Towards reliable software performance modelling using stochastic process algebra

The aim of any modelling exercise is to develop a better understanding of the system that is being studied, however it is unfortunately not always easy to understand abstract performance models or the metrics that are derived from them. In this tutorial paper we focus on the facilitation of more reliable performance prediction through better understanding of models and solutions in the context of a stochastic process algebra. As well as being confident that the model is accurate, the designer must also have confidence in the measures derived. Partly this is a matter of ensuring that the correct measures are derived, but also that those measures are sufficiently bounded to be applicable.