The Palladio component model for model-driven performance prediction

One aim of component-based software engineering (CBSE) is to enable the prediction of extra-functional properties, such as performance and reliability, utilising a well-defined composition theory. Nowadays, such theories and their accompanying prediction methods are still in a maturation stage. Several factors influencing extra-functional properties need additional research to be understood. A special problem in CBSE stems from its specific development process: Software components should be specified and implemented independently from their later context to enable reuse. Thus, extra-functional properties of components need to be specified in a parametric way to take different influencing factors like the hardware platform or the usage profile into account. Our approach uses the Palladio component model (PCM) to specify component-based software architectures in a parametric way. This model offers direct support of the CBSE development process by dividing the model creation among the developer roles. This paper presents our model and a simulation tool based on it, which is capable of making performance predictions. Within a case study, we show that the resulting prediction accuracy is sufficient to support the evaluation of architectural design decisions.