Constraint-Based Approaches to the Covering Test Problem

Covering arrays have been studied for their applications to drug screening and software and hardware testing. In this paper, we model the problem as a constraint program. Our proposed models exploit non-binary (global) constraints, redundant modelling, channelling constraints, and symmetry breaking constraints. Our initial experiments show that with our best integrated model, we are able to either prove optimality of existing bounds or find new optimal values for arrays of moderate size. Local search on a SAT-encoding of the model is able to find improved bounds on larger problems.