Design of Fractal-Based Systems Within MDA: Platform Independent Modelling (original) (raw)
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Component-based software engineering (CBSE) [32] and software architecture [30] have become mature and very active fields of study. 1 Both can be traced back to an early vision of systematically produced software [24] and are primarily concerned with the construction of software systems by composition or assembly of software components, with well-defined interfaces and explicit dependencies. Nowadays, it is generally recognized that component-based software engineering and software architecture approaches are crucial to the development, deployment, management, and maintenance of large, dependable software systems [6]. Several component models and associated architecture description languages (i.e., notations for defining components and component assemblages) have been defined in the past
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Component-based system development is now a well accepted design approach in software engineering. Numerous component models have been proposed, and for most of them, specific software tools allow building component-based systems (CBS). Although these tools perform several checks on the built system, few of them provide formal verification of behavioural properties nor performance evaluation of the resulting system. In this context, we have developed a general method associating to a CBS, a formal model, based on stochastic well formed nets, a class of high-level Petri nets, allowing qualitative behavioural analysis together with performance evaluation of this CBS. The definition of the model heavily depends on the (run time) component model used to describe the CBS. In this paper, we instantiate our method to Fractal CBS and its reference Java implementation Julia. The method starts from the Fractal architectural description of a system and defines rules to systematically generate element models of the CBS and their interactions. We then apply a structured method for both qualitative and performance analysis, taking into account the given implementation of the Fractal model. The main interest of our method is to take advantage of the compositional definition of such systems to carry out an efficient analysis. The paper concentrates on performance evaluation and presents our method step by step with an illustrative example.
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