I enjoy tackling problems that require algorithmic thinking.
I often supplement my learning on sites like Codility, LeetCode, HackerRank, and HackerEarth to explore new ways to solve problems.
This repository records how I use Codility's Lessons to develop my algorithmic thinking by consulting docs and interacting with AI. For each problem I compare alternative methods with my initial solution, refine them if needed, and present a final solution.
This is not a scientifically rigorous method. The content of this repository reflects my personal musings and leverages AI for architectural review and peer-like feedback, similar to what you might expect from a team.
Each lesson will consist of:
- Initial solution — my first implementation
- Test data — inputs and expected outputs
- AI chat log — notes from conversations with AI
- Improved solution — refinements
- What I learned — lessons and insights
- References
I'll do my best to credit original authors for algorithms or ideas; apologies for any oversights and please open an issue or submit a PR so I can fix them and add the proper attribution.
You’re welcome to reuse code and documentation from this repository for personal or commercial projects; please include a short attribution in your README or source file header such as:
Adapted from tioback/codility-lessons — https://github.com/tioback/codility-lessonsBased on work by tioback (https://github.com/tioback/codility-lessons)
Prefer opening an issue for attribution errors or reporting uncredited code. For code changes, open a pull request with a clear description and tests when applicable. Follow the project's style and add tests where relevant.
Code in this repository is licensed under the MIT License — see LICENSE for details. By using material from this repo you agree to credit the author as described in CONTRIBUTING.md.