State dependence in performance evaluation of component-based software systems
| Authors | |
|---|---|
| Year of publication | 2010 |
| Type | Article in Proceedings |
| Conference | Proceedings of the Joint WOSP/SIPEW International Conference on Performance Engineering (ICPE'10) |
| MU Faculty or unit | |
| Citation | |
| Web | http://portal.acm.org/citation.cfm?id=1712605.1712613&coll=Portal&dl=GUIDE&CFID=75638867&CFTOKEN=77599524 |
| Field | Informatics |
| Keywords | Component-based systems; performance models; internal state of a component |
| Description | 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). In the paper, we have conducted a state-of-the-art survey of existing approaches addressing their expressiveness to model stateful components. Based on the results, we introduce a classification scheme and present the state-defining and state-dependent model parameters. We extend the Palladio Component Model (PCM), a model-based performance prediction approach, with state-modelling capabilities, and study the performance impact of modelled state. A practical influences of the internal state on software performance is evaluated on a realistic case study. |
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