Randomization is a key element in sequential and distributed computing. Reasoning about
randomized algorithms is highly non-trivial. In the 1980s, this initiated first proof methods …

A comprehensive introduction to the foundations of model checking, a fully automated
technique for finding flaws in hardware and software; with extensive examples and both …

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 …

Because they incorporate both time-and event-driven dynamics, stochastic hybrid systems
(SHS) have become ubiquitous in a variety of fields, from mathematical finance to biological …

This paper studies the effect of bisimulation minimisation in model checking of monolithic
discrete-time and continuous-time Markov chains as well as variants thereof with rewards …

Abstract Generalised Stochastic Petri Nets (GSPN s) are a popular modelling formalism for
performance and dependability analysis. Their semantics is traditionally associated to …

This paper considers algorithms for counterexample generation for (bounded) probabilistic
reachability properties in fully probabilistic systems. Finding the strongest evidence (ie, the …

We present a constructive procedure for obtaining a finite approximate abstraction of a
discrete-time stochastic hybrid system. The procedure consists of a partition of the state …

This paper proposes a novel abstraction technique for continuous-time Markov chains
(CTMCs). Our technique fits within the realm of three-valued abstraction methods that have …