Abstract

In recognising that performance modelling is increasingly of interest to professionals who do not have a background in mathematical analysis, it is important to provide additional mechanisms by which such communities may improve their confidence in the models they evaluate accurately reflect the systems they are studying. One such community is traditional software engineering, where visualisation techniques are well established aids to understanding complex software systems. In this paper we seek to apply some basic visualisation techniques from program comprehension to some example performance models expressed in the stochastic process algebra, PEPA. An interesting side line to this work is that it provides an additional mechanism for understanding complex software systems. 1

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