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English(EN) When Does the Dependency Graph Help Code-to-Architecture Mapping?

图神经网络改进代码到架构的映射

研究人员开发了一种半监督节点分类方法,用于将代码映射到架构模块,以解决架构技术债务问题。该方法利用有向多关系依赖图,其中文件作为节点,依赖关系作为边。实验表明,图卷积网络(GCN)和图注意力网络(GAT)在Google Chrome等大型代码库上,其性能显著优于多层感知器(MLP)和朴素贝叶斯分类器,其中GAT取得了最高的F1分数。 AI

影响 这项研究为理解和管理软件架构提供了改进的方法,可能有助于大型项目中的开发人员。

排序理由 学术论文,详细介绍了使用图神经网络进行代码到架构映射的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

图神经网络改进代码到架构的映射

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学术论文,详细介绍了使用图神经网络进行代码到架构映射的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Rakhshanda Jabeen, Morgan Ericsson, Jonas Nordqvist, Anna Wingkvist ·

    依赖图何时有助于代码到架构的映射?

    arXiv:2610.19769v1 Announce Type: cross Abstract: Architectural technical debt arises when a system's implementation drifts from its inten ded modular decomposition, while the mapping between source files and architectural modu les is missing, incomplete, or costly to maintain ma…