Construction of Mixed Covering Arrays of strengths 2 through 6 Using a Tabu Search Approach

The development of a new software system involves extensive tests of the software functionality in order to identify possible failures. Also, a software system already built requires a fine tuning of its configurable options to give the best performance in the environment where it is going to work. Both cases require a finite set of tests that avoids testing all the possible combinations (which is time consuming); to this situation mixed covering arrays (MCAs) are a feasible alternative. MCAs are combinatorial structures having a case per row. MCAs are small, in comparison with exhaustive search, and guarantee a level of interaction among the involved parameters (a difference with random testing). We present a tabu search algorithm (TSA) for the construction of MCAs. Also, we report the fine tuning process used to identify the best parameter values for TSA. The analyzed TSA parameters were three different initialization functions, five different tabu list sizes and the mixture of four neighborhood functions. The performance of TSA was evaluated with two benchmarks previously reported. The results showed that TSA improved the algorithms IPOG-F, ITCH, Jenny, TConfig, and TVG in relation with the size of the constructed matrices. Particularly, TSA found the optimal size in 20 of the 23 cases tested.