ABSTRACT
To manage bugs that appear in a software, developers often make use of a bug tracking system such as Bugzilla. Users can report bugs that they encounter in such a system. Whenever a user reports a new bug report, developers need to read the summary and description of the bug report and manually locate the buggy files based on this information. This manual process is often time consuming and tedious. Thus, a number of past studies have proposed bug localization techniques to automatically recover potentially buggy files from bug reports. Unfortunately, none of these techniques are integrated to bug tracking systems and thus it hinders their adoption by practitioners. To help disseminate research in bug localization to practitioners, we develop a tool named BugLocalizer, which is implemented as a Bugzilla extension and builds upon a recently proposed bug localization technique. Our tool extracts texts from summary and description fields of a bug report and source code files. It then computes similarities of the bug report with source code files to find the buggy files. Developers can use our tool online from a Bugzilla web interface by providing a link to a git source code repository and specifying the version of the repository to be analyzed. We have released our tool publicly in GitHub, which is available at: https://github.com/smagsmu/buglocalizer. We have also provided a demo video, which can be accessed at: http://youtu.be/iWHaLNCUjBY.
- J. Anvik, L. Hiew, and G. C. Murphy. Coping with an open bug repository. In ETX, 2005. Google ScholarDigital Library
- D. Kawrykow and M. P. Robillard. Non-essential changes in version histories. In ICSE, pages 351–360, 2011. Google ScholarDigital Library
- T.-D. B. Le, S. Wang, and D. Lo. Multi-abstraction concern localization. In ICSM, 2013. Google ScholarDigital Library
- Lucia, F. Thung, D. Lo, and L. Jiang. Are faults localizable? In MSR, pages 74–77, 2012. Google ScholarDigital Library
- S. K. Lukins, N. A. Kraft, and L. H. Etzkorn. Bug localization using latent dirichlet allocation. Information and Software Technology, 52(9):972–990, 2010. Google ScholarDigital Library
- C. Manning, P. Raghavan, and H. Schutze. Introduction to Information Retrieval. Cambridge, 2008. Google ScholarCross Ref
- A. Marcus and J. I. Maletic. Recovering documentation-to-source-code traceability links using latent semantic indexing. In ICSE, 2003. Google ScholarDigital Library
- M. Porter. An algorithm for suffix stripping. Program, 1980.Google ScholarCross Ref
- S. Rao and A. Kak. Retrieval from software libraries for bug localization: a comparative study of generic and composite text models. In MSR, 2011. Google ScholarDigital Library
- R. K. Saha, M. Lease, S. Khurshid, and D. E. Perry. Improving bug localization using structured information retrieval. In ASE, pages 345–355, 2013.Google ScholarDigital Library
- F. Thung, D. Lo, and L. Jiang. Automatic recovery of root causes from bug-fixing changes. In WCRE, 2013.Google ScholarCross Ref
- S. Wang and D. Lo. Version history, similar report, and structure: Putting them together for improved bug localization. In ICPC, 2014. Google ScholarDigital Library
- S. Wang, D. Lo, and J. Lawall. Compositional vector space models for improved bug localization. In ICSME, 2014.Google ScholarDigital Library
- J. Zhou, H. Zhang, and D. Lo. Where should the bugs be fixed? - more accurate information retrieval-based bug localization based on bug reports. In ICSE, 2012. Introduction Preliminaries Bugzilla IR Based Bug Localization BugLocalizer Related Work Conclusion and Future Work References Google ScholarDigital Library
Index Terms
- BugLocalizer: integrated tool support for bug localization
Recommendations
Bug localization via searching crowd-contributed code
Internetware '14: Proceedings of the 6th Asia-Pacific Symposium on InternetwareBug localization, i.e., locating bugs in code snippets, is a frequent task in software development. Although static bug-finding tools are available to reduce manual effort in bug localization, these tools typically detect bugs with known project-...
Will this localization tool be effective for this bug? Mitigating the impact of unreliability of information retrieval based bug localization tools
Information retrieval (IR) based bug localization approaches process a textual bug report and a collection of source code files to find buggy files. They output a ranked list of files sorted by their likelihood to contain the bug. Recently, several IR-...
Potential biases in bug localization: do they matter?
ASE '14: Proceedings of the 29th ACM/IEEE International Conference on Automated Software EngineeringIssue tracking systems are valuable resources during software maintenance activities and contain information about the issues faced during the development of a project as well as after its release. Many projects receive many reports of bugs and it is ...
Comments