Increase development productivity by domain-specific conceptual modeling

IF 2.7 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Data & Knowledge Engineering Pub Date : 2023-12-15 DOI:10.1016/j.datak.2023.102263
Martin Paczona , Heinrich C. Mayr , Guenter Prochart
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Abstract

This paper addresses the question of whether and how the development and use of a domain-specific modeling method (DSMM) can increase productivity in the development of technical systems in an industrial setting. This is because an essential prerequisite for DSMMs to become established in operational practice is that productivity increases can be achieved with them and qualitative benefits such as quality assurance, innovation potential, and the like can be exploited. After all, managers’ decisions are ultimately based on whether or not the use of a new method pays off. We illustrate our findings using the example of a DSMM development for the design and realization of electric vehicle testbeds, which we carried out as part of a cooperation project. This work sets the base for possible generalization into other automotive, mechatronic, and technical areas.

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通过特定领域的概念建模提高开发效率
本文探讨的问题是:在工业环境中,开发和使用特定领域建模方法(DSMM)能否以及如何提高技术系统开发的生产率。这是因为,DSMM 在操作实践中得以确立的一个基本前提是,使用 DSMM 可以提高生产率,并能获得质量保证、创新潜力等质量效益。毕竟,管理者的决策最终取决于新方法的使用是否带来回报。我们以电动汽车测试平台设计和实现的 DSMM 开发为例,说明我们的研究成果。这项工作为可能推广到其他汽车、机电一体化和技术领域奠定了基础。
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
Data & Knowledge Engineering
Data & Knowledge Engineering 工程技术-计算机:人工智能
CiteScore
5.00
自引率
0.00%
发文量
66
审稿时长
6 months
期刊介绍: Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these systems.
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