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AI agents now optimize software with machine-checked proofs

研究人员开发了一种名为 agentic verified optimization 的方法,该方法使用 AI 代理来提高软件性能,同时通过机器检查的证明确保功能等价性。该方法利用现有代码作为规范,无需手动编写规范。该框架名为 Aqueduct,将 C++、Go 和 Rust 等语言的程序转换为 Lean 4 进行执行和推理,然后使用代理生成具有正确性证明的优化版本。对基准实现和实际应用程序的测试表明速度显著提高,尽管应用程序级别的收益小于函数级别的收益,这凸显了选择要优化哪些函数的重要性。 AI

影响 这种方法可以通过保证正确性的自动化性能优化来显著提高软件开发效率和可靠性。

排序理由 学术论文,详细介绍了使用 AI 代理和形式化验证进行软件优化的新方法。[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 →

AI agents now optimize software with machine-checked proofs

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学术论文,详细介绍了使用 AI 代理和形式化验证进行软件优化的新方法。[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) · Zhe Ye, Udaya Ghai, Zhizhen Qin, Dawn Song, Soonho Kong ·

    Agentic Verified Optimization of Real-World Software

    arXiv:2610.30188v1 Announce Type: cross Abstract: Program optimization aims to improve performance while preserving behavior. Coding agents can already make programs faster by changing algorithms, data structures, and execution strategies. However, existing equivalence checks mos…