Improving Smart Contract Code with LLMs

Abstract

Smart contracts are pivotal in blockchain systems, yet ensuring their reliability and security remains challenging due to coding complexities and potential vulnerabilities. This paper explores the use of Large Language Models (LLMs) in enhancing the smart contract code quality. As part of leveraging extensive training data and language understanding, we experiment with different approaches. LLMs aid developers by offering automated code suggestions, identifying vulnerabilities and promoting best practices. Through experimentation, we demonstrate how integrating LLM-based approaches improves code quality and reliability in blockchain applications.