Andrea Turrini

iscasMc: A Web-Based Probabilistic Model Checker

We introduce the web-based model checker iscasMc for probabilistic systems see http://iscasmc.ios.ac.cn/IscasMC . This Java application offers an easy-to-use web interface for the evaluation of Markov chains and decision processes against PCTL and PCTL* specifications. Compared to PRISM or MRMC, iscasMc is particularly efficient in evaluating the probabilities of LTL properties.

Comparative analysis of bisimulation relations on alternating and non-alternating probabilistic models

We consider bisimulation and weak bisimulation relations in the context of the labeled Markov chains of Hansson and Jonsson, the concurrent labeled Markov chains of Philippou, Lee, and Sokolsky, and the probabilistic automata of Segala. We identify a taxonomy of bisimulation relations that captures the existing definitions for each one of the three models, and we compare the relations within each model and across models. The comparison across models is given according to a notion of embedding, where we order the three models by generality and we view objects in less general models as objects of more general models.

Approximated Computationally Bounded Simulation Relations for Probabilistic Automata

We study simulation relations for probabilistic automata that require transitions to be matched up to negligible sets provided that computation lengths are polynomially bounded. These relations are meant to provide rigorous grounds to parts of correctness proofs for cryptographic protocols that are usually carried out by semi-formal arguments. We illustrate our ideas by recasting a correctness proof of Bellare and Rogaway based on the notion of matching conversation.

Deciding Probabilistic Automata Weak Bisimulation in Polynomial Time

Deciding in an efficient way weak probabilistic bisimulation in the context of Probabilistic Automata is an open problem for about a decade. In this work we close this problem by proposing a procedure that checks in polynomial time the existence of a weak combined transition satisfying the step condition of the bisimulation. We also present several extensions of weak combined transitions, such as hyper-transitions and the new concepts of allowed weak combined and hyper-transitions and of equivalence matching, that turn out to be verifiable in polynomial time as well. These results set the ground for the development of more effective compositional analysis algorithms for probabilistic systems.

The quest for minimal quotients for probabilistic automata

One of the prevailing ideas in applied concurrency theory and verification is the concept of automata minimization with respect to strong or weak bisimilarity. The minimal automata can be seen as canonical representations of the behaviour modulo the bisimilarity considered. Together with congruence results wrt. process algebraic operators, this can be exploited to alleviate the notorious state space explosion problem. In this paper, we aim at identifying minimal automata and canonical representations for concurrent probabilistic models. We present minimality and canonicity results for probabilistic automata wrt. strong and weak bisimilarity, together with polynomial time minimization algorithms.

Deciding bisimilarities on distributions

Probabilistic automata (PA) are a prominent compositional concurrency model. As a way to justify property-preserving abstractions, in the last years, bisimulation relations over probability distributions have been proposed both in the strong and the weak setting. Different to the usual bisimulation relations, which are defined over states, an algorithmic treatment of these relations is inherently hard, as their carrier set is uncountable, even for finite PAs. The coarsest of these relation, weak distribution bisimulation, stands out from the others in that no equivalent state-based characterisation is known so far. This paper presents an equivalent state-based reformulation for weak distribution bisimulation, rendering it amenable for algorithmic treatment. Then, decision procedures for the probability distribution-based bisimulation relations are presented.

QPMC: A Model Checker for Quantum Programs and Protocols

We present QPMC (Quantum Program/Protocol Model Checker), an extension of the probabilistic model checker IscasMC to automatically verify quantum programs and quantum protocols. QPMC distinguishes itself from the previous quantum model checkers proposed in the literature in that it works for general quantum programs and protocols, not only those using Clifford operations. A command-line version of QPMC is available at http://iscasmc.ios.ac.cn/tool/qmc/ .

A Quantitative Doxastic Logic for Probabilistic Processes and Applications to Information-Hiding

We introduce a novel modal logic, namely the doxastic μ-calculus with error control (DμCEC), and propose a formalization of probabilistic anonymity and oblivious transfer in the logic, and the validation of these formalizations on implementations formalized in probabilistic CCS. The distinguishing feature of our logic is to provide a combination of dynamic operators for belief (whence the attribute “doxastic”) with a control on the possible error of apprehension of the perceived reality, and for internalized probability. Both operators are dynamic (non-monotonic) thanks to the possibility of combining them with temporal operators, and are parameterized with a lower and upper probability bound (the error control).

Polynomial time decision algorithms for probabilistic automata

Deciding in an efficient way weak probabilistic bisimulation in the context of probabilistic automata is an open problem for about a decade. In this work we close this problem by proposing a procedure that checks in polynomial time the existence of a weak combined transition satisfying the step condition of the bisimulation. This enables us to arrive at a polynomial time algorithm for deciding weak probabilistic bisimulation, and also branching probabilistic bisimulation. We furthermore present several extensions to interesting related problems, in particular weak and branching probabilistic simulation, setting the ground for the development of more effective and compositional analysis algorithms for probabilistic systems.

Computing Behavioral Relations for Probabilistic Concurrent Systems

Behavioral equivalences and preorders are fundamental notions to formalize indistinguishability of transition systems and provide means to abstraction and refinement. We survey a collection of models used to represent concurrent probabilistic real systems, the behavioral equivalences and preorders they are equipped with and the corresponding decision algorithms. These algorithms follow the standard refinement approach and they improve their complexity by taking advantage of the efficient algorithms developed in the optimization community to solve optimization and flow problems.