Multidimensional arrays for C++. (Conditionally accepted Boost library) GitHub mirror: https://github.com/correaa/boost-multi

Accepted NeetCode submissions synced from the platform with topic based folders, multi language solutions and interview preparation practice.

Structured competitive programming workspace with LeetCode, NeetCode and Codeforces solutions plus reusable templates across multiple languages.

High-performance data structures and algorithms library for Zig. Includes graphs, trees, caching, string search, and serialization (DOT/GQL).

igraph graph algorithm library bindings for Kit

https://dsa.nopejs.me :)

Low-frequency Excision of the Atmosphere in Parallel (LEAP) Calibration using GPU acceleration.

[CC BY-NC-SA] A compendium of the community knowledge on game design and development

Algorithms Exercises solved in C++17, running with CMake and Catch2 unittest framework. Developed with TDD.

A sandbox environment for C++ experimentation

Leonardus is an open source project. It is a minimalist, stack-based programming system designed as a flexible framework for implementing and exploring algorithms. The syntax and semantics of its scripting language, LeoScript, are inspired by PostScript and Forth. It is extended with a prototype-based, object-oriented paradigm, has seamless integration into JupyterLab and Docker, and provides a concise and expressive environment for learning and experimentation.

The project name is a nod to Leonardus Pisanus, who was named and became known as Fibonacci.

Consult the project's GitLab Pages for documentation.

Algorithms Exercises solved in C (GNU11), running with CMake and Catch2 (C++) unittest framework. Developed with TDD.

Fundamental theory and practice in Data Science (DS). 🧮

Daily LeetCode practice – clean solutions, explanations, and daily updates.

Reusable algorithm and data structure templates for fast competitive programming practice in Python, C++, Java and other languages.

Algorithms and data structures implemented in C, guided and inspired by Low Level Learning

Framework for modeling financial systems using weighted automata, with analysis of worst-case and best-case outcomes

My lab assignments for IT013IU Data Structures & Algorithms course at HCMIU.

Object oriented python implementation of a user driven workout scheduler. With the use of recursive algorithms and user input, it creates optimal workouts for the user.