IncBL: Incremental Bug Localization

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. Users can deploy and use IncBL locally as well. The demo video for IncBL can be viewed at https://youtu.be/G4gMuvlJSb0, and the source code can be found at https://github.com/soarsmu/IncBL.