Data abstraction and constraint solving for conformance testing

Conformance testing is one of the most rigorous and well-developed testing techniques. Model-based test generation is an essential phase of the conformance testing approach. The main problem in this phase is the explosion of the number of test cases, often caused by large or infinite data domains for input and output data. In this paper we propose a test generation framework based on the use of data abstraction and constraint solving to suppress the number of test cases. The approach is evaluated on the CEPS (common electronic purse specifications) case study.