A Tuned Version of Ant Colony Optimization Algorithm (TACO) for Uniform Strength T-way Test Suite Generator: An Execution’s Time Comparison

Software testing is one of important phase in software development. The capabilities of t-way testing to cater bugs due to interactions while reducing the test suite size compare to exhaustive testing has been proven in past decades. However, the execution’s time of the t-way strategy also should be...

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Bibliographic Details
Published in:Journal of physics. Conference series 2021-07, Vol.1962 (1), p.12037
Main Authors: Ahmad, Mohd Zamri Zahir, Othman, Rozmie Razif, Ali, Mohd Shaiful Aziz Rashid, Ramli, Nuraminah, Nasrudin, Mohd Wafi, Halim, Ahmad Ashraf Abdul
Format: Article
Language:English
Subjects:
Algorithms
Ant Colony Optimization
Combinatorial testing
Fuzzy logic
Heuristic methods
Optimization algorithms
Software development
Software testing
T-way testing
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Summary:Software testing is one of important phase in software development. The capabilities of t-way testing to cater bugs due to interactions while reducing the test suite size compare to exhaustive testing has been proven in past decades. However, the execution’s time of the t-way strategy also should be given attention as it could increase the productivity of the testing phase. Thus, this paper proposed a tune version of ant colony optimization algorithm (TACO). TACO is metaheuristic strategy where it adopts ant colony optimization in generating test suites. As further improvement, TACO also integrated with fuzzy logic to dynamically select amount of ant in the algorithm. TACO able to supports uniform strength t-way testing. Experiment result shows that TACO produce a remarkable result of test suite size and execution’s time compared to other strategy for uniform strength t-way testing.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1962/1/012037