David N. Jansen

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The Markov Reward Model Checker (MRMC) is a software tool for verifying properties over probabilistic models. It supports PCTL and CSL model checking, and their reward extensions. Distinguishing features of MRMC are its support for computing timeand reward-bounded reachability probabilities, (property-driven) bisimulation minimization, and precise(More)
Abstraction techniques based on simulation relations have become an important and effective proof technique to avoid the infamous state space explosion problem. In the context of Markov chains, strong and weak simulation relations have been proposed [17, 6], together with corresponding decision algorithms [3, 5], but it is as yet unclear whether they can be(More)
This paper studies the efficiency of several probabilistic model checkers by comparing verification times and peak memory usage for a set of standard case studies. The study considers the model checkers ETMCC, MRMC, PRISM (sparse and hybrid mode), YMER and VESTA, and focuses on fully probabilistic systems. Several of our experiments show significantly(More)
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. Our results show that—as for traditional model checking—enormous state space reductions (up to logarithmic savings) may be obtained. In contrast to traditional model checking, in(More)
Priced Probabilistic Timed Automata (PPTA) extend timed automata with cost-rates in locations and discrete probabilistic branching. The model is a natural combination of Priced Timed Automata and Probabilistic Timed Automata. In this paper we focus on cost-bounded probabilistic reachability for PPTA, which determines if the maximal probability to reach a(More)
We introduce Fortuna, the first tool for model checking priced probabilistic timed automata (PPTAs). Fortuna can handle the combination of real-time, probabilistic and cost features, which is required for addressing key design trade-offs that arise in many practical applications. For example the Zeroconf, Bluetooth, IEEE802.11 and Firewire protocols,(More)
We explore whether LearnLib, a state-of-the-art automata learning tool, is able to learn a model of the Engine Status Manager (ESM), a piece of control software that is used in many printers and copiers of Océ. Finding counterexamples for incorrect hypotheses for the ESM turns out to be challenging due to the large number of inputs. A first contribution of(More)
For continuous-time Markov chains, the model-checking problem with respect to continuous-time stochastic logic (CSL) has been introduced and shown to be decidable by Aziz, Sanwal, Singhal and Brayton in 1996. The presented decision procedure, however, has exponential complexity. In this paper, we propose an effective approximation algorithm for full CSL.(More)
OBJECTIVES The objectives of this study were to describe changes in glyburide prescribing in cohorts that were and were not targeted by a risk reduction project, assess factors associated with glyburide discontinuation, and evaluate changes in glycated hemoglobin (ie, HbA(1c)) levels and rates of serious hypoglycemia. METHODS This historical cohort study(More)