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Agentic AI-based Coverage Closure for Formal Verification

arXiv – CS AI|Sivaram Pothireddypalli, Ashish Raman, Deepak Narayan Gadde, Aman Kumar|March 4, 2026 at 05:00 AM|1 views

🤖AI Summary

Researchers have developed an agentic AI-driven workflow using Large Language Models to automate coverage analysis for formal verification in integrated chip development. The approach systematically identifies coverage gaps and generates required formal properties, demonstrating measurable improvements in coverage metrics that correlate with design complexity.

Key Takeaways

→Traditional exhaustive approaches often fail to achieve full coverage within project timelines for IC development.
→The new framework uses LLM-enabled Generative AI to automate coverage analysis and generate formal properties.
→Benchmarking revealed measurable increases in coverage metrics correlated to design complexity.
→The agentic AI approach accelerates verification efficiency by systematically addressing coverage holes.
→Results validate the potential for AI-based techniques to improve formal verification productivity.

#ai #formal-verification #llm #generative-ai #integrated-circuits #automation #coverage-analysis #chip-development

Read Original →via arXiv – CS AI

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