• DocumentCode
    1728109
  • Title

    A Modified Genetic Algorithm for Parameter Estimation of Software Reliability Growth Models

  • Author

    Hsu, Chao-Jung ; Huang, Chin-Yu ; Chen, Tsan-Yuan

  • Author_Institution
    Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu
  • fYear
    2008
  • Firstpage
    281
  • Lastpage
    282
  • Abstract
    In this paper, we propose a modified genetic algorithm (MGA) with calibrating fitness functions, weighted bit mutation, and rebuilding mechanism for the parameter estimation of software reliability growth models (SRGMs). An example using a real failure data is given to demonstrate the performance of proposed method. Experimental result shows that MGA is effective for estimating the parameters of SRGM.
  • Keywords
    genetic algorithms; parameter estimation; software reliability; fitness function calibration; modified genetic algorithm; parameter estimation; software reliability growth models; weighted bit mutation; Biological cells; Genetic algorithms; Genetic engineering; Genetic mutations; Least squares approximation; Maximum likelihood estimation; Parameter estimation; Reliability engineering; Software reliability; Wheels; modified genetic algorithm; parameter estimation; software reliability growth model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Reliability Engineering, 2008. ISSRE 2008. 19th International Symposium on
  • Conference_Location
    Seattle, WA
  • ISSN
    1071-9458
  • Print_ISBN
    978-0-7695-3405-3
  • Electronic_ISBN
    1071-9458
  • Type

    conf

  • DOI
    10.1109/ISSRE.2008.35
  • Filename
    4700336
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1728109