General Variable Strength T-Way Strategy Supporting Flexible Interactions

Ensuring conformance as well as establishing quality, software testing is an integral part of software engineering lifecycle. However, due to resource and time-to-market constraints, testing all exhaustive possibilities is impossible in nearly all practical testing problems. Considering the aforementioned constraints, much research is now focusing on a sampling technique based on interaction testing (termed t-way strategy). Although helpful, most existing t-way strategies (e.g. AETG, IPOG and GTWay) assume that all parameters have uniform interaction. However, in reality, the interaction between parameters is rarely uniform. Some parameters may not even interact rendering wasted testing efforts. As a result, a number of newly developed t-way strategies that considers variable strength interaction based on input-output relationships have been developed in the literature e.g. Union, ParaOrder and Density. Although useful, these strategies often lack in optimality i.e. in term of the generated test size. Furthermore, no single strategy appears to be dominant as the optimal generation of t-way interaction test suite is considered NP hard problem. Motivated by the abovementioned challenges, this paper proposes and implements a new strategy, called General Variable Strength (GVS). It is demonstrated that GVS, in some cases, produces better results than other competing strategies