• DocumentCode
    2978260
  • Title

    Detection and Correction Process Modeling Considering the Time Dependency

  • Author

    Wu, Y.P. ; Hu, Q.P. ; Xie, M. ; Ng, S.H.

  • Author_Institution
    Dept. of Ind. & Syst. Eng., Nat. Univ. of Singapore
  • fYear
    2006
  • fDate
    Dec. 2006
  • Firstpage
    19
  • Lastpage
    25
  • Abstract
    Most of the models for software reliability analysis are based on reliability growth models which deal with the fault detection process only. In this paper, some useful approaches to the modeling of both software fault detection and fault correction processes are discussed. Since the estimation of model parameters in software testing is essential to give accurate prediction and help make the right decision about software release, the problem of estimating the parameters is addressed. Taking into account the dependency between the fault correction process and the fault detection process, a new explicit formula for the likelihood function is derived and the maximum likelihood estimates are obtained under various time delay assumptions. An actual set of data from a software development project is used as an illustrative example. A Monte Carlo simulation is carried out to compare the predictive capability between the LSE method and the MLE method
  • Keywords
    Monte Carlo methods; maximum likelihood estimation; program testing; software fault tolerance; software process improvement; Monte Carlo simulation; correction process modeling; fault correction process; fault detection process; maximum likelihood estimates; software development project; software reliability analysis; software testing; Delay effects; Delay estimation; Fault detection; Maximum likelihood detection; Maximum likelihood estimation; Parameter estimation; Predictive models; Programming; Software reliability; Software testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Dependable Computing, 2006. PRDC '06. 12th Pacific Rim International Symposium on
  • Conference_Location
    Riverside, CA
  • Print_ISBN
    0-7695-2724-8
  • Type

    conf

  • DOI
    10.1109/PRDC.2006.27
  • Filename
    4041884