Optimized Test Case Selection using Scout-less Hybrid Artificial Bee Colony Approach and Crossover Operator
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2021 by IJETT Journal|
|Year of Publication : 2021|
|Authors : Palak, Preeti Gulia, Nasib Singh Gill
|DOI : 10.14445/22315381/IJETT-V69I3P208|
MLA Style: Palak, Preeti Gulia, Nasib Singh Gill "Optimized Test Case Selection using Scout-less Hybrid Artificial Bee Colony Approach and Crossover Operator" International Journal of Engineering Trends and Technology 69.3(2021):39-45.
APA Style:Palak, Preeti Gulia, Nasib Singh Gill. Optimized Test Case Selection using Scout-less Hybrid Artificial Bee Colony Approach and Crossover Operator International Journal of Engineering Trends and Technology, 69(3),39-45.
Efficient software testing depends on the quality of test cases that are capable of catching defects from every corner of the software and achieving higher coverage. In this article, a hybrid artificial bee colony optimization-based technique is proposed. The proposed approach defines the scout bee phase for abandoned solutions and incorporates features of a genetic algorithm for diversification. The proposed approach selects a minimal test suite with equivalent or better efficiency of its superset. It offers time and money-saving and contributes towards early product delivery. The proposed technique is assessed using five widely used programming problems and their mutants. When compared with similar existing techniques (i.e., Particle Swarm Optimization, Ant Colony Optimization, and Original Artificial Bee Colony) over various fitness ranges, the performance of the proposed approach shows better results and outperforms in terms of overall execution time and coverage.
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Artificial bee colony, Genetic Algorithm, Software testing, Swarm intelligence, Test case selection.