• DocumentCode
    1871000
  • Title

    Importance Sampling Based Safety-Critical Software Statistical Testing Acceleration

  • Author

    Yan Jiong ; Zhou Kun-Peng ; Deng Chang-Hong ; Ji Meng-Luo

  • Author_Institution
    Postdoctoral Res. Station, Hubei Electr. Power Co., Wuhan, China
  • fYear
    2010
  • fDate
    10-12 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    It is necessary to assess the reliability of safety-critical software to a high degree of confidence before they are deployed in the field. However, safety-critical software often includes some rarely executed critical operations that are often inadequately tested in statistical testing based reliability estimation. This paper discusses software statistical testing acceleration based on importance sampling technique. When both the critical operations and the entire software are adequately tested, the method can still get the unbiased software reliability from the test results with much less test cases. Thus, the statistical testing cost of safety-critical software can be reduced effectively The simulated annealing algorithm for calculating optimum transition probabilities of the Markov chain usage model for software statistical testing accelerating is also presented.
  • Keywords
    Markov processes; program testing; safety-critical software; simulated annealing; software reliability; statistical analysis; Markov chain; optimum transition probability; safety-critical software; sampling technique; simulated annealing; software quality; software reliability; statistical testing; Markov processes; Probability; Software; Software reliability; Statistical analysis; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5391-7
  • Electronic_ISBN
    978-1-4244-5392-4
  • Type

    conf

  • DOI
    10.1109/CISE.2010.5676800
  • Filename
    5676800