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Abstract

Model-based testing (MBT) can reduce the cost of making test cases for critical applications significantly. Depending on the formality of the models, they can also be used for verification. Once the models are available model-based test case generation and verification can be seen as "push-button solutions." However, making the models is often perceived by practitioners as being extremely difficult, error prone, and overall daunting. This paper outlines an approach for generating models out of observations gathered while a system is operating. After refining the models with moderate effort, they can be used for verification and test case generation. The approach is illustrated with a concrete system from the safety and security domain.