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2018 | OriginalPaper | Chapter

Application of Evolutionary Particle Swarm Optimization Algorithm in Test Suite Prioritization

Authors : Chug Anuradha, Narula Neha

Published in: Computational Vision and Bio Inspired Computing

Publisher: Springer International Publishing

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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.

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Metadata
Title
Application of Evolutionary Particle Swarm Optimization Algorithm in Test Suite Prioritization
Authors
Chug Anuradha
Narula Neha
Copyright Year
2018
Book
Computational Vision and Bio Inspired Computing

Print ISBN: 978-3-319-71766-1

Electronic ISBN: 978-3-319-71767-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-71767-8_2