Efficacy of Various Large Language Models in Generating Smart Contracts
This addresses the problem of automating secure smart contract creation for blockchain developers, but it is incremental as it builds on prior AI code generation work.
The study evaluated large language models for generating secure Solidity smart contracts on Ethereum, finding they struggled with security details but succeeded in common contracts, with results showing specific performance metrics.
This study analyzes the application of code-generating Large Language Models in the creation of immutable Solidity smart contracts on the Ethereum Blockchain. Other works have previously analyzed Artificial Intelligence code generation abilities. This paper aims to expand this to a larger scope to include programs where security and efficiency are of utmost priority such as smart contracts. The hypothesis leading into the study was that LLMs in general would have difficulty in rigorously implementing security details in the code, which was shown through our results, but surprisingly generally succeeded in many common types of contracts. We also discovered a novel way of generating smart contracts through new prompting strategies.