Recommending Code Reviewers for Proprietary Software Projects: A Large Scale Study

Code review is an important activity in software development, which offers benefits such as improving code quality, reducing defects and distributing knowledge. Tencent, as a giant company, hosts a great number of proprietary software projects that are only open to specific internal developers. Since these proprietary projects receive up to 100,000 of newly submitted code changes per month, it is extremely needed to automatically recommend code reviewers. To this end, we first conduct an empirical study on a large scale of proprietary projects from Tencent, to understand their characteristics and how code reviewer recommendation approaches work on them. Based on the derived findings and implications, we propose a new approach named Camp that recommends reviewers by considering their collaboration and expertise in multiple projects, to fit the context of proprietary software development. The evaluation results show that Camp can achieve higher scores on proprietary projects across most metrics than other state-of-the-art approaches, i.e., Revfinder, CHREV, Tie and Comment Network and produce acceptable performance scores for more projects. In addition, we discuss the possible directions of code reviewer recommendation.