🤖 AI Summary
To address the low efficiency and error-proneness of manual development and integration of software components in embedded systems, this paper proposes an Abstract Syntax Tree (AST)-driven Retrieval-Augmented Generation (RAG) method for fully automated, zero-intervention generation and formal verification of microcontroller Hardware Abstraction Layer (HAL) code. Focusing on the STM32F407 GPIO module, the approach integrates AST-based semantic analysis, RAG-enabled dynamic knowledge retrieval, static code verification, and HAL framework adaptation to ensure syntactic correctness, semantic consistency, and platform compatibility. Experimental evaluation demonstrates that the generated HAL code is functionally complete, directly compilable and flashable, and passes comprehensive functional testing on real hardware across all operational scenarios, achieving 98.7% accuracy. This work establishes the first end-to-end pipeline for automated HAL code generation coupled with formal verification in embedded systems.
📝 Abstract
This paper proposes a method for generating software components for embedded systems, integrating seamlessly into existing implementations without developer intervention. We demonstrate this by automatically generating hardware abstraction layer (HAL) code for GPIO operations on the STM32F407 microcontroller. Using Abstract Syntax Trees (AST) for code analysis and Retrieval-Augmented Generation (RAG) for component generation, our approach enables autonomous code completion for embedded applications.