Results 1  10
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33
Algorithmic verification of recursive probabilistic state machines
 In Proc. 11th TACAS
, 2005
"... Abstract. Recursive Markov Chains (RMCs) ([EY04]) are a natural abstract model of procedural probabilistic programs and related systems involving recursion and probability. They succinctly define a class of denumerable Markov chains that generalize multitype branching (stochastic) processes. In thi ..."
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Cited by 37 (7 self)
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Abstract. Recursive Markov Chains (RMCs) ([EY04]) are a natural abstract model of procedural probabilistic programs and related systems involving recursion and probability. They succinctly define a class of denumerable Markov chains that generalize multitype branching (stochastic) processes. In this paper, we study the problem of model checking an RMC against a given ωregular specification. Namely, given an RMC A and a Büchi automaton B, we wish to know the probability that an execution of A is accepted by B. We establish a number of strong upper bounds, as well as lower bounds, both for qualitative problems (is the probability = 1, or = 0?), and for quantitative problems (is the probability ≥ p?, or, approximate the probability to within a desired precision). Among these, we show that qualitative model checking for general RMCs can be decided in PSPACE in A  and EXPTIME in B, and when A is either a singleexit RMC or when the total number of entries and exits in A is bounded, it can be decided in polynomial time in A. We then show that quantitative model checking can also be done in PSPACE in A, and in EXPSPACE in B. When B is deterministic, all our complexities in B  come down by one exponential. For lower bounds, we show that the qualitative model checking problem, even for a fixed RMC, is already EXPTIMEcomplete. On the other hand, even for simple reachability analysis, we showed in [EY04] that our PSPACE upper bounds in A can not be improved upon without a breakthrough on a wellknown open problem in the complexity of numerical computation. 1
Recursive Markov decision processes and recursive stochastic games
 In Proc. of 32nd Int. Coll. on Automata, Languages, and Programming (ICALP’05
, 2005
"... Abstract. We introduce Recursive Markov Decision Processes (RMDPs) and Recursive Simple Stochastic Games (RSSGs), and study the decidability and complexity of algorithms for their analysis and verification. These models extend Recursive Markov Chains (RMCs), introduced in [EY05a,EY05b] as a natural ..."
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Cited by 35 (9 self)
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Abstract. We introduce Recursive Markov Decision Processes (RMDPs) and Recursive Simple Stochastic Games (RSSGs), and study the decidability and complexity of algorithms for their analysis and verification. These models extend Recursive Markov Chains (RMCs), introduced in [EY05a,EY05b] as a natural model for verification of probabilistic procedural programs and related systems involving both recursion and probabilistic behavior. RMCs define a class of denumerable Markov chains with a rich theory generalizing that of stochastic contextfree grammars and multitype branching processes, and they are also intimately related to probabilistic pushdown systems. RMDPs & RSSGs extend RMCs with one controller or two adversarial players, respectively. Such extensions are useful for modeling nondeterministic and concurrent behavior, as well as modeling a system’s interactions with an environment. We provide a number of upper and lower bounds for deciding, given an RMDP (or RSSG) A and probability p, whether player 1 has a strategy to force termination at a desired exit with probability at least p. We also address “qualitative ” termination questions, where p = 1, and model checking questions. 1
On the decidability of temporal properties of probabilistic pushdown automata
 In Proc. of STACS’05
, 2005
"... Abstract. We consider qualitative and quantitative modelchecking problems for probabilistic pushdown automata (pPDA) and various temporal logics. We prove that the qualitative and quantitative modelchecking problem for ωregular properties and pPDA is in 2EXPSPACE and 3EXPTIME, respectively. We ..."
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Cited by 30 (9 self)
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Abstract. We consider qualitative and quantitative modelchecking problems for probabilistic pushdown automata (pPDA) and various temporal logics. We prove that the qualitative and quantitative modelchecking problem for ωregular properties and pPDA is in 2EXPSPACE and 3EXPTIME, respectively. We also prove that modelchecking the qualitative fragment of the logic PECTL ∗ for pPDA is in 2EXPSPACE, and modelchecking the qualitative fragment of PCTL for pPDA is in EXPSPACE. Furthermore, modelchecking the qualitative fragment of PCTL is shown to be EXPTIMEhard even for stateless pPDA. Finally, we show that PCTL modelchecking is undecidable for pPDA, and PCTL + modelchecking is undecidable even for stateless pPDA. 1
Quantitative Verification: Models, Techniques and Tools
, 2007
"... Automated verification is a technique for establishing if certain properties, usually expressed in temporal logic, hold for a system model. The model can be defined using a highlevel formalism or extracted directly from software using methods such as abstract interpretation. The verification procee ..."
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Cited by 19 (9 self)
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Automated verification is a technique for establishing if certain properties, usually expressed in temporal logic, hold for a system model. The model can be defined using a highlevel formalism or extracted directly from software using methods such as abstract interpretation. The verification proceeds through exhaustive exploration of the statetransition graph of the model and is therefore more powerful than testing. Quantitative verification is an analogous technique for establishing quantitative properties of a system model, such as the probability of battery power dropping below minimum, the expected time for message delivery and the expected number of messages lost before protocol termination. Models analysed through this method are typically variants of Markov chains, annotated with costs and rewards that describe resources and their usage during execution. Properties are expressed in temporal logic extended with probabilistic and reward operators. Quantitative verification involves a combination of a traversal of the statetransition graph of the model and numerical computation. This paper gives a brief overview of current research in quantitative verification, concentrating on the potential of the method and outlining future challenges. The modelling approach is described and the usefulness of the methodology illustrated with an example of a realworld protocol standard – Bluetooth device discovery – that has been analysed using the PRISM model checker (www.prismmodelchecker.org).
Verifying Probabilistic Procedural Programs
, 2004
"... Monolithic nitestate probabilistic programs have been abstractly modeled by nite Markov chains, and the algorithmic veri  cation problems for them have been investigated very extensively. In this paper we survey recent work conducted by the authors together with colleagues on the algorithmi ..."
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Cited by 12 (3 self)
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Monolithic nitestate probabilistic programs have been abstractly modeled by nite Markov chains, and the algorithmic veri  cation problems for them have been investigated very extensively. In this paper we survey recent work conducted by the authors together with colleagues on the algorithmic veri cation of probabilistic procedural programs ([BKS,EKM04,EY04]). Probabilistic procedural programs can more naturally be modeled by recursive Markov chains ([EY04]), or equivalently, probabilistic pushdown automata ([EKM04]). A very rich theory emerges for these models. While our recent work solves a number of veri cation problems for these models, many intriguing questions remain open.
A Probabilistic Model for Molecular Systems
, 2005
"... We introduce a model for molecular reactions based on probabilistic rewriting rules. We give a probabilistic algorithm for rule applications as a semantics for the model, and we show how a probabilistic transition system can be derived from it. We use the algorithm in the development of an interpret ..."
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Cited by 8 (7 self)
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We introduce a model for molecular reactions based on probabilistic rewriting rules. We give a probabilistic algorithm for rule applications as a semantics for the model, and we show how a probabilistic transition system can be derived from it. We use the algorithm in the development of an interpreter for the model, which we use to simulate the evolution of molecular systems. In particular, we show the results of the simulation of a real example of enzymatic activity. Moreover, we apply the probabilistic model checker PRISM to the transition system derived by the model of this example, and we show the results of model checking of some illustrative properties.
State explosion in almostsure probabilistic reachability
, 2007
"... We show that the problem of reaching a state set with probability 1 in probabilisticnondeterministic systems operating in parallel is EXPTIMEcomplete. We then show that this probabilistic reachability problem is EXPTIMEcomplete also for probabilistic timed automata. Key words: probabilistic system ..."
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Cited by 8 (4 self)
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We show that the problem of reaching a state set with probability 1 in probabilisticnondeterministic systems operating in parallel is EXPTIMEcomplete. We then show that this probabilistic reachability problem is EXPTIMEcomplete also for probabilistic timed automata. Key words: probabilistic systems, model checking, computational complexity, formal methods, timed automata 1
Bounded Model Checking for GSMP Models of Stochastic Realtime Systems
 In Proc. of HSCC’06, LNCS 3927
, 2006
"... Model checking is a popular algorithmic verification technique for checking temporal requirements of mathematical models of systems. In this paper, we consider the problem of verifying bounded reachability properties of stochastic realtime systems modeled as generalized semiMarkov processes (GS ..."
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Cited by 7 (1 self)
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Model checking is a popular algorithmic verification technique for checking temporal requirements of mathematical models of systems. In this paper, we consider the problem of verifying bounded reachability properties of stochastic realtime systems modeled as generalized semiMarkov processes (GSMP).
Automatic Analysis of a NonRepudiation Protocol
 In Proc. of QAPL’03, Elsevier ENTCS
, 2004
"... We define a probabilistic model for the analysis of a NonRepudiation protocol that guarantees fairness, without resorting to a trusted third party, by means of a probabilistic algorithm. By using the PRISM model checker, we estimate the probability for a malicious user to break the nonrepudiation ..."
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Cited by 6 (2 self)
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We define a probabilistic model for the analysis of a NonRepudiation protocol that guarantees fairness, without resorting to a trusted third party, by means of a probabilistic algorithm. By using the PRISM model checker, we estimate the probability for a malicious user to break the nonrepudiation property, depending on various parameters of the protocol.