  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.
