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Register a new userFrom model checking to a temporal proof for partial models: preliminary example
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Added by
Anna Bernasconi
Publication date
2017
fields
Informatics Engineering
and research's language is
English
Authors
A. Bernasconi
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This paper describes in detail the example introduced in the preliminary evaluation of THRIVE. Specifically, it evaluates THRIVE over an abstraction of the ground model proposed for a critical component belonging to a medical device used by optometrists and ophtalmologits to dected visual problems.
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While model checking has often been considered as a practical alternative to building formal proofs, we argue here that the theory of sequent calculus proofs can be used to provide an appealing foundation for model checking. Since the emphasis of model checking is on establishing the truth of a property in a model, we rely on the proof theoretic notion of additive inference rules, since such rules allow provability to directly describe truth conditions. Unfortunately, the additive treatment of quantifiers requires inference rules to have infinite sets of premises and the additive treatment of model descriptions provides no natural notion of state exploration. By employing a focused proof system, it is possible to construct large scale, synthetic rules that also qualify as additive but contain elements of multiplicative inference. These additive synthetic rules -- essentially rules built from the description of a model -- allow a direct treatment of state exploration. This proof theoretic framework provides a natural treatment of reachability and non-reachability problems, as well as tabled deduction, bisimulation, and winning strategies.
In the last decades much research effort has been devoted to extending the success of model checking from the traditional field of finite state machines and vario
In the last years, model checking with interval temporal logics is emerging as a viable alternative to model checking with standard point-based temporal logics, such as LTL, CTL, CTL*, and the like. The behavior of the system is modeled by means of (finite) Kripke structures, as usual. However, while temporal logics which are interpreted point-wise describe how the system evolves state-by-state, and predicate properties of system states, those which are interpreted interval-wise express properties of computation stretches, spanning a sequence of states. A proposition letter is assumed to hold over a computation stretch (interval) if and only if it holds over each component state (homogeneity assumption). A natural question arises: is there any advantage in replacing points by intervals as the primary temporal entities, or is it just a matter of taste? In this paper, we study the expressiveness of Halpern and Shohams interval temporal logic (HS) in model checking, in comparison with those of LTL, CTL, and CTL*. To this end, we consider three semantic variants of HS: the state-based one, introduced by Montanari et al., that allows time to branch both in the past and in the future, the computation-tree-based one, that allows time to branch in the future only, and the trace-based variant, that disallows time to branch. These variants are compared among themselves and to the aforementioned standard logics, getting a complete picture. In particular, we show that HS with trace-based semantics is equivalent to LTL (but at least exponentially more succinct), HS with computation-tree-based semantics is equivalent to finitary CTL*, and HS with state-based semantics is incomparable with all of them (LTL, CTL, and CTL*).
Many complex systems can be described by population models, in which a pool of agents interacts and produces complex collective behaviours. We consider the problem of verifying formal properties of the underlying mathematical representation of these models, which is a Continuous Time Markov Chain, often with a huge state space. To circumvent the state space explosion, we rely on stochastic approximation techniques, which replace the large model by a simpler one, guaranteed to be probabilistically consistent. We show how to efficiently and accurately verify properties of random individual agents, specified by Continuous Stochastic Logic extended with Timed Automata (CSL-TA), and how to lift these specifications to the collective level, approximating the number of agents satisfying them using second or higher order stochastic approximation techniques.
We define a logical framework with singleton types and one universe of small types. We give the semantics using a PER model; it is used for constructing a normalisation-by-evaluation algorithm. We prove completeness and soundness of the algorithm; and get as a corollary the injectivity of type constructors. Then we give the definition of a correct and complete type-checking algorithm for terms in normal form. We extend the results to proof-irrelevant propositions.
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