Learning in Uppaal for Test Case Generation for Cyber-Physical Systems

We propose a test-case generation method for testing cyber-physical systems by using learning and statistical model checking. We use timed game automata for modelling. Different from other studies, we construct the model from the environment’s perspective. After building the model, we synthesize policies for different kinds of environments by using reinforcement learning in Uppaal and parse the policies for test-case generation. Statistical model checking enables us to analyse the test cases for finding the ones that are more likely to detect bugs.