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arXiv 2603.25697cs.SEcs.AI
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厨房循环:用户驱动的自演化代码库开发

The Kitchen Loop: User-Spec-Driven Development for a Self-Evolving Codebase

Yannick Roy

AI总结:

本文提出厨房循环框架,通过统一信任模型实现自主演化软件,包含规范表面、用户模拟、不可战胜测试和漂移控制,验证两个生产系统285+次迭代,产生1,094+合并请求且无回归。

摘要:

代码生产如今已成为一种商品;瓶颈在于知道要构建什么并证明其有效。我们提出了厨房循环框架,这是一个基于统一信任模型的自主自演化软件框架:(1)规范表面,列出产品声称支持的功能;(2)'作为用户x1000',其中LLM代理以合成权力用户身份执行该表面,速度达到人类的1000倍;(3)不可战胜的测试,地面真实验证代码作者无法伪造的验证;(4)漂移控制,持续质量测量带有自动化暂停门。我们验证了两个生产系统超过285次迭代,产生了1,094次合并请求,且未被回归 oracle 检测到回归(方法论见第6.1节)。我们观察到规模化后的涌现特性:多轮自修正链、自主基础设施修复、以及单调改进的质量门。这些原始构件并不新颖;我们的贡献是将它们组合成一个经过生产测试的系统,并具有使长期自主演化安全的操作纪律。

英文摘要:

Code production is now a commodity; the bottleneck is knowing what to build and proving it works. We present the Kitchen Loop, a framework for autonomous, self-evolving software built on a unified trust model: (1) a specification surface enumerating what the product claims to support; (2) 'As a User x 1000', where an LLM agent exercises that surface as a synthetic power user at 1,000x human cadence; (3) Unbeatable Tests, ground-truth verification the code author cannot fake; and (4) Drift Control, continuous quality measurement with automated pause gates. We validate across two production systems over 285+ iterations, producing 1,094+ merged pull requests with zero regressions detected by the regression oracle (methodology in Section 6.1). We observe emergent properties at scale: multi-iteration self-correction chains, autonomous infrastructure healing, and monotonically improving quality gates. The primitives are not new; our contribution is their composition into a production-tested system with the operational discipline that makes long-running autonomous evolution safe.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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