Smart contracts software metrics: A first study

Roberto Tonelli; Giuseppe Antonio Pierro; Marco Ortu; Giuseppe Destefanis

doi:10.1371/journal.pone.0281043

Smart contracts software metrics: A first study

PLoS One. 2023 Apr 12;18(4):e0281043. doi: 10.1371/journal.pone.0281043. eCollection 2023.

Authors

Roberto Tonelli¹, Giuseppe Antonio Pierro¹, Marco Ortu², Giuseppe Destefanis³

Affiliations

¹ Dept. of Computer Science and Mathematics, University Of Cagliari, Cagliari, Italy.
² Dept. of Economics and Business Sciences, University Of Cagliari, Cagliari, Italy.
³ Dept. of Computer Science, Brunel University, Uxbridge, London, United Kingdom.

Abstract

Smart contracts (SC) are software programs that reside and run over a blockchain. The code can be written in different languages with the common purpose of implementing various kinds of transactions onto the hosting blockchain. They are ruled by the blockchain infrastructure with the intent to automatically implement the typical conditions of traditional contracts. Programs must satisfy context-dependent constraints which are quite different from traditional software code. In particular, since the bytecode is uploaded in the hosting blockchain, the size, computational resources, interaction between different parts of the program are all limited. This is true even if the specific programming languages implement more or less the same constructs as that of traditional languages: there is not the same freedom as in normal software development. The working hypothesis used in this article is that Smart Contract specific constraints should be captured by specific software metrics (that may differ from traditional software metrics). We tested this hypothesis on 85K Smart Contracts written in Solidity and uploaded on the Ethereum blockchain. We analyzed Smart Contracts from two repositories "Etherscan" and "Smart Corpus" and we computed the statistics of a set of software metrics related to Smart Contracts and compared them to the metrics extracted from more traditional software projects. Our results show that generally, Smart Contract metrics have more restricted ranges than the corresponding metrics in traditional software systems. Some of the stylized facts, like power law in the tail of the distribution of some metrics, are only approximate but the lines of code follow a log-normal distribution which reminds us of the same behaviour already found in traditional software systems.

Copyright: © 2023 Tonelli et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Blockchain*
Programming Languages
Software

Grants and funding

This study was financially supported by the Italian Ministry of University and Research (MUR) in the form of a grant (MUR 4 - Public research - PRIN 2020 cup F73C22000430001) to R.T. and A.P, and in the form of a grant to M.O (CUP: PE00000018). This work was also financially supported by Fondazione Di Sardegna in the form of a grant (2020/22, F72F20000190007) to R.T. and A.P. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.