• DocumentCode
    69596
  • Title

    Where Should We Fix This Bug? A Two-Phase Recommendation Model

  • Author

    Dongsun Kim ; Yida Tao ; Sunghun Kim ; Zeller, A.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China
  • Volume
    39
  • Issue
    11
  • fYear
    2013
  • fDate
    Nov. 2013
  • Firstpage
    1597
  • Lastpage
    1610
  • Abstract
    To support developers in debugging and locating bugs, we propose a two-phase prediction model that uses bug reports\´ contents to suggest the files likely to be fixed. In the first phase, our model checks whether the given bug report contains sufficient information for prediction. If so, the model proceeds to predict files to be fixed, based on the content of the bug report. In other words, our two-phase model "speaks up" only if it is confident of making a suggestion for the given bug report; otherwise, it remains silent. In the evaluation on the Mozilla "Firefox" and "Core" packages, the two-phase model was able to make predictions for almost half of all bug reports; on average, 70 percent of these predictions pointed to the correct files. In addition, we compared the two-phase model with three other prediction models: the Usual Suspects, the one-phase model, and BugScout. The two-phase model manifests the best prediction performance.
  • Keywords
    formal verification; program debugging; BugScout; Core packages; Firefox packages; Mozilla packages; bug report; debugging; speaks up; two-phase model; two-phase prediction model; two-phase recommendation model; Computational modeling; Computer bugs; Data mining; Feature extraction; Noise; Predictive models; Software; Bug reports; machine learning; patch file prediction;
  • fLanguage
    English
  • Journal_Title
    Software Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0098-5589
  • Type

    jour

  • DOI
    10.1109/TSE.2013.24
  • Filename
    6517844