Combining Satisfiability Solving and Heuristics to Constrained Combinatorial Interaction Testing

Combinatorial interaction testing aims at revealing errors inside a system under test triggered by unintended interaction between values of its input parameters. In this context we defined a new greedy approach to generate a combinatorial interaction test suites in the presence of constraints, based on integration of an SMT solver, and ordered processing of test goals. Based on the observation that the processing order of required combinations determines the size of the final test suite, this approach has been then used as a framework to evaluate a set of deterministic ordering strategies, each based on a different heuristic optimization criteria. Their performance has been assessed and contrasted also with those of random and dummy ordering strategies. Results of experimental assessment are presented and compared with well-known combinatorial tools