CIBench: A Dataset and Collection of Techniques for Build and Test Selection and Prioritization in Continuous Integration

CIBench: A Dataset and Collection of Techniques for Build and Test Selection and Prioritization in Continuous Integration

연구 분야: Software Development

학회: 2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)

Continuous integration (CI) is a widely used practice in modern software engineering. Unfortunately, it is also an expensive practice — Google and Mozilla estimate their CI systems in millions of dollars. There are a number of techniques and tools designed to or having the potential to save the cost of CI or expand its benefit - reducing time to feedback. However, their benefits in some dimensions may also result in drawbacks in others. They may also be beneficial in other scenarios where they are not designed to help. Therefore, we built CIBench, a dataset and collection of techniques for build and test selection and prioritization in Continuous Integration. CIBench is based on a popular existing dataset for CI — TravisTorrent [2] and extends it in multiple ways including mining additional Travis logs, Github commits, and building dependency graphs for studied projects. This dataset allows us to replicate and evaluate existing techniques to improve CI under the same settings, to better understand the impact of applying different strategies in a more comprehensive way.