  The syntactic nature and compositionality characteristic of stochastic
process algebras make models to be easily understood by human beings, but not
convenient for machines as well as people to directly carry out mathematical
analysis and stochastic simulation. This paper presents a numerical
representation schema for the stochastic process algebra PEPA, which can
provide a platform to directly and conveniently employ a variety of
computational approaches to both qualitatively and quantitatively analyse the
models. Moreover, these approaches developed on the basis of the schema are
demonstrated and discussed. In particular, algorithms for automatically
deriving the schema from a general PEPA model and simulating the model based on
the derived schema to derive performance measures are presented.
