Micro-Patterns in Solidity Code

TL;DR

This paper identifies and analyzes 18 micro-patterns in Solidity smart contracts, revealing their widespread adoption and platform-specific variations, to improve understanding and analysis of blockchain code.

Contribution

It introduces a set of Solidity-specific micro-patterns and demonstrates their prevalence and significance across multiple blockchain platforms.

Findings

99% of contracts implement at least one micro-pattern

Average of 2.76 patterns per contract

Storage Saver pattern has 84.62% adoption

Abstract

Solidity is the predominant programming language for blockchain-based smart contracts, and its characteristics pose significant challenges for code analysis and maintenance. Traditional software analysis approaches, while effective for conventional programming languages, often fail to address Solidity-specific features such as gas optimization and security constraints. This paper introduces micro-patterns - recurring, small-scale design structures that capture key behavioral and structural peculiarities specific to a language - for Solidity language and demonstrates their value in understanding smart contract development practices. We identified 18 distinct micro-patterns organized in five categories (Security, Functional, Optimization, Interaction, and Feedback), detailing their characteristics to enable automated detection. To validate this proposal, we analyzed a dataset of 23258 smart contracts from five popular blockchains (Ethereum, Polygon, Arbitrum, Fantom and Optimism). Our analysis reveals widespread adoption of micro-patterns, with 99% of contracts implementing at least one pattern and an average of 2.76 patterns per contract. The Storage Saver pattern showed the highest adoption (84.62% mean coverage), while security patterns demonstrated platform-specific adoption rates. Statistical analysis revealed significant platform-specific differences in pattern adoption, particularly in Borrower, Implementer, and Storage Optimization patterns.