RL-based test generation found corner-case bugs that 18 months of manual testing missed
Two consecutive respins on their flagship 5G RF module had cost $22M and put them 9 months behind schedule. The VP of Engineering told the CEO: 'Our verification methodology is broken.' They needed a fundamentally different approach — not more of the same.
Verification consumed 65% of their chip development cycle. Engineers had written 14,000+ test cases, but coverage analysis showed persistent gaps in corner-case scenarios. The combinatorial explosion of states in their mixed-signal designs made exhaustive testing impossible. Meanwhile, their main competitor had just taped out a competing product.
We deployed reinforcement learning agents that systematically explore the RTL design state space, targeting uncovered paths and corner cases that directed tests miss. A coverage prediction model identifies the highest-risk areas based on design complexity and change history. Our overnight verification team in Vietnam runs extended simulation campaigns, reviews AI-generated results, and delivers prioritized coverage reports before the Irvine team's morning standup.
The AI found a race condition in our power management logic that would have bricked 100,000 units in the field. That single bug justify the entire investment ten times over.— Director of ASIC Verification
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