# xtaci/algorithms

Algorithms & Data structures in C++.

Repository: https://github.com/xtaci/algorithms
Canonical: https://ross.abutalabs.com/products/xtaci-algorithms
Language: C++
License: MIT
License Family: permissive
Last push: 2024-08-01T09:49:56+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4894, "days_push": 762, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5459, forks 1516 (observed 2026-08-28T04:09:19.450568+00:00)

## What it is
A collection of classical algorithms and data structures implemented in C++, with one header file per algorithm plus a demo program. It targets Linux/gcc and serves as both a reference implementation and a learning resource.

## Use cases
- learn how classic sorting algorithms are implemented in C++
- find a header-only skip list or fibonacci heap implementation
- study data structures like binary search trees and bit sets
- reference implementations of Miller-Rabin primality testing
- grab a single-header algorithm to adapt into a C++ project

## When to choose
- you want readable, per-algorithm header files with demos for learning or reference
- you need a small standalone data structure without pulling in a large library
- you are on Linux with gcc and want minimal dependencies

## When to avoid
- you need a production-grade, heavily optimized algorithm library like Boost or the C++ standard library
- you need cross-platform support beyond Linux/gcc
- you need actively maintained, tested guarantees for critical systems

## Facets
- artifact type: library
- maturity: maintenance
- function: developer-tools
- domain: education, developer-tools
- platform: cpp
- tags: data-structures, header-only, learning-resource, c-plus-plus, algorithms, linux

## Member repositories
- xtaci/algorithms (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:19.450568+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 2026-08-29T17:56:47.560685+00:00, confidence not recorded.
  - readme: https://github.com/xtaci/algorithms (fetched 2026-08-28T04:09:19.450568+00:00, sha 20fe39ca2153)
- Data as of 2026-08-30T08:39:29.467469+00:00.