Banerjee, AvikAvikBanerjeeSober, MichaelMichaelSoberSchulte, StefanStefanSchulte2025-06-202025-06-202025-0340th Annual ACM Symposium on Applied Computing, SAC 2025: 248-357979-8-400-70629-5https://hdl.handle.net/11420/55917Deploying smart contracts and invoking their functions on block-chains incur gas costs, which depend on the operations executed by those functions. This makes optimizing the gas cost of smart contract functions a rewarding goal. However, existing approaches to gas cost optimization of smart contracts mainly involve rule-based optimization or automatic optimization for specific types of patterns. In this paper, we discuss a novel approach to automatically retrieving optimized versions of Solidity functions from a repository of smart contracts. The system identifies and suggests gas-efficient alternatives that maintain functional equivalence by comparing the opcode sequences of individual functions. We evaluate this approach on a dataset of 16,529 functions from real-world contracts, demonstrating substantial gas savings, as high as 34% on average when considering the most similar functions.enblockchain | code mining | code similarity | control flow graph | gas cost | optimization | smart contractsTechnology::600: TechnologyConference Paper10.1145/3672608.3707768Conference Paper