Industrial Requirements for Supporting AI-Enhanced Model-Driven Engineering

TL;DR

This paper identifies and consolidates industrial requirements for integrating AI with model-driven engineering to support cyber-physical systems development, highlighting industry needs and collaboration challenges.

Contribution

It presents a set of 30 generic requirements derived from industrial and academic collaboration, addressing the integration of AI, DevOps, and MDE in cyber-physical systems.

Findings

78 high-level requirements elicited from industry

30 generalized requirements identified for AI and MDE integration

Highlights industry hot spots and collaboration needs

Abstract

There is an increasing interest in research on the combination of AI techniques and methods with MDE. However, there is a gap between AI and MDE practices, as well as between researchers and practitioners. This paper tackles this gap by reporting on industrial requirements in this field. In the AIDOaRt research project, practitioners and researchers collaborate on AI-augmented automation supporting modeling, coding, testing, monitoring, and continuous development in cyber-physical systems. The project specifically lies at the intersection of industry and academia collaboration with several industrial use cases. Through a process of elicitation and refinement, 78 high-level requirements were defined, and generalized into 30 generic requirements by the AIDOaRt partners. The main contribution of this paper is the set of generic requirements from the project for enhancing the development of cyber-physical systems with artificial intelligence, DevOps, and model-driven engineering, identifying the hot spots of industry needs in the interactions of MDE and AI. Future work will refine, implement and evaluate solutions toward these requirements in industry contexts.