Stochastic process algebras: integrating qualitative and quantitative modelling.
Jane Elizabeth Hillston, Holger Hermanns, Ulrich Herzog, Vassilis Mertsiotakis, Michael Rettelbach · 1994
In this paper we present an extension of the process algebra modelling methodology which allows qualitative and quantitative modelling to be integrated. This extension, to form stochastic process algebras (SPA), has been recently demonstrated to have many interesting features. Such languages serve two purposes as a formal description language for computer system models. Quantitative information may be used to predict the performance of the system whereas qualitative information may be exploited when reasoning about the functional behaviour of the system (e.g. when finding deadlocks or when exhibiting equivalences between subcomponents). While qualitative analysis is carried out using standard techniques for process algebras, quantitative analysis is based on an underlying continuous time Markov chain (CTMC). Several stochastic process algebras have recently appeared in the literature. Here we present the emerging concensus of the salient features for such languages and discuss their us...