Towards a superset of Basic Lotos for Performance Prediction

Stochastic process algebras (SPA) provide primitive operators that serve as means to incorporate stochastic timing aspects into a process algebraic speciication. In this paper we add some comfortable operators to an SPA where the passing of time is separated from the occurrence of activities. We present a superset of Basic Lotos which integrates probabilistic branching and exponentially distributed time delays into the language, as well as value passing. The treatment of these ingredients is formally deened on the (interleaving) semantic model. After explaining the details of thelanguagès semantics, we deene a congruence relation based on Milner`s observational congruence that is central for the reduction of the semantic model into a Continuous Time Markov Chain.