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Application of Evolutionary Particle Swarm Optimization Algorithm in Test Suite Prioritization

  • Chug AnuradhaEmail author
  • Narula Neha
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 28)

Abstract

Regression testing is a software verification activity carried out when the software is modified during maintenance phase. To ensure the correctness of the updated software it is suggested to execute the entire test suite again but this would demand large amount of resources. Hence, there is a need to prioritize and execute the test cases in such a way that changed software is tested with maximum coverage of code in minimum time. In this work, Particle Swarm Optimization (PSO) algorithm is used to prioritize test cases based on three benchmark functions Sphere, Rastrigin and Griewank. The result suggests that the test suites are prioritized in least time when Griewank is used as benchmark function to calculate the fitness. This approach approximately saves 80% of the testing efforts in terms of time and manpower since only 1/5 of the prioritized test cases from the entire test suite need to be executed.

Keywords

Particle swarm optimization Benchmark functions Prioritization Regression testing 

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Copyright information

© Springer International Publishing AG  2018

Authors and Affiliations

  1. 1.University School of Information TechnologyGGSIPUDelhiIndia

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