society"],"series":["WKDD '10"],"title":["User-based collaborative-filtering recommendation algorithms on hadoop"],"url":["https://doi.org/10.1109/WKDD.2010.54"]},"creators":{"author":[{"lastName":"Zhao","firstName":"Zhi-Dan"},{"lastName":"Shang","firstName":"Ming-sheng"}]},"sentenceCased":true},{"key":"Zheng201210","type":"article","fields":{"abstract":["Almost all previous approaches on coronary artery centerline extraction are data-driven, which try to trace a centerline from an automatically detected or manually specified coronary ostium. No or little high level prior information is used; therefore, the centerline tracing procedure may terminate early at a severe occlusion or an anatomically inconsistent centerline course may be generated. In this work, we propose a model-driven approach to extracting the three major coronary arteries. The relative position of the major coronary arteries with respect to the heart chambers is stable, therefore the automatically segmented chambers can be used to predict the initial position of these coronary centerlines. The initial centerline is further refined using a machine learning based vesselness measurement. The proposed approach can handle variations in the length and topology of an artery, and it is more robust under severe occlusions than a data-driven approach. The extracted centerlines are already labeled, therefore no additional vessel labeling procedure is needed. Quantitative comparison on 54 cardiac CT datasets demonstrates the robustness of the proposed method over a state-of-the-art data-driven approach. © 2012 Springer-Verlag."],"author":["Zheng, Y.","Shen, J.","Tek, H.","Funka-Lea, G."],"date":["2012"],"document_type":["Conference Paper"],"doi":["10.1007/978-3-642-35428-1_2"],"isbn":["9783642354274"],"issn":["03029743"],"journaltitle":["Lect. Notes Comput. Sci. Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinforma."],"note":["cited By 6"],"pages":["10–18"],"source":["Scopus"],"title":["Model-driven centerline extraction for severely occluded major coronary arteries"],"volume":["7588 LNCS"]},"creators":{"author":[{"lastName":"Zheng","firstName":"Y."},{"lastName":"Shen","firstName":"J."},{"lastName":"Tek","firstName":"H."},{"lastName":"Funka-Lea","firstName":"G."}]},"sentenceCased":true},{"key":"Zheng201375","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["Proc Int Conf Appl Spec Syst Arcitec Process Proc"],"affiliation":["NanoSystem Design Laboratory, University of North Texas, Denton, TX 76203, United States"],"art_number":["6567553"],"author":["Zheng, G.","Mohanty, S.P.","Kougianos, E.","Okobiah, O."],"coden":["PIAAF"],"correspondence_address1":["NanoSystem Design Laboratory, , Denton, TX 76203, United States"],"date":["2013"],"document_type":["Conference Paper"],"doi":["10.1109/ASAP.2013.6567553"],"isbn":["978-1-4799-0492-1"],"issn":["10636862"],"note":["cited By 0"],"pages":["75–78"],"series":["Proceedings of the International Conference on Application-Specific Systems, Architectures and Processors"],"source":["Scopus"],"title":["IVAMS: Intelligent metamodel-integrated Verilog-AMS for circuit-accurate system-level mixed-signal design exploration"]},"creators":{"author":[{"lastName":"Zheng","firstName":"G."},{"lastName":"Mohanty","firstName":"S.P."},{"lastName":"Kougianos","firstName":"E."},{"lastName":"Okobiah","firstName":"O."}]},"sentenceCased":true},{"key":"zhengCodEXSourceCode2018","type":"inproceedings","fields":{"author":["Zheng, Mengya","Pan, Xingyu","Lillis, David"],"bibsource":["dblp computer science bibliography, https://dblp.org"],"biburl":["https://dblp.org/rec/bib/conf/aics/ZhengPL18"],"booktitle":["Proc. 26th AIAI Ir. Conf. Artif. Intell. Cogn. Sci. Trinity Coll. Dublin Dublin Irel. Dec. 6-7th 2018"],"date":["2018"],"pages":["362–373"],"timestamp":["Tue, 08 Jan 2019 17:34:19 +0100"],"title":["CodEX: Source code plagiarism detection based on abstract syntax tree"],"url":["http://ceur-ws.org/Vol-2259/aics_33.pdf"]},"creators":{"author":[{"lastName":"Zheng","firstName":"Mengya"},{"lastName":"Pan","firstName":"Xingyu"},{"lastName":"Lillis","firstName":"David"}]},"sentenceCased":true},{"key":"zhou_assessing_2021","type":"inproceedings","fields":{"abstract":["Pre-trained models like BERT have achieved strong improvements on many natural language processing (NLP) tasks, showing their great generalizability. The success of pre-trained models in NLP inspires pre-trained models for programming language. Recently, CodeBERT, a model for both natural language (NL) and programming language (PL), pre-trained on code search dataset, is proposed. Although promising, CodeBERT has not been evaluated beyond its pre-trained dataset for NL-PL tasks. Also, it has only been shown effective on two tasks that are close in nature to its pre-trained data. This raises two questions: Can CodeBERT generalize beyond its pre-trained data? Can it generalize to various software engineering tasks involving NL and PL? Our work answers these questions by performing an empirical investigation into the generalizability of CodeBERT. First, we assess the generalizability of CodeBERT to datasets other than its pre-training data. Specifically, considering the code search task, we conduct experiments on another dataset containing Python code snippets and their corresponding documentation. We also consider yet another dataset of questions and answers collected from Stack Overflow about Python programming. Second, to assess the generalizability of CodeBERT to various software engineering tasks, we apply CodeBERT to the just-in-time defect prediction task. Our empirical results support the generalizability of CodeBERT on the additional data and task. CodeBERT-based solutions can achieve higher or comparable performance than specialized solutions designed for the code search and just-in-time defect prediction tasks. However, the superior performance of the CodeBERT requires a tradeoff; for example, it requires much more computation resources as compared to specialized code search approaches."],"author":["Zhou, Xin","Han, DongGyun","Lo, David"],"booktitle":["2021 IEEE Int. Conf. Softw. Maint. Evol. ICSME"],"date":["2021-09"],"doi":["10.1109/ICSME52107.2021.00044"],"keywords":["CodeBERT","Codes","Computational modeling","Conferences","Documentation","generalizability","Natural language processing","pre-trained model","Programming","Software maintenance"],"note":["ISSN: 2576-3148"],"pages":["425–436"],"title":["Assessing Generalizability of CodeBERT"]},"creators":{"author":[{"lastName":"Zhou","firstName":"Xin"},{"lastName":"Han","firstName":"DongGyun"},{"lastName":"Lo","firstName":"David"}]}},{"key":"zhou_boosting_2020","type":"article","fields":{"langid":["english"],"abstract":["Developers often need to use appropriate APIs to program efficiently, but it is usually a difficult task to identify the exact one they need from a vast of candidates. To ease the burden, a multitude of API recommendation approaches have been proposed. However, most of the currently available API recommenders do not support the effective integration of users’ feedback into the recommendation loop. In this paper, we propose a framework, BRAID (Boosting RecommendAtion with Implicit FeeDback), which leverages learningto-rank and active learning techniques to boost recommendation performance. By exploiting users’ feedback information, we train a learning-to-rank model to re-rank the recommendation results. In addition, we speed up the feedback learning process with active learning. Existing query-based API recommendation approaches can be plugged into BRAID. We select three state-of-the-art API recommendation approaches as baselines to demonstrate the performance enhancement of BRAID measured by Hit@k (Top-k), MAP, and MRR. Empirical experiments show that, with acceptable overheads, the recommendation performance improves steadily and substantially with the increasing percentage of feedback data, comparing with the baselines."],"author":["Zhou, Yu","Yang, Xinying","Chen, Taolue","Huang, Zhiqiu","Ma, Xiaoxing","Gall, Harald"],"date":["2020-02"],"eprint":["2002.01264"],"eprintclass":["cs"],"eprinttype":["arxiv"],"journaltitle":["ArXiv200201264 Cs"],"keywords":["Computer Science - Information Retrieval","Computer Science - Software Engineering"],"note":["arXiv: 2002.01264 \n\nComment: 13 pages, 4 figures \n\nTL;DR \n\nA framework, BRAID (Boosting RecommendAtion with Implicit FeeDback), which leverages learning-to-rank and active learning techniques to boost recommendation performance and speed up the feedback learning process with active learning is proposed."],"nourl":["http://arxiv.org/abs/2002.01264"],"title":["Boosting API Recommendation with Implicit Feedback"]},"creators":{"author":[{"lastName":"Zhou","firstName":"Yu"},{"lastName":"Yang","firstName":"Xinying"},{"lastName":"Chen","firstName":"Taolue"},{"lastName":"Huang","firstName":"Zhiqiu"},{"lastName":"Ma","firstName":"Xiaoxing"},{"lastName":"Gall","firstName":"Harald"}]}},{"key":"Zhou201913073","type":"inproceedings","fields":{"abstract":["In this paper we show that generative adversarial networks (GANs) without restriction on the discriminative function space commonly suffer from the problem that the gradient produced by the discriminator is uninformative to guide the generator. By contrast, Wasserstein GAN (WGAN), where the discriminative function is restricted to 1-Lipschitz, does not suffer from such a gradient uninformativeness problem. We further show in the paper that the model with a compact dual form of Wasserstein distance, where the Lipschitz condition is relaxed, may also theoretically suffer from this issue. This implies the importance of Lipschitz condition and motivates us to study the general formulation of GANs with Lipschitz constraint, which leads to a new family of GANs that we call Lipschitz GANs (LGANs). We show that LGANs guarantee the existence and uniqueness of the optimal discriminative function as well as the existence of a unique Nash equilibrium. We prove that LGANs are generally capable of eliminating the gradient uninformativeness problem. According to our empirical analysis, LGANs arc more stable and generate consistently higher quality samples compared with WGAN. © 36th International Conference on Machine Learning, ICML 2019. All rights reserved."],"author":["Zhou, Z.","Liang, J.","Song, Y.","Yu, L.","Wang, H.","Zhang, W.","Yu, Y.","Zhang, Z."],"date":["2019"],"document_type":["Conference Paper"],"isbn":["978-1-5108-8698-8"],"keywords":["TECHNIQUE_CNN"],"note":["cited By 8 \n\nTL;DR \n\nLGANs guarantee the existence and uniqueness of the optimal discriminative function as well as the existence of a unique Nash equilibrium and it is proved that LGANs are generally capable of eliminating the gradient uninformativeness problem."],"pages":["13073–13082"],"publisher":["International Machine Learning Society (IMLS)"],"series":["36th International Conference on Machine Learning, ICML 2019"],"source":["Scopus"],"title":["Lipschitz generative adversarial nets"],"url":["https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078069337&partnerID=40&md5=57519b6411b2d299d1e26de2d419dcef"],"volume":["2019-June"]},"creators":{"author":[{"lastName":"Zhou","firstName":"Z."},{"lastName":"Liang","firstName":"J."},{"lastName":"Song","firstName":"Y."},{"lastName":"Yu","firstName":"L."},{"lastName":"Wang","firstName":"H."},{"lastName":"Zhang","firstName":"W."},{"lastName":"Yu","firstName":"Y."},{"lastName":"Zhang","firstName":"Z."}]},"sentenceCased":true},{"key":"zhouMoreAccurateContent2014","type":"inproceedings","fields":{"acmid":["2597142"],"author":["Zhou, Bo","Xia, Xin","Lo, David","Tian, Cong","Wang, Xinyu"],"booktitle":["Proc. 22Nd Int. Conf. Program Comprehension"],"date":["2014"],"isbn":["978-1-4503-2879-1"],"keywords":["API Discussion","Cache-Based Method","Composite Method","Text Categorization"],"location":["New York, NY, USA"],"nodoi":["10.1145/2597008.2597142"],"note":["TL;DR \n\nA Cache-bAsed compoSitE algorithm, short formed as CASE, to automatically categorize API discussions, which outperforms the state-of-the-art method proposed by Hou and Mo by 11%, 10%, and 2%, respectively."],"numpages":["11"],"pages":["95–105"],"publisher":["ACM"],"series":["ICPC 2014"],"title":["Towards more accurate content categorization of API discussions"],"url":["http://doi.acm.org/10.1145/2597008.2597142"]},"creators":{"author":[{"lastName":"Zhou","firstName":"Bo"},{"lastName":"Xia","firstName":"Xin"},{"lastName":"Lo","firstName":"David"},{"lastName":"Tian","firstName":"Cong"},{"lastName":"Wang","firstName":"Xinyu"}]},"sentenceCased":true},{"key":"Zhu20215434","type":"article","fields":{"abstract":["This paper considers the massive connectivity problem in an asynchronous grant-free random access system, where a huge number of devices sporadically transmit data to a base station (BS) with imperfect synchronization. The goal is to design algorithms for joint user activity detection, delay detection, and channel estimation. By exploiting the sparsity on both user activity and delays, we formulate a hierarchical sparse signal recovery problem in both the single-antenna and the multiple-antenna scenarios. While traditional compressed sensing algorithms can be applied to these problems, they suffer high computational complexity and often require the perfect statistical information of channel and devices. This paper solves these problems by designing the Learned Approximate Message Passing (LAMP) network, which belongs to model-driven deep learning approaches and ensures efficient performance without tremendous training data. Particularly, in the multiple-antenna scenario, we design three different LAMP structures, namely, distributed, centralized and hybrid ones, to balance the performance and complexity. Simulation results demonstrate that the proposed LAMP networks can significantly outperform the conventional AMP method thanks to their ability of parameter learning. It is also shown that LAMP has robust performance to the maximal delay spread of the asynchronous users. © 2002-2012 IEEE."],"art_number":["9390399"],"author":["Zhu, W.","Tao, M.","Yuan, X.","Guan, Y."],"date":["2021"],"document_type":["Article"],"doi":["10.1109/TWC.2021.3067903"],"issn":["15361276"],"journaltitle":["IEEE Trans. Wirel. Commun."],"note":["cited By 4"],"number":["8"],"pages":["5434–5448"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"source":["Scopus"],"title":["Deep-learned approximate message passing for asynchronous massive connectivity"],"volume":["20"]},"creators":{"author":[{"lastName":"Zhu","firstName":"W."},{"lastName":"Tao","firstName":"M."},{"lastName":"Yuan","firstName":"X."},{"lastName":"Guan","firstName":"Y."}]},"sentenceCased":true},{"key":"zhuCanChatGPTReproduce2023","type":"online","fields":{"abstract":["The release of ChatGPT has uncovered a range of possibilities whereby large language models (LLMs) can substitute human intelligence. In this paper, we seek to understand whether ChatGPT has the potential to reproduce human-generated label annotations in social computing tasks. Such an achievement could significantly reduce the cost and complexity of social computing research. As such, we use ChatGPT to re-label five seminal datasets covering stance detection (2x), sentiment analysis, hate speech, and bot detection. Our results highlight that ChatGPT does have the potential to handle these data annotation tasks, although a number of challenges remain. ChatGPT obtains an average precision 0.609. Performance is highest for the sentiment analysis dataset, with ChatGPT correctly annotating 64.9% of tweets. Yet, we show that performance varies substantially across individual labels. We believe this work can open up new lines of analysis and act as a basis for future research into the exploitation of ChatGPT for human annotation tasks."],"author":["Zhu, Yiming","Zhang, Peixian","Haq, Ehsan-Ul","Hui, Pan","Tyson, Gareth"],"date":["2023-04-20"],"eprint":["2304.10145"],"eprintclass":["cs"],"eprinttype":["arxiv"],"keywords":["Computer Science - Artificial Intelligence","Computer Science - Computation and Language","LOGSEQ"],"pubstate":["preprint"],"shorttitle":["Can ChatGPT Reproduce Human-Generated Labels?"],"title":["Can ChatGPT Reproduce Human-Generated Labels? A Study of Social Computing Tasks"],"url":["http://arxiv.org/abs/2304.10145"],"urldate":["2023-04-21"]},"creators":{"author":[{"lastName":"Zhu","firstName":"Yiming"},{"lastName":"Zhang","firstName":"Peixian"},{"lastName":"Haq","firstName":"Ehsan-Ul"},{"lastName":"Hui","firstName":"Pan"},{"lastName":"Tyson","firstName":"Gareth"}]}},{"key":"zhuMiningAPIUsage2014","type":"inproceedings","fields":{"langid":["english"],"abstract":["Lack of effective usage examples in API documents has been proven to be a great obstacle to API learning. To deal with this issue, several approaches have been proposed to automatically extract usage examples from client code or related web pages, which are unfortunately not available for newly released API libraries. In this paper, we propose a novel approach to mining API usage examples from test code. Although test code can be a good source of usage examples, the issue of multiple test scenarios might lead to repetitive and interdependent API usages in a test method, which make it complicated and difficult to extract API usage examples. To address this issue, we study the JUnit test code and summarize a set of test code patterns. We employ a code pattern based heuristic slicing approach to separate test scenarios into code examples. Then we cluster the similar usage examples for recommendation. An evaluation on four open source software libraries demonstrates that the accuracy of our approach is much higher than the state-of-art approach eXoaDoc on test code. Furthermore, we have developed an Eclipse plugin tool UsETeC."],"author":["Zhu, Zixiao","Zou, Yanzhen","Xie, Bing","Jin, Yong","Lin, Zeqi","Zhang, Lu"],"date":["2014-09"],"doi":["10.1109/ICSME.2014.52"],"isbn":["978-1-4799-6146-7"],"pages":["301–310"],"publisher":["IEEE"],"title":["Mining API Usage Examples from Test Code"]},"creators":{"author":[{"lastName":"Zhu","firstName":"Zixiao"},{"lastName":"Zou","firstName":"Yanzhen"},{"lastName":"Xie","firstName":"Bing"},{"lastName":"Jin","firstName":"Yong"},{"lastName":"Lin","firstName":"Zeqi"},{"lastName":"Zhang","firstName":"Lu"}]}},{"key":"zolotasRESTsecLowcodePlatform2018","type":"article","fields":{"langid":["english"],"abstract":["In the modern business world it is increasingly often that Enterprises opt to bring their business model online, in their effort to reach out to more end users and increase their customer base. While transitioning to the new model, enterprises consider securing their data of pivotal importance. In fact, many efforts have been introduced to automate this ‘webification’ process; however, they all fall short in some aspect: a) they either generate only the security infrastructure, assigning implementation to the developers, b) they embed mainstream, less powerful authorisation schemes, or c) they disregard the merits of the dominating REST architecture and adopt less suitable approaches. In this paper we present RESTsec, a Low-Code platform that supports rapid security requirements modelling for Enterprise Services, abiding by the state of the art ABAC authorisation scheme. RESTsec enables the developer to seamlessly embed the desired access control policy and generate the service, the security infrastructure and the code. Evaluation shows that our approach is valid and can help developers deliver secure by design enterprise services in a rapid and automated manner."],"author":["Zolotas, Christoforos","Chatzidimitriou, Kyriakos C.","Symeonidis, Andreas L."],"date":["2018-10-21"],"doi":["10.1080/17517575.2018.1462403"],"issn":["1751-7575, 1751-7583"],"journaltitle":["Enterprise Information Systems"],"keywords":["lowcode"],"number":["8-9"],"pages":["1007–1033"],"shorttitle":["RESTsec"],"title":["RESTsec: A low-code platform for generating secure by design enterprise services"],"volume":["12"]},"creators":{"author":[{"lastName":"Zolotas","firstName":"Christoforos"},{"lastName":"Chatzidimitriou","firstName":"Kyriakos C."},{"lastName":"Symeonidis","firstName":"Andreas L."}]},"sentenceCased":true},{"key":"zolotasTypeInferenceFlexible2018","type":"article","fields":{"langid":["english"],"author":["Zolotas, Athanasios","Matragkas, Nicholas","Devlin, Sam","Kolovos, Dimitrios S.","Paige, Richard F."],"date":["2018-01-23"],"doi":["10.1007/s10270-018-0658-5"],"issn":["1619-1366, 1619-1374"],"journaltitle":["Softw. Syst. Model."],"note":["TL;DR \n\nThe use of classification algorithms are proposed to help with the inference of models with elements that are unintentionally left untyped and the correct type prediction varies from 23 to 100% depending on the domain, the proportion of elements that were left untyped and the prediction algorithm used."],"title":["Type inference in flexible model-driven engineering using classification algorithms"]},"creators":{"author":[{"lastName":"Zolotas","firstName":"Athanasios"},{"lastName":"Matragkas","firstName":"Nicholas"},{"lastName":"Devlin","firstName":"Sam"},{"lastName":"Kolovos","firstName":"Dimitrios S."},{"lastName":"Paige","firstName":"Richard F."}]},"sentenceCased":true},{"key":"ZoomingPanningHTML5","type":"online","fields":{"abstract":["Often Zooming and Panning are required Chart Interactions when plotting a chart with large data. By making zoomEnabled to true, you can zoom into area of interest."],"organization":["CanvasJS"],"title":["Zooming & Panning in HTML5 & JavaScript Chart"],"url":["http://canvasjs.com/docs/charts/basics-of-creating-html5-chart/zooming-panning/"],"urldate":["2015-04-02"]},"creators":{}},{"key":"Zou2018174","type":"inproceedings","fields":{"langid":["english"],"abbrev_source_title":["IEEE Intell Veh Symp Proc"],"affiliation":["Center for Automotive Electronics, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China; Schaeffler Technologies AG and Co. KG, Germany; Electronic Measurement and Diagnostic Technology, Technische Universität, Berlin, Germany"],"art_number":["8500691"],"author":["Zou, J.","Huang, H.","Gühmann, C."],"date":["2018"],"document_type":["Conference Paper"],"doi":["10.1109/IVS.2018.8500691"],"isbn":["978-1-5386-4452-2"],"note":["cited By 0"],"pages":["174–178"],"publisher":["Institute of Electrical and Electronics Engineers Inc."],"series":["IEEE Intelligent Vehicles Symposium, Proceedings"],"source":["Scopus"],"title":["Improved sliding-mode on-Line adaptive position control for AMT clutch systems based on neural networks"],"volume":["2018-June"]},"creators":{"author":[{"lastName":"Zou","firstName":"J."},{"lastName":"Huang","firstName":"H."},{"lastName":"Gühmann","firstName":"C."}]},"sentenceCased":true}]