Toward Automatically Completing GitHub Workflows
- URL: http://arxiv.org/abs/2308.16774v3
- Date: Wed, 6 Sep 2023 09:33:29 GMT
- Title: Toward Automatically Completing GitHub Workflows
- Authors: Antonio Mastropaolo, Fiorella Zampetti, Gabriele Bavota, Massimiliano
Di Penta
- Abstract summary: We present GH-WCOM (GitHub COMpletion), a Transformer-based approach supporting developers in writing a specific type of CI/CD pipelines, namely GitHub.
Our empirical study shows that GH-WCOM provides up to 34.23% correct predictions.
- Score: 16.302521048148748
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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.
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