2010
DOI: 10.1016/j.peva.2009.07.006
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Parametric performance completions for model-driven performance prediction

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Cited by 42 publications
(38 citation statements)
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“…For example, the software architect can model simple resource demands, control flows or passive resources. This separate middleware model can encapsulate enhancements in the future such as research results as mentioned by Happe [8] and others.…”
Section: Platform-specific Componentsmentioning
confidence: 99%
“…For example, the software architect can model simple resource demands, control flows or passive resources. This separate middleware model can encapsulate enhancements in the future such as research results as mentioned by Happe [8] and others.…”
Section: Platform-specific Componentsmentioning
confidence: 99%
“…As shown in [11], it is possible to model asynchronous pointto-point communication using a combination of non-synchronized fork actions and external service calls. However, following this approach asynchronous events are modeled using synchronous service calls and therefore a semantic gap between the system implementation and the architecture model is introduced.…”
Section: Model Extensionsmentioning
confidence: 99%
“…The RD-SEFF representing the corresponding event handler is then associated with this service. Additionally, it is possible to integrate the marshalling of events as done in [11] for point-to-point connections.…”
Section: Model Extensionsmentioning
confidence: 99%
“…Mark models are a convenient way to work with parameterized transformations. MDA, certainly, allows for use of mark models in model transformations (Happe et al, 2009). Happe et al use mark models to annotate performance models in their work on performance completions (Happe et al, 2009).…”
mentioning
confidence: 99%
“…MDA, certainly, allows for use of mark models in model transformations (Happe et al, 2009). Happe et al use mark models to annotate performance models in their work on performance completions (Happe et al, 2009).  Ignoring BehaviorExecutionSpecifications (BESs) and Execution Occurrence Specifications (EOSs) model elements during pointcut detection and composition.…”
mentioning
confidence: 99%