Probabilistic model checking is a powerful technique for formally verifying quantitative
properties of systems that exhibit stochastic behaviour. Such systems are found in many …

Given a parametric Markov model, we consider the problem of computing the rational
function expressing the probability of reaching a given set of states. To attack this principal …

This paper reviews the model of interactive Markov chains (IMCs, for short), an extension of
labelled transition systems with exponentially delayed transitions. We show that IMCs are …

Formal methods are increasingly being used for control and verification of dynamic systems
against complex specifications. In general, these methods rely on a relatively simple system …

Probabilistic model checking is a formal verification technique that has been successfully
applied to the analysis of systems from a broad range of domains, including security and …

We consider the problem of synthesising rate parameters for stochastic biochemical
networks so that a given time-bounded CSL property is guaranteed to hold, or, in the case of …

We introduce the web-based model checker iscas M c for probabilistic systems (see
http://iscasmc. ios. ac. cn/IscasMC). This Java application offers an easy-to-use web …

We consider the problem of computing the satisfaction probability of a formula for stochastic
models with parametric uncertainty. We show that this satisfaction probability is a smooth …

Providing evidence for the refutation of a property is an essential, if not the most important,
feature of model checking. This paper considers algorithms for counterexample generation …

We present an on-the-fly abstraction technique for infinite-state continuous-time Markov
chains. We consider Markov chains that are specified by a finite set of transition classes …