• DocumentCode
    506744
  • Title

    Research of Software Reliability Estimation Method Based on Bayes theory

  • Author

    Zhang Bo-ping ; Zhang Cui-shan

  • Author_Institution
    Coll. of Comput. & Technol., Xuchang Univ., Xuchang, China
  • Volume
    3
  • fYear
    2009
  • fDate
    20-22 Nov. 2009
  • Firstpage
    66
  • Lastpage
    69
  • Abstract
    By the Bayesian method, a formalistic description is presented based on the random testing procedure of input area, a Software Reliability Estimation Method is bringed forward that make use of size of the random testing muster and the random right times, It will help to define the prior information needed by the Bayesian method. According to the general information, the prior information and the testing information, the post probability density function can be constructed, that can be used to calculate the correctness probability of a program. The selection method commendably solves the problem of the parameter estimate about the prior probability density function of the disabled behavior of software. When the method compares with Software Reliability Estimation Method Based on time area it has briefness character, sufficipost probability density functionent academic gist, easy intellect, and the data collectes easily etc.
  • Keywords
    Bayes methods; estimation theory; software reliability; Bayes theory; briefness character; formalistic description; input area random testing procedure; prior probability density function; random right times; random testing muster; software disabled behavior; software reliability estimation method; Decision support systems; Software reliability; Bayesian Method; Sofware Reliability; Sofware Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-4754-1
  • Electronic_ISBN
    978-1-4244-4738-1
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2009.5358235
  • Filename
    5358235