面向持续集成的机器学习

Ali Kazemi Arani, Mansooreh Zahedi, T. H. Le, M. A. Babar
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引用次数: 1

摘要

持续集成(CI)已经成为一种成熟的软件开发实践,用于在软件开发过程中自动和持续地集成代码更改。文献中报道了越来越多的基于机器学习(ML)的CI阶段自动化方法。为CI阶段提供基于ml的方法的知识系统化(SoK)是及时和相关的。本文报告了在CI中使用ML的不同方面的SoK。我们的系统分析还强调了现有的基于机器学习的解决方案的不足,这些解决方案可以通过改进来推进最先进的技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SoK: Machine Learning for Continuous Integration
Continuous Integration (CI) has become a well- established software development practice for automatically and continuously integrating code changes during software development. An increasing number of Machine Learning (ML) based approaches for automation of CI phases are being reported in the literature. It is timely and relevant to provide a Systemization of Knowledge (SoK) of ML-based approaches for CI phases. This paper reports an SoK of different aspects of the use of ML for CI. Our systematic analysis also highlights the deficiencies of the existing ML-based solutions that can be improved for advancing the state-of-the-art.
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