• DocumentCode
    2992599
  • Title

    Using Organizational Evolutionary Particle Swarm Techniques to Generate Test Cases for Combinatorial Testing

  • Author

    Pan, Xiaoying ; Chen, Hao

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Xi´´an Univ. of Posts & Telecommun., Xi´´an, China
  • fYear
    2011
  • fDate
    3-4 Dec. 2011
  • Firstpage
    1580
  • Lastpage
    1583
  • Abstract
    Based on the analysis of the characteristics of combinatorial testing, an organizational evolutionary particle swarm algorithm (OEPST) to generate test cases for combinatorial testing is proposed. This algorithm is used to select the test cases of local optimal coverage in current environment based on these test cases, and then a test suite satisfying the pair-wise coverage criterion is built. The empirical results show that this approach can effectively reduce the number of test case.
  • Keywords
    combinatorial mathematics; particle swarm optimisation; combinatorial testing; organizational evolutionary particle swarm algorithm; pair-wise coverage criterion; Algorithm design and analysis; Lead; Organizations; Particle swarm optimization; Software; Software algorithms; Testing; organizational evolutionary; pairwise coverage; particle swarm; test cases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Security (CIS), 2011 Seventh International Conference on
  • Conference_Location
    Hainan
  • Print_ISBN
    978-1-4577-2008-6
  • Type

    conf

  • DOI
    10.1109/CIS.2011.354
  • Filename
    6128395
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2992599