Who should review my code? A file location-based code-reviewer recommendation approach for Modern Code Review

• Published in: 2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER) pp. 141 - 150
• Main Authors: Thongtanunam, Patanamon, Tantithamthavorn, Chakkrit, Kula, Raula Gaikovina, Yoshida, Norihiro, Iida, Hajimu, Matsumoto, Ken-ichi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-03-2015
• Subjects: Androids; Code-Reviewer Recommendation; Distributed Software Development; History; Humanoid robots; Manuals; Modern Code Review; Open source software; Software systems
• ISSN: 1534-5351; 2640-7574
• DOI: 10.1109/SANER.2015.7081824

Software code review is an inspection of a code change by an independent third-party developer in order to identify and fix defects before an integration. Effectively performing code review can improve the overall software quality. In recent years, Modern Code Review (MCR), a lightweight and tool-based code inspection, has been widely adopted in both proprietary and open-source software systems. Finding appropriate code-reviewers in MCR is a necessary step of reviewing a code change. However, little research is known the difficulty of finding code-reviewers in a distributed software development and its impact on reviewing time. In this paper, we investigate the impact of reviews with code-reviewer assignment problem has on reviewing time. We find that reviews with code-reviewer assignment problem take 12 days longer to approve a code change. To help developers find appropriate code-reviewers, we propose RevFinder, a file location-based code-reviewer recommendation approach. We leverage a similarity of previously reviewed file path to recommend an appropriate code-reviewer. The intuition is that files that are located in similar file paths would be managed and reviewed by similar experienced code-reviewers. Through an empirical evaluation on a case study of 42,045 reviews of Android Open Source Project (AOSP), OpenStack, Qt and LibreOffice projects, we find that RevFinder accurately recommended 79% of reviews with a top 10 recommendation. RevFinder also correctly recommended the code-reviewers with a median rank of 4. The overall ranking of RevFinder is 3 times better than that of a baseline approach. We believe that RevFinder could be applied to MCR in order to help developers find appropriate code-reviewers and speed up the overall code review process.