Probabilistic model checking provides formal guarantees on quantitative properties such as
reliability, performance or risk, so the accuracy of the numerical results that it returns is …

This paper presents a retrospective view on probabilistic model checking. We focus on
Markov decision processes (MDPs, for short). We survey the basic ingredients of MDP …

Probabilistic model checking (PMC) is a well-established and powerful method for the
automated quantitative analysis of parallel distributed systems. Classical PMC-approaches …

The paper addresses the problem of computing maximal conditional expected accumulated
rewards until reaching a target state (briefly called maximal conditional expectations) in finite …

The Skolem problem and the related Positivity problem for linear recurrence sequences are
outstanding number-theoretic problems whose decidability has been open for many …

Graph games provide the foundation for modeling and synthesizing reactive processes. In
the synthesis of stochastic reactive processes, the traditional model is perfect-information …

LTL on finite traces (LTLf) is a logic that attracted much attention in recent literature, due to
its ability to formalize the qualitative behavior of dynamical systems in several application …

In this paper we review various automata-theoretic formalisms for expressing quantitative
properties. We start with finite-state Boolean automata that express the traditional regular …

Classical objectives in two-player zero-sum games played on graphs often deal with limit
behaviors of infinite plays: eg, mean-payoff and total-payoff in the quantitative setting, or …

Probabilistic Model Checking Page 1 Probabilistic Model Checking Christel BAIER a,1 a TU
Dresden, Department for Computer Science E-mail: christel.baier@tu-dresden.de Abstract …