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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 time-and reward-bounded reachability probabilities, (property-driven) bisimulation minimization, and precise(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)
ion 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 used as(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)
The UML is an influential and widespread notation for high-level modelling of information processing systems. UML statechart diagrams are a graphical language to describe system behaviour. They consitute one of the most intensively-used formalisms comprised by the UML. However, statechart diagrams are lacking concepts for describing real-time, performance,(More)
The following full text is a preprint version which may differ from the publisher's version. Abstract There are only very few natural ways in which arbitrary functions can be combined. One composition operator is override: for arbitrary functions f and g, f > g is the function with domain dom(f) U dom(g) that behaves like f on dom(f) and like g on dom(g) \(More)
Bisimulation minimisation mostly speeds up probabilistic model checking Outline Probabilistic model checking 1 Enjoys a rapid increase of interest 2 Case studies: Biological process modeling Communication protocols Randomised algorithms Quantum computing Planning and AI Security 3 Formalisms that use probabilistic model checking: Bisimulation minimisation(More)
In this paper we define a requirements-level execution semantics for object-oriented statecharts and show how properties of a system specified by these statecharts can be model checked using tool support for model checkers. Our execution semantics is requirements-level because it uses the perfect technology assumption, which abstracts from limitations(More)
Performance, dependability and quality of service (QoS) are prime aspects of the UML modeling domain. To capture these aspects effectively in a modeling language requires easy-to-use support for the specification and analysis of randomly varying behaviors. This paper introduces an extension of UML statecharts with randomly varying durations , by enriching a(More)
This paper presents an algorithm for cost-bounded probabilistic reach-ability in timed automata extended with prices (on edges and locations) and discrete probabilistic branching. The algorithm determines whether the probability to reach a (set of) goal location(s) within a given price bound (and time bound) can exceed a threshold p ∈ [0, 1]. We prove that(More)