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Abstract
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One of the important branches in software testing is array coverage testing, which is a subset of combinatorial testing. Array coverage testing is divided into two categories: array coverage with constant interaction strength and array coverage with variable interaction strength. In constant strength, all combinations use a single strength, while in variable strength, each subset of the system can have a different interaction strength, increasing flexibility in combinatorial testing. Different strategies have been proposed for array coverage generation, which are often divided into computational and meta-heuristic strategies; computational strategies are efficient in generating test sequences but usually lack efficiency, while meta-heuristic strategies have good efficiency but undesirable performance. A strategy that simultaneously has efficiency and performance in variable strength is impressive. In this research, we have attempted to generate optimal variable strength array coverage using Particle Swarm Optimization (PSO) and Biogeography-Based Optimization (BBO) algorithms, which show promising results in terms of efficiency and performance compared to other previous works.
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