A Matrix-based Method for Analysing Stochastic Process Algebras

This paper demonstrates how three stochastic process algebras can be mapped on to a generally-distributed stochastic transition system. We demonstrate an aggregation technique on these stochastic transition systems and show how this can be implemented as a matrix-analysis method for finding steady-state distributions. We verify that the time complexity of the algorithm is a considerable improvement upon a previous method and discuss how the technique can be used to generate partial steady-state distributions for SPA systems.