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[logseq-plugin-git:commit] 2025-06-05T08:12:38.896Z

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Davide Di Ruscio
2025-06-05 10:12:39 +02:00
parent 4f7ee4e0df
commit 1d459a7e65
11 changed files with 552 additions and 6 deletions
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journals/2025_06_05.md
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progress:: {{renderer :todomaster}}
icon:: 📅
- ## Tasks
- Inviare materiale studente Asad a revisori esterni
- Finalizzare verbale
- Raffinare linee guida per afferenza collegio
-
- ## Notes
logseq/bak/journals/2025_06_04/2025-06-05T08_02_31.303Z.Desktop.md
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icon:: 📅
- ## Tasks
- DONE [[REVIEWS]]
id:: 5b54cf10-4738-44a1-b930-fcff797d0b75
:LOGBOOK:
CLOCK: [2025-06-04 Wed 11:29:14]--[2025-06-04 Wed 11:29:16] => 00:00:02
:END:
- Rispondere alle discussioni ICSE
- TODO [[SERVICES/PHDICT]]
- Questione maggiorazione borsa
-
- ## Notes
logseq/bak/logseq/config/2025-06-04T09_51_45.815Z.Desktop.edn → logseq/bak/logseq/config/2025-06-05T08_02_31.258Z.Desktop.edn
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:ui/show-full-blocks? true
;; Expand block references automatically when zoom-in
:ui/auto-expand-block-refs? true
:ui/auto-expand-block-refs? false
;; Enable Block timestamp
:feature/enable-block-timestamps? false
logseq/bak/logseq/custom/2023-04-29T22_07_02.671Z.Desktop.css
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@import url('https://piotrsss.github.io/logseq-tools/public/bujo-css/main.css');
@import url('https://piotrsss.github.io/logseq-tools/public/bujo-css/dark-black.css');
@import url('https://piotrsss.github.io/logseq-tools/public/bujo-css/dark-black-dots.css');
@import url('https://piotrsss.github.io/logseq-tools/public/bujo-css/light-white.css');
@import url('https://piotrsss.github.io/logseq-tools/public/bujo-css/light-white-dots.css');
logseq/bak/logseq/custom/2025-06-05T08_02_31.266Z.Desktop.css
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.block-properties {
display: none;
}
.block:hover .block-properties {
display: block;
}
logseq/bak/pages/DONE/2025-06-05T08_02_31.324Z.Desktop.md
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icon:: ✅
- ### [[2025/05]]
- ✔️ [[May 26th, 2025]] *22:39* ((68341e4c-22c0-498c-8b18-bf3c03b3f7ea))
- ✔️ [[26-05-2025]] *22:52* ((6673db98-f12a-4d48-b1ec-281082dfec1f))
- ✔️ [[27-05-2025]] *16:18* ((6831929a-bb3a-4d1e-a0ab-5dd96aedb5a1))
- ✔️ [[28-05-2025]] *09:22* ((68342adf-7c9d-4937-8d81-7ce37d084360))
- ✔️ [[28-05-2025]] *09:23* ((6836208c-160c-483a-b6fe-939605fbb4fc))
- ✔️ [[28-05-2025]] *12:40* ((683620bb-651c-44a0-8fd0-4e5e835a9090))
- ✔️ [[28-05-2025]] *12:44* ((683620b6-4510-470b-90ef-d8ec1122471c))
- ✔️ [[28-05-2025]] *12:44* ((683620b6-ca0a-4855-846c-952d9add8ef5))
- ✔️ [[29-05-2025]] *12:57* ((68372640-5f76-4640-8b49-7d79dc1e8c7a))
- ✔️ [[30-05-2025]] *11:19* ((683952a8-5c44-4441-8f3f-bbfb8797674f))
- ✔️ [[30-05-2025]] *18:00* ((6839ce19-2f24-43d2-a1ab-b615a34bd92f))
- ✔️ [[30-05-2025]] *18:04* ((6839cd22-cd1c-4541-bea1-50c655611104))
- ✔️ [[30-05-2025]] *21:28* ((68362092-aafa-44b6-83b2-8f4a163dd2a0))
- ✔️ [[10-05-2025]] *22:52* ((66ed695f-a60d-473d-8855-ec948f4a8bf8))
- ✔️ [[10-05-2025]] *22:56* ((66ed6960-90a9-44e0-842f-61c071f4b607))
- ✔️ [[10-05-2025]] *23:05* ((93b5aeab-7030-401b-b111-f27673af6d28))
- ✔️ [[10-05-2025]] *23:06* ((681fbf91-62b7-49bc-bf11-aad4d56a6f83))
- ✔️ [[10-05-2025]] *23:07* :LOGBOOK:
CLOCK: [2025-05-10 Sat 23:07:09]--[2025-05-10 Sat 23:07:11] => 00:00:02
:END:
- ✔️ [[May 21st, 2025]] *09:04* ((65c8d43c-9e5e-455f-9c48-cb6d035417fc))
- ✔️ [[May 24th, 2025]] *19:02* ((6831961e-c3a3-4890-99ae-ffda429333c8))
- ✔️ [[May 24th, 2025]] *20:47* ((6659d0ed-b485-4423-9c75-a8f5d715b31f))
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- ✔️ [[May 25th, 2025]] *15:49* ((66e80dfd-0f7c-4020-aa87-906662c9eebd))
- ✔️ [[May 25th, 2025]] *19:26* ((6832257a-f98d-4f5e-850c-ddf8ffd0b5fb))
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- ✔️ [[May 26th, 2025]] *22:21* ((65d8963d-5b6c-48da-bd21-21e3ffe41570))
- ✔️ [[May 26th, 2025]] *22:21* ((65c8d45b-545c-4ca4-acc3-b35ef663757f))
- ✔️ [[May 26th, 2025]] *22:21* ((65c8d45b-3974-4a0e-ac6e-7dbc798340ab))
- ✔️ [[May 26th, 2025]] *22:21* ((65c35633-d1fd-4840-a6bc-ee79a2db5ffa))
- ✔️ [[May 26th, 2025]] *22:22* ((65c8d45b-1a21-40d2-9003-5b9c13d08e01))
- ✔️ [[May 26th, 2025]] *22:22* ((65d8963d-f00b-44a0-97c3-10f5510ab44e))
- ✔️ [[May 26th, 2025]] *22:22* ((683432dd-8909-4466-b7ec-c4861aaf2fe0))
- ✔️ [[May 26th, 2025]] *22:23* ((65c8d46f-f70f-4d0f-9fce-14c2ab11ab68))
- ✔️ [[May 26th, 2025]] *22:23* Coprire anche aspetti di collaborative modeling
- ### [[2025/06]]
- ✔️ [[02-06-2025]] *23:42* ((6836208c-cf9d-4d40-9f87-db1045f739e1))
- ✔️ [[03-06-2025]] *16:05* ((683f0108-c7ac-41ae-a6bd-b9c02829e6fc))
- ✔️ [[03-06-2025]] *16:07* ((683ee6f2-7304-4ea7-8000-46b4106b3ef5))
- ✔️ [[03-06-2025]] *21:54* ((683620b6-dd45-402c-80d5-0eb8facf914d))
- ✔️ [[04-06-2025]] *11:29* ((5b54cf10-4738-44a1-b930-fcff797d0b75))
logseq/bak/pages/GOALS-TODOIST/2025-06-05T08_02_31.330Z.Desktop.md
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icon:: ⚽
progress:: {{renderer :todomaster}}
- #.tabular
- [[P1]]
- {{query (and (task TODO) (priority A))}}
query-table:: true
query-properties:: [:block :todoist-desc :todoist-id]
- [[P2]]
- {{query (and (task TODO) (priority B))}}
query-table:: true
query-properties:: [:block :todoist-desc :todoist-id]
-
- TODO Fare timesheets
- TODO [[PAPERS/ILIRIAN-COLLABORATION]]
- TODO [[EditoringChairing/SOSYM-AI-MDE-SpecialIssue]]
- TODO Literature review on adversarial ML for SE
todoist-id:: [6841676473](https://todoist.com/app/task/6841676473)
todoist-desc:: [Literature Review - Online LaTeX Editor Overleaf](https://www.overleaf.com/project/643e68c8a424e0027e19fc5d)
- TODO Finalizzazione questione documentale
- TODO [#B] [[PAPERS/DSL-FOR-IOT-TESTING]]
- TODO [[PAPERS/SSTD-LLMS]]
- TODO [[PAPERS/JSS-2024-PERFORMANCE-TEST-COVERAGE]]
- TODO [[PAPERS/SOSYM-EXPERT-VOICE-2024-ML-EVOLUTION]]
- DONE Visita Riccardo
todoist-desc:: ✉: http://s.diruscio.org/u9fPP
todoist-id:: [7602643924](https://app.todoist.com/app/task/7602643924)
- TODO [[PAPERS/2024-ONTOLOGY-AI]]
todoist-id:: [7658261760](https://todoist.com/app/task/7658261760)
- TODO NIER paper on how our two-level agent architecture
- TODO [#C] [[PAPERS/2024-BiasInRSSEwithLLM]]
todoist-id:: [7688827022](https://todoist.com/app/task/7688827022)
todoist-desc:: [https://github.com/MDEGroup/BiasInRSSEwithLLM](https://github.com/MDEGroup/BiasInRSSEwithLLM)
- TODO [#B] [FRINGE] Collaborazione su Fairness Mutation/Metamorphic Testing?
- DONE [[EditoringChairing/2024-MODELS-WS-LOWCODE]]
id:: 6832257a-cbb8-4881-ab20-bebcda629999
- TODO [[PAPERS/2024-TESORO]]
- DONE [[PAPERS/TOSEM-2024-0258]]
id:: 6832257a-eea4-45f9-ab9f-98dbc36328cf
- TODO [[PAPERS/AML4SE]]
todoist-id:: [8113443070](https://todoist.com/app/task/8113443070)
todoist-desc:: [AMLinRSSE - Online LaTeX Editor Overleaf](https://www.overleaf.com/project/66683cbaf1ed22bc12efee72)
- DONE [#B] popup UnivAQ Street Science 2024
todoist-desc:: ✉: http://s.diruscio.org/eTBkR
todoist-id:: [8117885918](https://app.todoist.com/app/task/8117885918)
:LOGBOOK:
CLOCK: [2025-05-10 Sat 22:52:25]--[2025-05-10 Sat 22:52:27] => 00:00:02
:END:
- TODO [[PAPERS/BADGES-IMPACT]]
- TODO [#C] Convenzione Erasmus Nazionale
- DONE [#A] [[PAPERS/JSS-SATD]]
todoist-desc:: ✉: http://s.diruscio.org/bWUfi
todoist-id:: [8230073873](https://app.todoist.com/app/task/8230073873)
- TODO [[PAPERS/EMELIOT-EXPERIMENT]]
- DONE Career Day 24
todoist-desc:: ✉: http://s.diruscio.org/Y20BN
todoist-id:: [8359671703](https://app.todoist.com/app/task/8359671703)
- TODO Panel Invitation (MODELS 2024)
- TODO [[PAPERS/FSE2024-UserStories]]
todoist-id:: [8407326252](https://todoist.com/app/task/8407326252)
todoist-desc:: ✉: http://s.diruscio.org/fcx9l
- DONE [#A] [ICSE 2025, Research Track] Review Assignment and Instructions (Half Review Deadline: *Aug 30*)
todoist-desc:: ✉: [http://s.diruscio.org/vMkXT](http://s.diruscio.org/vMkXT)
todoist-id:: [8286706547](https://app.todoist.com/app/task/8286706547)
- DONE [#A] Progressione Phuong ad Associato
todoist-desc:: ✉: http://s.diruscio.org/hJoCt
todoist-id:: [8419941589](https://app.todoist.com/app/task/8419941589)
- DONE [#A] Notifica nomina commissione RTD/A S.S.D INFO-01/A (Progetto MATTERS, Allegato A del Bando di selezione)
todoist-desc:: ✉: http://s.diruscio.org/Z3tSx
todoist-id:: [8424508957](https://app.todoist.com/app/task/8424508957)
- TODO Orientamento 2026 PNRR - Anno 24/25
- DONE [#B] Progressione seconda fascia Phuong Nguyen
todoist-desc:: ✉: http://s.diruscio.org/MjM5n
todoist-id:: [8427313493](https://app.todoist.com/app/task/8427313493)
SCHEDULED: <2025-01-10 Fri>
- DONE [#A] Conscorso RTD/a MATTERS
todoist-desc:: ✉: http://s.diruscio.org/ouj19
todoist-id:: [8434113580](https://app.todoist.com/app/task/8434113580)
SCHEDULED: <2024-11-08 Fri 11:10>
- TODO Ridefinizione Piano Formativo e regole di riconoscimento CFU
- TODO [#B] [[PAPERS/2024-AMLinRSSE]]
id:: 6832257a-6e4b-4f1f-9d7b-1f520b8197ca
SCHEDULED: <2025-05-26 Mon>
- DONE [Lavoro Davide Sciarra e Giovanni Sicchio](https://outlook.office365.com/owa/?ItemID=AAkALgAAAAAAHYQDEapmEc2byACqAC%2FEWg0AjoVpQvBez0Ss5ZY2WGWEJgAHeU%2BoMgAA&exvsurl=1&viewmodel=ReadMessageItem)
todoist-id:: [8558858426](https://app.todoist.com/app/task/8558858426)
- DONE [#A] [[PAPERS/TOSEM-FAIRNESS]]
todoist-desc:: [[TOSEM] Towards Early Detection of Algorithmic Bias from Dataset's Bias Symptoms: An Empirical Study - Online LaTeX Editor Overleaf](https://www.overleaf.com/project/65b7d77455b46f44b87e2331)
todoist-id:: [8565953885](https://app.todoist.com/app/task/8565953885)
SCHEDULED: <2025-01-14 Tue 12:00>
- TODO [[PAPERS/SANER2025-FAIRNESS]]
- TODO [[PAPERS/SANER-2025-Popbias-LLM]]
- DONE [[PAPERS/MSR-2025-CodeXHug-dataset]]
id:: 6832257a-7e7e-4ed8-abf8-dd88c6643863
:LOGBOOK:
CLOCK: [2025-05-25 Sun 19:29:04]--[2025-05-25 Sun 19:29:05] => 00:00:01
:END:
- TODO Nuova edizione del PinKamp
todoist-id:: [8644892780](https://app.todoist.com/app/task/8644892780)
todoist-desc:: From: giuseppe.dellapenna@univaq.it
- TODO ICSE 2026 Program Committee
- TODO [[PAPERS/Experience-Report-to-EMSE]]
- DONE [[PAPERS/FSE2025-NIER]]
id:: 68362092-aafa-44b6-83b2-8f4a163dd2a0
- TODO [#C] Dottorato industriale riservato a dipendenti
- TODO Esplorare e approfondire gli aspetti fondamentali e pratici dei large language models
- TODO [#C] [[PAPERS/JOURNAL-LLMS4Edelta]]
- TODO Richiesta afferenza al Collegio di Mauro Cappelli, ricercatore all’Enea
- TODO [#C] Vedere per compenso per la De Masi
- TODO [#B] [[PAPERS/Journal-Green-Paper]]
- TODO [#B] Rivedere Composizione Collegio
todoist-id:: [8750396305](https://app.todoist.com/app/task/8750396305)
SCHEDULED: <2025-06-04 Wed>
- TODO [#C] [[PAPERS/ABSTRACT-ENGINEERING]]
- TODO [#C] [[PAPERS/TOSEM2025-TESORO]]
- TODO [#B] [R: Scheda XLI ciclo e richieste di afferenza al Collegio](https://outlook.office365.com/owa/?ItemID=AAkALgAAAAAAHYQDEapmEc2byACqAC%2FEWg0AjoVpQvBez0Ss5ZY2WGWEJgAHueDXAQAA&exvsurl=1&viewmodel=ReadMessageItem)
- TODO [#B] Informiamo che entro e non oltre il ciascun Coordinatore dovrà caricare sulla piattaforma telematica dedicata: - il verbale del collegio dei docenti con esplicita ammissione all’esame finale; - la copia della tesi finale del dottorando; - il verbale della commissione dell’esame finale.
SCHEDULED: <2025-07-31 Thu>
- TODO [#B] MODELS Journal-First-track + 1 more
id:: 6832257a-2676-4bf1-8958-81797e5c7003
SCHEDULED: <2025-05-26 Mon>
- DONE Revision of manuscript #EMSE-D-25-00044
id:: 6832257a-85cb-46bd-9018-855f59070a41
- TODO [#B] [[PAPERS/MAS-4-POPULARITY-BIAS]]
- TODO [#B] [ICSE 2026, Research Track] Review Assignment and Instructions (Half Review Deadline: *Apr 18*; All reviews deadline: May 16)
todoist-desc:: From: noreply-icse2026@hotcrp.com
todoist-id:: [9001461730](https://app.todoist.com/app/task/9001461730)
- TODO Dottorato industriale
todoist-id:: [9006116046](https://app.todoist.com/app/task/9006116046)
id:: 6823acce-6cc8-4da4-9a2c-5ffacf92e168
SCHEDULED: <2025-05-22 Thu>
- DONE [#B] Models Conference 2025
id:: 682ecc99-b356-4086-9ff8-4e4736018009
SCHEDULED✔️ <2025-05-26 Mon>
:LOGBOOK:
CLOCK: [2025-05-24 Sat 22:02:34]--[2025-05-24 Sat 22:02:35] => 00:00:01
CLOCK: [2025-05-24 Sat 22:02:52]--[2025-05-24 Sat 22:02:52] => 00:00:00
:END:
- DONE Review MODELS 2025 conference submissions
id:: 6832257a-4373-4560-a7e2-79fba9f4c9e6
:LOGBOOK:
CLOCK: [2025-05-24 Sat 22:02:27]--[2025-05-24 Sat 22:02:28] => 00:00:01
:END:
- DONE [#B] [[PAPERS/2025-SEAA-CodeXHug]]
id:: 6832257a-f98d-4f5e-850c-ddf8ffd0b5fb
:LOGBOOK:
CLOCK: [2025-05-25 Sun 19:26:07]--[2025-05-25 Sun 19:26:08] => 00:00:01
:END:
- DONE [[PAPERS/2025-Survey-MOSAICO]]
id:: 6832257a-63a4-4c89-8353-25f0e94caa51
- TODO [#B] Sinergia con GSSI
- TODO [#B] SLIDES DI PRESENTAZIONE
todoist-desc:: Con HOWTO etc.
todoist-id:: [9193848277](https://app.todoist.com/app/task/9193848277)
- TODO [#B] [[MODELS Journal-First-track + 1 more]]
todoist-desc:: From: noreply@researchr.org
todoist-id:: [8933176944](https://app.todoist.com/app/task/8933176944)
SCHEDULED: <2025-06-04 Wed>
- DONE [[PAPERS/2025-SEAA-CodeXHug]]
todoist-id:: [9123770472](https://app.todoist.com/app/task/9123770472)
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type:: [[JournalPaper]]
date:: [[11-01-2024]] - 16:15
full-title::
external-links:: [Sosym Expert voice: Co-evo in the era of Low code - Online LaTeX Editor Overleaf](https://www.overleaf.com/project/680d243a75547ff8d273e791)
year:: 2024
date-start:: [[11-01-2024]]
deadline-submission::
status:: [[DOING]]
venue:: [[SOSYM]]
leader:: [[people/ludovico]]
progress:: {{renderer : todomaster}}
- ## **MEETINGS**
- **Meeting con [[people/ludovico]] del [[30-05-2025]]**
- Abbiamo discusso di un possibile raffinamento del paper con l'obiettivo di avere la seguente struttura
- Overview del problema della coevoluzione cosi come funzionava 10 anni fa, facendo riferimento alle attività peculiare del problema, quindi:
- Calcolo delle differenze del metamodello
- Identificazione degli artefatti impattati dalla evoluzione
- Generazione/sviluppo degli adattamenti
- Applicazione degli adattamenti
- Overview delle piattaforme low-code ed esempio di airtable
- Il messaggio poi e' quello che la parte fondazionale fatta vedere prima sul problema della co-evoluzione applica ancora ora. Gli elementi costitutivi sono gli stessi concettualmente. E' cambiata la modalità di interezione e di accesso ai vari artefatti. Quindi qui si fa vedere come e' possibile accedere tramite API ai questi concetti.
- Una rivisitazione del processo di co-evoluzione da un punto architetturale. Invece di accedere agli artefatti coinolti localmente, ora viene fatto tramite API
- ![image.png](../assets/image_1748613428814_0.png)
- Questa figura va quindi raffinata da un punto architetturale evidenzianto le componenti coinvolte nella coevoluzione e i punti abilitanti di accesso e scrittura dei vari artefatti coinvolti.
- Le attività di co-evoluzione che si possono avere dipendono dalle possibilità di accesso agli artefatti tramite API
-
- query-table:: true
- ## [[PAPERS/NOTES]]
collapsed:: true
- Revised section
- The evolution of data-intensive web applications has predominantly relied on model-driven approaches that emphasize the separation of functional descriptions from implementation platforms. Over the last decades, many modeling languages have been proposed mainly based on three modeling constructs, i.e., data, page, and navigation. In particular, *data modeling* was crucial. Early frameworks used relatively homogeneous data sources, which were meticulously structured to ensure consistency and ease of maintenance. The models described the data schema—defining entities, relationships, and attributes—that formed the backbone of the applications. The concept of *pages* in early web applications was straightforward yet foundational. Each page represented a cohesive unit of content and functionality structured around the underlying data model. Pages were designed using templates that dictated layout and style, often leading to static presentations that required significant effort to update or personalize. *Navigation* models were integral, defining the paths users would take through an application. These models outlined how pages were interconnected, facilitating user movement across sections and functions of the website. Navigation was typically rigid, reflecting the static nature of early web architectures, with limited dynamic capabilities or user-driven paths.
- As shown in Table \ref{tab:}, initial modeling platforms were often standalone systems that provided tools for defining and manipulating these constructs without detailed programming knowledge. However, these systems commonly offered a low level of user experience and were not designed to support rapid, iterative changes. The platforms were monolithic, coupling data, presentation, and navigation in ways that made updates cumbersome. The development processes were traditional and non-agile, lacking the flexibility to adapt quickly to new requirements or user feedback. Integration with emerging DevOps practices was limited, further slowing the evolution of applications as they could not effectively leverage continuous integration or automated deployment techniques.
- The development of data-intensive web applications has undergone significant transformations, moving from rigid, model-driven approaches to more dynamic, agile methodologies that better address the demands of today's users and technological environments. Unlike in the past, where data sources were mostly homogeneous and static, modern applications often need to *integrate heterogeneous data sources*. These can range from live data feeds to unstructured data pools, necessitating advanced data management techniques such as real-time data processing and big data technologies. The focus has shifted from merely managing data to extracting value through sophisticated analytics and machine learning algorithms. Moreover, modern web applications have moved away from the static pages of the past to *dynamic interfaces* that can adapt to user behavior and preferences. Using frameworks like React, Angular, and Vue.js allows developers to create responsive, single-page applications that provide seamless user experiences. These frameworks support modular and component-based architectures, making updating and maintaining complex applications easier. Navigation in contemporary web applications is no longer just about linking pages but providing *dynamic navigation models* that best fit user preferences, with capabilities like dynamic menus, personalized breadcrumbs, and AI-driven suggestions that improve usability and accessibility.
- The evolution of data-intensive application development is indeed not finished. We envision a future that require the management of several challenges including the following ones:
- **Collaborative and Agile Modeling:** Modern web applications demand agility and adaptability. Thus, advancing collaborative modeling tools and environments is pivotal. Such tools should support real-time collaboration and agile methodologies, incorporating practices like version control and conflict resolution to facilitate simultaneous model evolution. Further exploration into integrating agile practices within model-driven development will also be a key focus, aiming to enhance the flexibility and responsiveness of development processes.
- **Artificial Intelligence in Modeling:** The potential of AI technologies to revolutionize model-driven development is immense. From AI-driven code generation to the maintenance and optimization of models, AI could significantly enhance the efficiency and effectiveness of development processes. Additionally, applying machine learning to predict trends in application evolution could enable developers to anticipate and adapt to changes proactively.
- **Integration and Interoperability:** The seamless integration of heterogeneous data sources remains a cornerstone of our research. This involves not only enhancing data consistency and accessibility across diverse platforms but also developing robust standards that foster interoperability between varying modeling frameworks. By refining these standards, particularly in the context of API management and microservices architectures, we aim to maintain contextual integrity across interconnected systems.
- **Low-Code and No-Code Platforms:** The rise of low-code and no-code platforms presents both challenges and opportunities. Our research will assess the effectiveness of these platforms in the lifecycle of data-intensive applications, focusing on customization and scalability. Investigating the integration of traditional modeling techniques with these low-code solutions will help us understand how to enhance their functionality and flexibility.
- **Addressing Lock-in Issues with Low-Code Platforms** Investigate methodologies and frameworks that enable model-driven engineering approaches to mitigate lock-in problems inherent in low-code platforms. This includes developing strategies for model portability and interoperability across different platforms, allowing for more flexibility and reducing dependency on a single vendor.
-
- ---
-
-
- As we envision the future trajectory of model evolution for data-intensive web applications, our research agenda is shaped by the imperative to address current challenges while capitalizing on emergent technological opportunities. Our focus spans several crucial domains:
-
- **Security and Privacy:** As the complexity of web applications increases, so does the need for robust security and privacy measures. Our agenda includes developing security frameworks that ensure data integrity and privacy without impeding the agility of model updates. Additionally, researching privacy-preserving techniques in model-driven development will help incorporate privacy by design, which is crucial for applications handling sensitive user data.
- **Sustainability and Scalability:** Finally, our research will explore sustainable development practices that promote the long-term maintainability and minimal resource consumption of web applications. Studying scalable architectural models and patterns that optimize the performance of these applications will also be a key area of focus.
- Through these varied yet interconnected research themes, we aim to pave the way for a robust, flexible, and user-centric future in model-driven development for data-intensive web applications. This narrative not only reflects our commitment to technical advancements but also aligns with the broader goals of making web development more agile, secure, and scalable.
- Possibly for each point I would refer our papers, or some inital investigation about the point under analysis and discuss what's needed and thus what are additional topics of research.
- At that time the approach was to address very specific problems. While technologies and methods evolved and become more mature, the focus shifted on generalizing the proposed solutions making them usable, scalable, and efficient.
- Some points for the research agenda:
- **Interoperability Among Modeling Formalisms and Platforms**
- Investigate strategies to enhance interoperability between different modeling languages and platforms, focusing on establishing common semantic frameworks or intermediaries that facilitate seamless data and model exchange.
- **AI-Driven Automation in Model Evolution**: Explore the potential of AI and machine learning algorithms to predict and automate aspects of model evolution, thereby reducing manual efforts in maintaining and updating models in response to evolving data-intensive application requirements.
- In the rapidly evolving landscape of data-intensive applications, the agility to adapt and refine underlying models becomes paramount. Traditional approaches, while effective, often necessitate considerable manual oversight, a task both time-consuming and prone to human error. This is where the integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies presents an intriguing avenue. The essence of employing AI-driven mechanisms in the context of model evolution lies in harnessing predictive analytics and automation capabilities to foresee and enact necessary modifications within models. Such a methodology not only promises to significantly curtail manual labor but also introduces a level of precision and foresight previously unattainable.
- To fully capitalize on AI and ML's potential, a focused exploration into specific algorithms that excel in pattern recognition and predictive modeling is essential. The goal is to develop systems that can accurately predict when a model requires evolution based on emerging trends and application requirements. These systems would, ideally, not just alert developers to the necessity of changes but also suggest precise modifications or automatically implement updates where applicable. This could range from adjusting attributes and relationships within a model to more complex alterations that align with the shifting paradigms of data usage and application functionality.
- Moreover, embedding AI-driven automation within model evolution processes necessitates a comprehensive understanding of the domain-specific nuances of data-intensive applications. This involves training algorithms on extensive datasets to recognize the intricacies of various domains, ensuring that suggested model evolutions are not only technically viable but also contextually relevant. Furthermore, the integration of AI and ML in model-driven engineering should be approached with an emphasis on collaborative intelligence, where AI systems augment human expertise rather than replace it. By providing tools that offer insightful suggestions, automate routine tasks, and enable developers to focus on strategic decisions, we can achieve a symbiosis that amplifies the strengths of both human and machine.
- In synthesizing AI-driven automation with model evolution, we stand at the cusp of a paradigm shift. This initiative beckons a future where the development, maintenance, and evolution of data-intensive applications are not only more efficient but also inherently more dynamic and responsive to the needs of both users and the market. By pursuing this research agenda, we aim to unlock new methodologies that streamline the evolution of models, thereby ensuring that data-intensive applications remain robust, adaptable, and at the forefront of technological innovation.
-
-
- **Managing Technical Debt in Coupled Evolution**
- Develop methodologies and tools for identifying, quantifying, and managing technical debt arising from the coupled evolution of models and their implementations, ensuring long-term sustainability and flexibility of data-intensive systems.
- In the intricate dance of coupled evolution, where models and their implementations evolve in tandem, the specter of technical debt looms large. As these intertwined components shift and grow, they invariably accumulate compromises and shortcuts that, while expedient in the short term, threaten the system's long-term sustainability and adaptability. Recognizing and addressing this technical debt is not merely a maintenance task; it's a strategic imperative that ensures the ongoing vitality and relevance of data-intensive systems.
- To navigate this complex landscape, the development of sophisticated methodologies and tools is paramount. These resources must not only unearth the hidden and often overlooked debt embedded within the evolving tapestry of models and code but also provide actionable insights into its quantification. By moving beyond mere identification, we aim to establish a metric-driven approach that can gauge the weight and impact of accumulated debt, offering a clear picture of its implications on system performance, maintainability, and evolution.
- However, identifying and quantifying technical debt is only the first step. The crux of the challenge lies in the active management and mitigation of this debt. This involves crafting strategies and mechanisms that allow developers and system architects to prioritize debt resolution based on its projected impact on the system's future evolution. These strategies may range from refactoring efforts that untangle complex model relationships and streamline implementations to more radical architectural overhauls that address systemic issues contributing to debt accumulation.
- Integral to this approach is the establishment of a feedback loop between the evolution of models and their implementations. This loop, powered by continuous monitoring and analysis tools, serves as a dynamic ledger of technical debt, capturing its genesis, evolution, and resolution. By embedding this feedback mechanism into the development process, we can foster a culture of proactive debt management, where technical debt is not only managed but anticipated and preemptively addressed.
- In charting the course for managing technical debt in coupled evolution, we envisage a future where technical debt is no longer an invisible burden carried by data-intensive systems. Instead, it becomes a quantifiable, manageable aspect of the development process, one that is consistently monitored and judiciously addressed. Through the development and adoption of these methodologies and tools, we can secure the long-term sustainability and flexibility of data-intensive systems, ensuring they remain robust and responsive to the ever-evolving demands of the digital world.
- **Safety and Security in Model Evolution**
- Address safety and security concerns in the evolution of data-intensive applications, proposing model-driven approaches that incorporate security-by-design principles and assess the implications of model changes on application security posture.
- **Collaborative Model-Driven Engineering**
- Innovate on collaborative tools and workflows that support distributed teams in model-driven engineering efforts, particularly for data-intensive applications, focusing on version control, conflict resolution, and real-time collaboration in model evolution.
- **Extensible Metamodel Refactoring Catalogs**
- Create and maintain comprehensive catalogs of refactoring patterns for common evolution scenarios in data-intensive applications, supporting modelers in applying best practices and ensuring consistency across model evolutions.
- **Live Metamodel Evolutions and Dynamic Co-Evolution Support**
- Advance the support for live metamodel evolutions, enabling models and related artifacts to adapt dynamically to changes, minimizing disruption and downtime in data-intensive application development and deployment.
- **Standardization Efforts for Model-Driven Techniques**
- Contribute to standardization efforts aimed at defining clear specifications and protocols for model-driven engineering practices, particularly in the context of data-intensive applications, to foster interoperability, reusability, and tool compatibility.
- **Integration of Model-Driven Engineering and Digital Twin Technologies**
- Investigate the synergies between model-driven engineering and digital twin technologies, exploring how MDE can facilitate the creation and maintenance of digital twins for data-intensive applications, enhancing simulation, analysis, and real-time monitoring capabilities.
-
- **Enhancing Model-Driven Engineering (MDE) Integration with Low-Code Environments**
- Develop best practices and tools for integrating MDE methodologies within low-code development environments, aiming to preserve the benefits of abstraction and automation offered by MDE while leveraging the accessibility and rapid prototyping capabilities of low-code platforms.
- **Standardizing Model Interchange Formats for Low-Code Platforms**
- Propose and advocate for standardization of model interchange formats specific to low-code development environments. This effort would focus on enabling seamless model exchange and reuse across different low-code platforms, thus addressing one of the critical aspects of platform lock-in and enhancing ecosystem interoperability.
- **Facilitating Citizen Developer Participation in Model-Driven Processes**
- Design methodologies and tools that empower citizen developers to actively participate in model-driven development processes without the steep learning curve. This involves simplifying model abstraction layers and providing intuitive interfaces and guidance, thereby harmonizing the power of MDE with the user-friendly nature of low-code platforms.
- **Cross-Platform Model Deployment and Management Strategies**
- Explore strategies and develop tools for the deployment and management of models across multiple low-code platforms, addressing the challenges of maintaining consistency, versioning, and performance across diverse environments while avoiding vendor lock-in.
- **Automated Migration Pathways Between Low-Code Platforms**
- Research and develop automated migration tools and services that support the transition of applications and their underlying models from one low-code platform to another. This would involve identifying commonalities between platforms, mapping functional equivalents, and automating the transformation processes to minimize manual intervention.
- **Assessing the Impact of Low-Code Development on Technical Debt**
- Investigate the implications of low-code development practices on the accumulation of technical debt in model-driven engineering projects. This includes identifying patterns of debt specific to low-code platforms and proposing mitigation strategies that leverage model-driven techniques.
-
- We have the following ingredients:
- Who cited the paper:
- Model Consistency/conflict management
- Surveys on Web application development
-
-
- Alcune note per elaborare la sezione research agenda:
- **Evolution with Existing Tools for Developing Data-Intensive Applications:**
Over the past decade, significant progress has been made in developing tools and techniques for managing the evolution of data-intensive applications. However, despite these advancements, challenges persist in effectively handling model evolution, particularly when utilizing existing tools such as Eclipse Modeling Framework (EMF). When dealing with systems like EMF, issues related to dependency management and scalability remain prevalent, hindering the seamless evolution of models over time. Interestingly, integrated modeling environments like MetaEdit have demonstrated better capabilities in managing dependencies and facilitating model evolution. The absence of Low-Code platforms implemented with EMF raises questions about the adaptability and suitability of existing tools for addressing the evolving needs of data-intensive application development.
- **Low-Code Platforms:**
Low-Code platforms have emerged as promising solutions for accelerating application development by enabling visual, declarative approaches to software design. These platforms abstract away complex coding tasks, allowing developers to focus more on high-level logic and business requirements. In the context of model evolution for data-intensive applications, the role of Low-Code platforms is worthy of exploration. By providing intuitive interfaces and streamlined development processes, Low-Code platforms have the potential to simplify the evolution of application models, making it more accessible to a broader range of stakeholders. Understanding how Low-Code platforms integrate with model-driven techniques and their impact on the evolution process is essential for advancing the state-of-the-art in this domain.
- **General Discussion on Co-Evolution:**
Co-evolution, the concept of interconnected changes between different elements of a system, is a fundamental aspect of software evolution. In the context of data-intensive applications, co-evolution encompasses not only the evolution of application models but also the associated infrastructure, data schemas, and deployment environments. A broader discussion on co-evolution is necessary to explore the intricate relationships between these elements and the implications for managing their evolution cohesively. By understanding the dynamics of co-evolution, researchers and practitioners can develop more holistic approaches to model evolution that consider the interdependencies between different aspects of the software ecosystem.
- **Usability, Labor Shortage, and Low-Code Solutions:**
Usability concerns and labor shortages continue to pose significant challenges in software development, particularly in the context of data-intensive applications. The complexity of traditional development approaches often requires specialized skills and extensive training, contributing to the shortage of skilled developers in the industry. Low-Code solutions offer a promising alternative by democratizing application development and reducing the barrier to entry for individuals with diverse backgrounds. By providing intuitive interfaces and abstracting away technical complexities, Low-Code platforms empower a broader range of users to participate in the development process, potentially mitigating the impact of labor shortages and improving overall usability.
- **Technological Evolution:**
The technological landscape for developing data-intensive applications has undergone significant transformations over the past decade. Advancements in cloud computing, containerization, microservices architectures, and other technologies have reshaped the way applications are designed, deployed, and managed. These changes have profound implications for model evolution, as the evolving technological stack introduces new challenges and opportunities for managing application complexity. Understanding how these technological advancements influence the evolution of application models is crucial for developing adaptive and future-proof solutions. By staying abreast of technological trends and aligning model-driven techniques with emerging technologies, researchers can ensure the continued relevance and effectiveness of model evolution approaches in the ever-changing landscape of data-intensive application development.
- Somme additional notes from Consensus
- \section{Introduction}
- The rapid advancement of web technologies has significantly impacted the development and evolution of data-intensive applications. Model-Driven Engineering (MDE) approaches have been pivotal in addressing the complexities associated with these applications, providing a structured methodology for their design, development, and maintenance. This paper explores the evolution of model-driven techniques for managing data-intensive web applications, emphasizing the challenges of coupled evolution and interoperability issues across different modeling platforms. Through a comprehensive analysis, we propose a forward-looking research agenda aimed at overcoming these challenges, leveraging the latest advancements in AI-based technologies and low-code platforms.
- \section{Evolution of Model-Driven Techniques for Data-Intensive Applications}
- Model-Driven Engineering (MDE) has emerged as a transformative approach for the development of data-intensive applications, advocating for the use of models as primary artifacts in the software development lifecycle. This section provides a mini-survey of the significant advancements in MDE for data-intensive applications, drawing upon the foundational works and recent innovations presented in key forums like the Models conference. The evolution of MDE practices highlights a transition from traditional development paradigms towards more abstract, model-based techniques, offering enhanced productivity and adaptability. However, this evolution also underscores a critical challenge: the co-evolution of data models and their applications. As data-intensive applications grow in complexity and scale, managing this co-evolution becomes increasingly pivotal, serving as a segue into the subsequent discussion on coupled evolution and interoperability challenges.
- \section{Coupled Evolution and Interoperability Issues}
- The concept of coupled evolution in the context of data-intensive applications refers to the simultaneous and interdependent changes within the application's data models and the application itself. This section delves into the research efforts over the past decade aimed at addressing coupled evolution, presenting a mini-survey of the literature. Despite significant progress, the landscape of model-driven development is fraught with interoperability challenges, stemming from the diverse array of formalisms and platforms used in application development. These challenges are further exacerbated by the evolving nature of web technologies, necessitating continuous adaptation and integration of new models and systems. The discussion here not only highlights the complexities of managing coupled evolution but also sets the stage for exploring potential solutions within the broader context of modern development environments.
- \section{Research Agenda}
- Looking ahead, the field of model-driven development for data-intensive applications stands at a crucial juncture, with the potential to significantly benefit from advancements in Large Language Models (LLMs) and low-code platforms. This section outlines a research agenda that aims to address the challenges of (co-)evolution in web-based, data-intensive systems. By incorporating LLMs, the agenda suggests exploring how AI-based technologies can automate aspects of model evolution, potentially offering more intelligent and adaptive solutions for managing coupled evolution. Furthermore, the integration of low-code platforms presents an opportunity to democratize the development process, making it more accessible and efficient. This research agenda advocates for a holistic approach that not only tackles the technical challenges of evolution and interoperability but also embraces the socio-technical dimensions of software development in the modern era.
- \section{Conclusion}
- The evolution of model-driven techniques for data-intensive applications has paved the way for significant advancements in software development. However, the journey is far from complete. The challenges of coupled evolution and interoperability remain substantial barriers to achieving fully agile and adaptive development environments. This paper has outlined a research agenda aimed at addressing these challenges, leveraging the potential of AI and low-code platforms. As we move forward, the collaboration between researchers, practitioners, and technology providers will be crucial in realizing the vision of more efficient, adaptable, and accessible model-driven development for data-intensive applications.
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icon:: ☢️
-
- {{namespace [[SERVICES]] }}
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icon:: 🔴
progress:: {{renderer :todomaster}}
- ## TASKS
- {{query (and [[TODOIST-LOGSEQED]] (task TODO DOING) (not [[GOALS-TODOIST]]))}}
query-table:: true
query-properties:: [:block :todoist-id]
query-sort-by:: block
query-sort-desc:: false
- -----
- TODO [#B] [[Gestione studenti del primo anno che hanno già seguito corsi non nell'offerta formativa]]
todoist-desc:: logseq://graph/Logseq?page=Gestione%20studenti%20del%20primo%20anno%20che%20hanno%20gi%C3%A0%20seguito%20corsi%20non%20nell'offerta%20formativa
todoist-id:: [9201712096](https://app.todoist.com/app/task/9201712096)
collapsed:: true
- DONE [#A] [[Mutuazione parziale corsi magistrale e o triennale]]
todoist-desc:: logseq://graph/Logseq?page=Chiamare%20Antonio%20per%20mutuazione%20parziale%20corsi%20magistrale%20e%2Fo%20triennale
todoist-id:: [9201764330](https://app.todoist.com/app/task/9201764330)
collapsed:: true
SCHEDULED✔️ <2025-05-28 Wed>
- TODO [#B] [[Definizione processo gestione moduli didattica studenti]]
todoist-desc:: logseq://graph/Logseq?page=Definizione%20processo%20gestione%20moduli%20didattica%20studenti
todoist-id:: [9204275059](https://app.todoist.com/app/task/9204275059)
SCHEDULED: <2025-06-04 Wed>
- TODO [#B] [[Progettazione Offerta Formativa]]
todoist-desc:: logseq://graph/Logseq?page=Progettazione%20Offerta%20Formativa
todoist-id:: [9205819498](https://app.todoist.com/app/task/9205819498)
SCHEDULED: <2025-06-07 Sat>
- TODO [#A] [[Missione STAF 2025]]
todoist-id:: [9135141990](https://app.todoist.com/app/task/9135141990)
SCHEDULED: <2025-06-16 Mon>
- TODO [#C] [[Proposta di corso avanzato su machine learning]]
todoist-desc:: https://outlook.office365.com/owa/?ItemID=AAkALgAAAAAAHYQDEapmEc2byACqAC%2FEWg0AjoVpQvBez0Ss5ZY2WGWEJgAH1wAvQQAA&exvsurl=1&viewmodel=ReadMessageItem
todoist-id:: [9057940282](https://app.todoist.com/app/task/9057940282)
SCHEDULED: <2025-06-07 Sat>
- TODO [#B] [[PAPERS/SOSYM-EXPERT-VOICE-2024-ML-EVOLUTION]]
todoist-desc:: [Sosym Expert voice: Co-evo in the era of Low code - Online LaTeX Editor Overleaf](https://www.overleaf.com/project/680d243a75547ff8d273e791)
todoist-id:: [7584640828](https://app.todoist.com/app/task/7584640828)
- TODO [#C] [[PAPERS/AUSE-Metagente]]
todoist-desc:: [MDEGroup/AUSE-Metagente: A paper to be submitted to a special issue of the Automated Software Engineering journal](https://github.com/MDEGroup/AUSE-Metagente)
todoist-id:: [9213097648](https://app.todoist.com/app/task/9213097648)
- TODO [#B] [[Call per posizioni MOSAICO]]
todoist-desc:: logseq://graph/Logseq?page=Call%20per%20posizioni%20MOSAICO
todoist-id:: [8663268357](https://app.todoist.com/app/task/8663268357)
SCHEDULED: <2025-06-05 Thu>
- TODO [#C] [[Missione FSE 2025]]
todoist-id:: [9074935545](https://app.todoist.com/app/task/9074935545)
todoist-desc:: [FSE 2025](https://conf.researchr.org/home/fse-2025)
- TODO [#B] [[PAPERS/MOSAICO-Technical-Report]]
todoist-desc:: logseq://graph/Logseq?page=PAPERS%2FMOSAICO-Technical-Report
todoist-id:: [9187744429](https://app.todoist.com/app/task/9187744429)
SCHEDULED: <2025-06-04 Wed>
- TODO [#A] [[Intervento PINKAMP]]
todoist-id:: [9179967916](https://app.todoist.com/app/task/9179967916)
SCHEDULED: <2025-06-06 Fri>
- TODO [#B] [[Update fondi progetti]]
todoist-id:: [9143259271](https://app.todoist.com/app/task/9143259271)
SCHEDULED: <2025-06-04 Wed>
- TODO [[[mosaico-all] MOSAICO meetings in Rome July 2025]]
todoist-id:: [9224183665](https://app.todoist.com/app/task/9224183665)
todoist-desc:: From: zhanna.zhussupova@imt-atlantique.fr
SCHEDULED: <2025-06-06 Fri>
- TODO [[Invited talk at LLMA4SE Summer School website]]
todoist-id:: [9201031612](https://app.todoist.com/app/task/9201031612)
todoist-desc:: From: chemacm@unex.es
SCHEDULED: <2025-08-18 Mon>
logseq/bak/pages/Writing Challenges/2025-06-05T08_02_31.763Z.Desktop.md
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- ## List of challenges
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- {{query (and (task TODO DOING DONE) [[Writing Challenges]])}}
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- ---
- [[31-05-2025]]
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- DONE **🎯 Sfida di scrittura: “Il messaggio nella macchina”**
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- **Prompt:**
- Accendi un vecchio computer in un laboratorio abbandonato. All’avvio, compare un messaggio di errore. Ma qualcosa non torna: il messaggio sembra rivolgersi direttamente a te, come se la macchina stesse cercando di comunicare.
- **Il tuo compito:**
- In circa 200–300 parole, scrivi un breve testo in prima o terza persona. Concentrati sull’atmosfera: può essere inquietante, malinconica, misteriosa o surreale. Il messaggio dovrebbe lasciare spazio a domande, dubbi o presagire qualcosa di più profondo.
- **Vincolo opzionale:**
- Inserisci una riga di “codice” o output di sistema che sembri al confine tra il tecnico e l’emotivo (es. `Eccezione nel thread "memoria": frammento non trovato.`).
- {{renderer :wordcount_683a9b29-4a30-4226-8c1e-4a6bd11560b3, 300}}
- Sono le due del pomeriggio, con fatica sono in cammino verso il laboratorio. Fuori il sole è cocente, non si respira, l'aria brucia i polmoni quando entra. Le porte scorrevoli dell'edificio F del laboratorio di genetica si aprono automaticamente appena mi avvicino facendo uscire aria gelida che contrasta con quella bollente dell'esterno. Arrivato al tornello avvicino il mio badge al lettore che fa fatica a riconoscermi. Devo insistere due volte prima di vedere il led verde accendersi e il passaggio sbloccarsi. Abbottono la camicia al collo, il sudore diventa gelido per tutta la schiena. Entro nel mio studio, accendo le luci a led. Anche loro fanno fatica ad attivarsi, sono necessari alcuni secondi prima di vedere la luce bianca accecante. Sono impaziente, voglio vedere il contenuto della chiavetta USB che mi ha dato Franco, esperto genetista fidato a cui ho chiesto un parere in merito alle tracce di sangue trovate sul pantalone della povera Clara. Aveva appena finito il suo turno di pomeriggio quando quel bastardo l'ha bloccata con forza sulla strada di casa. Spero che Franco abbia fatto un buon lavoro, è da incastrare quel figlio di puttana. Inserisco la chiavetta nella porta USB. Il mio vecchio PC, dopo minuti interminabili, si è finalmente messo in moto. Visualizzo il contenuto della chiavetta, contiene molte cartelle, sono necessari diversi secondi prima di riuscire a vedere la cartella con i file di famiglia. Entro dentro e trovo il file referto_clara.pdf. Mi tremano le dita, a malapena riesco a fare doppio click sul pulsante sinistro del mouse. Finalmente riesco ad aprire il documento, e' lento a caricare, vedo solo 5 pagine vuote, a fatica comincia a comparire il contenuto della prima pagina. Ma prima che riesca a leggere una sola riga, lo schermo si spegne. Poi, sullo sfondo nero, compare una scritta: "Eccezione nel thread "memoria": frammento non trovato....
- Cosa ne pensa chat?
- Il testo ha un’ottima atmosfera, costruita con cura e attenzione ai dettagli sensoriali. C’è tensione crescente, un ritmo incalzante, e un efficace equilibrio tra elementi realistici e quel tocco di mistero che culmina perfettamente nel messaggio finale. Ecco qualche osservazione e suggerimento per migliorare ulteriormente:
- ---
- ### ✅ Punti di forza
- **Atmosfera**: Il caldo torrido, la fatica fisica, il gelo improvviso dell’aria condizionata — tutto crea un coinvolgente senso di disagio e urgenza.
- **Dettagli visivi e corporei**: Il sudore gelido sulla schiena, la luce bianca accecante, il badge che non funziona al primo colpo: ottimi espedienti per rendere la scena viva.
- **Finale aperto**: L’errore del sistema, con quel messaggio ambiguo, è perfetto per la sfida. “Eccezione nel thread ‘memoria’: frammento non trovato” è suggestivo e coerente con il tono.
- ---
- ### 🔧 Suggerimenti di miglioramento
- **Correzioni minori di forma e grammatica:**
- "svorrevoli" → "scorrevoli"
- "camica" → "camicia"
- "sono necessari alcuni secondo" → "sono necessari alcuni secondi"
- "prima che riesco a leggere" → "prima che riesca a leggere"
- **Fluidità e ritmo**: Alcune frasi risultano un po' lunghe e affaticano la lettura. Puoi spezzarle per dare maggiore impatto emotivo:
- Ad esempio:
> "Inserisco la chiavetta nella porta USB del mio vecchio PC che nel frattempo dopo diversi minuti si e' messo in moto."
Potrebbe diventare:
"Inserisco la chiavetta nella porta USB. Il mio vecchio PC, dopo minuti interminabili, si è finalmente messo in moto."
- **Caricamento lento del file**: Potresti rendere più ansiosa l’attesa prima del messaggio, con qualche effetto visivo descritto meglio (“il cursore gira all’infinito”, “le pagine si caricano una riga alla volta”).
- ---
- ### ✨ Frase finale proposta (leggermente rifinita):
> Finalmente il documento si apre. Ma prima che riesca a leggere una sola riga, lo schermo si spegne. Poi, sullo sfondo nero, compare una scritta:
**`Eccezione nel thread "memoria": frammento non trovato.`**
- [[01-06-2025]]
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- TODO **🎯 Sfida di scrittura: “L’inventario delle piccole cose”**
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- **Prompt:**
- Scegli un luogo ordinario (una cucina, una fermata dell’autobus, una sala d’attesa, la tua scrivania…) e descrivilo come se fosse un universo interiore. Ogni oggetto presente deve rappresentare un ricordo, un pensiero o un’emozione.
- **Il tuo compito:**
- In circa 200–300 parole, scrivi un testo in prima persona con uno stile poetico, riflessivo. Non spiegare troppo: lascia che il lettore “senta” cosa significano gli oggetti attraverso immagini, accostamenti e silenzi.
- **Vincolo opzionale:**
- Inserisci la frase:
- **“Era lì da sempre, eppure non l’avevo mai davvero visto.”**
- {{renderer :wordcount_683df732-07bf-4df5-866e-645918812343, 300}}
- [[02-06-2025]]
- DOING **🎯 Sfida di scrittura: “Il mestiere dei sogni perduti”**
:LOGBOOK:
CLOCK: [2025-06-02 Mon 21:33:46]
:END:
- **Prompt:**
- Immagina un mondo in cui esiste una professione molto particolare: raccogliere i sogni dimenticati dalle persone. Chi svolge questo lavoro cammina tra la realtà e qualcosa di più fragile, raccoglie sogni abbandonati nei parchi, nei cassetti, nei mezzi pubblici… e li cataloga, li cura, o forse li ricicla per chi non ne ha più.
- **Il tuo compito:**
- Scrivi un breve racconto in prima persona: sei tu il raccoglitore (o raccoglitrice) di sogni perduti. Racconta una giornata di lavoro, un sogno strano che hai trovato, oppure una scoperta che ti ha fatto dubitare del tuo ruolo.
- **Vincolo opzionale:**
- Chiudi il testo con la frase:
- **“Quel sogno, però, mi aveva riconosciuto.”**
- {{renderer :wordcount_683dfc64-1824-497c-b591-44816e0a83aa, 300}}
- La sveglia suona alle 5:00 puntuale come tutti i lunedì mattina. Il programma di oggi prevede la cura del "Parco delle rimembranze", un giardino non troppo lontano dalla piazza principale di "Gioia del Colle", un paese arroccato dell'appennino centrale che conta non più di trecento anime. Ho sempre avuto la passione per la cura del verde ... non avrei mai pensato che quella passione sarebbe diventanta il mio lavoro.
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