Toward Interactive Optimization of Source Code Differences: An Empirical Study of Its Performance
Year: 2024
Type: conference-paper
Abstract: 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.
Authors: Tsukasa Yagi, Shinpei Hayashi
Institution: Tokyo Institute of Technology
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: Autorepairability: creating and disseminating a new software quality indicator, The Era of Machine-Driven Bug Repair: Advancing Pseudo-Oracle Generation and Automated Bug Fixing Technologies, Enhancing Automated Software Evolution via Building and Utilizing Large-Scale Software Evolution Corpora, G8800516981, Advancing Software Engineering Tasks Based on Building Functional Equivalent Method Datasets
OpenAlex ID: W4403795289