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A domain-specific language for context modeling in context-aware systems

机译:在上下文感知系统中用于上下文建模的领域特定语言

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摘要

Context-awareness refers to systems that can both sense and react based on their environment. One of the main difficulties that developers of context-aware systems must tackle is how to manage the needed context information. In this paper we present MLContext, a textual Domain-Specific Language (DSL) which is specially tailored for modeling context information. It has been implemented by applying Model-Driven Development (MDD) techniques to automatically generate software artifacts from context models. The MLContext abstract syntax has been defined as a metamodel, and model-to text transformations have been written to generate the desired software artifacts. The concrete syntax has been defined with the EMFText tool, which generates an editor and model injector. MLContext has been designed to provide a high-level abstraction, to be easy to learn, and to promote reuse of context models. A domain analysis has been applied to elicit the requirements and design choices to be taken into account in creating the DSL As a proof of concept of the proposal, the generative approach has been applied to two different middleware platforms for context management.
机译:上下文感知是指可以根据其环境进行感知和响应的系统。上下文感知系统的开发人员必须解决的主要困难之一是如何管理所需的上下文信息。在本文中,我们介绍了MLContext,这是一种文本领域专用语言(DSL),专门为建模上下文信息而量身定制。它已通过应用模型驱动开发(MDD)技术从上下文模型自动生成软件工件来实现。 MLContext抽象语法已定义为元模型,并且已编写了从模型到文本的转换以生成所需的软件工件。已使用EMFText工具定义了具体语法,该工具会生成编辑器和模型注入器。 MLContext旨在提供高级抽象,易于学习并促进上下文模型的重用。已应用领域分析来得出创建DSL时要考虑的要求和设计选择。作为建议概念的证明,生成方法已应用于上下文管理的两个不同的中间件平台。

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