[国際会議] Revisiting the Effect of Branch Handling Strategies on Change Recommendation

小林教授が参加した変更履歴抽出戦略に関する共同研究の成果が, 米国Pittsburgh でハイブリッド開催された 30th IEEE/ACM International Conference on Program Comprehension (ICPC 2022) のReplications and Negative Results (RENE) Trackで発表されました．

著者：Keisuke Isemoto, Takashi Kobayashi, Shinpei Hayashi:
題目： Revisiting the Effect of Branch Handling Strategies on Change Recommendation
掲載誌：Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension (ICPC 2022), Pages 162–172, 2022
DOI: 10.1145/3524610.3527870, (Preprint: arXiv:2204.04423 [cs.SE])
概要：
Although literature has noted the effects of branch handling strategies on change recommendation based on evolutionary coupling, they have been tested in a limited experimental setting. Additionally, the branches characteristics that lead to these effects have not been investigated. In this study, we revisited the investigation conducted by Kovalenko et al. on the effect to change recommendation using two different branch handling strategies: including changesets from commits on a branch and excluding them. In addition to the setting by Kovalenko et al., we introduced another setting to compare: extracting a changeset for a branch from a merge commit at once. We compared the change recommendation results and the similarity of the extracted co-changes to those in the future obtained using two strategies through 30 open-source software systems. The results show that handling commits on a branch separately is often more appropriate in change recommendation, although the comparison in an additional setting resulted in a balanced performance among the branch handling strategies. Additionally, we found that the merge commit size and the branch length positively influence the change recommendation results.