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Automated software test optimisation framework – an artificial bee colony optimisation-based approach

Automated software test optimisation framework – an artificial bee colony optimisation-based approach

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Software test suite optimisation is one of the most important problems in software engineering research. To achieve this optimisation, a novel approach based on artificial bee colony (ABC) optimisation is proposed here. The work applied in this approach is motivated by the intelligent behaviour of honey bees. Since the ABC system combines local search methods carried out by employed and onlooker bees with global search methods managed by scouts, the approach attains global or near-global optima. Here, the parallel behaviour of the three bees is used to reach the solution generation faster. The performance of the proposed approach is investigated based on coverage-based test adequacy criteria by comparing it with sequential ABC, random testing and genetic algorithm-based approaches. Based on the experimental results, it has been proved that the proposed parallel ABC approach outperforms the other approaches in test suite optimisation.

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