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International Journal of Information Technology

, Volume 11, Issue 4, pp 633–637 | Cite as

Total fault exposing potential based test case prioritization using genetic algorithm

  • Deepti Bala MishraEmail author
  • Namita Panda
  • Rajashree Mishra
  • Arup Abhinna Acharya
Original Research
  • 47 Downloads

Abstract

The quality of modified software depends on selecting an efficient technique of Regression testing, in which the test cases are selected based on how fast the mutants are detected. The process of executing the most beneficial test case is called as test case prioritization. The redundant test cases which detect the same mutants can be eliminated for minimization, which results in reducing the cost and time of regression testing. This paper presents a code based prioritization technique in which total statement coverage, total fault exposing potential award and total mutant coverage is taken as prioritization factors to prioritize test cases for software under test. In the proposed method, Genetic Algorithm is used for prioritization and further test cases are minimized based on total mutant coverage. The effectiveness of the prioritized order is measured by Average Percentage of Statement Coverage metric.

Keywords

Software test case Genetic algorithm Test case prioritization Fault exposing potential (FEP) Statement coverage APSC 

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Copyright information

© Bharati Vidyapeeth's Institute of Computer Applications and Management 2018

Authors and Affiliations

  • Deepti Bala Mishra
    • 1
    Email author
  • Namita Panda
    • 1
  • Rajashree Mishra
    • 2
  • Arup Abhinna Acharya
    • 1
  1. 1.School of Computer EngineeringKIIT UniversityBhubaneswarIndia
  2. 2.School of Applied SciencesKIIT UniversityBhubaneswarIndia

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