We introduce a framework to study stochastic systems, i.e. systems in which the time of occurrence of activities is a general random variable. We introduce and discuss in depth a stochastic process algebra (named) adequate to specify and analyse those systems. In order to give semantics to , we also introduce a model that is an extension of traditional automata with clocks which are basically r...

We introduce a new class of probabilistic automata: Probabilistic Residual Finite State Automata. We show that this class can be characterized by a simple intrinsic property of the stochastic languages they generate (the set of residual languages is finitely generated) and that it admits canonical minimal forms. We prove that there are more languages generated by PRFA than by Probabilistic Dete...

Microscopic traffic models have recently gained considerable importance as a mean of optimising traffic control strategies. Computationally efficient and sufficiently accurate microscopic traffic models have been developed based on the cellular automata theory. However, the real-time application of the available cellular automata models in traffic control systems is a difficult task due to thei...

This work presents version 1.3 of the Finite Improbability Generator (FIG): a statistical model checker to estimate transient and steady-state reachability properties in stochastic automata. Specialised rare event simulation via importance splitting, FIG implements RESTART Fixed Effort algorithms. Its distinctive feature is push-button automation: users need not define an function, because can ...

The analysis of hybrid systems exhibiting probabilistic behaviour is notoriously difficult. To enable mechanised analysis of such systems, we extend the reasoning power of arithmetic satisfiability-modulo-theory solving (SMT) by a comprehensive treatment of randomized (a.k.a. stochastic) quantification over discrete variables within the mixed Boolean-arithmetic constraint system. This provides ...