Test strategy generation using quantified CSPs

Abstract

Testing is the process of stimulating a system with inputs in order to reveal hidden parts of the system state. We consider a variant of the constraint-based testing problem that was put forward in the model-based diagnosis literature, and consists of finding input patterns that can discriminate between different, possibly non-deterministic models. We show that this problem can be framed as a game played between two opponents, and naturally lends itself towards a formulation in terms of quantified CSPs. This QCSP-based formulation is a starting point to extend testing to the practically relevant class of systems with limited controllability, where tests consist of stimulation strategies instead of simple input patterns. © 2008 Springer-Verlag Berlin Heidelberg.