# FangWW/Document

📘  各种编程学习资料 (Android C C++ DataBase HTML5 JavaWeb ios python uml 人工智能 操作系统 数学 数据结构 程序员需要的技术 程序设计 编译原理 计算机组成与结构 计算机网络 设计模式 软件工程 面试经验)

Repository: https://github.com/FangWW/Document
Canonical: https://ross.abutalabs.com/products/document
Language: Java
License Family: other
Last push: 2020-12-10T15:08:57+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3244, "days_push": 2092, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2507, forks 570 (observed 2026-08-28T04:06:57.225331+00:00)

## What it is
A curated collection of programming learning materials covering Android, C/C++, Java, Python, databases, algorithms, operating systems, networking, and interview preparation, mostly as Chinese-language documents. It is a repository of downloadable study files rather than runnable software.

## Use cases
- find computer science study materials
- prepare for programming job interviews
- learn android development basics
- review data structures and algorithms notes
- study operating systems and computer networks
- find chinese-language programming tutorials

## When to choose
- you want a broad archive of Chinese programming study documents and interview question banks
- you are a student reviewing CS fundamentals like OS, networking, and data structures

## When to avoid
- you need runnable code, libraries, or tools
- you need up-to-date or English-language materials
- you require a maintained resource with a license

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation
- domain: education, tutorials, developer-tools
- platform: cross-platform
- tags: study-materials, interview-preparation, computer-science, chinese-language, ebooks

## Member repositories
- FangWW/Document (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:57.225331+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:26:32.973104+00:00, confidence not recorded.
  - readme: https://github.com/FangWW/Document (fetched 2026-08-28T04:06:57.225331+00:00, sha 911af5797fea)
- Data as of 2026-08-30T08:39:29.467469+00:00.