首页> 外文期刊>Software and systems modeling >Using structural decomposition and refinements for deep modeling of software architectures
【24h】

Using structural decomposition and refinements for deep modeling of software architectures

机译:用于软件架构的深层建模的结构分解和改进

获取原文
获取原文并翻译 | 示例
       

摘要

Traditional metamodeling in two levels gets to its limits when model elements of a domain should be described as instances of other model elements. For example in architecture description languages, components may be instances of their component types. Although workarounds to model such instance relations between model elements exist, they require many validation constraints and imply a cumbersome interface. To obtain more elegant metamodels, deep modeling seeks ways to represent non-transitive instantiation chains directly. However, existing concepts cannot be applied in some situations we refer as composite instantiation patterns. Further, these concepts make existing technologies for model transformation and analysis obsolete as these languages have to be adapted. In this paper, we present an approach to realize deep modeling through structural decomposition and refinements that can be implemented as a noninvasive extension to EMOF-like meta-metamodels. As a consequence, existing tools need not be adapted and composite instantiation patterns are fully supported. We validate our concept by creating a deep modeling architecture description language based on the Palladio Component Model and demonstrate its advantages by modeling a synthetic web application. We show that existing tools for incremental model analysis can be reused and manifest several orders of speedup for a synthetic example analysis.
机译:当域的模型元素应被描述为其他模型元素的实例时,两个级别的传统元模型都会达到其限制。例如,在架构描述语言中,组件可能是其组件类型的实例。虽然替代方法来模拟模型元素之间的这种实例关系,但它们需要许多验证约束并意味着繁琐的接口。为了获得更优雅的元模型,深度建模试图直接代表非传递实例化链。但是,在某些情况下,现有概念不能应用于复合实例化模式。此外,这些概念使现有技术用于模型转换和分析随意,随着这些语言必须调整。在本文中,我们介绍了一种通过结构分解和改进来实现深度建模的方法,其可以作为非侵入性扩展到EMOF类似的元元模型。结果,不需要调整现有工具,并且完全支持复合实例化模式。我们通过基于Palladio组件模型创建深度建模架构描述语言来验证我们的概念,并通过模拟合成Web应用程序来展示其优点。我们表明,可以重复使用用于增量模型分析的现有工具,并表现出综合示例分析的几个加速度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号