IncBL: Incremental Bug Localization
Zhou Yang, Jieke Shi, Shaowei Wang, David Lo

TL;DR
IncBL introduces an incremental bug localization tool that significantly reduces computation time in evolving software repositories while maintaining accuracy, enhancing efficiency for real-world applications.
Contribution
This paper develops an incremental update method for bug localization models and implements IncBL, a practical tool for efficient bug localization in dynamic codebases.
Findings
IncBL reduces runtime by 77.79% on average.
IncBL maintains the same accuracy as re-computing models.
IncBL is available as a GitHub App for easy deployment.
Abstract
Numerous efforts have been invested in improving the effectiveness of bug localization techniques, whereas little attention is paid to making these tools run more efficiently in continuously evolving software repositories. This paper first analyzes the information retrieval model behind a classic bug localization tool, BugLocator, and builds a mathematical foundation illustrating that the model can be updated incrementally when codebase or bug reports evolve. Then, we present IncBL, a tool for Incremental Bug Localization in evolving software repositories. IncBL is evaluated on the Bugzbook dataset, and the results show that IncBL can significantly reduce the running time by 77.79% on average compared with the re-computing the model, while maintaining the same level of accuracy. We also implement IncBL as a Github App that can be easily integrated into open-source projects on GitHub.…
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Taxonomy
TopicsSoftware Engineering Research · Software Testing and Debugging Techniques · Advanced Malware Detection Techniques
