We study the accurate and efficient computation of the expected number of times each state
is visited in discrete-and continuous-time Markov chains. To obtain sound accuracy …

We study the complexity of reductions for weighted reachability in parametric Markov
decision processes. That is, we say a state p is never worse than q if for all valuations of the …

We present a method for constructing the composition of Probabilistic Control Flow
Programs, which model probabilistic programs using transitions between control-flow …

Probabilistic model checking is a fully automated technique to rigorously prove correctness
of a system model with randomness against a formal specification. Its key algorithmic …