# doocs/coding-interview

😀 代码面试题集，包括剑指 Offer、编程之美等

Repository: https://github.com/doocs/coding-interview
Canonical: https://ross.abutalabs.com/products/coding-interview
Homepage: https://interview.doocs.org
Language: Java
License: CC-BY-SA-4.0
License Family: other
Topics: coding-interviews, algorithms, offer, notes, doocs
Last push: 2026-08-24T12:46:52+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 2868, "days_push": 9, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2353, forks 544 (observed 2026-08-28T04:06:40.462579+00:00)

## What it is
A curated collection of notes and solutions for classic coding interview questions and technical books, including 'Coding Interviews (Jianzhi Offer)', 'The Beauty of Programming', 'Clean Code', and 'Effective Java'. It is published as a documentation site by the Doocs community and is primarily written in Java.

## Use cases
- prepare for coding interviews at tech companies
- study solutions to Jianzhi Offer (Coding Interviews) problems
- learn clean code practices from book summaries
- review Java coding standards from the Alibaba Java Development Manual
- find platforms to practice interview problems online
- brush up on algorithms and data structures before an interview

## When to choose
- you are preparing for Java-focused technical interviews at internet companies
- you want structured notes on classic interview books like Jianzhi Offer and Clean Code
- you prefer reading curated explanations alongside LeetCode-style practice

## When to avoid
- you need an interactive coding judge or auto-graded exercises
- you work primarily in languages other than Java
- you want a comprehensive structured course rather than book notes

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation
- domain: tutorials, education, programming-languages
- platform: -
- tags: coding-interviews, book-notes, java, algorithms, interview-preparation, doocs, web-server

## Member repositories
- doocs/coding-interview (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:40.462579+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 2026-08-30T02:36:29.358130+00:00, confidence not recorded.
  - readme: https://github.com/doocs/coding-interview (fetched 2026-08-28T04:06:40.462579+00:00, sha 3fab52600d82)
  - homepage: https://interview.doocs.org (fetched 2026-08-29T10:17:08.293787+00:00, sha 51c3d742215a)
  - site_page: https://interview.doocs.org/getting-started (fetched 2026-08-29T10:17:08.302771+00:00, sha e1b4bd378ed9)
- Data as of 2026-08-30T08:39:29.467469+00:00.