• DocumentCode
    1528871
  • Title

    Evaluating capture-recapture models with two inspectors

  • Author

    Emam, Khaled El ; Laitenberger, Oliver

  • Author_Institution
    Inst. for Inf. Technol., Nat. Res. Council of Canada, Ottawa, Ont., Canada
  • Volume
    27
  • Issue
    9
  • fYear
    2001
  • fDate
    9/1/2001 12:00:00 AM
  • Firstpage
    851
  • Lastpage
    864
  • Abstract
    Capture-recapture (CR) models have been proposed as an objective method for controlling software inspections. CR models were originally developed to estimate the size of animal populations. In software, they have been used to estimate the number of defects in an inspected artifact. This estimate can be another source of information for deciding whether the artifact requires a reinspection to ensure that a minimal inspection effectiveness level has been attained. Little evaluative research has been performed thus far on the utility of CR models for inspections with two inspectors. We report on an extensive Monte Carlo simulation that evaluated capture-recapture models suitable for two inspectors assuming a code inspections context. We evaluate the relative error of the CR estimates as well as the accuracy of the reinspection decision made using the CR model. Our results indicate that the most appropriate capture-recapture model for two inspectors is an estimator that allows for inspectors with different capabilities. This model always produces an estimate (i.e., does not fail), has a predictable behavior (i.e., works well when its assumptions are met), will have a relatively high decision accuracy, and will perform better than the default decision of no reinspections. Furthermore, we identify the conditions under which this estimator will perform best
  • Keywords
    program testing; reviews; software quality; Monte Carlo simulation; capture-recapture models; fault estimation; inspectors; predictable behavior; quality control; reinspection; software inspections; Animals; Chromium; Computer Society; Context modeling; Information resources; Inspection; Performance evaluation; Process control; Software engineering; Software quality;
  • fLanguage
    English
  • Journal_Title
    Software Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0098-5589
  • Type

    jour

  • DOI
    10.1109/32.950319
  • Filename
    950319