一句话：提出 GH-WCOM，用 Transformer 加抽象化处理自动补全 GitHub workflow 形式的 CI/CD 配置。
持续集成与交付（CI/CD）已成为软件开发的核心，但搭建和维护 CI/CD 流水线需要与常规开发任务正交的知识与技能，而现有自动化支持十分有限。本文提出 GH-WCOM，一种基于 Transformer 的方法，帮助开发者编写 GitHub workflow 这一特定类型的 CI/CD 流水线配置。为应对该任务，作者设计了一个抽象化过程，既有助于 Transformer 的学习，又使模型仍能推荐工具选项、脚本片段等非常细碎的工作流元素。实证研究显示，GH-WCOM 最多可给出 34.23% 的正确预测，且模型的置信度是推荐正确可能性的可靠指标。
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.
DOI 原文 ·
@inproceedings{paperbot11382,
title = {Toward Automatically Completing GitHub Workflows},
author = {Antonio Mastropaolo and Fiorella Zampetti and Gabriele Bavota and Massimiliano Di Penta},
booktitle = {ICSE},
year = {2024},
doi = {10.1145/3597503.3623351}
}