• DocumentCode
    2387888
  • Title

    A Bootstrap Method for Software Reliability Assessment Based on a Discretized NHPP Model

  • Author

    Inoue, S. ; Yamada, S.

  • Author_Institution
    Dept. of Social Manage. Eng., Tottori Univ., Tottori, Japan
  • fYear
    2012
  • fDate
    18-19 Nov. 2012
  • Firstpage
    23
  • Lastpage
    27
  • Abstract
    We discuss a bootstrap method for software reliability assessment based on a discretized no homogeneous Poisson process (NHPP) model. Ordinarily, model parameters of the discretized NHPP model are estimated by using the regression analysis based on the regression equation derived from a difference equation of the discretized NHPP model. However, it is not so easy to derive some information for the statistical inference on software reliability assessment by the existing estimation approach for the model parameters because it is very difficult to identify the probability distribution function for the parameter estimates analytically. In this paper, we discuss a method for statistical inference on software reliability assessment based on the discretized NHPP model by applying a bootstrap method to the regression analysis, and show numerical examples of interval estimations for the several software reliability assessment measures by using actual data.
  • Keywords
    inference mechanisms; regression analysis; software reliability; stochastic processes; bootstrap method; discretized NHPP model; nonhomogeneous Poisson process; probability distribution function; regression analysis; regression equation; software reliability assessment; statistical inference; Bootstrap method; Discretized NHPP model; Regression analysis; Software reliability assessment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Dependable Transportation Systems/Recent Advances in Software Dependability (WDTS-RASD), 2012 Workshop on
  • Conference_Location
    Niigata
  • Print_ISBN
    978-1-4799-0315-3
  • Type

    conf

  • DOI
    10.1109/WDTS-RASD.2012.14
  • Filename
    6532144