Inferring Needless Write Memory Accesses on Ethereum Bytecode (Extended Version)

TL;DR

This paper introduces a static analysis method for Ethereum bytecode that identifies needless memory write operations, enabling significant cost reductions in smart contract deployment and execution.

Contribution

It presents a novel static analysis technique at the bytecode level to detect and remove needless memory writes in Ethereum smart contracts, improving efficiency.

Findings

Detected about 6,200 needless write accesses in over 19,000 contracts

Identified memory patterns that can be optimized by removing bytecode blocks

Existing tools cannot infer such needless write accesses

Abstract

Efficiency is a fundamental property of any type of program, but it is even more so in the context of the programs executing on the blockchain (known as smart contracts). This is because optimizing smart contracts has direct consequences on reducing the costs of deploying and executing the contracts, as there are fees to pay related to their bytes-size and to their resource consumption (called gas). Optimizing memory usage is considered a challenging problem that, among other things, requires a precise inference of the memory locations being accessed. This is also the case for the Ethereum Virtual Machine (EVM) bytecode generated by the most-widely used compiler, \texttt{solc}, whose rather unconventional and low-level memory usage challenges automated reasoning. This paper presents a static analysis, developed at the level of the EVM bytecode generated by \texttt{solc}, that infers write memory accesses that are needless and thus can be safely removed. The application of our implementation on more than 19,000 real smart contracts has detected about 6,200 needless write accesses in less than 4 hours. Interestingly, many of these writes were involved in memory usage patterns generated by \texttt{solc} that can be greatly optimized by removing entire blocks of bytecodes. To the best of our knowledge, existing optimization tools cannot infer such needless write accesses, and hence cannot detect these inefficiencies that affect both the deployment and the execution costs of Ethereum smart contracts.