# acm-clan/algorithm-stone

ACM/LeetCode算法竞赛路线图，最全的算法学习地图！

Repository: https://github.com/acm-clan/algorithm-stone
Canonical: https://ross.abutalabs.com/products/algorithm-stone
Language: C++
License: MIT
License Family: permissive
Last push: 2023-01-06T10:14:29+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": 2022, "days_push": 1335, "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 2272, forks 645 (observed 2026-08-28T04:06:33.231832+00:00)

## What it is
A curated algorithm learning roadmap for ACM/LeetCode competitive programming, presented as interactive SVG maps of ordered practice problems. It includes beginner tutorials for git and VSCode, recommended algorithm books, and topic-specific roadmaps (trees, dynamic programming, stacks/queues).

## Use cases
- find a structured order to practice leetcode problems
- prepare for ACM competitive programming contests
- learn data structures and algorithms step by step
- get a roadmap for coding interview preparation
- find recommended algorithm textbooks and resources
- track progress while grinding algorithm problems

## When to choose
- you want a carefully sequenced problem list that minimizes difficulty jumps
- you are a beginner needing git/VSCode setup guidance for practicing
- you prefer visual SVG roadmaps with clickable problem links

## When to avoid
- you need an interactive judge or automated grading platform
- you want video-based courses rather than problem lists and book links
- you need up-to-date content, as the project has not released since early 2023

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: developer-tools, documentation
- domain: education, tutorials
- platform: cross-platform
- tags: competitive-programming, leetcode, algorithm-roadmap, acm-icpc, interview-prep, study-guide, algorithms

## Member repositories
- acm-clan/algorithm-stone (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:33.231832+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 2026-08-30T02:41:42.204080+00:00, confidence not recorded.
  - readme: https://github.com/acm-clan/algorithm-stone (fetched 2026-08-28T04:06:33.231832+00:00, sha db1514bcdf9c)
- Data as of 2026-08-30T08:39:29.467469+00:00.