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Register a new userPolsat: A Portfolio LTL Satisfiability Solver
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Added by
Jianwen Li
Publication date
2013
fields
Informatics Engineering
and research's language is
English
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In this paper we present a portfolio LTL-satisfiability solver, called Polsat. To achieve fast satisfiability checking for LTL formulas, the tool integrates four representative LTL solvers: pltl, TRP++, NuSMV, and Aalta. The idea of Polsat is to run the component solvers in parallel to get best overall performance; once one of the solvers terminates, it stops all other solvers. Remarkably, the Polsat solver utilizes the power of modern multi-core compute clusters. The empirical experiments show that Polsat takes advantages of it. Further, Polsat is also a testing plat- form for all LTL solvers.
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In recent years, there is growing need and interest in formalizing and reasoning about the quality of software and hardware systems. As opposed to traditional verification, where one handles the question of whether a system satisfies, or not, a given specification, reasoning about quality addresses the question of emph{how well} the system satisfies the specification. One direction in this effort is to refine the eventually operators of temporal logic to {em discounting operators}: the satisfaction value of a specification is a value in $[0,1]$, where the longer it takes to fulfill eventuality requirements, the smaller the satisfaction value is. In this paper we introduce an augmentation by discounting of Linear Temporal Logic (LTL), and study it, as well as its combination with propositional quality operators. We show that one can augment LTL with an arbitrary set of discounting functions, while preserving the decidability of the model-checking problem. Further augmenting the logic with unary propositional quality operators preserves decidability, whereas adding an average-operator makes some problems undecidable. We also discuss the complexity of the problem, as well as various extensions.
This continuously extended technical report collects and compares commonly used formulae from the literature and provides them in a machine readable way.
Propositional linear time temporal logic (LTL) is the standard temporal logic for computing applications and many reasoning techniques and tools have been developed for it. Tableaux for deciding satisfiability have existed since the 1980s. However, the tableaux for this logic do not look like traditional tree-shaped tableau systems and their processing is often quite complicated. We present a new simple traditional-style tree-shaped tableau for LTL and prove that it is sound and complete. As well as being simple to understand, to introduce to students and to use manually, it also seems simple to implement and promises to be competitive in its automation. It is particularly suitable for parallel implementations.
Whether the satisfiability of any formula F of propositional calculus can be determined in polynomial time is an open question. I propose a simple procedure based on some real world mechanisms to tackle this problem. The main result is the blueprint for a machine which is able to test any formula in conjunctive normal form (CNF) for satisfiability in linear time. The device uses light and some electrochemical properties to function. It adapts itself to the scope of the problem without growing exponentially in mass with the size of the formula. It requires infinite precision in its components instead.
This paper presents a novel framework for decentralized monitoring of Linear Temporal Logic (LTL), under the situation where processes are synchronous, uniform (i.e. all processes are peers), and the formula is represented as a tableau. The tableau technique allows one to construct a semantic tree for the input formula, which can be used to optimize the decentralized monitoring of LTL in various ways. Given a system P and an LTL formula L, we construct a tableau for L. The tableauis used for two purposes: (a) to synthesize an efficient round-robin communication policy for processes, and (b) to allow processes to propagate their observations in an optimal way. In our framework, processes can propagate truth values of atomic formulas, compound formulas, and temporal formulas depending on the syntactic structure of the input LTL formula and the observation power of processes. We demonstrate that this approach of decentralized monitoring based on tableau construction is more straightforward, more flexible, and more likely to yield efficient solutions than alternative approaches.
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