Performance prediction (Palladio)
The Palladio research project aims at the development of methods and tools for systematically constructing component based software architectures with predictable quality attributes. For predicting the quality of service of software architectures we utilise and enhance existing prediction models, such as stochastic Petri nets, queuing models and Markov models in general is a special modeling language targeted at model-driven performance predictions. The PCM is accompanied by several model transformations, which derive stochastic regular expressions, queuing network models, or Java source code from a software design model. Software architects can use the results of the analytical models to evaluate the feasibility of performance requirements, identify performance bottlenecks, and support architectural design decisions quantitatively.
Contact: Ralf Reussner