With a dream of adding this library to the official Java Collections Framework, I am keeping this project open to contributions ☁️✨.
Got an idea for an awesome new feature? Found a bug that's been bugging you? Want to add some witty comments of your own? We'd love to hear from you!
Start by creating a personal copy of the repository:
- Navigate to the Graph Algorithms Library GitHub repository.
- Click the Fork button at the top-right of the page.
Clone your fork to your local machine:
git clone https://github.com/yourusername/graph-algorithms-library.git
cd graph-algorithms-library
Create a new branch for your changes:
git checkout -b feature-branch
Replace feature-branch
with a descriptive name for your branch.
Make your changes in your local repository. This could include:
- Adding New Features: Implement new features or algorithms.
- Fixing Bugs: Resolve issues or bugs.
- Improving Documentation: Enhance the README or other documentation.
- Refactoring Code: Clean up or optimize existing code.
Before you commit, make sure to test your changes. Run any existing tests or add new ones to ensure your changes work as expected and don't break existing functionality.
Add and commit your changes with a descriptive message:
git add .
git commit -m "Add a descriptive message about your changes"
Push your changes to your fork on GitHub:
git push origin feature-branch
Go to the original repository on GitHub and open a Pull Request:
- Navigate to the Pull Requests section.
- Click on New Pull Request.
- Select your branch and compare it with the
main
branch of the original repository. - Provide a clear description of your changes and why they should be merged.
- Submit the Pull Request.
- Provide a Clear Description: Explain what changes you made and why.
- Follow Code Style: Ensure your code adheres to the project's coding style.
- Include Tests: Add or update tests to cover your changes.
- Be Responsive: Be prepared to address feedback or make further changes as requested.
We expect all contributors to adhere to our Code of Conduct. Be respectful, considerate, and inclusive in all communications.
If you have any questions or need assistance, feel free to:
We appreciate your contributions and look forward to collaborating with you to make the Graph Algorithms Library even better. Happy coding! 🚀