Clean, tested implementations of foundational data structures and algorithms in multiple languages.
This repository serves as a curated, multi-language library of fundamental data structures and algorithms. The primary goal is to provide a clean, tested, and well-documented reference for these core computer science concepts, suitable for accelerating development, creating training materials, or as a technical reference.
Each implementation in this collection adheres to the following principles:
- Tested & Validated: Each module is accompanied by a comprehensive suite of unit tests to ensure correctness, reliability, and edge-case handling.
- Clean & Idiomatic Code: The focus is on writing clear, maintainable, and idiomatic code that follows the best practices of each respective language.
- Well-Documented: Every concept includes its own
READMEexplaining its principles, common use cases, and a performance analysis (Big O notation for time and space complexity). - Multi-Language Perspective: Where applicable, concepts are implemented in multiple languages (e.g., Python, C++) to compare and contrast different programming paradigms and standard library features.
The repository is organized by concept, with language-specific implementations nested within.
- /Data_Structures: Contains foundational data structures like Linked Lists, Stacks, Queues, Trees, etc.
- /Algorithms: Contains fundamental algorithms for Sorting, Searching, Graph Traversal, and more.
Feel free to use the code within as a building block for projects or as a reference for technical implementation.
I am actively expanding this library to focus on Modern C++ primitives and clean architectural patterns.
- Learn with me: Sponsor on GitHub to support the creation of more educational code samples and clean C++ implementations.