Automation in Model-Driven Engineering: A look back, and ahead

TL;DR

This paper reviews the history and future prospects of automation in Model-Driven Engineering, emphasizing AI's role and discussing challenges and opportunities for enhancing automation in complex system development.

Contribution

It provides a comprehensive overview of past automation techniques in MDE and offers perspectives on future improvements and research challenges involving AI integration.

Findings

AI can significantly enhance MDE automation capabilities

Identifies key obstacles to future automation in MDE

Highlights the importance of human-in-the-loop in automation

Abstract

Model-Driven Engineering (MDE) provides a huge body of knowledge of automation for many different engineering tasks, especially those involving transitioning from design to implementation. With the huge progress made in Artificial Intelligence (AI), questions arise about the future of MDE, such as how existing MDE techniques and technologies can be improved or how other activities that currently lack dedicated support can also be automated. However, at the same time, it has to be revisited where and how models should be used to keep the engineers in the loop for creating, operating, and maintaining complex systems. To trigger dedicated research on these open points, we discuss the history of automation in MDE and present perspectives on how automation in MDE can be further improved and which obstacles have to be overcome in both the medium and long-term.