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English(EN) STAB: Specification-driven Testing for Algorithmic Bottlenecks

新流水线STAB生成测试用例以暴露算法瓶颈

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了STAB，这是一个新的流水线，旨在自动生成测试用例，以暴露代码中的算法瓶颈。STAB通过分析自然语言问题规范来识别约束和对抗性输入结构。这种方法显著提高了测试用例揭示性能问题的比率，将开源LLM的效率从50.43%提高到73.45%，将闭源LLM的效率从57.45%提高到71.85%。该方法在Python、Java和C++编程语言中都显示出了一致的收益。 AI

影响 自动化代码中性能瓶颈的识别，提高软件开发效率。

排序理由 该集群包含一篇研究论文，详细介绍了一种用于测试算法代码的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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

新流水线STAB生成测试用例以暴露算法瓶颈

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该集群包含一篇研究论文，详细介绍了一种用于测试算法代码的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Soohan Lim, Joonghyuk Hahn, Hyundong Jin, Yo-Sub Han ·

    STAB：算法瓶颈的面向规范的测试

    arXiv:2605.27981v1 Announce Type: new Abstract: Evaluating the efficiency of algorithmic code requires test cases that expose runtime bottlenecks. Previous methods generate efficiency test cases either by increasing input size or by generating code-specific inputs that make the g…

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