@blytheory

Cost-efficient fuzzing strategies optimize smart contract security testing by prioritizing high-risk code paths. Genetic algorithms mutate input data to explore edge cases, reducing redundant tests. Coverage-guided fuzzing, like Echidna, focuses on unexecuted contract branches, improving vulnerability discovery rates by 40%. Hybrid approaches combine symbolic execution (for precise path analysis) with random testing (for broad coverage). However, fuzzing gas-intensive contracts remains expensive. Cloud-based fuzzing services distribute computational costs, while incremental fuzzing reuses prior test cases, cutting expenses. Automated triage systems prioritize critical bugs, ensuring developers address threats before deployment.

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