• DocumentCode
    884044
  • Title

    Estimating defects in commercial software during operational use

  • Author

    Kenny, G.Q.

  • Author_Institution
    IBM Corp., Research Triangle Park, NC
  • Volume
    42
  • Issue
    1
  • fYear
    1993
  • fDate
    3/1/1993 12:00:00 AM
  • Firstpage
    107
  • Lastpage
    115
  • Abstract
    A new model that accounts for the usage growth of commercial software during the operational phase, and that incorporates a factor to estimate (from field-failure reports) the usage growth is presented. The model can estimate the number of remaining unique defects in wide-distribution commercial software during the operational phase, and the anticipated arrival times of customer-reported failures attributable to these unique defects. The model is based on the Weibull distribution, which assumes that field usage of commercial software increases as a power function of time. The model was fit to the actual failure times for two commercial software products-one that runs on 105 systems, and the other that runs on 104 systems. The model fits the general shape of the arrival distribution for the actual defect discovery times, but there are minor peaks in the example data that are not explained by the model. Some of the minor modes correspond to peak defect discovery times for subsequent releases of the software
  • Keywords
    reliability theory; software reliability; statistical analysis; Weibull distribution; actual defect discovery times; arrival distribution; commercial software; customer-reported failures; field-failure reports; growth model; operational use; peak defect discovery times; power function of time; software reliability; unique defects estimation; usage growth; Monitoring; Phase estimation; Power system modeling; Predictive models; Software development management; Software engineering; Software quality; Software reliability; System testing; Weibull distribution;
  • fLanguage
    English
  • Journal_Title
    Reliability, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9529
  • Type

    jour

  • DOI
    10.1109/24.210280
  • Filename
    210280