用生成式AI自动构建领域模型JSON，提升软件设计效率。
Leveraging Generative AI for Enhancing Domain-Driven Software Design
- 用代码大模型生成符合领域需求的JSON结构。
- 4位量化+LoRA微调，在消费级显卡上表现优异。
- 适合希望提速领域建模的开发团队使用。
领域驱动设计（DDD）是面向客户软件开发的关键框架，强调对应用领域的精准建模。传统上，领域元模型由系统设计师手动创建，作为迭代开发的基础。本文探索利用生成式AI部分自动化元模型生成，特别是生成特定领域的JSON对象。通过在真实DDD项目数据上训练模型，我们证明生成式AI可根据简单提示生成语法正确的JSON对象，显著提升设计效率。为应对资源限制，模型在消费级GPU上使用4位量化Code Llama与低秩适配（LoRA）进行微调，尽管硬件受限，仍实现高精度输出，几乎无需后处理。研究验证了生成式AI融入DDD流程的可行性，提升了效率并降低资源需求，为未来AI驱动的软件开发奠定基础。
原文摘要 · Abstract (English)
Domain-Driven Design (DDD) is a key framework for developing customer-oriented software, focusing on the precise modeling of an application's domain. Traditionally, metamodels that describe these domains are created manually by system designers, forming the basis for iterative software development. This paper explores the partial automation of metamodel generation using generative AI, particularly for producing domain-specific JSON objects. By training a model on real-world DDD project data, we demonstrate that generative AI can produce syntactically correct JSON objects based on simple prompts, offering significant potential for streamlining the design process. To address resource constraints, the AI model was fine-tuned on a consumer-grade GPU using a 4-bit quantized version of Code Llama and Low-Rank Adaptation (LoRA). Despite limited hardware, the model achieved high performance, generating accurate JSON objects with minimal post-processing. This research illustrates the viability of incorporating generative AI into the DDD process, improving efficiency and reducing resource requirements, while also laying the groundwork for further advancements in AI-driven software development.
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