A compositional semantics for UML state machines aimed at performance evaluation

J. Merseguer, J. Campos, Simona Bernardi, S. Donatelli
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引用次数: 90

Abstract

Unified Modeling Language (UML) is gaining acceptance to describe the behaviour of systems. It has attracted the attention of researchers that are interested in deriving, automatically, performance evaluation models from system's descriptions. A required step to automatically produce a performance model (as any executable model) is that the semantics of the description language is formally defined. Among the UML diagrams, we concentrate on state machines (SMs) and we build a semantics for a significant subset of them in terms of generalized stochastic Petri nets (GSPNs). The paper shows how to derive an executable GSPN model from a description of a system, expressed as a set of SMs. The semantics is compositional since the executable GSPN model is obtained by composing, using standard Petri net operators, the GSPN models of the single SMs, and each GSPN model is obtained by composition of submodels for SM basic features.
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针对性能评估的UML状态机的组合语义
统一建模语言(UML)被越来越多的人接受来描述系统的行为。它引起了对从系统描述中自动导出性能评估模型感兴趣的研究人员的注意。自动生成性能模型(与任何可执行模型一样)的必要步骤是正式定义描述语言的语义。在UML图中,我们专注于状态机(SMs),并根据广义随机Petri网(gspn)为其中的一个重要子集构建语义。本文展示了如何从系统的描述中推导出一个可执行的GSPN模型,该模型表示为一组SMs。使用标准Petri网算子对单个SMs的GSPN模型进行组合得到可执行的GSPN模型,而每个GSPN模型又通过对SM基本特征的子模型进行组合得到。
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