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.
Paper Type
Poster
DOI
10.62036/ISD.2024.66
Improving Smart Contract Code with LLMs
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.
Recommended Citation
Klimek, R. (2024). Improving Smart Contract Code with LLMs. In B. Marcinkowski, A. Przybylek, A. Jarzębowicz, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Harnessing Opportunities: Reshaping ISD in the post-COVID-19 and Generative AI Era (ISD2024 Proceedings). Gdańsk, Poland: University of Gdańsk. ISBN: 978-83-972632-0-8. https://doi.org/10.62036/ISD.2024.66