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Bug localization using revision log analysis and open bug repository text categorization

Moin, A. H ; Sharif University of Technology | 2010

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  1. Type of Document: Article
  2. DOI: 10.1007/978-3-642-13244-5_15
  3. Publisher: 2010
  4. Abstract:
  5. In this paper, we present a new approach to localize a bug in the software source file hierarchy. The proposed approach uses log files of the revision control system and bug reports information in open bug repository of open source projects to train a Support Vector Machine (SVM) classifier. Our approach employs textual information in summary and description of bugs reported to the bug repository, in order to form machine learning features. The class labels are revision paths of fixed issues, as recorded in the log file of the revision control system. Given an unseen bug instance, the trained classifier can predict which part of the software source file hierarchy (revision path) is more likely to be related to this issue. Experimental results on more than 2000 bug reports of 'UI'component of the Eclipse JDT project from the initiation date of the project until November 24, 2009 (about 8 years) using this approach, show weighted precision and recall values of about 98% on average
  6. Keywords:
  7. Bug reports ; Class labels ; Log analysis ; Log file ; Open source projects ; Precision and recall ; Revision control systems ; Source files ; Text categorization ; Textual information ; Control systems ; Support vector machines ; Text processing ; Open systems
  8. Source: 6th International IFIP WG 2.13 Conference on Open Source Systems, OSS 2010, Notre Dame, IN, 30 May 2010 through 2 June 2010 ; Volume 319 AICT , 2010 , Pages 188-199 ; 18684238 (ISSN) ; 9783642132438 (ISBN)
  9. URL: http://link.springer.com/chapter/10.1007%2F978-3-642-13244-5_15