Dataset: 2026-10-27-catalog-ai-v2
Ruleset: b2e8889c66f7
Scanned: 2026-10-27
Window: February–September 15, 2026

Catalog tracking observation. This repository is measured with the same fixed window and ruleset, but it is not part of the published benchmark or its aggregate claims.

涵盖了 Spring 框架的核心概念和关键功能，包括控制反转（IOC）容器的使用，面向切面编程（AOP）的原理与实践，事务管理的方式与实现，Spring MVC 的流程与控制器工作机制，以及 Spring 中数据访问、安全、Boot 自动配置等方面的深入研究。此外，它还包含了 Spring 事件机制的应用、高级主题如缓存抽象和响应式编程，以及对 Spring 源码的编程风格与设计模式的深入探讨。

01Result

xuchengsheng/spring-reading ↗

xuchengsheng/spring-reading AI coding statistics: 0%

of 0 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate

Too little recent activity to publish. Only 0 commits landed in this window, so the percentage is noisy. Repositories below 100 are excluded from the index for this reason.

No signed agent commits found

No agent signatures were found in the last 0 considered commits. That is a real result, not a failure to measure.

It does not mean no AI was used here. A developer can use an agent and commit by hand without leaving a detectable git signature.

agent commits

other considered commits

—

agent contributors

—

largest contributor

02Drivers

What shapes this result

Mode, timing, and detected signatures show whether the result reflects broad adoption or one concentrated workflow.

No agent signatures were detected, so there are no agent, mode, or timing drivers to break down.

03Evidence

Inspect the matches

Public commit samples let you inspect the signatures behind the aggregate result.

No matched commit samples are available for this observation.

04Method

What entered the denominator

The result begins with commit history, removes merges and routine automation, and reports literal agent signatures as a lower bound.

Exclusion ledger

Commits in window	0
Merge commits removed	−0
CI / dependency bots removed	−0
Considered	0

Bots are excluded from the denominator entirely. Agent attribution requires a literal supported signature; no code-style inference is used.

Continue exploring

Java AI coding statisticsCompare evidence across Java repositories →GitHub AI commit analyzerInspect another repository with the same evidence model →

Reproduce this observation

Run the same detector locally.

Deterministic signature matching; no code-style inference. Squash merges can remove trailers, so this result remains a measured floor.

npx qmmit-cli xuchengsheng/spring-reading

Scan another repository

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