资源

指南、基准测试和发布资产。

了解确定性代码库理解如何改变自主代码修复。

资源

基准测试报告

Codna 与领先编码智能体对比的方法论和各场景结果。

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01

自主代码修复

为什么智能体在修复前需要确定性地图。

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02

AI 代码审查

影响范围和回归风险如何加速 PR 审查。

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03

Sentry 到 PR

将生产故障转化为聚焦的修复 Pull Request。

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Frequently asked

Codna was tested head-to-head against Cursor. It used 5× fewer tokens and ran 1.7× faster, with every fix test-verified.

Token consumption, wall-clock speed, and verified fix rate across 8 real bug-fix scenarios run against OpenAI Codex CLI and Google Gemini CLI. Every fix counted only when your own tests passed.

A deterministic engine maps the repository in roughly 60ms without any LLM calls. It then hands the AI agent an evidence bundle of around 600 tokens — measured 162x smaller than reading the full repo — so the agent fixes the right code immediately.

Yes — Codna supports 250+ languages, and the engine mapped 130 repositories in 9.2 seconds, consuming zero tokens for the mapping step.

Codna locates the affected code using its dependency and blast-radius graph, generates a fix from the evidence bundle, then runs your tests to verify the result. On GitHub, it opens a pull request with the verified fix.

You can self-host the engine, bring your own API key, and configure fail-closed egress. Codna never trains on your code.