Extracting structural information from bug reports

ABSTRACT

In software engineering experiments, the description of bug reports is typically treated as natural language text, although it often contains stack traces, source code, and patches. Neglecting such structural elements is a loss of valuable information; structure usually leads to a better performance of machine learning approaches. In this paper, we present a tool called infoZilla that detects structural elements from bug reports with near perfect accuracy and allows us to extract them. We anticipate that infoZilla can be used to leverage data from bug reports at a different granularity level that can facilitate interesting research in the future.

REFERENCES

• 1: J. Anvik, L. Hiew, and G. C. Murphy. Who should fix this bug? In ICSE '06: Proceeding of the 28th International Conference on Software Engineering, pages 361--370, 2006.
• 2: N. Bettenburg, S. Just, A. Schröter, C. Weiss, R. Premraj, and T. Zimmermann. Quality of bug reports in Eclipse. In Proceedings of the 2007 OOPSLA Workshop on Eclipse Technology eXchange (ETX), October 2007.
• 3: C. Bird, A. Gourley, and P. Devanbu. Detecting patch submission and acceptance in oss projects. In MSR '07: Proceedings of the Fourth International Workshop on Mining Software Repositories, 2007.
• 4: G. Canfora and L. Cerulo. Fine grained indexing of software repositories to support impact analysis. In MSR '06: Proceedings of the 2006 International Workshop on Mining Software Repositories, pages 105--111, 2006.
• 5: A. Dekhtyar, J. H. Hayes, and T. Menzies. Text is software too. In Proc. International Workshop on Mining Software Repositories (MSR), pages 22--26, Edinburgh, Scotland, UK, May 2004.
• 6: Comparing and Merging Files. http://www.gnu.org/software/ diffutils/manual/html_node/index.html. Last accessed 2008-01-16.
• 7: J. H. Hayes, A. Dekhtyar, and S. Sundaram. Text mining for software engineering: how analyst feedback impacts final results. In MSR '05: Proceedings of the 2005 international workshop on Mining software repositories, 2005.
• 8: L. Moonen. Generating robust parsers using island grammars. In Proceedings of the 8th Working Conference on Reverse Engineering, pages 13--22, Oct. 2001.
• 9: P. Runeson, M. Alexandersson, and O. Nyholm. Detection of duplicate defect reports using natural language processing. In ICSE '07: Proceedings of the 29th International Conference on Software Engineering, pages 499--510, 2007.
• 10: C. Weiss, R. Premraj, T. Zimmermann, and A. Zeller. How long will it take to fix this bug? In MSR '07: Proceedings of the Fourth International Workshop on Mining Software Repositories, 2007.
• 11: I. H. Witten and E. Frank. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann, 2000.

INDEX TERMS

Primary Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.7 Distribution, Maintenance, and Enhancement
          Subjects: Corrections**

Additional Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.5 Testing and Debugging
          Subjects: Diagnostics

General Terms:
Management, Measurement

Keywords:
bug reports, patches, source code, stack traces, structural information