Towards a taxonomy of software connectors
Proceedings of the 22nd international conference on Software engineering
Model-Based Performance Prediction in Software Development: A Survey
IEEE Transactions on Software Engineering
The Palladio component model for model-driven performance prediction
Journal of Systems and Software
Automated Feature Model-Based Generation of Refinement Transformations
SEAA '09 Proceedings of the 2009 35th Euromicro Conference on Software Engineering and Advanced Applications
The Performance Cockpit Approach: A Framework For Systematic Performance Evaluations
SEAA '10 Proceedings of the 2010 36th EUROMICRO Conference on Software Engineering and Advanced Applications
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Typically, to provide accurate predictions, a performance model has to include low-level details such as used communication infrastructure, or connectors and influence of the underlying middleware platform. In order to profit from the research on inter-component communication and connector design, performance prediction approaches need to include models of different kinds of connectors. It is not always feasible to model complex connectors with all their details. The choice of suitable abstraction filter, which reduces the amount of detailed information needed with respect to the model purpose, is crucial to decrease modelling effort. We propose an approach by which an abstract connector model can be augmented with selected adaptations and enhancements using model completions to result in a more detailed connector model. As the purpose of our models is performance prediction, we designed a suitable abstraction filter based on the Pipes & Filters pattern to produce performance models of connectors. Thus, we need to characterize only a small set of compositional and reusable transformations. The selection of applied transformations is then based on the feature-oriented design of the connector's completion.