• DocumentCode
    2688636
  • Title

    Estimation of distribution algorithms for testing object oriented software

  • Author

    Sagarna, Ramón ; Arcuri, Andrea ; Yao, Xin

  • Author_Institution
    Univ. of Birmingham, Birmingham
  • fYear
    2007
  • fDate
    25-28 Sept. 2007
  • Firstpage
    438
  • Lastpage
    444
  • Abstract
    One of the main tasks software testing involves is the generation of the test cases to be used during the test. Due to its expensive cost, the automation of this task has become one of the key issues in the area. While most of the work on test data generation has concentrated on procedural software, little attention has been paid to object oriented programs, even so they are a usual practice nowadays. We present an approach based on estimation of distribution algorithms (EDAs) for dealing with the test data generation of a particular type of objects, that is, containers. This is the first time that an EDA has been applied to testing object oriented software. In addition to automated test data generation, the EDA approach also offers the potential of modelling the fitness landscape defined by the testing problem and thus could provide some insight into the problem. Firstly, we show results from empirical evaluations and comment on some appealing properties of EDAs in this context. Next, a framework is discussed in order to deal with the generation of efficient tests for the container classes. Preliminary results are provided as well.
  • Keywords
    object-oriented methods; program testing; automated test data generation; container classes; estimation of distribution algorithms; fitness landscape; object oriented software testing; procedural software; Automatic testing; Containers; Costs; Electronic design automation and methodology; Object oriented modeling; Probability distribution; Software algorithms; Software quality; Software testing; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-1339-3
  • Electronic_ISBN
    978-1-4244-1340-9
  • Type

    conf

  • DOI
    10.1109/CEC.2007.4424504
  • Filename
    4424504