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English(EN) Graph Construction and Matching for Imperative Programs using Neural and Structural Methods

研究人员开发使用神经方法为命令式程序构建图

作者 PulseAugur 编辑部 · [3 个来源] ·

研究人员开发了一个管道，将命令式程序及其注解转换为类型化、属性化的图。该过程结合了抽象语法树解析与来自 SentenceTransformer 和 CodeBERT 等模型的语义嵌入。目标是识别程序之间的结构和语义相似性，以便重用验证工件。使用 C、Java 和 Dafny 进行的实验证明了跨不同语言和注解风格创建一致图表示的能力。 AI

影响 通过改进程序相似性检测，实现软件验证工件更有效的重用。

排序理由 这是一篇描述程序分析新方法的学术论文。

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →

研究人员开发使用神经方法为命令式程序构建图

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报道来源 [3]

  1. arXiv cs.AI TIER_1 English(EN) · Arshad Beg, Diarmuid O'Donoghue, Rosemary Monahan ·

    使用神经和结构化方法为命令式程序构建和匹配图

    arXiv:2604.26578v1 Announce Type: cross Abstract: Reusing verification artefacts requires identifying structural and semantic similarities across programs and their specifications. In this paper, we focus on graph construction as a foundational step toward this goal. We present a…

  2. arXiv cs.AI TIER_1 English(EN) · Rosemary Monahan ·

    使用神经和结构化方法为命令式程序构建和匹配图

    Reusing verification artefacts requires identifying structural and semantic similarities across programs and their specifications. In this paper, we focus on graph construction as a foundational step toward this goal. We present a pipeline that converts imperative programs and th…

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

    使用神经和结构化方法构建和匹配命令式程序图

    Reusing verification artefacts requires identifying structural and semantic similarities across programs and their specifications. In this paper, we focus on graph construction as a foundational step toward this goal. We present a pipeline that converts imperative programs and th…

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