# TheAlgorithms/C-Plus-Plus

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

Repository: https://github.com/TheAlgorithms/C-Plus-Plus
Canonical: https://ross.abutalabs.com/products/c-plus-plus
Homepage: https://thealgorithms.github.io/C-Plus-Plus
Language: C++
License: MIT
License Family: permissive
Topics: cpp, algorithm, algorithms-implemented, data-structures, algorithm-competitions, interview-preparation, interview-questions, search, sort, educational, instructor-materials, machine-learning-algorithms, artificial-intelligence-algorithms, computer-science, machine-learning, mathematics
Last push: 2025-10-11T14:51:22+00:00

## Health v2 (maintenance only)
Score: 53/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 46, release rhythm 35, longevity 100
- inputs: {"age_days": 3700, "days_push": 326, "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 34612, forks 7852 (observed 2026-08-28T04:12:00.645154+00:00)

## What it is
A large open-source collection of algorithms and data structures implemented in C++17 for educational purposes, covering computer science, mathematics, statistics, machine learning, and physics. Each implementation is atomic, well-documented, and dependency-free, with Doxygen-generated documentation and CI testing on major platforms.

## Use cases
- learn sorting and searching algorithms in C++
- prepare for coding interviews with algorithm implementations
- study data structures with well-commented C++ code
- find reference implementations of machine learning algorithms
- teach computer science courses with example code
- compare different algorithm strategies for the same problem

## When to choose
- you want readable, dependency-free C++ implementations to learn from
- you need educational reference code for algorithms or data structures
- you are preparing for interviews or competitive programming
- you want MIT-licensed algorithm snippets to adapt into projects

## When to avoid
- you need a production-grade, performance-optimized algorithm library
- you want a package-manager-installable library with a stable API
- you need battle-tested numerical or ML libraries like Eigen or PyTorch

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools, documentation, testing
- domain: education, mathematics, machine-learning, computer-vision, tutorials
- platform: cpp, cross-platform, windows
- tags: data-structures, interview-preparation, competitive-programming, sorting, searching, educational, stl, c-plus-plus-17, algorithms, linux, macos

## Member repositories
- TheAlgorithms/C-Plus-Plus (main) score 53

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:00.645154+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 2026-08-29T16:27:28.295603+00:00, confidence not recorded.
  - readme: https://github.com/TheAlgorithms/C-Plus-Plus (fetched 2026-08-28T04:12:00.645154+00:00, sha c8ff4a610af9)
  - homepage: https://thealgorithms.github.io/C-Plus-Plus (fetched 2026-08-29T07:48:10.919968+00:00, sha a80b5ad4d384)
- Data as of 2026-08-30T08:39:29.467469+00:00.