AI - Driven Automated UML Modeling Framework Design and Practice

The Unified Modeling Language (UML) is a core modeling tool in the field of software engineering, playing an irreplaceable role in system design and team collaboration. However, traditional UML modeling tools suffer from inefficiency, version conflicts, and disconnection between design and code. In recent years, breakthroughs in Generative Artificial Intelligence (AIGC) have provided new solutions for automated modeling. This study proposes a deep learning-based UML intelligent generation framework, aiming to directly generate standardized PlantUML code from natural language requirements. The framework achieves end-to-end automated generation from requirements to UML models through deep semantic parsing, multi-view collaborative mechanisms, and dynamic syntax validation pipelines. Experimental results show that the framework can compress the modeling cycle from hours to minutes, significantly improving modeling efficiency and providing a new paradigm for intelligent software engineering.