Generating customized low-code development platforms for digital twins

IF 1.8 3区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Manuela Dalibor , Malte Heithoff , Judith Michael , Lukas Netz , Jérôme Pfeiffer , Bernhard Rumpe , Simon Varga , Andreas Wortmann
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引用次数: 17

Abstract

A digital twin improves our use of a cyber–physical system and understanding of its emerging behavior. To this effect, a digital twin is to be developed and configured and potentially also operated by domain experts, who rarely have a professional software engineering background and for whom easy access and support, e.g., in form of low-code platforms are missing. In this paper, we report on an integrated method for the model-driven engineering of low-code development platforms for digital twins that enables domain experts to create and operate digital twins for cyber–physical systems using the most appropriate modeling languages. The foundation of this method is (1) a code generation infrastructure for information systems combined with (2) an extensible base architecture for self-adaptive digital twins and (3) reusable language components for their configuration. Using this method, software engineers first configure the information system with the required modeling languages to generate the low-code development platform for digital twins before domain experts leverage the generated platform to create digital twins. This two-step method facilitates creating tailored low-code development platforms as well as creating and operating customized digital twins for a variety of applications.

为数字孪生生成定制的低代码开发平台
数字双胞胎提高了我们对网络-物理系统的使用和对其新兴行为的理解。为此,数字孪生将由领域专家开发和配置,并可能由他们操作,这些专家很少有专业的软件工程背景,也缺少简单的访问和支持,例如低代码平台。在本文中,我们报告了一种用于数字孪生的低代码开发平台的模型驱动工程的集成方法,该方法使领域专家能够使用最合适的建模语言为网络-物理系统创建和操作数字孪生。该方法的基础是(1)信息系统的代码生成基础设施,与(2)自适应数字孪生的可扩展基础架构和(3)用于其配置的可重用语言组件相结合。使用这种方法,软件工程师首先用所需的建模语言配置信息系统,为数字双胞胎生成低代码开发平台,然后领域专家利用生成的平台创建数字双胞胎。这种分两步的方法有助于创建量身定制的低代码开发平台,以及为各种应用程序创建和操作定制的数字双胞胎。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Computer Languages
Journal of Computer Languages Computer Science-Computer Networks and Communications
CiteScore
5.00
自引率
13.60%
发文量
36
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