Improving code review effectiveness through reviewer recommendations
Patanamon Thongtanunam, Raula Gaikovina Kula, Ana Erika Camargo Cruz, Norihiro Yoshida, Hajimu Iida · 2014
Effectively performing code review increases the quality of software and reduces occurrence of defects. However, this requires reviewers with experiences and deep understandings of system code. Manual selection of such reviewers can be a costly and time-consuming task. To reduce this cost, we propose a reviewer recommendation algorithm determining file path similarity called FPS algorithm. Using three OSS projects as case studies, FPS algorithm was accurate up to 77.97%, which significantly outperformed the previous approach.