Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm

Software plays an important part of our daily life in order to aid and facilitate our routine tasks, especially a household one. However, the failure of software is a major threat to our lives, particularly the critical applications that employed daily. Due to the large number of inputs as well as time consumption for a test and cost, it is becoming hard to get exhaustive testing for any software in order to fault detection. For this reason, Combinatorial Testing Technique (CTT) is one of the famous techniques that have been used in fault detection of the software systems. Pairwise testing is one of the efficient CTT that used widely for fault detection based on the caused failures by two interactions parameters. There are many researchers that have been developed a pairwise testing strategy. Complementing to the earlier researches, this paper proposes a new pairwise test suite generation called Pairwise Hybrid Artificial Bee Colony (PhABC) strategy based on hybridize of an Artificial Bee Colony (ABC) algorithm with a Particle Swarm Optimization (PSO) algorithm. Empirical results shows that PhABC strategy outperforms other strategies in some cases and provides competitive results in other cases by generating the final test suite. © 2020, Springer Nature Singapore Pte Ltd.