Design and implementation of a harmony-search-based variable-strength t-way testing strategy with constraints support

ContextAlthough useful, AI-based variable strength t-way strategies are lacking in terms of the support for high interaction strength. Additionally, most AI-based strategies generally do not address the support for constraints. Addressing the aforementioned issues, this paper elaborates the design, implementation, and evaluation of a novel variable-strength-based on harmony search algorithm, called Harmony Search Strategy (HSS).ObjectiveThe objective of this work is to investigate the adoption of harmony search algorithm for constructing variable-strength t-way strategy.MethodImplemented in Java, HSS integrates the harmony search algorithm as parts of its search engine.ResultBenchmarking results demonstrate that HSS gives competitive results against most existing AI-based (and pure computational) counterparts. However, unlike other AI-based counterparts, HSS addresses the support for high interaction strength and permits the support for constraints.ConclusionAI-based t-way strategies tend to outperform the pure computational-based strategies in terms of test size.

► HSS is the first variable strength t-way strategy that adopts HS algorithm as its core implementation.
► HSS also addresses the support for high interaction strength (i.e. t > 6) and implements the support for constraints.
► HSS performance in term of test size is statistically significant as compared to competing strategies.