Date Added: Jan 2010
Integrating rising variability of software systems in performance prediction models is crucial to allow widespread industrial use of performance prediction. One of such variabilities is the dependency of system performance on the context and history-dependent internal state of the system (or its components). The questions that rise for current prediction models are: how to include the state properties in a prediction model and how to balance the expressiveness and complexity of created models. Only a few performance prediction approaches deal with modelling states in component-based systems.