T-Evos: A Large-Scale Longitudinal Study on CI Test Execution and Failure

IEEE Transactions on Software Engineering(2023)

引用 0|浏览6
暂无评分
摘要
Continuous integration is widely adopted in software projects to reduce the time it takes to deliver the changes to the market. To ensure software quality, developers also run regression test cases in a continuous fashion. The CI practice generates commit-by-commit software evolution data that provides great opportunities for future testing research. However, such data is often unavailable due to space limitation (e.g., developers only keep the data for a certain period) and the significant effort involved in re-running the test cases on a per-commit basis. In this paper, we present T-Evos, a dataset on test result and coverage evolution, covering 8,093 commits across 12 open-source Java projects. Our dataset includes the evolution of statement-level code coverage for every test case (either passed and failed), test result, all the builds information, code changes, and the corresponding bug reports. We conduct an initial analysis to demonstrate the overall dataset. In addition, we conduct an empirical study using T-Evos to study the characteristics of test failures in CI settings. We find that test failures are frequent, and while most failures are resolved within a day, some failures require several weeks to resolve. We highlight the relationship between code changes and test failure, and provide insights for future automated testing research. Our dataset may be used for future testing research and benchmarking in CI. Our findings provide an important first step in understanding code coverage evolution and test failures in a continuous environment.
更多
查看译文
关键词
Codes,Computer bugs,Benchmark testing,Java,Manuals,Data collection,Software testing,Evolution and maintenance,mining software repositories,software testing
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要