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Test Suite Optimization Using Firefly and Genetic Algorithm

Test Suite Optimization Using Firefly and Genetic Algorithm
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Author(s): Abhishek Pandey (University of Petroleum and Energy Studies, Dehradun & Birla Institute of Technology, Mesra-Ranchi, India) and Soumya Banerjee (Conservatoire Nationale des Arts et Metiers & INRIA Paris ex-visiting CNRS INSA de Lyon, Paris, France)
Copyright: 2019
Volume: 11
Issue: 1
Pages: 16
Source title: International Journal of Software Science and Computational Intelligence (IJSSCI)
Editor(s)-in-Chief: Brij Gupta (National Institute of Technology, Kurukshetra, India) and Andrew W.H. Ip (University of Saskatchewan, Canada)
DOI: 10.4018/IJSSCI.2019010103


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Software testing is essential for providing error-free software. It is a well-known fact that software testing is responsible for at least 50% of the total development cost. Therefore, it is necessary to automate and optimize the testing processes. Search-based software engineering is a discipline mainly focussed on automation and optimization of various software engineering processes including software testing. In this article, a novel approach of hybrid firefly and a genetic algorithm is applied for test data generation and selection in regression testing environment. A case study is used along with an empirical evaluation for the proposed approach. Results show that the hybrid approach performs well on various parameters that have been selected in the experiments.

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