CONTRIBUTING.md

Contributing to SecureLens

Thank you for your interest in contributing to SecureLens! This document provides guidelines and instructions for contributing.

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Code of Conduct

• Be respectful and professional
• Focus on medical ethics and patient privacy
• Follow Python best practices
• Maintain code quality and test coverage

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Getting Started

1. Setup Development Environment

# Clone repository
git clone https://github.com/yourusername/securelens.git
cd securelens

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements-dev.txt

# Install pre-commit hooks
pre-commit install

2. Create a Feature Branch

git checkout -b feature/your-feature-name

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Development Guidelines

Code Style

• Use Black for formatting: black .
• Use Flake8 for linting: flake8 .
• Use Pylint for analysis: pylint cloud_server/
• Use isort for imports: isort .

Type Hints

All functions should have type hints:

def predict(image: np.ndarray, context: ts.Context) -> dict:
    """
    Run encrypted inference on X-ray image.
    
    Args:
        image: Preprocessed X-ray image
        context: CKKS encryption context
        
    Returns:
        dict: {"prediction": "NORMAL/PNEUMONIA", "confidence": 0.95}
    """

Testing

• Write tests for new features
• Run full test suite: pytest tests/ -v --cov
• Maintain >80% code coverage
• Include edge cases and error conditions

# Run tests
pytest tests/

# Run with coverage
pytest tests/ --cov=cloud_server --cov=crypto_layer

# Run specific test
pytest tests/test_api.py::test_predict

Documentation

• Add docstrings to all functions
• Update README if behavior changes
• Document CKKS parameter changes
• Include examples for new features

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Commit Guidelines

Use conventional commits:

feat: Add differential privacy option
fix: Handle corrupted image uploads
docs: Update encryption parameter docs
test: Add security test cases
refactor: Optimize inference latency

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Pull Request Process

1. Update your branch with latest main:

   git fetch origin
   git rebase origin/main
   

2. Run all checks locally:

   pytest tests/ -v
   black --check .
   flake8 .
   

3. Create pull request with:

   • Clear description of changes
   • Motivation/problem solved
   • Testing performed
   • Backwards compatibility notes

4. Link issues: Reference any related issues (#123)

5. Code review: Address reviewer feedback

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Areas for Contribution

Priority Areas (High Impact)

• ReLU Approximation — Polynomial approximations for deeper HE
• GPU Acceleration — CUDA-based SEAL integration
• Multi-disease — Extend to ChestX-ray14 dataset
• HIPAA Audit — Formal security audit
• Federated Learning — Hospital network training

Medium Priority

• Performance optimization
• Better error messages
• Enhanced logging
• API authentication
• Web UI improvements

Low Priority

• Documentation improvements
• Code style cleanup
• Test coverage increase
• Dependency updates

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Testing Requirements

All submissions must:

1. Pass unit tests: pytest tests/
2. Pass type checking: mypy cloud_server/
3. Pass linting: flake8 .
4. Have >80% code coverage
5. Include docstrings
6. Have at least one test case per function

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Medical/Regulatory Considerations

When contributing medical-related features:

1. Privacy-First: Always assume patient data could be leaked
2. Accuracy: Medical accuracy is non-negotiable
3. Compliance: Consider HIPAA/GDPR/DPDP implications
4. Testing: Include both accuracy and edge case tests
5. Documentation: Clearly mark limitations and disclaimers

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Reporting Issues

When reporting bugs:

1. Use clear title describing the issue
2. Include steps to reproduce
3. Provide expected vs actual behavior
4. Include relevant logs/error messages
5. Specify Python version and OS

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Security

If you discover a security vulnerability:

1. Do NOT create a public GitHub issue
2. Email: securelens-security@example.com
3. Include description and proof of concept
4. Allow 90 days for fix before disclosure

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License

By contributing, you agree that your contributions will be licensed under the MIT License.

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Questions?

• Open a GitHub issue with [question] prefix
• Check existing documentation and FAQs
• Review discussion threads

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Thank you for contributing to SecureLens! 🎉

Your work helps advance privacy-preserving medical AI for everyone.