HAVEN combines LLM agents for planning and gap analysis with protocol-specific templates and a custom DSL to generate correct UVM testbenches, achieving 100% compilation success, 90.6% code coverage, and 87.9% functional coverage on 19 open-source designs across three protocols.
Llm4cov: Execution-aware agentic learning for high-coverage testbench genera- tion
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HAVEN: Hybrid Automated Verification ENgine for UVM Testbench Synthesis with LLMs
HAVEN combines LLM agents for planning and gap analysis with protocol-specific templates and a custom DSL to generate correct UVM testbenches, achieving 100% compilation success, 90.6% code coverage, and 87.9% functional coverage on 19 open-source designs across three protocols.