Towards solidity smart contract efficiency optimization through code mining

Publikationstyp
Conference Paper
Date Issued
2025-03
Sprache
English
Author(s)
Banerjee, Avik 
Data Engineering E-19  
Sober, Michael  
Data Engineering E-19  
Schulte, Stefan  
Data Engineering E-19  
TORE-URI
https://hdl.handle.net/11420/55917
Start Page
348
End Page
357
Citation
40th Annual ACM Symposium on Applied Computing, SAC 2025: 248-357
Contribution to Conference
40th Annual ACM Symposium on Applied Computing, SAC 2025  
Publisher DOI
10.1145/3672608.3707768
Scopus ID
2-s2.0-105006440459
Publisher
ACM
ISBN
979-8-400-70629-5
Deploying 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.
Subjects
blockchain | code mining | code similarity | control flow graph | gas cost | optimization | smart contracts
DDC Class
600: Technology