TTool-AI: A Large Language Model-Based Assistant for Model Driven Engineering

Throughout the history of engineering, successive innovations have been implemented to assist engineers in their tasks, enabling them to focus on high-value activities while minimizing time-consuming and error-prone tasks. Large language models (LLMs) represent one of these innovations, with significant potential for developing new kinds of engineering assistants, as demonstrated by a rich body of recent literature. The paper introduces TTool-AI, a model-driven engineering assistant based on LLMs and integrated within the SysML modeling and formal verification toolkit TTool. TTool-AI enables system architects to generate and incrementally refine various types of SysML diagrams directly from textual specifications with a single click. The core mechanisms of TTool-AI (contextual knowledge injection, automated prompt generation, and iterative feedback) enable it to produce good quality models that can serve as a sound foundation for system architects in MDE processes. Building on our previous work presented at MODELSWARD 2024, this paper provides a comprehensive description of TTool-AI’s MDE assistance features. It introduces new functionalities, including requirement engineering and automated model mutation generation. An evaluation of these features, comparing their performance against Master-level students, demonstrates the tool’s efficacy and suggests a strong potential to significantly enhance engineering productivity by enabling engineers to focus on high-value tasks.