Probabilistic Environments in the Quantitative Analysis of (Non-Probabilistic) Behaviour Models
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BibTeX
@MISC{Pavese_probabilisticenvironments,
author = {Esteban Pavese and Víctor Braberman and Sebastian Uchitel},
title = {Probabilistic Environments in the Quantitative Analysis of (Non-Probabilistic) Behaviour Models},
year = {}
}
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Abstract
System specifications have long been expressed through automata-based languages, enabling verification techniques such as model checking. These verification techniques can assess whether a property holds or not, given a system specification. Quantitative model checking can provide additional information on the probability of these properties holding. We are interested in quantitatively analysing the probability of errors in non-probabilistic system models by composing them with probabilistic models of the environment. Although many probabilistic automata-based formalisms and composition operators exist, these are not adequate for such a setting. In this work we present a formalism inspired on interface automata and a suitable composition operator for these automata that enables validation of environment models in isolation and sound analysis of its composition with the non-probabilistic model of the system-under-analysis.
