The problem addressed in this work is how to prevent low-quality code reviews resulting from reviewer inattentiveness. The authors propose to address this problem by introducing the concept of mutation testing into code reviews. Mutation testing is a method of assessing the efficacy of automated code testing by injecting known artificial bugs into the code under test. The authors adopt a similar approach of introducing known, artificial bugs into code under review. This enables reviewer attention and efficacy to be measured based on their ability to discover the introduced bugs. The authors implemented a proof-of-concept solution integrated with GitHub that allows developers to introduce mutations into their pull request code. Experiments with the prototype showed that developers were likely to use the tool in practice and regarded it as a means to improve the code review process and evaluate reviewer performance. This paper is available in the IEEE Digital Library. It can be cited as:

Z. Mukhtarov et al., “Towards Better Code Reviews: Using Mutation Testing to Improve Reviewer Attention,” 2023 IEEE/ACM International Conference on Software and System Processes (ICSSP), Melbourne, Australia, 2023, pp. 92-96, doi: 10.1109/ICSSP59042.2023.00020.

Note that this is one of two Best Paper awards made at ICSSP 2023. An announcement of the other can be found here.