# walkccc/CLRS

📚 Solutions to Introduction to Algorithms Third Edition

Repository: https://github.com/walkccc/CLRS
Canonical: https://ross.abutalabs.com/products/walkccc-clrs
Homepage: https://walkccc.me/CLRS
Language: Markdown
License: MIT
License Family: permissive
Topics: clrs, introduction-to-algorithms, solutions
Last push: 2026-06-08T23:46:26+00:00

## Health v2 (maintenance only)
Score: 71/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 86, release rhythm 35, longevity 100
- inputs: {"age_days": 3117, "days_push": 86, "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 5111, forks 1293 (observed 2026-08-28T04:09:09.898699+00:00)

## What it is
A crowdsourced collection of nearly complete solutions to the textbook Introduction to Algorithms (Third Edition, CLRS), published as a static website built with MkDocs and rendered with KaTeX. It is a study reference rather than software, organized as Markdown files readable on mobile devices.

## Use cases
- find solutions to CLRS exercises
- study algorithms textbook problems
- check my answer to an Introduction to Algorithms problem
- prepare for algorithms course exams
- learn algorithms with worked solutions
- reference solutions while reading CLRS

## When to choose
- you are studying the CLRS textbook and want worked solutions
- you need a mobile-friendly, math-rendered reference for algorithm exercises
- you want a free, community-maintained answer key

## When to avoid
- you need executable algorithm implementations or a code library
- you want a primary learning resource rather than a solutions supplement
- you need solutions verified by the textbook authors

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, markdown
- domain: education, tutorials
- platform: browser, cross-platform
- tags: clrs, textbook-solutions, mkdocs, katex, study-guide, computer-science, algorithms, web-server

## Member repositories
- walkccc/CLRS (main) score 71

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:09.898699+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 2026-08-29T18:02:09.185478+00:00, confidence not recorded.
  - readme: https://github.com/walkccc/CLRS (fetched 2026-08-28T04:09:09.898699+00:00, sha 39e8429f86ae)
  - homepage: https://walkccc.me/CLRS (fetched 2026-08-29T08:56:55.458082+00:00, sha 8eb304300b8d)
- Data as of 2026-08-30T08:39:29.467469+00:00.