LLM-Based Generation of Solidity Smart Contracts from System Requirements in Natural Language: The AstraKode Case

Abstract

As blockchain technology continues to evolve, the need for accessible solutions for developing smart contracts has grown, especially for non-technical users. This paper addresses practitioners' challenges in generating Solidity smart contracts from natural language requirements within the AstraKode Blockchain no-code platform (AKB). Our goal is to lower the barrier of entry into smart contract development, making it more accessible to users with limited technical expertise. We propose three methods, i.e., Naive Generation, Augmented Generation, and Enhanced Generation, each utilizing large language models to streamline the code generation process. These methods cater to different user needs, from rapid prototyping to handling complex business scenarios, improving accessibility and usability within AKB. We demonstrate their practical relevance, potential, and limitations in addressing real-world challenges in smart contract development through empirical evaluations and practitioner feedback. Thanks to collaboration with academia and effective knowledge transfer, these methods provide innovative solutions to the challenges of smart contract generation. Furthermore, they have been integrated into AKB to enhance user services, ultimately promoting the development and deployment of secure and efficient smart contracts in the industry.