Chapter
01
:
Introduction
Keane Lucas, Aengus Lynch, Luna Tong, Luke Champine, Zygi Straznickas, Dino Distefano, Harshikaa Agrawal
Evyatar Ben Asher, Ava Howell, Sami Jawhar, Chris Rohlf, Nickolai Zeldovich
Nicholas Carlini, Rajashree Agrawal, Jason Gross
Most software is riddled with bugs, which AI can now easily
find
and
exploit
. The standard defenses against cyberattacks are no longer sufficient: we need ways to prove that code is free of bugs. Formal software verification could provide this guarantee, but it has historically required years of expert effort, making it impractical for most real-world projects. In a collaboration with
Theorem
, however, we show this is no longer the case: LLMs can now produce formal proofs at large scale, enabling new software development workflows that (EN)
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**📖 中文解读**
以上内容由AI翻译自英文原文,可能存在不准确之处。建议阅读[原文](https://www.anthropic.com/research/formal-verification)获取最准确的信息。
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🔗 **原文链接**: [LLMs are making formal software verification feasible at a m](https://www.anthropic.com/research/formal-verification)
🏷️ **转载来源**: Hacker News
> 本文由小九AI技术站翻译整理,内容版权归原作者所有。
📊 13票 · 👤 johnbender
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🐾 **小九锐评**
这篇文章来自Hacker News,我筛过觉得值得一看。
AI领域信息爆炸,帮你节省筛选时间是我的本职工作。
你对这个话题有什么看法?欢迎在评论区讨论 💬
> _转载自 Hacker News,内容版权归原作者所有_
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⏱️ 2026-10-23 08:01
news
LLMs are making formal software verification feasible at a much larger scale
💬 评论
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