arXiv:2607.26181cs.AI2026-07

用智能体框架实现硬件验证闭环,覆盖率达98%以上

GoGoTB: Agentic RTL Verification with Specification-Grounded Coverage Closure

  • 构建三层智能体系统,分层控制与动态调用专业知识
  • 在8个RTL设计上实现100%环境生成成功率,平均覆盖率超97%
  • 每项未覆盖项对应具体规范,可定位问题并精准修复

功能验证占集成电路前端工程工作量的主导地位,单个漏检的漏洞可能导致昂贵的流片返工。现有基于大语言模型的方法依赖独立单轮调用,缺乏上下文共享,导致接口不匹配且覆盖率与规范脱节。为此,我们提出GoGoTB,一个通过三个子系统实现端到端验证闭环的智能体框架:执行控制层在工具与阶段边界分离确定性执行与模型推理;知识系统按需调度方法论与设计专有知识;覆盖框架将每个覆盖项与命名规范行为对齐,使每项剩余缺口均有可诊断根因和针对性修复方案。在8个无需人工干预的RTL设计上测试,GoGoTB实现100%环境生成成功,平均行覆盖率98.4%、分支覆盖率97.2%、翻转覆盖率97.0%、功能覆盖率83.2%。此前无任何工作能在相同基准上成功生成完整验证环境或达到有意义覆盖率。

原文摘要 · Abstract (English)

Functional verification dominates integrated circuit (IC) front-end engineering effort, and a single missed bug that escapes to silicon can trigger a costly respin. Recent large language models (LLMs) offer new opportunities to automate this process, yet existing LLM-based approaches generate each component through independent single-turn calls with no shared context, leaving interface mismatches undetected and reported coverage disconnected from specification requirements. To address these challenges, we present GoGoTB, an agentic framework that achieves end-to-end verification closure through three subsystems: an agentic execution control layer, an evolvable knowledge system, and specification-grounded coverage closure. The execution control layer separates deterministic enforcement from LLM reasoning at every tool and stage boundary. The knowledge system dispatches methodology and design-specific expertise on demand. The coverage framework anchors every bin to a named specification behavior so that each residual gap has a diagnosable root cause and a targeted remedy. Tested on 8 register transfer level (RTL) designs without any human intervention, GoGoTB achieves 100\% environment generation success and averages 98.4\% line, 97.2\% branch, 97.0\% toggle, and 83.2\% functional coverage. No prior work successfully generates a complete verification environment or achieves meaningful coverage on the same benchmarks.

硬件验证智能体覆盖率LLM

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