Testing & Quality Assurance๏ƒ

The Financial Debt Optimizer has a comprehensive test suite ensuring reliability and correctness of all financial calculations.

Test Coverage๏ƒ

Our test suite includes 167 comprehensive tests covering:

๐Ÿงช Unit Tests

  • Core financial calculations and algorithms

  • Data validation and error handling

  • Excel I/O operations

  • Visualization components

  • CLI command functionality

๐Ÿ”— Integration Tests

  • End-to-end workflow testing

  • Excel template โ†’ analysis โ†’ report generation

  • Multi-strategy comparison workflows

  • Performance testing with large datasets

โšก Performance Tests

  • Large dataset handling (20+ debts, 10+ expenses)

  • Memory usage stability

  • Processing time benchmarks

๐ŸŽฏ Validation Tests

  • Financial scenario validation

  • Data integrity checks

  • Edge case handling

Running Tests๏ƒ

For developers working on the project:

# Install development dependencies
pip install -e .[dev]

# Run all tests
pytest

# Run with coverage report
pytest --cov=debt_optimizer --cov-report=html

# Run specific test categories
pytest -m unit          # Unit tests only
pytest -m integration   # Integration tests only
pytest -m excel        # Excel I/O tests only

Test Categories๏ƒ

Our tests are organized by functionality:

Financial Calculations (test_financial_calc.py)

Tests for core financial data classes, payment calculations, and interest computations.

Debt Optimization (test_debt_optimizer.py)

Tests for optimization algorithms, strategy comparisons, and result generation.

Excel I/O (test_excel_io.py)

Tests for Excel template generation, data reading, and report writing.

Validation (test_validation.py)

Tests for data validation, error handling, and financial scenario validation.

CLI Commands (test_cli_commands.py)

Tests for command-line interface functionality and user interactions.

Integration (test_integration.py)

End-to-end workflow tests and realistic scenario validation.

Visualization (test_visualization.py)

Tests for chart generation and visualization components.

Quality Metrics๏ƒ

  • 167 tests with 100% pass rate

  • Comprehensive coverage of all core functionality

  • Performance benchmarks for large datasets

  • Realistic scenario testing with sample financial data

  • Error handling validation for edge cases

The test suite ensures that all financial calculations are accurate and all features work reliably across different scenarios and data sizes.

Continuous Integration๏ƒ

All tests are automatically run on:

  • Every pull request

  • Every commit to main branch

  • Before each release

This ensures that the codebase maintains high quality and reliability standards.