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This paper presents an algorithm for cost-bounded probabilistic reachability 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)

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)

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)

The idea to use simulations (or refinements) as a composi-tional abstraction device is well-known, both in untimed and timed settings , and has already been studied theoretically and practically in many papers during the last three decades. Nevertheless, existing approaches do not handle two fundamental modeling concepts which, for instance, are frequently… (More)

The model checker Uppaal is used to formally model and analyze parts of Zeroconf, a protocol for dynamic configuration of IPv4 link-local addresses that has been defined in RFC 3927 of the IETF. Our goal has been to construct a model that (a) is easy to understand by engineers, (b) comes as close as possible to the informal text (for each transition in the… (More)

- On Reachability, Priced Probabilistic, Timed Automata, Jasper Berendsen, David N Jansen, Joost-Pieter Katoen

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)

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