• DocumentCode
    3659760
  • Title

    Variable strength interaction test set generation using Multi Objective Genetic Algorithms

  • Author

    Sangeeta Sabharwal;Manuj Aggarwal

  • Author_Institution
    Department of Information Technology, NSIT, Delhi, India
  • fYear
    2015
  • Firstpage
    2049
  • Lastpage
    2053
  • Abstract
    Combinatorial testing aims at identifying faults that are caused due to interactions of a small number of input parameters. It provides a technique to select a subset of exhaustive test cases covering all the t-way interactions without much loss of the fault detection capability. The test set generated is for a fixed value of t. In this paper, an approach is proposed to generate test set for a system where some variables have higher interaction strength among them as compared to that of the system. Variable Strength Covering Arrays are used for testing such systems. We propose to generate Variable Strength Covering Arrays using Multi objective optimization (Multi Objective Genetic Algorithms). We attempt to reduce the test set size while covering all the base level interactions of the system and higher strength interactions of its components. Experimental results indicate that the proposed approach generates results comparable to or better in some cases as compared to that of existing approaches.
  • Keywords
    "Genetic algorithms","Optimization","Software testing","Biological cells","Conferences","Particle swarm optimization"
  • Publisher
    ieee
  • Conference_Titel
    Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on
  • Print_ISBN
    978-1-4799-8790-0
  • Type

    conf

  • DOI
    10.1109/ICACCI.2015.7275918
  • Filename
    7275918