• DocumentCode
    2443761
  • Title

    WhoseFault: Automatic developer-to-fault assignment through fault localization

  • Author

    Servant, Francisco ; Jones, James A.

  • Author_Institution
    Dept. of Inf., Univ. of California, Irvine, CA, USA
  • fYear
    2012
  • fDate
    2-9 June 2012
  • Firstpage
    36
  • Lastpage
    46
  • Abstract
    This paper describes a new technique, which automatically selects the most appropriate developers for fixing the fault represented by a failing test case, and provides a diagnosis of where to look for the fault. This technique works by incorporating three key components: (1) fault localization to inform locations whose execution correlate with failure, (2) history mining to inform which developers edited each line of code and when, and (3) expertise assignment to map locations to developers. To our knowledge, the technique is the first to assign developers to execution failures, without the need for textual bug reports. We implement this technique in our tool, WHOSEFAULT, and describe an experiment where we utilize a large, open-source project to determine the frequency in which our tool suggests an assignment to the actual developer who fixed the fault. Our results show that 81% of the time, WHOSEFAULT produced the same developer that actually fixed the fault within the top three suggestions. We also show that our technique improved by a difference between 4% and 40% the results of a baseline technique. Finally, we explore the influence of each of the three components of our technique over its results, and compare our expertise algorithm against an existing expertise assessment technique and find that our algorithm provides greater accuracy, by up to 37%.
  • Keywords
    data mining; program diagnostics; program testing; public domain software; software fault tolerance; WHOSEFAULT; automatic developer-to-fault assignment; execution failure; expertise assignment; failing test case; fault diagnosis; fault fixing; fault localization; history mining; location mapping; open-source project; Correlation; Data mining; History; Informatics; Measurement; Software; Software algorithms; developer assignment; expertise assignment; fault localization; mining software repositories;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering (ICSE), 2012 34th International Conference on
  • Conference_Location
    Zurich
  • ISSN
    0270-5257
  • Print_ISBN
    978-1-4673-1066-6
  • Electronic_ISBN
    0270-5257
  • Type

    conf

  • DOI
    10.1109/ICSE.2012.6227208
  • Filename
    6227208