Composite Applications on top of SAPs implementation of SOA (Enterprise SOA) enable the extension of already existing business logic. In this paper we show, based on a case study, how model-drivenengineering concepts...
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ISBN:
(纸本)9783540690955
Composite Applications on top of SAPs implementation of SOA (Enterprise SOA) enable the extension of already existing business logic. In this paper we show, based on a case study, how model-drivenengineering concepts are applied in the development of such Composite Applications. Our Case Study extends a back-end business process which is required for the specific needs of a demo company selling wine. We use this to describe how the business centric models specifying the modified business behaviour of our case study can be utilized for business performance analysis where most of the actions are performed by humans. In particular, we apply a refined version of model-driven performance engineering that we proposed in our previous work and motivate which business domain specifics have to be taken into account for business performance analysis. We additionally motivate the need for performance related decision support for domain experts, who generally lack performance related skills. Such a support should offer visual guidance about what should be changed in the design and resource mapping to get improved results with respect to modification constraints and performance objectives, or objectives for time.
performance prediction methods can help software architects to identify potential performance problems, such as bottlenecks, in their software systems during the design phase. In such early stages of the software life...
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performance prediction methods can help software architects to identify potential performance problems, such as bottlenecks, in their software systems during the design phase. In such early stages of the software life-cycle, only a little information is available about the system's implementation and execution environment. However, these details are crucial for accurate performance predictions. performance completions close the gap between available high-level models and required low-level details. Using model-driven technologies, transformations can include details of the implementation and execution environment into abstract performancemodels. However, existing approaches do not consider the relation of actual implementations and performancemodels used for prediction. Furthermore, they neglect the broad variety of possible implementations and middleware platforms, possible configurations, and possible usage scenarios. In this paper, we (i) establish a formal relation between generated performancemodels and generated code, (ii) introduce a design and application process for parametric performance completions, and (iii) develop a parametric performance completion for Message-oriented Middleware according to our method. Parametric performance completions are independent of a specific platform, reflect performance-relevant software configurations, and capture the influence of different usage scenarios. To evaluate the prediction accuracy of the completion for Message-oriented Middleware, we conducted a real-world case study with the SPECjms2007 Benchmark [http://***/jms2007/]. The observed deviation of measurements and predictions was below 10% to 15%. (c) 2009 Elsevier B.V. All rights reserved.
The recent rise of the NoSQL movement motivates investigation on the performance impact that new persistence approaches can bring in the model-driven re-engineering of a consolidated object-oriented software architect...
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ISBN:
(纸本)9781450340809
The recent rise of the NoSQL movement motivates investigation on the performance impact that new persistence approaches can bring in the model-driven re-engineering of a consolidated object-oriented software architecture. We report comparative experimental performance results attained by combining a pattern-based domain logic with a persistence layer based on different paradigms and we describe how data model is persisted in various implementation based on MySQL, Neo4j, and MongoDB.
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