A framework for performance evaluation and functional verification in stochastic process algebras

Despite its relatively short history, a wealth of formalisms exist for algebraic specification of stochastic systems. The goal of this paper is to give such formalisms a unifying framework for performance evaluation and functional verification. To this end, we propose an approach enabling a provably sound transformation from some existing stochastic process algebras, e.g., PEPA and MTIPP, to a generic form in the mCRL2 language. This way, we resolve the semantic differences among different stochastic process algebras themselves, on one hand, and between stochastic process algebras and classic ones, such as mCRL2, on the other hand. From the generic form, one can generate a state space and perform various functional and performance-related analyses, as we illustrate in this paper.