C-Plus-Plus

A collection of C++ algorithm implementations built as a learning resource, with several strategies offered for the same problem.

The repository holds open source implementations of a variety of algorithms in C++, licensed under MIT, spanning computer science, mathematics and statistics, data science, machine learning, and engineering. The README says the implementations and documentation are a learning resource, so the same objective can appear more than once with different strategies and optimizations. The GitHub description adds mathematics, machine learning, computer science, and physics to the topics, all implemented in C++ for educational purposes.

Each source is atomic, using STL classes with no external libraries needed. The code is compiled and tested on every commit across Windows, macOS, and Ubuntu using MSVC, AppleClang, and GNU, adheres strictly to C++17, and includes self checks so the implementations can be trusted. Strict C++17 adherence is also cited as keeping the code portable to embedded systems like ESP32 and ARM Cortex.

Online documentation is generated directly from the source code, including snippets, execution details, diagrammatic representations of program flow, and links to external resources. The documentation itself is licensed under CC BY-SA 4.0, and the README says it also introduces interactive source code with links to documentation for the C++ STL functions used.

The repository is community developed and maintained, and it welcomes new, un plagiarized, quality contributions after reading the contribution guidelines. That open posture is how the collection keeps growing, and GitHub lists C++ as the primary language with the MIT license for the code, while the documentation carries its own CC BY-SA 4.0 license.

The README presents this as learning material rather than a production codebase, and the review stays at that level, describing the collection without compiling anything.

• Source 1 · Project repository
• Source 2 · README