Toward Interactive Optimization of Source Code Differences: An Empirical Study of Its Performance
<|reference_start|>Toward Interactive Optimization of Source Code Differences: An Empirical Study of Its Performance: A source code difference (diff) indicates changes made by comparing new and old source codes, and it can be utilized in code reviews to help developers understand the changes made to the code. Although many diff generation methods have been proposed, existing automatic methods may generate nonoptimal diffs, hindering reviewers from understanding the changes. In this paper, we propose an interactive approach to optimize diffs. Users can provide feedback for the points of a diff that should not be matched but are or parts that should be matched but are not. The edit graph is updated based on this feedback, enabling users to obtain a more optimal diff. We simulated our proposed method by applying a search algorithm to empirically assess the number of feedback instances required and the amount of diff optimization resulting from the feedback to investigate the potential of this approach. The results of 23 GitHub projects confirm that 92% of nonoptimal diffs can be addressed with less than four feedback actions in the ideal case.<|reference_end|>
@article{yagi2024toward,
    title={Toward Interactive Optimization of Source Code Differences: An Empirical
  Study of Its Performance},
    author={Tsukasa Yagi, Shinpei Hayashi},
    journal={Proceedings of the 24th IEEE International Conference on Source
  Code Analysis and Manipulation, 224-234, 2024},
    year={2024},
    doi={10.1109/SCAM63643.2024.00030},
    archivePrefix={arXiv},
    eprint={2409.13590},
    primaryClass={cs.SE}
}