🏆 People’s Choise Award in IWSC2019! Congrats to Ihara

🏆 伊原先生と奈良先端科学技術大学院大学との共著論文が国際会議IWSC2019で発表し，People’s Choise Awardを受賞しました

Mining Source Code Improvement Patterns from Similar Code Review Works
?People’s Choise Award?

Authors – Yuki Ueda, Takashi Ishio, Akinori Ihara, and Kenichi Matsumoto
Venue – International Workshop on Software Clones, 2019
Abstract—Code review is key to ensuring the absence of poten- tial issues in source code. Code reviewers spend a large amount of time to manually check submitted patches based on their knowledge. Since a number of patches sometimes have similar potential issues, code reviewers need to suggest similar source code changes to patch authors. If patch authors notice similar code improvement patterns by themselves before submitting to code review, reviewers’ cost would be reduced. In order to detect similar code changes patterns, this study employs a sequential pattern mining to detect source code improvement patterns that frequently appear in code review history. In a case study using a code review dataset of the OpenStack project, we found that the detected patterns by our proposed approach included effective examples to improve patches without reviewers’ manual check. We also found that the patterns have been changed in time series; our pattern mining approach timely achieves to track the effective code improvement patterns.
Preprint – [PDF]

伊原先生と奈良先端科学技術大学院大学ソフトウェア工学研究室との共著論文が国際会議IWSC2019 (International Workshop on Code Clones)においてPeople’s Choise Awardを受賞しました．

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[Web] 奈良先端科学技術大学院大学　ソフトウェア工学研究室