Model-checking for probabilistic real-time systems

Alur, Rajeev; Courcoubetis, Costas; Dill, David L.

doi:10.1007/3-540-54233-7_128

Cited by 123 publications

(106 citation statements)

References 13 publications

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“…Inspired by the success of real-time modelcheckers such as Kronos [14] and Uppaal [30], the direction taken is that of automatic verification through model checking, adapting the formalisms and algorithms for model-checking of classical (non-probabilistic) timed systems [2] to the case of timed probabilistic systems. Within this approach 1 , timed probabilistic systems are modelled as probabilistic timed automata [1,28], i.e. timed automata with discrete probability distributions associated with the edges, and properties are specified in the logic PTCTL, which extends the quantitative branching temporal logic TCTL with a probabilistic operator.…”

Section: Introductionmentioning

confidence: 99%

Automatic verification of the IEEE 1394 root contention protocol with KRONOS and PRISM

Daws

Kwiatkowska

Norman

2004

STTT

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Abstract. We report on the automatic verification of timed probabilistic properties of the IEEE 1394 root contention protocol combining two existing tools: the real-time model-checker Kronos and the probabilistic model-checker Prism. The system is modelled as a probabilistic timed automaton. We first use Kronos to perform a symbolic forward reachability analysis to generate the set of states that are reachable with non-zero probability from the initial state, and before the deadline expires. We then encode this information as a Markov decision process to be analyzed with Prism. We apply this technique to compute the minimal probability of a leader being elected before a deadline, for different deadlines, and study how this minimal probability is influenced by using a biased coin and considering different wire lengths.

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Section: Introductionmentioning

confidence: 99%

Automatic verification of the IEEE 1394 root contention protocol with KRONOS and PRISM

Daws

Kwiatkowska

Norman

2004

STTT

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“…We need to sum up over all t's in I(s, e 1 ) the probability of runs starting by such a move. Normalisation factor 1 2 ensures that the probability of all finite runs be one. 7 Let us illustrate the previous definition on an example.…”

Section: Definition Of a Probability Measure Over Finite Pathsmentioning

confidence: 99%

“…The model of real-time probabilistic processes introduced in [1,2] seems similar to timed automata interpreted with our probabilistic semantics, but it is indeed not the case. First, such a system is composed of a number of independent processes with a single clock, which implies in particular that clocks are completely independent.…”

Section: Related Workmentioning

confidence: 99%

Probabilistic and Topological Semantics for Timed Automata

Baier

Bertrand

Bouyer

et al. 2007

FSTTCS 2007: Foundations of Software Technology and Theoretical Computer Science

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Abstract. Like most models used in model-checking, timed automata are an idealized mathematical model used for representing systems with strong timing requirements. In such mathematical models, properties can be violated, due to unlikely (sequences of) events. We propose two new semantics for the satisfaction of LTL formulas, one based on probabilities, and the other one based on topology, to rule out these sequences. We prove that the two semantics are equivalent and lead to a PSPACEComplete model-checking problem for LTL over finite executions.

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“…In certain cases, for example when considering real-time randomized protocols, although the protocol has an infinite state space one can reduce the verification problem to checking a finite-state quotient of the system, for example [2] present a method for probabilistic real-time systems, using the region graph approach [3]. In this work it is demonstrated that, verifying whether (infinite state) probabilistic real time systems satisfy branching time temporal properties with probability 1, reduces to analyzing a finite-state nondeterministic system.…”

Section: 2mentioning

confidence: 99%

Analysing Randomized Distributed Algorithms

Norman

2004

Lecture Notes in Computer Science

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Abstract. Randomization is of paramount importance in practical applications and randomized algorithms are used widely, for example in co-ordinating distributed computer networks, message routing and cache management. The appeal of randomized algorithms is their simplicity and elegance. However, this comes at a cost: the analysis of such systems become very complex, particularly in the context of distributed computation. This arises through the interplay between probability and nondeterminism. To prove a randomized distributed algorithm correct one usually involves two levels: classical, assertion-based reasoning, and a probabilistic analysis based on a suitable probability space on computations. In this paper we describe a number of approaches which allows us to verify the correctness of randomized distributed algorithms.

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Model-checking for probabilistic real-time systems

Cited by 123 publications

References 13 publications

Automatic verification of the IEEE 1394 root contention protocol with KRONOS and PRISM

Automatic verification of the IEEE 1394 root contention protocol with KRONOS and PRISM

Probabilistic and Topological Semantics for Timed Automata

Analysing Randomized Distributed Algorithms

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