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

Parker

2009

Self Cite

Abstract. Probabilistic timed automata (PTAs) are used for formal modelling and verification of systems with probabilistic, nondeterministic and real-time behaviour. For non-probabilistic timed automata, forwards reachability is the analysis method of choice, since it can be implemented extremely efficiently. However, for PTAs, such techniques are only able to compute upper bounds on maximum reachability probabilities. In this paper, we propose a new approach to the analysis of PTAs using abstraction and stochastic games. We show how efficient forwards reachability techniques can be extended to yield both lower and upper bounds on maximum (and minimum) reachability probabilities. We also present abstraction-refinement techniques that are guaranteed to improve the precision of these probability bounds, providing a fully automatic method for computing the exact values. We have implemented these techniques and applied them to a set of large case studies. We show that, in comparison to alternative approaches to verifying PTAs, such as backwards reachability and digital clocks, our techniques exhibit superior performance and scalability.

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stochastic Games for Verification of Probabilistic Timed Automata

Kwiatkowska

Parker

2009

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“…Properties are specified using PCTL for DTMCs and MDPs, and CSL for CTMCs. Probabilistic timed automata have a logic PTCTL, an extension of TCTL, a subset of which is supported via a connection to the timed automata model checking tool Kronos [24].…”

Section: The Probabilistic Model Checker Prismmentioning

confidence: 99%

Stochastic Model Checking

Kwiatkowska

Parker

Self Cite

460

353

Abstract. This tutorial presents an overview of model checking for both discrete and continuous-time Markov chains (DTMCs and CTMCs). Model checking algorithms are given for verifying DTMCs and CTMCs against specifications written in probabilistic extensions of temporal logic, including quantitative properties with rewards. Example properties include the probability that a fault occurs and the expected number of faults in a given time period. We also describe the practical application of stochastic model checking with the probabilistic model checker PRISM by outlining the main features supported by PRISM and three real-world case studies: a probabilistic security protocol, dynamic power management and a biological pathway.

“…The efficient algorithm for calculating bounds on the maximal reachability probability of probabilistic real-time automata presented in [56] has subsequently been implemented in [19]. For case studies concerning the qualitative verification of real-time randomized distributed algorithms protocols see [19,59,58].…”

Section: Verifying Complex Parameterized and Infinite-state Protocolsmentioning

confidence: 99%

Analysing Randomized Distributed Algorithms

2004

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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.