SEAIApr 12

Vibe-driven model-based engineering

arXiv:2604.1064512.9h-index: 1
Predicted impact top 81% in SE · last 90 daysOriginality Synthesis-oriented
AI Analysis

For software engineers, this is a conceptual proposal that outlines opportunities and challenges, but lacks concrete results or validation.

The paper argues that vibe coding (using LLMs) and model-driven engineering can complement each other, introducing 'vibe-driven model-based engineering' to integrate both for faster development of reliable complex systems.

There is a pressing need for better development methods and tools to keep up with the growing demand and increasing complexity of new software systems. New types of user interfaces, the need for intelligent components, sustainability concerns, etc. bring new challenges that we need to handle. In the last years, model-driven engineering (MDE), including its latest incarnation, i.e. low/no-code development, has been key to improving the quality and productivity of software development, but models themselves are becoming increasingly complex to specify and manage. At the same time, we are witnessing the growing popularity of vibe coding approaches that rely on Large Language Models (LLMs) to transform natural language descriptions into running code at the expense of potential code vulnerabilities, scalability issues and maintainability concerns. While many may think vibe coding will replace model-based engineering, in this paper we argue that, in fact, the two approaches can complement each other and provide altogether different development paths for different types of software systems, development scenarios, and user profiles. In this sense, we introduce the concept of \textit{vibe-driven model-based engineering} as a novel approach to integrate the best of both worlds (AI and MDE) to accelerate the development of reliable complex systems. We outline the key concepts of this new approach and highlight the opportunities and open challenges it presents for the future of software development.

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