Configurable Model Refinements for Palladio based on a Generic Model

In Component-Based Software Engineering (CBSE), abstract views of systems are realized. These abstract design models ignore low-level details that are not relevant at early stages of the conception. In software performance engineering, design models are used to predict performance characteristics of systems prior to their implementation. The Palladio approach uses CBSE concepts to predict the performance and other qualities of software architectures. To perform accurate performance predictions, design models need to be refined with low-level details. Including these details directly into design models would increase the modeling effort and the complexity of models in an undesired manner. Performance model completions are model refinements which close the gap between abstract models and low-level details needed to perform accurate performance predictions. They need to be configurable so that inserted low-level details fit specific considered cases. In the context of PCM models, two model completions are implemented using two different model transformation languages. In this thesis these two completions are realized using model weaving. The applied completion concepts are compared with those used in model weaving based completions. One completion adds information on networks and middleware composing a connector. It is implemented in Java. The second completion specifies details on thread pools used in parallel processing. It is realized using Higher Order Transformations (HOTs) implemented in the general-purpose model transformation language QVT-R. Model weaving approaches lack configurability. To counter this problem, configuration-based variability is introduced in a model weaving approach. Similarly to HOTs, aspects are applied on aspects to specialize their behavior. The chosen model weaving approach is then adjusted to fit PCM models. The three introduced realizations of performance model completions using model transformation languages and model weaving are finally compared in terms of length, complexity and execution time using the two model completions as case studies.

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