Translating Regulatory Clauses into Executable Codes for Building Design Checking via Large Language Model Driven Function Matching and Composing
Engineering Applications of Artificial Intelligence, 2025
Recommended citation: Zheng, Z., Han, J., Chen, K.Y., Cao, X.Y., Lu, X.Z., Lin, J.R.* (2026). Translating Regulatory Clauses into Executable Codes for Building Design Checking via Large Language Model Driven Function Matching and Composing. Engineering Applications of Artificial Intelligence, 163, 112823. doi: 10.1016/j.engappai.2025.112823 http://doi.org/10.1016/j.engappai.2025.112823
Abstract
Translating clauses into executable code is a vital stage of automated rule checking (ARC) and is essential for effective building design compliance checking, particularly for rules with implicit properties or complex logic requiring domain knowledge. Thus, by systematically analyzing building clauses, 66 atomic functions are defined first to encapsulate common computational logics. Then, LLM-FuncMapper is proposed, a large language model (LLM)-based approach with rule-based adaptive prompts that match clauses to atomic functions. Finally, executable code is generated by composing functions through the LLMs. Experiments show LLM-FuncMapper outperforms fine-tuning methods by 19% in function matching while significantly reducing manual annotation efforts. Case study demonstrates that LLM-FuncMapper can automatically compose multiple atomic functions to generate executable code, boosting rule-checking efficiency. To our knowledge, this research represents the first application of LLMs for interpreting complex design clauses into executable code, which may shed light on further adoption of LLMs in the construction domain.
The authors are grateful for the financial support received from the Beijing Municipal Science and Technology Plan Project (Z231100005923043), and National Natural Science Foundation of China (No. 52238011, No.52378306, No. 51908323).
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