# indy256/codelibrary

:gem:Collection of algorithms and data structures

Repository: https://github.com/indy256/codelibrary
Canonical: https://ross.abutalabs.com/products/codelibrary
Language: Java
License: Unlicense
License Family: permissive
Topics: algorithm, data-structures, java, cpp, kotlin
Last push: 2026-07-05T05:58:05+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 91, release rhythm 35, longevity 100
- inputs: {"age_days": 5648, "days_push": 59, "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 2028, forks 520 (observed 2026-08-28T04:06:06.961715+00:00)

## What it is
A curated collection of algorithm and data structure implementations in C++, Java, Kotlin, Python, and Rust. It serves as a reference code library for competitive programming and algorithm study.

## Use cases
- find reference implementations of segment trees and Fenwick trees
- study competitive programming algorithms in Java and C++
- copy well-tested data structure code for contests
- learn how link/cut trees and treaps work
- compare algorithm implementations across multiple languages

## When to choose
- you need battle-tested implementations of classic data structures for competitive programming
- you want to study algorithm implementations in several languages side by side

## When to avoid
- you need a production-ready algorithm library with package management and stable APIs
- you want high-level abstractions rather than standalone reference code

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools
- domain: education, programming-languages
- platform: cpp, jvm, python, rust
- tags: competitive-programming, data-structures, algorithms, reference-implementation, code-library

## Member repositories
- indy256/codelibrary (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:06.961715+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 2026-08-30T02:59:39.955387+00:00, confidence not recorded.
  - readme: https://github.com/indy256/codelibrary (fetched 2026-08-28T04:06:06.961715+00:00, sha 63b01d6ba0a1)
- Data as of 2026-08-30T08:39:29.467469+00:00.