A Machine Learning Approach to Improve the Detection of CI Skip Commits
IEEE Transactions on Software Engineering(2021)
摘要
Continuous integration (CI) frameworks, such as Travis CI, are growing in popularity, encouraged by market trends towards speeding up the release cycle and building higher-quality software. A key facilitator of CI is to automatically build and run tests whenever a new commit is submitted/pushed. Despite the many advantages of using CI, it is known that the CI process can take a very long time to c...
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关键词
Machine learning,Decision trees,Feature extraction,Message systems,Documentation,Buildings
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