• DocumentCode
    2441612
  • Title

    ReBucket: A method for clustering duplicate crash reports based on call stack similarity

  • Author

    Dang, Yingnong ; Wu, Rongxin ; Zhang, Hongyu ; Zhang, Dongmei ; Nobel, Peter

  • Author_Institution
    Microsoft Res. Asia, Beijing, China
  • fYear
    2012
  • fDate
    2-9 June 2012
  • Firstpage
    1084
  • Lastpage
    1093
  • Abstract
    Software often crashes. Once a crash happens, a crash report could be sent to software developers for investigation upon user permission. To facilitate efficient handling of crashes, crash reports received by Microsoft´s Windows Error Reporting (WER) system are organized into a set of “buckets”. Each bucket contains duplicate crash reports that are deemed as manifestations of the same bug. The bucket information is important for prioritizing efforts to resolve crashing bugs. To improve the accuracy of bucketing, we propose ReBucket, a method for clustering crash reports based on call stack matching. ReBucket measures the similarities of call stacks in crash reports and then assigns the reports to appropriate buckets based on the similarity values. We evaluate ReBucket using crash data collected from five widely-used Microsoft products. The results show that ReBucket achieves better overall performance than the existing methods. On average, the F-measure obtained by ReBucket is about 0.88.
  • Keywords
    operating systems (computers); pattern clustering; program debugging; software engineering; Microsoft Windows Error Reporting; ReBucket; WER; bucket information; call stack similarity; crashing bugs; duplicate crash report clustering; software developers; stack matching; Computer bugs; Equations; Mathematical model; Measurement; Software; Training; WER; call stack trace; clustering; crash reports; duplicate crash report detection;
  • 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.2012.6227111
  • Filename
    6227111