logseq/pages/@Toward Automatically Completing GitHub Workflows.md

links:: Local library, Web library authors:: Antonio Mastropaolo, Fiorella Zampetti, Massimiliano Di Penta, Gabriele Bavota tags:: Computer Science - Software Engineering date:: 31-08-2023 item-type:: preprint title:: @Toward Automatically Completing GitHub Workflows

• 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.
• Attachments
  • arXiv.org Snapshot {{zotero-imported-file NZ2YKW8W, "2308.html"}}
  • Mastropaolo et al_2023_Toward Automatically Completing GitHub Workflows.pdf {{zotero-imported-file 9PRWJCJ7, "Mastropaolo et al_2023_Toward Automatically Completing GitHub Workflows.pdf"}}