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English(EN) Can LLMs Extract Architectural Design Decisions from Source Code Commits? - A Preliminary Exploratory Study

大型语言模型在从代码提交中提取软件设计决策方面显示出潜力

一项初步研究探讨了四种大型语言模型(LLM)从源代码提交中提取架构设计决策(ADDs)的能力。使用零样本和少样本提示,在30个ADDs上测试了包括Gemini 3-Pro、DeepSeek-R1、Kimi K2和Qwen3在内的模型。虽然所有模型的BERT-F1分数均高于0.81,但生成的决策通常过长、侧重于实现,并且缺乏根本原因,这表明需要更具架构意识的大型语言模型系统。 AI

影响 强调了对架构意识大型语言模型系统和自动化架构知识管理的机遇。

排序理由 该集群是关于一篇学术论文,该论文提出了关于大型语言模型在特定任务能力的研究。

在 Hugging Face Daily Papers 阅读 →

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大型语言模型在从代码提交中提取软件设计决策方面显示出潜力

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该集群是关于一篇学术论文,该论文提出了关于大型语言模型在特定任务能力的研究。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Amey Karan, Rudra Dhar, Mohamed Soliman, Karthik Vaidhyanathan ·

    大型语言模型能否从源代码提交中提取建筑设计决策?——一项初步探索性研究

    arXiv:2609.03721v1 Announce Type: cross Abstract: Context: Architectural Design Decisions (ADDs) capture the rationale behind the structure and evolution of software systems but are rarely documented explicitly, and are often hidden inside source code commits. Recovering them is …

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    大型语言模型能否从源代码提交中提取建筑设计决策?——一项初步探索性研究

    Context: Architectural Design Decisions (ADDs) capture the rationale behind the structure and evolution of software systems but are rarely documented explicitly, and are often hidden inside source code commits. Recovering them is important for Architectural Knowledge Management (…