How Do You Quantify Gas-Optimization Success in Blockchain QA Interviews?
Gas optimization feels like dark art. Developers claim they “saved 10 gas,” but as QA I never know if that’s meaningful. During a Layer-2 bridge audit, I saw a patch that reduced storage reads but slightly increased calldata.
It passed the profiler, but I couldn’t explain the trade-off clearly. In blockchain QA interviews, how do you quantify optimization beyond screenshots of Foundry traces? Are there accepted benchmarks that prove an improvement is real, not just noise?
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