• DocumentCode
    1884902
  • Title

    Evidence-Based Analysis and Inferring Preconditions for Bug Detection

  • Author

    Brand, Daniel ; Buss, Marcio ; Sreedhar, Vugranam C.

  • Author_Institution
    IBM TJ Watson Res. Center, Yorktown Heights
  • fYear
    2007
  • fDate
    2-5 Oct. 2007
  • Firstpage
    44
  • Lastpage
    53
  • Abstract
    An important part of software maintenance is fixing software errors and bugs. Static analysis based tools can tremendously help and ease software maintenance. In order to gain user acceptance, a static analysis tool for detecting bugs has to minimize the incidence of false alarms. A common cause of false alarms is the uncertainty over which inputs into a program are considered legal. In this paper we introduce evidence-based analysis to address this problem. Evidence-based analysis allows one to infer legal preconditions over inputs, without having users to explicitly specify those preconditions. We have found that the approach drastically improves the usability of such static analysis tools. In this paper we report our experience with the analysis in an industrial deployment.
  • Keywords
    software maintenance; bug detection; evidence-based analysis; software maintenance; software tools; static analysis tool; Computer bugs; Information analysis; Law; Legal factors; Libraries; Software debugging; Software maintenance; Software tools; Uncertainty; Usability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Maintenance, 2007. ICSM 2007. IEEE International Conference on
  • Conference_Location
    Paris
  • ISSN
    1063-6773
  • Print_ISBN
    978-1-4244-1256-3
  • Electronic_ISBN
    1063-6773
  • Type

    conf

  • DOI
    10.1109/ICSM.2007.4362617
  • Filename
    4362617