• DocumentCode
    2339274
  • Title

    The limitations of genetic algorithms in software testing

  • Author

    Aljahdali, Sultan H. ; Ghiduk, Ahmed S. ; El-Telbany, Mohammed

  • Author_Institution
    Coll. of Comput. & Inf. Sys, Taif Univ., Taif, Saudi Arabia
  • fYear
    2010
  • fDate
    16-19 May 2010
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Software test-data generation is the process of identifying a set of data, which satisfies a given testing criterion. For solving this difficult problem there were a lot of research works, which have been done in the past. The most commonly encountered are random test-data generation, symbolic test-data generation, dynamic test-data generation, and recently, test-data generation based on genetic algorithms. This paper gives a survey of the majority of software test-data generation techniques based on genetic algorithms. It compares and classifies the surveyed techniques according to the genetic algorithms features and parameters. Also, this paper shows and classifies the limitations of these techniques.
  • Keywords
    genetic algorithms; program testing; dynamic test data generation; genetic algorithm; random test data generation; software test data generation; software testing; symbolic test data generation; Biological cells; Classification algorithms; Genetics; Optimization; Software; Software testing; genetic algorithms; software testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Systems and Applications (AICCSA), 2010 IEEE/ACS International Conference on
  • Conference_Location
    Hammamet
  • Print_ISBN
    978-1-4244-7716-6
  • Type

    conf

  • DOI
    10.1109/AICCSA.2010.5586984
  • Filename
    5586984