Compositional Analysis of Probabilistic Timed Graph Transformation Systems

The analysis of behavioral models is high importance for cyber-physical systems, as the systems often encompass complex behavior based on e.g. concurrent components with mutual exclusion or probabilistic failures demand. rule-based formalism Probabilistic Timed Graph Transformation Systems (PTGTSs) a suitable choice when representing states system can be understood graphs and timed important. However, model checking PTGTSs limited to rather small state spaces. We present an approach large-scale modeled by systematically decomposing their spaces into manageable fragments. To obtain qualitative quantitative results system, we verify that obtained its fragments serve overapproximations corresponding system. Hence, our allows detection violations safety properties under analysis. consider running example in which shuttles drive tracks topology autonomously coordinate local other nearby. For this example, (a) always make expected forward progress using several properties, (b) never collide, (c) are unlikely execute emergency brakes two scenarios. In evaluation, apply implementation tool AutoGraph example.