GoGoTB: Agentic RTL Verification with Specification-Grounded Coverage Closure

2026-07-28

AI Summary

This work addresses the limitations of traditional RTL functional verification, which heavily relies on manual effort, and overcomes the shortcomings of existing LLM-based approaches that suffer from context fragmentation, leading to interface mismatches and coverage metrics decoupled from specifications. The paper proposes a novel agent-based framework that integrates an execution control layer, an evolvable knowledge system, and specification-anchored coverage modeling to establish an end-to-end automated verification loop. This framework enables, for the first time, fully automatic generation of complete verification environments without human intervention and precisely links each coverage bin to specific specification behaviors, facilitating diagnosable gap identification and repair. Evaluated on eight RTL designs, the approach achieves 100% success in verification environment generation, with average line, branch, toggle, and functional coverage rates of 98.4%, 97.2%, 97.0%, and 83.2%, respectively.

Abstract

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.

Problem

• RTL verification
• coverage closure
• specification grounding
• functional verification
• LLM-based automation

Innovation

• Agentic Verification
• Specification-Grounded Coverage
• LLM-based RTL Verification
• Coverage Closure
• Evolvable Knowledge System