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L. de la Torre

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#reinforcement learning Review Open access Sep 2026

A Systematic Survey of Smart Contract Fuzzing: Methods, Techniques, and Architectures for Ethereum and Beyond

A conceptual taxonomy establishing an explicit correspondence between classical and smart contract fuzzing is developed and an architectural taxonomy of representative fuzzers unified under a generalised waypoint architecture is presented that exposes key feedback domains and composition gaps.

Luis Alberto López Alvar, L. de la Torre, Ze-Hua Wang et al. · 0 citations

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