Revisiting the Effect of Branch Handling Strategies on Change Recommendation
Keisuke Isemoto, Takashi Kobayashi, Shinpei Hayashi

TL;DR
This study reevaluates how different branch handling strategies affect change recommendation accuracy, introducing a new comparison setting and analyzing branch characteristics' impact across multiple open-source projects.
Contribution
It extends prior research by comparing an additional branch handling strategy and analyzing branch features influencing change recommendation effectiveness.
Findings
Handling commits separately improves change recommendation in most cases.
Merge commit size and branch length positively influence recommendation accuracy.
A balanced performance among strategies was observed in the new comparison setting.
Abstract
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…
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