Today, performance prediction of component-based systems is important to help software engineers to analyze their applications in early stages of the development life-cycle, so that performance problems are avoided. To achieve performance prediction, modelling is a crucial step. It would be interesting if component performance models can be derived automatically. To this aim, we describe in this paper a software toolset which allows component designers of specific systems, that are
systems, to generate performance models, starting from the
architectural description of their system and component behaviours. These models consist of Stochastic Well formed Nets (SWN) and Stochastic Petri nets (SPN), and can be analyzed using SPN/SWN analysis tools. A case study illustrates the effectiveness of our approach.