SEAIARDec 19, 2025

LLM-based Behaviour Driven Development for Hardware Design

arXiv:2512.17814v2h-index: 1
Originality Synthesis-oriented
AI Analysis

This work addresses the problem of limited practical use of BDD in hardware design for engineers, representing an incremental step by applying existing LLM methods to a new domain.

The paper tackles the challenge of automating the manual effort in deriving behavioral scenarios from textual specifications for hardware design by investigating the use of LLM-based techniques to support Behavior Driven Development, aiming to reduce complexity in test and verification as system sizes increase.

Test and verification are essential activities in hardware and system design, but their complexity grows significantly with increasing system sizes. While Behavior Driven Development (BDD) has proven effective in software engineering, it is not yet well established in hardware design, and its practical use remains limited. One contributing factor is the manual effort required to derive precise behavioral scenarios from textual specifications. Recent advances in Large Language Models (LLMs) offer new opportunities to automate this step. In this paper, we investigate the use of LLM-based techniques to support BDD in the context of hardware design.

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