ThingML:针对异构目标的语言和代码生成框架

Nicolas Harrand, Franck Fleurey, Brice Morin, Knut Eilif Husa
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引用次数: 117

摘要

模型驱动软件工程(MDSE)的卖点之一是通过从模型自动生成代码来提高生产力。然而,代码生成的实际采用仍然相对缓慢,并且仅限于特定的应用程序。工具问题经常被指出,但更根本的是,经验表明:(i)用于其他目的的模型和建模语言不一定很适合代码生成,(ii)代码生成器通常被视为不容易信任的黑盒,并产生次优代码。本文介绍并讨论了我们将ThingML方法应用于不同领域的经验。ThingML包括一个建模语言和工具,旨在支持代码生成,以及一个高度可定制的多平台代码生成框架。该方法是在一个开源工具中实现的,该工具提供了一系列针对异构平台的代码生成器。它已经通过几个案例研究进行了评价,并正在用于开发商业环境辅助生活系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ThingML: a language and code generation framework for heterogeneous targets
One of the selling points of Model-Driven Software Engineering (MDSE) is the increase in productivity offered by automatically generating code from models. However, the practical adoption of code generation remains relatively slow and limited to niche applications. Tooling issues are often pointed out but more fundamentally, experience shows that: (i) models and modeling languages used for other purposes are not necessarily well suited for code generation and (ii) code generators are often seen as black-boxes which are not easy to trust and produce sub-optimal code. This paper presents and discusses our experiences applying the ThingML approach to different domains. ThingML includes a modeling language and tool designed for supporting code generation and a highly customizable multi-platform code generation framework. The approach is implemented in an open-source tool providing a family of code generators targeting heterogeneous platforms. It has been evaluated through several case studies and is being used for in the development of a commercial ambient assisted living system.
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