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English(EN) From Resource Flow to Executable Tests: Petri-Net-Guided LLM Test Generation for Concurrent Stateful Rust APIs

Petri网引导LLM生成并发Rust API测试

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种新方法，利用大型语言模型（LLM）为并发有状态Rust API生成可执行测试。该方法使用Petri网引导LLM进行测试合成，Petri网代表API资源、生命周期条件和依赖关系。通过为代码合成提供受限的中间表示，基于Petri网引导的方法旨在克服当前LLM测试生成中的局限性，例如违反API先决条件或过度简化并发。该技术还包含一个局部忠实契约和一个结构修复循环，以在测试创建过程中保持预期行为。 AI

影响 增强了LLM在为软件API生成复杂并发测试方面的能力，有望提高软件质量和开发效率。

排序理由 该集群描述了一篇详细介绍LLM测试生成新方法的学术论文。

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

Petri网引导LLM生成并发Rust API测试

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该集群描述了一篇详细介绍LLM测试生成新方法的学术论文。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Kaiwen Zhang, Guanjun Liu ·

    从资源流到可执行测试：基于Petri网引导的并发有状态Rust API的LLM测试生成

    arXiv:2607.21530v1 Announce Type: cross Abstract: Concurrent stateful library APIs expose behavior through evolving resource ownership, lifecycle states, and competing interleavings. Large language models can synthesize executable Rust tests, but their outputs often violate API p…

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

    从资源流到可执行测试：基于Petri网引导的并发状态Rust API的LLM测试生成

    Concurrent stateful library APIs expose behavior through evolving resource ownership, lifecycle states, and competing interleavings. Large language models can synthesize executable Rust tests, but their outputs often violate API preconditions, remain shallow, or reduce concurrenc…

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