Case studies in learning-based testing

We present case studies which show how the paradigm of learning-based testing (LBT) can be successfully applied to black-box requirements testing of industrial reactive systems. For this, we apply a new testing tool LBTest, which combines algorithms for incremental black-box learning of Kripke structures with model checking technology. We show how test requirements can be modeled in propositional linear temporal logic extended by finite data types.We then provide benchmark performance results for LBTest applied to three industrial case studies.
QC 20140320