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Efficacy of Various Large Language Models in Generating Smart Contracts
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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.
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Guiding LLM-based Smart Contract Generation with Finite State Machine
A finite-state-machine intermediate representation, fine-tuning, and compilation and security feedback improve LLM-generated smart contract compilation rates and lower vulnerability scores on a synthetic benchmark.
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