Rate Lifting for Stochastic Process Algebra: Exploiting Structural Properties

TL;DR

This paper introduces an algorithm that determines unknown rates in stochastic process algebra models by leveraging structural properties, aiding in model reengineering and repair.

Contribution

It presents the first formulation of structural properties of stochastic process algebra systems and an algorithm that exploits these for rate lifting.

Findings

Algorithm effectively determines unknown rates from flat model data.

Structural properties facilitate rate adjustment without altering transition systems.

Complete pseudo-code provided for implementation.

Abstract

This report presents an algorithm for determining the unknown rates in the sequential processes of a Stochastic Process Algebra model, provided that the rates in the combined flat model are given. Such a rate lifting is useful for model reengineering and model repair. Technically, the algorithm works by solving systems of nonlinear equations and, if necessary, adjusting the model`s synchronisation structure without changing its transition system. This report contains the complete pseudo-code of the algorithm. The approach taken by the algorithm exploits some structural properties of Stochastic Process Algebra systems, which are formulated here for the first time and could be very beneficial also in other contexts.