# Ariadne Developer Guide

This guide provides comprehensive information for developers who want to contribute to or extend the Ariadne Intelligent Quantum Router.

## Project Overview

Ariadne is an intelligent quantum circuit routing system that automatically analyzes circuit properties and selects the optimal simulator backend. The core philosophy emphasizes transparent, deterministic algorithms and mathematical analysis for routing decisions.

### Architecture Overview

Ariadne's architecture consists of several key components:

1. **Router System**: The intelligent routing logic that analyzes circuits and selects backends
2. **Backend Interface**: A unified interface for all supported quantum simulators
3. **Circuit Analysis**: Mathematical analysis of circuit properties (entropy, treewidth, Clifford ratio)
4. **Resource Management**: Memory and computational resource tracking and allocation
5. **Configuration System**: Flexible configuration management for different environments

## Development Setup

### Prerequisites

- Python 3.11 or higher
- Git
- Virtual environment tool (venv, conda, etc.)

### Installation for Development

```bash
git clone https://github.com/Shannon-Labs/ariadne.git
cd ariadne
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -e .[dev,apple,cuda,viz]
pre-commit install
```

### Directory Structure

```
ariadne/
├── src/ariadne/           # Main source code
│   ├── backends/          # Backend implementations
│   ├── core/              # Core systems and utilities
│   ├── route/             # Routing logic
│   ├── config/            # Configuration system
│   └── ...                # Other modules
├── tests/                 # Test suite
├── examples/              # Usage examples
├── docs/                  # Documentation
├── benchmarks/            # Performance benchmarks
└── pyproject.toml         # Project configuration
```

## Core Concepts

### Backend Interface

All backends must implement the standard backend interface defined in `src/ariadne/backends/__init__.py`. The interface includes:

- `simulate(circuit, shots)`: Main simulation method
- `get_capacity()`: Returns backend capacity information
- `is_available()`: Checks if backend is available on current system
- `get_info()`: Returns backend-specific information

### Circuit Analysis

Circuit analysis is performed by the `EnhancedQuantumRouter` class, which evaluates several key metrics:

- **Circuit Entropy**: Measures the entanglement and complexity of the circuit
- **Clifford Ratio**: Determines what percentage of gates are Clifford gates
- **Treewidth**: Analyzes the circuit graph structure
- **Qubit Count and Depth**: Basic circuit dimensions

### Routing Decision Process

The routing decision process follows this flow:

1. Analyze circuit properties using mathematical metrics
2. Evaluate available backends against circuit requirements
3. Calculate confidence scores for each backend option
4. Select the optimal backend based on performance predictions
5. Execute simulation with fallback logic if needed

## Adding New Backends

To add a new backend to Ariadne:

### 1. Create Backend Implementation

Create a new file in `src/ariadne/backends/` (e.g., `new_backend.py`):

```python
from . import BaseBackend
from ..types import BackendType, BackendCapacity

class NewBackend(BaseBackend):
    """Implementation of the new quantum simulator backend."""

    def __init__(self, **kwargs):
        super().__init__(BackendType.NEW_BACKEND)
        # Initialize backend-specific resources

    def simulate(self, circuit, shots):
        # Implement simulation logic
        pass

    def get_capacity(self):
        # Return backend capacity information
        return BackendCapacity(...)

    def is_available(self):
        # Check if backend dependencies are available
        return True

    def get_info(self):
        # Return backend-specific information
        return {"version": "1.0.0", "features": ["feature1", "feature2"]}
```

### 2. Update Backend Registry

Add your backend to the backend registry in `src/ariadne/backends/__init__.py`:

```python
from .new_backend import NewBackend

# Add to available backends list
AVAILABLE_BACKENDS = [
    # ... existing backends
    NewBackend,
]
```

### 3. Update BackendType Enum

Add your backend type to the `BackendType` enum in `src/ariadne/types.py`:

```python
class BackendType(Enum):
    # ... existing backends
    NEW_BACKEND = "new_backend"
```

### 4. Update Router Logic

Modify the routing logic in `src/ariadne/route/enhanced_router.py` to include your backend in the decision process.

## Testing Guidelines

### Unit Tests

All new functionality must include unit tests in the `tests/` directory. Follow these guidelines:

- Use pytest as the testing framework
- Aim for 85%+ test coverage
- Include both positive and negative test cases
- Test edge cases and error conditions
- Use parameterized tests for multiple scenarios

Example test structure:

```python
import pytest
from ariadne import EnhancedQuantumRouter
from qiskit import QuantumCircuit

class TestNewBackend:
    def test_new_backend_simulation(self):
        """Test basic simulation functionality."""
        circuit = QuantumCircuit(2)
        circuit.h(0)
        circuit.cx(0, 1)
        circuit.measure_all()

        # Test simulation
        result = simulate(circuit, shots=100, backend="new_backend")
        assert result.backend_used.value == "new_backend"
        assert len(result.counts) > 0

    def test_new_backend_unavailable(self):
        """Test behavior when backend is unavailable."""
        # Mock backend unavailability
        # Test fallback behavior
```

### Integration Tests

Integration tests should verify that your backend works correctly with the routing system:

- Test automatic routing decisions
- Verify fallback behavior when backend fails
- Test resource management and memory usage
- Validate performance characteristics

### Benchmark Tests

Add benchmark tests to the `benchmarks/` directory to measure performance:

```python
def test_new_backend_performance():
    """Benchmark new backend performance."""
    circuit = create_test_circuit()
    result = benchmark_backend("new_backend", circuit, shots=1000)
    assert result.execution_time < expected_threshold
```

## Documentation Requirements

All new features must include comprehensive documentation:

### API Documentation

- Docstrings for all public classes, methods, and functions
- Type hints for all parameters and return values
- Examples in docstrings where applicable

### User Guide

- Add usage examples to the examples directory
- Update the main documentation to include your feature
- Create a dedicated backend guide if applicable

### Developer Documentation

- Document internal architecture decisions
- Explain any complex algorithms or mathematical concepts
- Provide troubleshooting information

## Code Quality Standards

Ariadne follows strict code quality standards:

### Code Style

- Follow PEP 8 guidelines
- Use double quotes for strings
- Maximum line length of 100 characters
- Use type hints everywhere possible
- Follow the existing code patterns in the codebase

### Static Analysis

- All code must pass ruff linting
- All code must pass mypy type checking
- Address all security warnings from bandit
- Fix all dependency vulnerabilities from safety

### Performance Considerations

- Optimize critical paths for performance
- Minimize memory allocations in hot paths
- Use appropriate data structures for the use case
- Profile performance bottlenecks before optimizing

## Contribution Process

### Pull Request Guidelines

1. Fork the repository
2. Create a feature branch
3. Implement your changes with tests and documentation
4. Run all tests locally (`make test`)
5. Format code with ruff (`ruff format .`)
6. Create a pull request with a clear description
7. Address reviewer feedback

### Code Review Process

All contributions undergo code review focusing on:

- Correctness and reliability
- Performance and efficiency
- Code quality and maintainability
- Documentation completeness
- Test coverage adequacy

### Release Process

Ariadne follows semantic versioning. Major releases include breaking changes, minor releases add new features, and patch releases fix bugs.

## Common Development Tasks

### Debugging Routing Decisions

To debug routing decisions, use the verbose logging:

```python
from ariadne import EnhancedQuantumRouter, configure_logging
import logging

configure_logging(level=logging.DEBUG)
router = EnhancedQuantumRouter()
decision = router.select_optimal_backend(circuit)
print(decision.reasoning)
```

### Profiling Performance

Use the built-in profiling tools:

```python
from ariadne.performance import profile_backend

results = profile_backend("cuda", test_circuit, shots=1000)
print(results)
```

### Testing Backend Compatibility

Use the compatibility test suite:

```bash
python -m pytest tests/test_backends.py::test_new_backend_compatibility
```

## Support and Community

- **GitHub Issues**: Report bugs and request features
- **GitHub Discussions**: Ask questions and share ideas
- **Contributing Guidelines**: Detailed contribution process
- **Code of Conduct**: Community standards

## License

Ariadne is released under the Apache 2.0 License. See the LICENSE file for details.

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*Happy coding! Remember: Transparency through mathematical analysis.*
