arXiv:2610.40042v1 Announce Type: cross
Abstract: For more than three decades, UPPAAL has supported the modelling and analysis of real-time and cyber-physical systems. Yet building a suitable model, formalising the intended properties, choosing analysis techniques and interpreting counterexamples remain iterative tasks that demand substantial expertise. Large language models (LLMs) can offer plausible explanations and even solutions, but they are not necessarily correct. We present UPPAAI, an extension of UPPAAL in which users construct, explain, debug and specify models in dialogue with an LLM. The guiding principle is that the user requests, the LLM proposes, explains and orchestrates, and UPPAAL verifies. UPPAAI exposes the UPPAAL editor, queries and verifier through a Tools API. We report on seven case studies, from explaining to a newcomer to learning a controller, covering timed automata, stochastic hybrid automata and strategy learning. LLMs proved to be extremely helpful in not just generating solutions but also pro-actively suggesting relevant UPPAAL features it was not asked about.
arxiv
UPPAAI Connects LLM Assistance to UPPAAL Formal Verification
Researchers present UPPAAI, an extension of UPPAAL that lets users construct, explain, debug and specify models through dialogue with an LLM. A Tools API exposes the editor, queries and verifier, with the LLM proposing and orchestrating actions while UPPAAL performs verification. The paper reports seven case studies spanning timed automata, stochastic hybrid automata and strategy learning.
The work offers a concrete approach to combining LLM assistance with formal verification rather than relying on the correctness of generated suggestions alone.
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