Μ-calculus Model Checking Research Articles

Modular Primal-Dual Fixpoint Logic Solving for Temporal Verification

We present a novel approach to deciding the validity of formulas in first-order fixpoint logic with background theories and arbitrarily nested inductive and co-inductive predicates defining least and greatest fixpoints. Our approach is constraint-based, and reduces the validity checking problem of the given first-order-fixpoint logic formula (formally, an instance in a language called µCLP) to a constraint satisfaction problem for a recently introduced predicate constraint language. Coupled with an existing sound-and-relatively-complete solver for the constraint language, this novel reduction alone already gives a sound and relatively complete method for deciding µCLP validity, but we further improve it to a novel modular primal-dual method. The key observations are (1) µCLP is closed under complement such that each (co-)inductive predicate in the original primal instance has a corresponding (co-)inductive predicate representing its complement in the dual instance obtained by taking the standard De Morgan’s dual of the primal instance, and (2) partial solutions for (co-)inductive predicates synthesized during the constraint solving process of the primal side can be used as sound upper-bounds of the corresponding (co-)inductive predicates in the dual side, and vice versa. By solving the primal and dual problems in parallel and exchanging each others’ partial solutions as sound bounds, the two processes mutually reduce each others’ solution spaces, thus enabling rapid convergence. The approach is also modular in that the bounds are synthesized and exchanged at granularity of individual (co-)inductive predicates. We demonstrate the utility of our novel fixpoint logic solving by encoding a wide variety of temporal verification problems in µCLP, including termination/non-termination, LTL, CTL, and even the full modal µ-calculus model checking of infinite state programs. The encodings exploit the modularity in both the program and the property by expressing each loops and (recursive) functions in the program and sub-formulas of the property as individual (possibly nested) (co-)inductive predicates. Together with our novel modular primal-dual µCLP solving, we obtain a novel approach to efficiently solving a wide range of temporal verification problems.

The μ-Calculus Model-Checking Algorithm for Generalized Possibilistic Decision Process

Model checking is a formal automatic verification technology for complex concurrent systems. It is used widely in the verification and analysis of computer software and hardware systems, communication protocols, security protocols, etc. The generalized possibilistic μ-calculus model-checking algorithm for decision processes is studied to solve the formal verification problem of concurrent systems with nondeterministic information and incomplete information on the basis of possibility theory. Firstly, the generalized possibilistic decision process is introduced as the system model. Then, the classical proposition μ-calculus is improved and extended, and the concept of generalized possibilistic μ-calculus (GPoμ) is given to describe the attribute characteristics of nondeterministic systems. Then, the GPoμ model-checking algorithm is proposed, and the model-checking problem is simplified to fuzzy matrix operations. Finally, a specific example and a case study are analyzed and verified. Compared with the classical μ-calculus, the generalized possibilistic μ-calculus has a stronger expressive power and can better characterize the attributes of nondeterministic systems. The model-checking algorithm can give the possibility that the system satisfies the attributes. The research work provides a new idea and method for model checking nondeterministic systems.

Fixpoint games on continuous lattices

Many analysis and verifications tasks, such as static program analyses and model-checking for temporal logics, reduce to the solution of systems of equations over suitable lattices. Inspired by recent work on lattice-theoretic progress measures, we develop a game-theoretical approach to the solution of systems of monotone equations over lattices, where for each single equation either the least or greatest solution is taken. A simple parity game, referred to as fixpoint game, is defined that provides a correct and complete characterisation of the solution of systems of equations over continuous lattices, a quite general class of lattices widely used in semantics. For powerset lattices the fixpoint game is intimately connected with classical parity games for µ-calculus model-checking, whose solution can exploit as a key tool Jurdziński’s small progress measures. We show how the notion of progress measure can be naturally generalised to fixpoint games over continuous lattices and we prove the existence of small progress measures. Our results lead to a constructive formulation of progress measures as (least) fixpoints. We refine this characterisation by introducing the notion of selection that allows one to constrain the plays in the parity game, enabling an effective (and possibly efficient) solution of the game, and thus of the associated verification problem. We also propose a logic for specifying the moves of the existential player that can be used to systematically derive simplified equations for efficiently computing progress measures. We discuss potential applications to the model-checking of latticed µ-calculi.

Distributed Symbolic Model Checking for μ-Calculus

In this paper we propose a distributed symbolic algorithm for model checking of propositional ?-calculus formulas. ?-calculus is a powerful formalism and ?-calculus model checking can solve many problems, including, for example, verification of (fair) CTL and LTL properties. Previous works on distributed symbolic model checking were restricted to reachability analysis and safety properties. This work thus significantly extends the scope of properties that can be verified distributively, enabling us to use them for very large designs. The algorithm distributively evaluates subformulas. It results in sets of states which are evenly distributed among the processes. We show that this algorithm is scalable and therefore can be implemented on huge distributed clusters of computing nodes. The memory modules of the computing nodes collaborate to create a very large memory space, thus enabling the checking of much larger designs. We formally prove the correctness of the parallel algorithm. We complement the distribution of the state sets by showing how to distribute the transition relation.

Predicate Abstraction for Dense Real-Time Systems

We propose predicate abstraction as a means for verifying a rich class of safety and liveness properties for dense real-time systems. First, we define a restricted semantics of timed systems which is observationally equivalent to the standard semantics in that it validates the same set of μ-calculus formulas without a next-step operator. Then, we recast the model checking problem S ⊨ ϕ for a timed automaton S and a μ-calculus formula ϕ in terms of predicate abstraction. Whenever a set of abstraction predicates forms a so-called basis, the resulting abstraction is strongly preserving in the sense that S validates ϕ iff the corresponding finite abstraction validates this formula ϕ. Now, the abstracted system can be checked using familiar μ-calculus model checking. Like the region graph construction for timed automata, the predicate abstraction algorithm for timed automata usually is prohibitively expensive. In many cases it suffices to compute an approximation of a finite bisimulation by using only a subset of the basis of abstraction predicates. Starting with some coarse abstraction, we define a finite sequence of refined abstractions that converges to a strongly preserving abstraction. In each step, new abstraction predicates are selected nondeterministically from a finite basis. Counterexamples from failed μ-calculus model checking attempts can be used to heuristically choose a small set of new abstraction predicates for refining the abstraction.

A symbolic semantics for abstract model checking

In this paper we present a symbolic semantics of value-passing concurrent processes where classical branching is replaced by separate relations of non-deterministic branch and alternative choice. The obtained symbolic graph is finite for regular processes and can suitably be interpreted over abstract values to effectively compute a safe abstract model for full μ-calculus model checking. The representation of non-determinism and alternative choice in symbolic transitions allows to achieve more precise approximations of the two dual next modalities.

Deciding the winner in parity games is in UP ∩ co-UP

We observe that the problem of deciding the winner in mean payoff games is in the complexity class UP ∩ co-UP. We also show a simple reduction from parify games to mean payoff games. From this it follows that deciding the winner in parity games and the modal μ-calculus model checking are in UP ∩ co-UP.