IDEAS home Printed from https://ideas.repec.org/a/igg/jncr00/v3y2012i3p21-40.html
   My bibliography  Save this article

Reducing Interface Mutation Costs with Multiobjective Optimization Algorithms

Author

Listed:
  • Tiago Nobre

    (Departamento de Informática, Universidade Federal do Paraná, Curitiba, PR, Brazil)

  • Silvia Regina Vergilio

    (Departamento de Informática, Universidade Federal do Paraná, Curitiba, PR, Brazil)

  • Aurora Pozo

    (Departamento de Informática, Universidade Federal do Paraná, Curitiba, PR, Brazil)

Abstract

To reduce mutation test costs, different strategies were proposed to find a set of essential operators that generates a reduced number of mutants without decreasing the mutation score. However, the operator selection is influenced by other factors, such as: number of test data, execution time, number of revealed faults, etc. In fact this is a multiobjective problem. For that, different good solutions exist. To properly deal with this problem, a selection strategy based on multiobjective algorithms was proposed and investigated for unit testing. This work explores the use of such strategy in the integration testing phase. Three multiobjective algorithms are used and evaluated with real programs: one algorithm based on tabu search (MTabu), one based on Genetic Algorithm (NSGA-II) and the third one based on Ant Colony Optimization (PACO). The results are compared with traditional strategies and contrasted with essential operators obtained in the unit testing level.

Suggested Citation

  • Tiago Nobre & Silvia Regina Vergilio & Aurora Pozo, 2012. "Reducing Interface Mutation Costs with Multiobjective Optimization Algorithms," International Journal of Natural Computing Research (IJNCR), IGI Global, vol. 3(3), pages 21-40, July.
    • Handle: RePEc:igg:jncr00:v:3:y:2012:i:3:p:21-40
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jncr.2012070102
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jncr00:v:3:y:2012:i:3:p:21-40. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.