• DocumentCode
    2348964
  • Title

    Software reliability modeling by concatenating failure rates

  • Author

    Singpurwalla, Nozer D.

  • Author_Institution
    George Washington Univ., Washington, DC, USA
  • fYear
    1998
  • fDate
    4-7 Nov 1998
  • Firstpage
    106
  • Lastpage
    110
  • Abstract
    The concatenation of failure rate functions results in point process models that need not possess independent increments, or lack memory features of Poisson processes. Processes having a memory are more realistic as compared to those that do not, and as a consequence provide a credible framework for tracking reliability and predicting failure times. The purpose of the paper is to propose and describe a model for software reliability based on this paradigm. The proposed model is adaptive, can explain empirically observed phenomena, and outperforms the predictive ability of its competitors. The model and its inferential mechanism are complex, but software to implement it with ease, is available
  • Keywords
    Poisson distribution; software quality; software reliability; Poisson processes; empirically observed phenomena; failure rate concatenation; failure rate functions; failure times; inferential mechanism; point process models; predictive ability; software reliability modeling; Concatenated codes; Failure analysis; History; Predictive models; Proposals; Software engineering; Software quality; Software reliability; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Reliability Engineering, 1998. Proceedings. The Ninth International Symposium on
  • Conference_Location
    Paderborn
  • ISSN
    1071-9458
  • Print_ISBN
    0-8186-8991-9
  • Type

    conf

  • DOI
    10.1109/ISSRE.1998.730860
  • Filename
    730860