Symbolic Input-Output Conformance Checking for Model-Based Mutation Testing

Abstract

This paper presents an approach to use symbolic input output conformance checking for mutation-based test case generation. In this approach, a possibly non-deterministic action system model is used as basis for generating a number of mutants. Subsequently after the generation of mutants, the original model and the mutants are simultaneously symbolically executed and tested for conformance. Distinguishing test cases are generated, if non-conformance is detected during this process. Several optimisations of the conformance check are presented and their effectiveness is underpinned by listing experimental results.