Metaheuristics for Multi Criteria Test Case Prioritization for Regression Testing


Abstract views: 78 / PDF downloads: 37

Authors

  • S Deepa Department of Information Science and Engineering, RV College of Engineering, Bengaluru, Karnataka, India 560026

DOI:

https://doi.org/10.57159/gadl.jcmm.1.1.22015

Keywords:

Software testing, Regression testing, Test case prioritization, Particle swarm optimization, Bat algorithm

Abstract

Under the constraints of project deliveries, it is too costly to frequency run a large number of test cases. Test case prioritization is needed to rank the test cases. The prioritization must be done in such way that it is able to detect maximum number of faults in available time. Though many test case prioritization techniques have been proposed they have not considered the risk is skipping the test cases. This work solves the test case prioritization or test case subset selection as a multi criteria optimization problem. A meta heuristics algorithm in proposed in this work combining Particle swarm optimization (PSO) with Bat algorithm is proposed to solve the problem of finding best subset of regression test cases with multi objectives of reducing risk in skipping test cases, maximizing the number of faults within the constraints of time

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Published

03-10-2022

How to Cite

Deepa, S. (2022). Metaheuristics for Multi Criteria Test Case Prioritization for Regression Testing. Journal of Computers, Mechanical and Management, 1(1), 42–51. https://doi.org/10.57159/gadl.jcmm.1.1.22015

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