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Towards quantitative analysis of real-time UML using stochastic Petri nets

In recent years the Unified Modeling Language (UML) including its profiles gained increasing acceptance as a specification language for modeling real-time systems. It is crucial to enable early quantitative predictions during the modeling phase of real-time systems development processes. UML itself is not directly analyzable. Performance evaluation techniques are thus necessary for these UML models. The challenge within our research work is the derivation of stochastic Petri nets (SPNs) from UML models aimed at performance evaluation of real-time systems.