• DocumentCode
    3335484
  • Title

    Software Defects Prediction using Operating Characteristic Curves

  • Author

    Bergander, Torsten ; Luo, Yan ; Ben Hamza, A.

  • Author_Institution
    SAP Labs Canada Inc., Montreal
  • fYear
    2007
  • fDate
    13-15 Aug. 2007
  • Firstpage
    713
  • Lastpage
    718
  • Abstract
    We present a software defect prediction model using operating characteristic curves. The main idea behind our proposed technique is to use geometric insight in helping construct an efficient and fast prediction method to accurately predict the. cumulative number of failures at any given stage during the software development process. Our predictive approach uses the number of detected faults instead of the software failure-occurrence time in the testing phase. Experimental results illustrate the effectiveness and the much improved performance of the proposed method in comparison with the Bayesian prediction approaches.
  • Keywords
    Bayes methods; computational geometry; mathematics computing; program testing; software fault tolerance; Bayesian prediction approaches; geometric insight; operating characteristic curves; software defects prediction; software development process; software failure-occurrence time; testing phase; Bayesian methods; Costs; Fault detection; Prediction methods; Predictive models; Production; Programming; Software performance; Software reliability; Software systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Reuse and Integration, 2007. IRI 2007. IEEE International Conference on
  • Conference_Location
    Las Vegas, IL
  • Print_ISBN
    1-4244-1500-4
  • Electronic_ISBN
    1-4244-1500-4
  • Type

    conf

  • DOI
    10.1109/IRI.2007.4296704
  • Filename
    4296704