RAGas: Retrieval-Augmented Gas Optimization for Smart Contracts with Continuous Knowledge Integration

2026-08-16

AI Summary

This study addresses the high gas costs and lack of continuous optimization mechanisms in Ethereum smart contracts by proposing an automated repair framework based on Retrieval-Augmented Generation (RAG). The research systematically categorizes twelve fine-grained gas anti-patterns to construct a specialized knowledge base and innovatively integrates a continuous knowledge integration mechanism with a three-stage RAG architecture. By combining syntactic and semantic analysis, the framework enables precise localization and remediation of inefficient code. Experimental results demonstrate that this approach significantly improves detection precision and recall while reducing gas consumption by up to 11%. Consequently, the proposed method effectively lowers contract deployment costs and provides a systematic solution for optimizing smart contract performance.

Abstract

Ethereum is now integral to mission-critical sectors, including finance, healthcare, and supply chain management. Execution fees, commonly referred to as Gas, scale with the computational complexity of their functions. Smart contracts on Ethereum incur execution fees, known as Gas, which increase with computational complexity. Thus, optimizing Gas-intensive code while preserving functional equivalence significantly lowers deployment costs. No existing system continuously exploits evolving Gas usage patterns. We systematically analyze syntactic and semantic constructs that drive excessive Gas use. This yields six high-level categories covering twelve fine-grained antipatterns underpinning a curated knowledge base. We operationalize these insights with RAGas, a three-stage retrieval-augmented generation framework that uses a large language model to pinpoint and automatically fix Gas inefficiencies. Experiments on deployed contracts demonstrate that RAGas reduces Gas usage by up to 11% and achieves high precision and recall in detecting code snippets exhibiting Gas wastage.

Problem

• Smart Contracts
• Gas Optimization
• Ethereum
• Code Inefficiency

Innovation

• Retrieval-Augmented Generation
• Gas Optimization
• Smart Contracts
• Continuous Knowledge Integration
• Anti-pattern Detection