We consider the model checking problem for probabilistic pushdown automata (pPDA) and properties expressible in various probabilistic logics. We start with properties that can be formulated as instances of a generalized random walk problem. We prove that both qualitative and quantitative model checking for this class of properties and pPDA is decidable. Then we show that model checking for the qualitative fragment of the logic PCTL and pPDA is also decidable. Moreover, we develop an error-tolerant model checking algorithm for general PCTL and the subclass of stateless pPDA. Finally, we consider the class of properties definable by deterministic B uchi automata, and show that both qualitative and quantitative model checking for pPDA is decidable. 1.

Abstract. We consider qualitative and quantitative model-checking problems for probabilistic pushdown automata (pPDA) and various temporal logics. We prove that the qualitative and quantitative model-checking problem for ω-regular properties and pPDA is in 2-EXPSPACE and 3-EXPTIME, respectively. We also prove that model-checking the qualitative fragment of the logic PECTL ∗ for pPDA is in 2-EXPSPACE, and model-checking the qualitative fragment of PCTL for pPDA is in EXPSPACE. Furthermore, model-checking the qualitative fragment of PCTL is shown to be EXPTIME-hard even for stateless pPDA. Finally, we show that PCTL model-checking is undecidable for pPDA, and PCTL + model-checking is undecidable even for stateless pPDA. 1

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We consider the problem of deciding whether an infinite-state system (expressed as a Markov chain) satisfies a correctness property with probability 1. This problem is, of course, undecidable for general infinite-state systems. We focus our attention on the model of probabilistic lossy channel systems consisting of finite-state processes that communicating over unbounded lossy FIFO channels. Abdulla and Jonsson have shown that safety properties are decidable while progress properties are not for non-probabilistic lossy channel systems. Under assumptions of "sufficiently high" probability of loss, Baier and Engelen have shown how to check whether a property holds of probabilistic lossy channel system with probability 1. In this paper we show that the problem of checking whether a progress property holds with probability 1 is undecidable, if the assumption about "sufficiently high" probability of loss is omitted. More surprisingly, we show that checking whether safety prop...

Abstract. Lossy channel systems (LCS’s) are systems of finite state automata that communicate via unreliable unbounded fifo channels. Several probabilistic versions of these systems have been proposed in recent years, with the two aims of modeling more faithfully the losses of messages, and circumventing undecidabilities by some kind of randomization. We survey these proposals and the verification techniques they support. 1

Abstract. We consider infinite-state discrete Markov chains which are eager: the probability of avoiding a defined set of final states for more thanÒsteps is bounded by some exponentially decreasing function�(Ò). We prove that eager Markov chains include those induced by Probabilistic Lossy Channel Systems, Probabilistic Vector Addition Systems with States, and Noisy Turing Machines, and that the bounding function�(Ò) can be effectively constructed for them. Furthermore, we study the problem of computing the expected reward (or cost) of runs until reaching the final states, where rewards are assigned to individual runs by computable reward functions. For eager Markov chains, an effective path exploration scheme, based on forward reachability analysis, can be used to approximate the expected reward up-to an arbitrarily small error. 1

Abstract. NPLCS’s are a new model for nondeterministic channel systems where unreliable communication is modeled by probabilistic message losses. We show that, for ω-regular linear-time properties and finite-memory schedulers, qualitative model-checking is decidable. The techniques extend smoothly to questions where fairness restrictions are imposed on the schedulers. The symbolic procedure underlying our decidability proofs has been implemented and used to study a simple protocol handling two-way transfers in an unreliable setting. 1

Channel systems [Brand and Zafiropulo 1983] are systems of finite-state components that communicate via asynchronous unbounded fifo channels. See Fig. 1 for an example of a channel systems with two components E1 and E2 that communicate through fifo channels c1 and c2. Lossy channel systems [Finkel 1994; Abdulla and Jonsson 1996b] are a

Constraint automata have been used as an operational model for Reo which o#ers a channel-based framework to compose complex component connectors. In this paper, we introduce a variant of constraint automata with discrete probabilities and nondeterminism, called probabilistic constraint automata. These can serve for compositional reasoning about connector components, modelled by Reo circuits with unreliable channels, e.g., that might loose or corrupt messages, or channels with random output values that, e.g., can be helpful to model randomized coordination principles.

Lossy channel systems (LCS's) are systems of finite state automata that communicate via unreliable unbounded fifo channels. We propose a new probabilistic model for these systems, where losses of messages are seen as faults occurring with some given probability, and where the internal behavior of the system remains nondeterministic, giving rise to a reactive Markov chains semantics. We then investigate the verification of linear-time properties on this new model. Our main result is that it is decidable whether a linear-time property holds almost-surely for all finite-memory scheduling policies.