• DocumentCode
    2779116
  • Title

    Genetic Algorithm Based on Software Diagnosis Testing

  • Author

    Yang Shunkun ; Zeng Fuping ; Yan Lin

  • Author_Institution
    Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China
  • Volume
    1
  • fYear
    2011
  • fDate
    24-25 Sept. 2011
  • Firstpage
    83
  • Lastpage
    86
  • Abstract
    Based on genetic algorithm, the problem of software diagnosis testing is considered in this paper to reproduce the failure for the kind of systems with multi-input/output variables. Firstly, the problem prototype is abstracted, and then solutions to the prototype problems are introduced. From the aspects of coding scheme, population initialization, genetic operation, selection of fitness function, and convergence criterion, etc., how genetic algorithm can be applied in such prototype problem as software fault reproduction is thoroughly described. The experimental result shows that the injected software failure can be reproduced rapidly in the given program.
  • Keywords
    genetic algorithms; program diagnostics; program testing; software fault tolerance; genetic algorithm; multi-input/output variables; prototype problem; software diagnosis testing; software fault reproduction; Encoding; Genetic algorithms; Genetics; Prototypes; Software; Testing; Vectors; fault diagnosis; genetic algorithm; software testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology, Computer Engineering and Management Sciences (ICM), 2011 International Conference on
  • Conference_Location
    Nanjing, Jiangsu
  • Print_ISBN
    978-1-4577-1419-1
  • Type

    conf

  • DOI
    10.1109/ICM.2011.291
  • Filename
    6113361