Temporal dataset evaluation is the problem of establishing to what extent a set of temporal data (histories) complies with a given temporal condition. Checking interval temporal logic formulas against a finite model has been recently proposed, and proved successful, as a tool to solve such a problem. In this paper, we address the problem of checking interval temporal logic specifications, supporting interval length constraints, against infinite, finitely representable models, and we show the applicability of the resulting procedure to the evaluation of incomplete temporal datasets viewed as finite prefixes of ultimately-periodic histories.

Ultimately-periodic interval model checking for temporal dataset evaluation

Guido Sciavicco
2019

Abstract

Temporal dataset evaluation is the problem of establishing to what extent a set of temporal data (histories) complies with a given temporal condition. Checking interval temporal logic formulas against a finite model has been recently proposed, and proved successful, as a tool to solve such a problem. In this paper, we address the problem of checking interval temporal logic specifications, supporting interval length constraints, against infinite, finitely representable models, and we show the applicability of the resulting procedure to the evaluation of incomplete temporal datasets viewed as finite prefixes of ultimately-periodic histories.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2411137
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