Mining Domain Models in Ethereum DApps using Code Cloning

TL;DR

This paper investigates using code clone detection to analyze smart contracts on Ethereum, aiming to identify domain-specific patterns and models by clustering similar code fragments and understanding their semantics.

Contribution

It introduces a method leveraging near-miss clone detection to characterize domain models in Ethereum smart contracts, revealing structural patterns and semantic clusters.

Findings

Detected clusters of similar smart contract functions

Categorized code clones into semantic groups

Discovered structural models of code patterns

Abstract

This research study explores the use of near-miss clone detection to support the characterization of domain models of smart contracts for each of the popular domains in which smart contracts are being rapidly adopted. In this paper, we leverage the code clone detection techniques to detect similarities in functions of the smart contracts deployed onto the Ethereum blockchain network. We analyze the clusters of code clones and the semantics of the code fragments in the clusters in an attempt to categorize them and discover the structural models of the patterns in code clones.