大模型在嵌入式软件开发中的应用

Applications of Large Language Models in Embedded Software Development

摘要: 嵌入式软件与硬件和领域知识高度相关，开发难度大，开发周期长。以Transformer架构为核心的大语言模型(LLMs)凭借强大的代码理解与生成能力，为提升嵌入式软件开发效率提供了可能。文章介绍大语言模型在嵌入式软件开发中的应用现状，包括应用过程、方法和常用的大语言模型及其技术特性，并重点梳理大模型在嵌入式软件开发中的应用场景，以及嵌入式软件代码缺陷检测的核心技术路径、场景适配方案。文章通过综述现有研究成果，为嵌入式软件研究和开发人员应用大模型提供参考，助力嵌入式软件开发方法的智能化转型。

Abstract: Embedded software is highly correlated with hardware and domain knowledge, featuring high development difficulty and long development cycles. Large Language Models (LLMs) centered on the Transformer architecture, with their robust capabilities in code understanding and generation, have made it possible to improve the efficiency of embedded software development. This paper introduces the current application status of large language models in embedded software development, including the application processes, methods, commonly used large language models and their technical characteristics. It also focuses on sorting out the application scenarios of large models in embedded software development, as well as the core technical approaches and scenario adaptation schemes for code defect detection in embedded software. Through a review of existing research findings, this paper provides a reference for embedded software researchers and developers in the application of large models, and facilitates the intelligent transformation of embedded software development methodologies.