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From Image to UML: First Results of Image Based UML Diagram Generation Using LLMs
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In software engineering processes, systems are first specified using a modeling language such as UML. These initial designs are often collaboratively created, many times in meetings where different domain experts use whiteboards, paper or other types of quick supports to create drawings and blueprints that then will need to be formalized. These proper, machine-readable, models are key to ensure models can be part of automated processes (e.g. input of a low-code generation pipeline, a model-based testing system, ...). But going from hand-drawn diagrams to actual models is a time-consuming process that sometimes ends up with such drawings just added as informal images to the software documentation, reducing their value a lot. To avoid this tedious task, we explore the usage of Large Language Models (LLM) to generate the formal representation of (UML) models from a given drawing. More specifically, we have evaluated the capabilities of different LLMs to convert images of UML class diagrams into the actual models represented in the images. While the results are good enough to use such an approach as part of a model-driven engineering pipeline we also highlight some of their current limitations and the need to keep the human in the loop to overcome those limitations.
Forward citations
Cited by 4 Pith papers
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Using XMI and control-flow-graph comparison as reinforcement-learning rewards makes a 4B open vision-language model competitive with larger proprietary models on handwritten UML-to-PlantUML, but the reward stage's ben...
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Automated Feedback on Student-Generated UML and ER Diagrams Using Large Language Models
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