• DocumentCode
    2905824
  • Title

    Estimating Markov Modulated Software Reliability Models via EM Algorithm

  • Author

    Ando, Takao ; Okamura, Hiroyuki ; Dohi, Tadashi

  • Author_Institution
    Dept. of Inf. Eng., Hiroshima Univ.
  • fYear
    2006
  • fDate
    Sept. 29 2006-Oct. 1 2006
  • Firstpage
    111
  • Lastpage
    118
  • Abstract
    In this paper, we develop a parameter estimation method to Markovian software reliability models. When software fault-detection rates change in the software testing phase, fault-detection processes can be generally modeled by Markov modulated processes. This paper deals with a unified parameter estimation method for Markov modulated software reliability models as well as the typical pure birth process models. In numerical examples, we evaluate a goodness-of-fit for the Markov modulated software reliability models with real fault data, and show numerically that the Markov modulated software reliability models are superior to the existing pure birth process models in the viewpoint of information criterion
  • Keywords
    Markov processes; expectation-maximisation algorithm; parameter estimation; program testing; software reliability; EM algorithm; Markov modulated software reliability; parameter estimation; software fault detection; software testing; Bayesian methods; Fault detection; Parameter estimation; Phase modulation; Reliability engineering; Software algorithms; Software debugging; Software reliability; Software testing; Stochastic processes; EM algorithm; Information criterion; Markov modulated; Software reliability models; processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Dependable, Autonomic and Secure Computing, 2nd IEEE International Symposium on
  • Conference_Location
    Indianapolis, IN
  • Print_ISBN
    0-7695-2539-3
  • Type

    conf

  • DOI
    10.1109/DASC.2006.29
  • Filename
    4030873