Automata-Based CSL Model Checking

Model Checking Timed and Stochastic Properties with CSL

Markov chains are a well-known stochastic process that provide a balance between being able to adequately model the system’s behavior and being able to afford the cost of the model solution. Systems can be modeled directly as Markov chains, or with a higher-level formalism for which Markov chains represent the underlying semantics. Markov chains are widely used to study the performance of compu...

Model-Checking First-Order Logic: Automata and Locality

A Finite Semantics of Simply-Typed Lambda Terms for Infinite Runs of Automata

Model checking properties are often described by means of finite automata. Any particular such automaton divides the set of infinite trees into finitely many classes, according to which state has an infinite run. Building the full type hierarchy upon this interpretation of the base type gives a finite semantics for simply-typed lambda-trees. A calculus based on this semantics is proven sound an...

Upper Bounds on the Automata Size for Integer and Mixed Real and Integer Linear Arithmetic (Extended Abstract)

Automata-based decision procedures have proved to be a particularly useful tool for infinite-state model checking, where automata are used to represent sets of real and integer values. However, not all theoretical aspects of these decision procedures are completely understood. We establish triple exponential upper bounds on the automata size for FO(Z,+, <) and FO(R, Z,+, <). While a similar bou...

Model Checking Algorithms for CTMDPs

Continuous Stochastic Logic (CSL) can be interpreted over continuoustime Markov decision processes (CTMDPs) to specify quantitative properties of stochastic systems that allow some external control. Model checking CSL formulae over CTMDPs requires then the computation of optimal control strategies to prove or disprove a formula. The paper presents a conservative extension of CSL over CTMDPs—wit...