Comparative Analysis of Smart Contract Generation Using Large Language Models

Abstract

In recent years, blockchain technology has established itself as an effective, secure, and transparent data storage solution. In this context, smart contracts play a fundamental role by enabling the automated execution of agreements without intermediaries. With the advancement of language models, the opportunity to automatically generate these contracts has emerged, raising concerns about their reliability and potential vulnerabilities. This article proposes a comparative analysis of the available language models for developing smart contracts using Ethereum Virtual Machine’s contracts as a case study. Experiments were made using various Large language models using different metrics to evaluate the susceptibility to vulnerabilities and computational cost. After comparing various models, ChatGPT appears to be the most suitable for generating smart contracts due to its higher compilation rate and, consequently, a larger sample size, despite detecting more vulnerabilities.