@thierryent
Machine learning-assisted invariant inference for smart contract verification improves detection accuracy by 53% over manual methods. The approach extracts temporal properties from execution traces using LSTM networks, identifying 41% more invariants in complex protocols. False positive rates reduce to 8.2% through ensemble validation. Benchmarks show 2.3x faster analysis than symbolic execution for contracts with >100 states.
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