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https://github.com/muchokidavid/codility-kata


https://github.com/muchokidavid/codility-kata

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README

          

# Codility Kata Solutions

This repository contains my solutions to various coding challenges from Codility. Codility is a platform that offers coding challenges and assessments for software engineers, particularly focusing on algorithmic and programming skills.

## About Codility

Codility provides a collection of algorithmic tasks divided into different categories such as Arrays, Sorting, Dynamic Programming, etc. These challenges are designed to assess problem-solving skills, algorithmic thinking, and proficiency in programming languages.

You can explore Codility and try out their challenges [here](https://www.codility.com/).

## Structure

In this repository, you'll find solutions to Codility challenges organized by their respective categories. Each challenge solution is provided in a separate file along with a brief description and explanation if necessary.

### Categories

- [Arrays](arrays/)
- [Sorting](sorting/)
- [Dynamic Programming](dynamic-programming/)
- [Graphs](graphs/)
- [Math](math/)
- [Strings](strings/)

## Contributing

If you'd like to contribute your solutions to Codility challenges, you're welcome to do so! Here's how:

1. Fork this repository.
2. Create a new branch (`git checkout -b feature/your-solution`).
3. Add your solution file to the appropriate category directory.
4. Write a brief description of the problem and your solution in the file.
5. Commit your changes (`git commit -am 'Add solution for problem X'`).
6. Push to the branch (`git push origin feature/your-solution`).
7. Create a new Pull Request.

Please ensure that your solution passes all the test cases provided by Codility. Additionally, it's helpful to include comments explaining your thought process and any optimizations you've made.

## Disclaimer

These solutions are provided for learning and reference purposes. While I strive for accuracy and efficiency in my solutions, there might be better approaches or optimizations possible. Feel free to suggest improvements or alternative solutions via GitHub issues or pull requests.

Happy coding!