SCEditor-Web: Bridging Model-Driven Engineering and Generative AI for Smart Contract Development

Smart contracts are central to blockchain ecosystems, yet their development remains technically demanding, error-prone, and tied to platform-specific programming languages. This paper introduces SCEditor-Web, a web-based modeling environment that combines model-driven engineering (MDE) with generative artificial intelligence (Gen-AI) to simplify contract design and code generation. Developers specify the structural and behavioral aspects of smart contracts through a domain-specific visual language grounded in a formal metamodel. The resulting contract model is exported as structured JSON and transformed into executable, platform-specific code using large language models (LLMs) guided by a tailored prompt engineering process. A prototype implementation was evaluated on Solidity contracts as a proof of concept, using representative use cases. Experiments with state-of-the-art LLMs assessed the generated contracts for compilability, semantic alignment with the contract model, and overall code quality. Results indicate that the visual-to-code workflow reduces manual effort, mitigates common programming errors, and supports developers with varying levels of expertise. The contributions include an abstract smart contract metamodel, a structured prompt generation pipeline, and a web-based platform that bridges high-level modeling with practical multi-language code synthesis. Together, these elements advance the integration of MDE and LLMs, demonstrating a step toward more accessible and reliable smart contract engineering.

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Published
2025-10-07
DOI
https://doi.org/10.3390/info16100870
Citations
1
Primary Topic
FinTech, Crowdfunding, Digital Finance
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article
Field-Weighted Citation Impact
2.28
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article

SCEditor-Web: Bridging Model-Driven Engineering and Generative AI for Smart Contract Development

Naziha Laaz, Samir Mbarki, Yassine Ait Hsain
1 citations
Information
FinTech, Crowdfunding, Digital Finance
2.28
article

SCEditor-Web: Bridging Model-Driven Engineering and Generative AI for Smart Contract Development

Naziha Laaz, Samir Mbarki, Yassine Ait Hsain
article en
1 citations

Abstract

Smart contracts are central to blockchain ecosystems, yet their development remains technically demanding, error-prone, and tied to platform-specific programming languages. This paper introduces SCEditor-Web, a web-based modeling environment that combines model-driven engineering (MDE) with generative artificial intelligence (Gen-AI) to simplify contract design and code generation. Developers specify the structural and behavioral aspects of smart contracts through a domain-specific visual language grounded in a formal metamodel. The resulting contract model is exported as structured JSON and transformed into executable, platform-specific code using large language models (LLMs) guided by a tailored prompt engineering process. A prototype implementation was evaluated on Solidity contracts as a proof of concept, using representative use cases. Experiments with state-of-the-art LLMs assessed the generated contracts for compilability, semantic alignment with the contract model, and overall code quality. Results indicate that the visual-to-code workflow reduces manual effort, mitigates common programming errors, and supports developers with varying levels of expertise. The contributions include an abstract smart contract metamodel, a structured prompt generation pipeline, and a web-based platform that bridges high-level modeling with practical multi-language code synthesis. Together, these elements advance the integration of MDE and LLMs, demonstrating a step toward more accessible and reliable smart contract engineering.

InformationVol. 16(10)
Université Ibn-Tofail (MA), Hassania School of Public Works (MA)
Openalex Percentile: Top 9%
FinTech, Crowdfunding, Digital Finance
2.28
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