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Article type: Research Article
Authors: Ghiduk, Ahmed S.a; * | Hashim, Marwab
Affiliations: [a] College of Computers and Information Technology, Taif University, Taif, Saudi Arabia | [b] Department of Mathematics and Computer Science, Faculty of Science, Beni-Suef University, Beni-Suef, Egypt
Correspondence: [*] Corresponding author. Ahmed S. Ghiduk, College of Computers and Information Technology, Taif University, PO Box 11099, Taif 21944, Saudi Arabia. E-mail: asaghiduk@tu.edu.sa.
Abstract: Mutation testing can evaluate the quality of the test inputs, generate test data, and simulate any test coverage criterion. Genetic algorithms and harmony search have been applied to reduce the cost of generating test inputs. Although hybridizing search algorithms enhances the efficiency of searching the solution domain, there is a shortage of applying the hybrid search techniques in mutation testing. This paper merges the genetic and harmony search algorithms to effectively generate test data to kill higher-order mutants. In addition, the performance of the proposed technique will be evaluated and compared with a stand-alone genetic algorithm and a stand-alone harmony search algorithm through an empirical study using a set of benchmark programs. The experimental study shows that the proposed technique outperformed the compared algorithms, reaching a higher killing ratio, where the proposed approach kills 92.8% of higher-order mutants for all tested programs. In comparison, GA kills 88.7%, and HA kills 86.6%. Besides, the proposed algorithm overcame the compared algorithm in reaching a targeted killing ratio faster than the compared algorithms. HGA reduced the execution time for each program with a reduction ratio ranging from 58.9% to 89.8%.
Keywords: Genetic algorithm, harmony search algorithm, higher-order mutation testing, test-data generation
DOI: 10.3233/JIFS-230226
Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 4429-4452, 2024
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