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25
Probabilistic Verification of Discrete Event Systems using Acceptance Sampling
 In Proc. 14th International Conference on Computer Aided Verification, volume 2404 of LNCS
, 2002
"... We propose a model independent procedure for verifying properties of discrete event systems. The dynamics of such systems can be very complex, making them hard to analyze, so we resort to methods based on Monte Carlo simulation and statistical hypothesis testing. The verification is probabilistic in ..."
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Cited by 86 (10 self)
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We propose a model independent procedure for verifying properties of discrete event systems. The dynamics of such systems can be very complex, making them hard to analyze, so we resort to methods based on Monte Carlo simulation and statistical hypothesis testing. The verification is probabilistic in two senses. First, the properties, expressed as CSL formulas, can be probabilistic. Second, the result of the verification is probabilistic, and the probability of error is bounded by two parameters passed to the verification procedure. The verification of properties can be carried out in an anytime manner by starting off with loose error bounds, and gradually tightening these bounds.
Numerical vs. statistical probabilistic model checking: An empirical study
 IN 10TH INTERNATIONAL CONFERENCE ON TOOLS AND ALGORITHMS FOR THE CONSTRUCTION AND ANALYSIS OF SYSTEMS (TACAS’04
, 2004
"... Numerical analysis based on uniformisation and statistical techniques based on sampling and simulation are two distinct approaches for transient analysis of stochastic systems. We compare the two solution techniques when applied to the verification of timebounded until formulae in the temporal st ..."
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Cited by 59 (10 self)
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Numerical analysis based on uniformisation and statistical techniques based on sampling and simulation are two distinct approaches for transient analysis of stochastic systems. We compare the two solution techniques when applied to the verification of timebounded until formulae in the temporal stochastic logic CSL. This study differs from most previous comparisons of numerical and statistical approaches in that CSL model checking is a hypothesis testing problem rather than a parameter estimation problem. We can therefore rely on highly efficient sequential acceptance sampling tests, which enables statistical solution techniques to quickly return a result with some uncertainty. This suggests that statistical techniques can be useful as a first resort during system prototyping, rather than as a last resort as often suggested. We also propose a novel combination of the two solution techniques for verifying CSL queries with nested probabilistic operators.
On statistical model checking of stochastic systems
 In Etessami, K., Rajamani, S.K., eds.: CAV. Volume 3576 of Lecture Notes in Computer Science
, 2005
"... Abstract. Statistical methods to model check stochastic systems have been, thus far, developed only for a sublogic of continuous stochastic logic (CSL) that does not have steady state operator and unbounded until formulas. In this paper, we present a statistical model checking algorithm that also ve ..."
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Cited by 35 (2 self)
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Abstract. Statistical methods to model check stochastic systems have been, thus far, developed only for a sublogic of continuous stochastic logic (CSL) that does not have steady state operator and unbounded until formulas. In this paper, we present a statistical model checking algorithm that also verifies CSL formulas with unbounded untils. The algorithm is based on Monte Carlo simulation of the model and hypothesis testing of the samples, as opposed to sequential hypothesis testing. We have implemented the algorithm in a tool called VESTA, and found it to be effective in verifying several examples. 1
Hypergraphbased Parallel Computation of Passage Time Densities in Large SemiMarkov Models
 NUMERICAL SOLUTION OF MARKOV CHAINS, P. 99–120
"... Passage time densities and quantiles are important performance and quality of service metrics, but their numerical derivation is, in general, computationally expensive. We present an iterative algorithm for the calculation of passage time densities in semiMarkov models, along with a theoretical an ..."
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Cited by 27 (16 self)
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Passage time densities and quantiles are important performance and quality of service metrics, but their numerical derivation is, in general, computationally expensive. We present an iterative algorithm for the calculation of passage time densities in semiMarkov models, along with a theoretical analysis and empirical measurement of its convergence behaviour. In order to implement the algorithm efficiently in parallel, we use hypergraph partitioning to minimise communication between processors and to balance workloads. This enables the analysis of models with very large state spaces which could not be held within the memory of a single machine. We produce passage time densities and quantiles for very large semiMarkov models with over 15 million states and validate the results against simulation.
Verification and Planning for Stochastic Processes with Asynchronous Events
, 2005
"... � Asynchronous processes are abundant in the real world � Telephone system, computer network, etc. ..."
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Cited by 20 (3 self)
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� Asynchronous processes are abundant in the real world � Telephone system, computer network, etc.
Automated performance and dependability evaluation using model checking
 In Performance Evaluation of Complex Systems: Techniques and Tools, Performance 2002, Tutorial Lectures
, 2002
"... Abstract. Markov chains (and their extensions with rewards) have been widely used to determine performance, dependability and performability characteristics of computer communication systems, such as throughput, delay, mean time to failure, or the probability to accumulate at least a certain amount ..."
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Cited by 20 (2 self)
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Abstract. Markov chains (and their extensions with rewards) have been widely used to determine performance, dependability and performability characteristics of computer communication systems, such as throughput, delay, mean time to failure, or the probability to accumulate at least a certain amount of reward in a given time. Due to the rapidly increasing size and complexity of systems, Markov chains and Markov reward models are difficult and cumbersome to specify by hand at the statespace level. Therefore, various specification formalisms, such as stochastic Petri nets and stochastic process algebras, have been developed to facilitate the specification of these models at a higher level of abstraction. Uptill now, however, the specification of the measureofinterest is often done in an informal and relatively unstructured way. Furthermore, some measuresofinterest can not be expressed conveniently at all. In this tutorial paper, we present a logicbased specification technique to specify performance, dependability and performability measuresofinterest and show how for a given finite Markov chain (or Markov reward model) such measures can be evaluated in a fully automated way. Particular emphasis will be given to socalled pathbased measures and hierarchicallyspecified measures. For this purpose, we extend socalled model checking techniques to reason about discrete and continuoustime Markov chains and their rewards. We also report on the use of techniques such as (compositional) model reduction and measuredriven statespace generation to combat the infamous state space explosion problem. 1
Performance Trees: Expressiveness and Quantitative Semantics
"... Performance Trees are a recentlyproposed mechanism for the specification of performance properties and measures. They represent an attractive alternative to stochastic logics, since they support traditional stochastic model checking queries, while also allowing for the direct extraction of a wide ..."
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Cited by 11 (8 self)
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Performance Trees are a recentlyproposed mechanism for the specification of performance properties and measures. They represent an attractive alternative to stochastic logics, since they support traditional stochastic model checking queries, while also allowing for the direct extraction of a wide range of quantitative measures. In this paper we illustrate differences in expressiveness between Performance Trees and Continuous Stochastic Logic (CSL), and present quantitative semantics showing the mathematical basis underlying Performance Tree operators. As a running example, we demonstrate performance query specification with Performance Trees on a stochastic Petri net model of a healthcare system.
Model Checking Meets Performance Evaluation
"... Markov chains are one of the most popular models for the evaluation of performance and dependability of information processing systems. To obtain performance measures, typically longrun or transient state probabilities of Markov chains are determined. Sometimes the Markov chain at hand is equipped ..."
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Cited by 5 (1 self)
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Markov chains are one of the most popular models for the evaluation of performance and dependability of information processing systems. To obtain performance measures, typically longrun or transient state probabilities of Markov chains are determined. Sometimes the Markov chain at hand is equipped with rewards and computations involve determining longrun or instantaneous reward probabilities.
Blackbox probabilistic verification
, 2004
"... This report is based upon work supported by DARPA and ARO under contract no. DAAD19–01–1–0485, and a grant from the ..."
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Cited by 4 (1 self)
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This report is based upon work supported by DARPA and ARO under contract no. DAAD19–01–1–0485, and a grant from the
Symbolic Analysis for GSMP Models with One Stateful Clock ⋆
"... Abstract. We consider the problem of verifying reachability properties of stochastic realtime systems modeled as generalized semiMarkov processes (GSMPs). The standard simulationbased techniques for GSMPs are not adequate for solving verification problems, and existing symbolic techniques either ..."
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Cited by 3 (0 self)
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Abstract. We consider the problem of verifying reachability properties of stochastic realtime systems modeled as generalized semiMarkov processes (GSMPs). The standard simulationbased techniques for GSMPs are not adequate for solving verification problems, and existing symbolic techniques either require memoryless distributions for firing times, or approximate the problem using discrete time or bounded horizon. In this paper, we present a symbolic solution for the case where firing times are random variables over a rich class of distributions, but only one event is allowed to retain its firing time when a discrete change occurs. The solution allows us to compute the probability that such a GSMP satisfies a property of the form “can the system reach a target, while staying within a set of safe states”. We report on illustrative examples and their analysis using our procedure. 1