From Language to Logic: Bridging LLMs & Formal Representations for RTL Assertion Generation
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arXiv
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| Natura: | Preprint |
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2026
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| author | Mashnoor, Nowfel Kamali, Hadi Azar, Kimia |
| author_facet | Mashnoor, Nowfel Kamali, Hadi Azar, Kimia |
| contents | SystemVerilog Assertions (SVA) are essential for formal verification of digital hardware, yet their manual creation demands significant expertise in both the design under verification and temporal logic. Recent studies have explored using large language models (LLMs) to automate SVA generation, but existing approaches suffer from incorrect signal references, missing timing constraints, and lack of formal correctness guarantees. This paper presents ProofLoop, a tool-augmented ReAct agent that generates SVA from natural-language specifications using a solver-in-the-loop approach. The agent operates in two phases: Phase A autonomously gathers design context by invoking EDA and formal tools, including semantic search over an AST-indexed vector database and JasperGold structural queries, while Phase B generates SVA and iteratively refines it using JasperGold formal proof feedback over up to fixed (here 3) verification rounds. We evaluate ProofLoop on FVEval Design2SVA design benchmarks and demonstrate that this framework can achieve 93.7% syntax correctness and 82.0% functional correctness. An ablation study confirms that each component, i.e., retrieval-augmented generation (RAG), JasperGold tools, and the verification loop contributes significantly (and orthogonally). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_23100 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | From Language to Logic: Bridging LLMs & Formal Representations for RTL Assertion Generation Mashnoor, Nowfel Kamali, Hadi Azar, Kimia Cryptography and Security Hardware Architecture Logic in Computer Science SystemVerilog Assertions (SVA) are essential for formal verification of digital hardware, yet their manual creation demands significant expertise in both the design under verification and temporal logic. Recent studies have explored using large language models (LLMs) to automate SVA generation, but existing approaches suffer from incorrect signal references, missing timing constraints, and lack of formal correctness guarantees. This paper presents ProofLoop, a tool-augmented ReAct agent that generates SVA from natural-language specifications using a solver-in-the-loop approach. The agent operates in two phases: Phase A autonomously gathers design context by invoking EDA and formal tools, including semantic search over an AST-indexed vector database and JasperGold structural queries, while Phase B generates SVA and iteratively refines it using JasperGold formal proof feedback over up to fixed (here 3) verification rounds. We evaluate ProofLoop on FVEval Design2SVA design benchmarks and demonstrate that this framework can achieve 93.7% syntax correctness and 82.0% functional correctness. An ablation study confirms that each component, i.e., retrieval-augmented generation (RAG), JasperGold tools, and the verification loop contributes significantly (and orthogonally). |
| title | From Language to Logic: Bridging LLMs & Formal Representations for RTL Assertion Generation |
| topic | Cryptography and Security Hardware Architecture Logic in Computer Science |
| url | https://arxiv.org/abs/2604.23100 |