• DocumentCode
    588602
  • Title

    When would this bug get reported?

  • Author

    Thung, Ferdian ; Lo, Daniel ; Lingxiao Jiang ; Lucia ; Rahman, Farin ; Devanbu, P.T.

  • Author_Institution
    Singapore Manage. Univ., Singapore, Singapore
  • fYear
    2012
  • fDate
    23-28 Sept. 2012
  • Firstpage
    420
  • Lastpage
    429
  • Abstract
    Not all bugs in software would be experienced and reported by end users right away: Some bugs manifest themselves quickly and may be reported by users a few days after they get into the code base; others manifest many months or even years later, and may only be experienced and reported by a small number of users. We refer to the period of time between the time when a bug is introduced into code and the time when it is reported by a user as bug reporting latency. Knowledge of bug reporting latencies has an implication on prioritization of bug fixing activities-bugs with low reporting latencies may be fixed earlier than those with high latencies to shift debugging resources towards bugs highly concerning users. To investigate bug reporting latencies, we analyze bugs from three Java software systems: AspectJ, Rhino, and Lucene. We extract bug reporting data from their version control repositories and bug tracking systems, identify bug locations based on bug fixes, and back-trace bug introducing time based on change histories of the buggy code. Also, we remove non-essential changes, and most importantly, recover root causes of bugs from their treatments/fixes. We then calculate the bug reporting latencies, and find that bugs have diverse reporting latencies. Based on the calculated reporting latencies and features we extract from bugs, we build classification models that can predict whether a bug would be reported early (within 30 days) or later, which may be helpful for prioritizing bug fixing activities. Our evaluation on the three software systems shows that our bug reporting latency prediction models could achieve an AUC (Area Under the Receiving Operating Characteristics Curve) of 70.869%.
  • Keywords
    Java; aspect-oriented programming; pattern classification; program debugging; AUC; AspectJ; Java software systems; Lucene; Rhino; area under-the-receiving operating characteristics curve; back-trace bug; bug fixing activities; bug location identification; bug reporting data extraction; bug reporting latency prediction models; bug tracking systems; classification models; debugging resources; software bugs; software systems; version control repositories; Computer bugs; Conferences; Databases; Feature extraction; Java; Predictive models; Software systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Maintenance (ICSM), 2012 28th IEEE International Conference on
  • Conference_Location
    Trento
  • ISSN
    1063-6773
  • Print_ISBN
    978-1-4673-2313-0
  • Type

    conf

  • DOI
    10.1109/ICSM.2012.6405302
  • Filename
    6405302