# ACE Connection Logger - Test Plan

## Executive Summary

This document outlines the comprehensive testing strategy for the ACE Connection Logger, a network connectivity monitoring tool with ping statistics and interactive dashboard capabilities.

## Testing Objectives

1. **Verify Functionality**: Ensure all features work as specified
2. **Ensure Reliability**: Validate error handling and recovery mechanisms
3. **Validate Performance**: Confirm system performs under expected load
4. **Guarantee Data Accuracy**: Verify statistics calculations are correct
5. **Confirm Production Readiness**: Validate system is ready for deployment

## Test Coverage Strategy

### Test Pyramid

```
       ┌─────────────┐
       │  E2E Tests  │ (10%)
       └─────────────┘
      ┌───────────────┐
      │Integration Tests│ (20%)
      └───────────────┘
     ┌──────────────────┐
     │   Unit Tests     │ (70%)
     └──────────────────┘
```

### Coverage Goals

- **Overall**: 80% minimum code coverage
- **Critical Components**: 90%+ coverage
  - Database operations
  - Ping functionality
  - Statistics calculations
  - Configuration loading
- **Nice-to-have**: 95%+ overall coverage

## Test Categories

### 1. Unit Tests (70% of test suite)

#### 1.1 Ping Functionality
**Objective**: Verify ping operations work correctly across various scenarios

**Test Cases**:
- [x] Successful ping with all packets received
- [x] Failed ping with complete packet loss
- [x] Partial success with packet loss
- [x] Host validation (IPv4, IPv6, domains, localhost)
- [x] Ping count variations (1, 5, 10, 20, 50, 100)
- [x] Timeout settings (1s, 2s, 5s, 10s)
- [x] Network error handling
- [x] Timeout error handling
- [x] Latency calculation accuracy
- [x] DNS resolution before ping
- [x] Concurrent ping execution

**Mocking Strategy**:
- Mock `subprocess.run` for ping commands
- Mock network responses for consistent testing
- Simulate various network conditions

#### 1.2 Database Operations
**Objective**: Ensure database operations are reliable and performant

**Test Cases**:
- [x] Schema creation and validation
- [x] Insert ping results
- [x] Query by host
- [x] Query by time range
- [x] Update existing results
- [x] Delete old records
- [x] Index existence and usage
- [x] Statistics calculations
- [x] Integrity constraints
- [x] Transaction rollback/commit
- [x] Bulk insert performance (100+ records)
- [x] Concurrent read access
- [x] NULL value handling
- [x] Database size management

**Test Data**:
- Sample ping results (recent)
- Old ping results (90+ days)
- Mixed success/failure results

#### 1.3 Statistics Calculations
**Objective**: Verify statistical calculations are mathematically correct

**Test Cases**:
- [x] Success rate (0%, 50%, 100%)
- [x] Latency min/max/avg
- [x] Packet loss percentage
- [x] Aggregated statistics across hosts
- [x] Time-based statistics (hourly, daily)
- [x] Percentile calculations (50th, 90th, 95th, 99th)
- [x] Moving averages
- [x] Standard deviation and jitter
- [x] Uptime/downtime calculations
- [x] Trend analysis
- [x] Reliability scoring
- [x] NULL value handling in calculations

**Validation**:
- Compare against manual calculations
- Test with known data sets
- Verify edge cases (empty data, single value)

#### 1.4 Configuration Management
**Objective**: Ensure configuration loading and validation work correctly

**Test Cases**:
- [x] Load valid configuration file
- [x] Required field validation
- [x] Host list validation (not empty)
- [x] Ping count validation (positive integer)
- [x] Interval validation (positive integer)
- [x] Timeout validation (positive integer)
- [x] Retention days validation (positive integer)
- [x] Dashboard port validation (1024-65535)
- [x] Invalid configuration detection
- [x] Missing configuration file handling
- [x] Malformed YAML handling
- [x] Default configuration generation
- [x] Host format validation (IP, domain, localhost)
- [x] Environment variable overrides
- [x] Configuration reloading
- [x] Unicode support

**Test Data**:
- Valid configuration files
- Invalid configuration files
- Edge case configurations

### 2. Integration Tests (20% of test suite)

#### 2.1 Cleanup Job Integration
**Objective**: Verify cleanup job works correctly with database

**Test Cases**:
- [x] Remove records older than retention period
- [x] Preserve recent records
- [x] Mixed-age record handling
- [x] Various retention periods (1, 7, 30, 90, 365 days)
- [x] Empty database handling
- [x] Transaction rollback on error
- [x] Database vacuum after cleanup
- [x] Performance with large datasets (1000+ records)
- [x] Database integrity after cleanup
- [x] Concurrent operations during cleanup
- [x] Scheduled execution simulation

#### 2.2 End-to-End Workflows
**Objective**: Verify complete workflows work correctly

**Test Cases**:
- [x] Complete monitoring cycle (ping → database → statistics)
- [x] Multiple host monitoring
- [x] Error recovery from failed pings
- [x] Database connection resilience
- [x] Concurrent read/write operations
- [x] Statistics calculation on real data
- [x] Cleanup integration with monitoring

**Success Criteria**:
- All components work together seamlessly
- Data flows correctly through system
- Errors are handled gracefully

### 3. Edge Cases and Failure Modes (10% of test suite)

#### 3.1 Input Validation Edge Cases
**Test Cases**:
- [x] Empty host list
- [x] Invalid host addresses
- [x] Very long host names (1000+ chars)
- [x] Unicode in host names
- [x] Extreme latency values
- [x] Zero/negative latency values
- [x] Packet loss edge cases (0%, 100%, 1 packet)

#### 3.2 Error Handling
**Test Cases**:
- [x] Network timeout handling
- [x] Permission denied errors
- [x] Database locked errors
- [x] Database corruption detection
- [x] Disk full simulation
- [x] Configuration errors

#### 3.3 Performance Edge Cases
**Test Cases**:
- [x] Rapid succession pings
- [x] Long-running monitoring (24h+ simulation)
- [x] Large dataset handling (10,000+ records)
- [x] Memory leak prevention
- [x] Concurrent operation stress test

#### 3.4 Timing Edge Cases
**Test Cases**:
- [x] Timestamp edge cases (past, future)
- [x] System clock changes
- [x] Configuration changes during runtime

## Test Execution Strategy

### Phase 1: Unit Testing (Week 1)
1. Implement all unit tests
2. Achieve 80%+ coverage on core modules
3. Fix any identified bugs

### Phase 2: Integration Testing (Week 2)
1. Implement integration tests
2. Test component interactions
3. Validate end-to-end workflows

### Phase 3: Edge Case Testing (Week 3)
1. Implement edge case tests
2. Stress test the system
3. Validate error handling

### Phase 4: Performance Testing (Week 4)
1. Run performance benchmarks
2. Identify bottlenecks
3. Optimize as needed

### Phase 5: Validation (Week 5)
1. Run complete test suite
2. Validate coverage targets met
3. Manual testing of dashboard
4. Documentation review

## Test Environment

### Development Environment
- Python 3.13
- SQLite 3.x
- pytest 8.4.2+
- All test dependencies installed via uv

### CI/CD Environment
- GitHub Actions or equivalent
- Automated test execution on push/PR
- Coverage reporting
- Test result notifications

### Test Data
- Synthetic ping results
- Mock network responses
- Temporary databases (auto-cleanup)
- Sample configuration files

## Test Tools and Frameworks

### Core Testing
- **pytest**: Test framework
- **pytest-cov**: Coverage reporting
- **pytest-mock**: Mocking utilities
- **pytest-timeout**: Test timeout management
- **pytest-asyncio**: Async test support
- **pytest-xdist**: Parallel test execution

### Mocking
- **unittest.mock**: Python standard library mocking
- Mock subprocess calls for pings
- Mock network responses
- Mock file system operations

### Coverage
- **coverage.py**: Coverage measurement
- HTML reports for detailed analysis
- XML reports for CI/CD integration
- Terminal reports for quick checks

## Test Fixtures

### Database Fixtures
```python
@pytest.fixture
def temp_db() -> str
    """Temporary SQLite database"""

@pytest.fixture
def db_connection(temp_db) -> sqlite3.Connection
    """Database connection with schema"""

@pytest.fixture
def populated_db(db_connection, sample_ping_data)
    """Database with sample data"""
```

### Data Fixtures
```python
@pytest.fixture
def sample_ping_data() -> List[dict]
    """Recent ping results"""

@pytest.fixture
def old_ping_data() -> List[dict]
    """Old ping results for cleanup testing"""
```

### Mock Fixtures
```python
@pytest.fixture
def mock_ping_response()
    """Successful ping response"""

@pytest.fixture
def mock_failed_ping_response()
    """Failed ping response"""
```

## Success Criteria

### Functional Requirements
- [ ] All ping scenarios handled correctly
- [ ] Database operations are reliable
- [ ] Statistics calculations are accurate
- [ ] Configuration loading is robust
- [ ] Cleanup job works as expected
- [ ] Dashboard displays data correctly

### Quality Requirements
- [ ] 80%+ overall code coverage
- [ ] 90%+ coverage on critical components
- [ ] All tests pass consistently
- [ ] No flaky tests
- [ ] Zero critical bugs
- [ ] All edge cases handled

### Performance Requirements
- [ ] Ping operations complete within timeout
- [ ] Database queries respond in <100ms
- [ ] Cleanup handles 10,000+ records efficiently
- [ ] Dashboard loads in <2 seconds
- [ ] No memory leaks in long-running operations

### Documentation Requirements
- [ ] Test documentation complete
- [ ] Test plan document
- [ ] README with test instructions
- [ ] Inline test documentation
- [ ] CI/CD configuration documented

## Risk Assessment

### High Risk Areas
1. **Network Operations**: Ping failures, timeouts
   - Mitigation: Comprehensive mocking, error handling tests

2. **Database Integrity**: Corruption, locks
   - Mitigation: Transaction tests, integrity checks

3. **Concurrent Operations**: Race conditions
   - Mitigation: Concurrent access tests

4. **Long-term Reliability**: Memory leaks, resource exhaustion
   - Mitigation: Long-running simulations, stress tests

### Medium Risk Areas
1. **Configuration Errors**: Invalid configs
   - Mitigation: Validation tests, defaults

2. **Time-based Issues**: Cleanup scheduling
   - Mitigation: Time-based test scenarios

### Low Risk Areas
1. **Statistics Calculations**: Math errors
   - Mitigation: Comprehensive calculation tests

2. **UI Rendering**: Dashboard display
   - Mitigation: Component testing (future)

## Test Metrics

### Track These Metrics
1. **Code Coverage**: % of code executed by tests
2. **Test Pass Rate**: % of tests passing
3. **Test Execution Time**: Total time to run suite
4. **Defect Detection Rate**: Bugs found per test
5. **Test Stability**: Flaky test count

### Target Metrics
- Code Coverage: 80%+ (90%+ for critical)
- Test Pass Rate: 100%
- Test Execution Time: <5 minutes
- Flaky Tests: 0
- Critical Bugs: 0

## Continuous Improvement

### Post-Release Testing
1. Monitor production for issues
2. Add regression tests for bugs found
3. Update test suite based on usage patterns
4. Expand coverage to new features

### Test Maintenance
1. Regular review of test suite
2. Remove obsolete tests
3. Update fixtures as system evolves
4. Refactor tests for maintainability

## Validation Checklist

Before marking testing complete:

- [x] All test files created
- [x] pytest configuration complete
- [x] Fixtures implemented
- [x] Unit tests for ping functionality
- [x] Unit tests for database operations
- [x] Unit tests for statistics
- [x] Unit tests for configuration
- [x] Integration tests for cleanup
- [x] Integration tests for workflows
- [x] Edge case tests
- [x] Test documentation complete
- [x] Test dependencies added to pyproject.toml
- [ ] Full test suite runs successfully
- [ ] Coverage targets met
- [ ] No flaky tests
- [ ] CI/CD integration configured

## Appendix A: Test Commands

```bash
# Run all tests
pytest

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

# Run specific categories
pytest -m unit
pytest -m integration
pytest -m slow

# Run specific test file
pytest tests/test_ping.py

# Run in parallel
pytest -n auto

# Run with verbose output
pytest -v

# Show slowest tests
pytest --durations=10
```

## Appendix B: Troubleshooting

### Common Issues

**Issue**: Tests fail with database locked errors
**Solution**: Increase timeout or ensure proper cleanup

**Issue**: Flaky tests
**Solution**: Remove external dependencies, use mocks

**Issue**: Low coverage
**Solution**: Identify gaps with `--cov-report=term-missing`

**Issue**: Slow test execution
**Solution**: Use pytest-xdist for parallel execution

## Conclusion

This comprehensive test plan ensures the ACE Connection Logger is production-ready, reliable, and maintainable. The test suite covers all critical functionality, edge cases, and integration scenarios, providing confidence in the system's behavior under various conditions.
