• DocumentCode
    1829582
  • Title

    An investigation into whether the NHPP framework is suitable for software reliability prediction and estimation

  • Author

    Lin, Chu-Ti ; Tang, Kai-Wei ; Chang, Jun-Ru ; Huang, Chin-Yu

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Chiayi Univ., Chiayi, Taiwan
  • fYear
    2010
  • fDate
    7-10 Dec. 2010
  • Firstpage
    626
  • Lastpage
    630
  • Abstract
    Many software reliability growth models (SRGMs) based on non-homogeneous Poisson process (NHPP) framework have been proposed for estimating the reliability growth of products. However, some concerns regarding the properties of NHPP framework were exposed and discussed while the NHPP models have received considerable attention. Two main concerns are (I) the variance of an NHPP-based model grows as software testing proceeds, which was considered an unreasonable NHPP property for describing software failure behavior; and (II) the numbers of failures observed in disjoint time intervals are independent, which may fails in the early stage of software testing. With regard to Concern (I), we will justify the validity of NHPP framework through a mathematical perspective, i.e. the process of parameter estimation for NHPP models. Considering Concern (II), we will explain why NHPP SRGMs are still workable from the applicable perspectives. As a result, we believe the NHPP framework may still have merit.
  • Keywords
    software reliability; stochastic processes; nonhomogeneous Poisson process framework; software failure behavior; software reliability growth models; software reliability prediction; Biological system modeling; Software; Software engineering; Software reliability; Software testing; Software testing; artificial neural network (ANN); homogeneous Poisson process (HPP); non-homogeneous Poisson process (NHPP); software reliability; software reliability growth models (SRGMs); statistical test;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IEEM), 2010 IEEE International Conference on
  • Conference_Location
    Macao
  • ISSN
    2157-3611
  • Print_ISBN
    978-1-4244-8501-7
  • Electronic_ISBN
    2157-3611
  • Type

    conf

  • DOI
    10.1109/IEEM.2010.5674524
  • Filename
    5674524