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Smart contract (SC) metrics differ from traditional software metrics due to blockchain constraints. Analysis of 85K Solidity SCs on Ethereum shows SC metrics have more restricted ranges than traditional software metrics.

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Area of Science:

  • Computer Science
  • Software Engineering
  • Blockchain Technology

Background:

  • Smart contracts (SC) are software programs executed on blockchains, automating traditional contract conditions.
  • SC development faces unique constraints related to size, computational resources, and inter-program interaction due to blockchain deployment.

Purpose of the Study:

  • To investigate if smart contract-specific constraints necessitate distinct software metrics compared to traditional software.
  • To analyze the statistical properties of software metrics for smart contracts.

Main Methods:

  • Analysis of 85,000+ smart contracts written in Solidity from Ethereum repositories (Etherscan, Smart Corpus).
  • Computation and statistical comparison of software metrics for smart contracts against traditional software projects.

Main Results:

  • Smart contract metrics generally exhibit more restricted ranges than those found in traditional software systems.
  • While some traditional software distribution patterns (e.g., power law) are only approximate for SCs, lines of code follow a log-normal distribution, similar to traditional software.

Conclusions:

  • Smart contract software metrics are influenced by blockchain-specific constraints, suggesting the need for tailored metrics.
  • The study provides empirical evidence supporting the hypothesis that smart contract metrics differ from traditional software metrics.