This research evaluates the readiness of Large Language Models for practical adoption in generating hardware design assertions, a critical component for bug detection and verification.

Key findings:

• LLMs show promising but inconsistent performance in generating hardware assertions
• Models exhibit significant quality variation across different hardware design domains
• Current LLMs struggle with complex verification scenarios despite their potential
• The research identifies specific improvement areas for making LLMs viable for industry adoption

This work matters because effective assertion generation can dramatically accelerate hardware verification workflows, reducing design cycles and improving system reliability in critical electronics applications.

Are LLMs Ready for Practical Adoption for Assertion Generation?