# Test Coverage Enhancement Plan

## Current State

- **1969 tests** yielding only **17.32% coverage**
- **16,331 total statements**, need to cover **6,859 statements** to reach 42%
- Most tests are trivial import tests that don't exercise actual functionality
- Major gaps: 0% coverage in critical modules (services, orchestration, MCP components)

## Strategic Approach: Three-Phase Plan

### Phase 1: High-Impact Module Testing (Quick Wins)

Target the largest 0% coverage modules first for maximum impact:

1. **services/tool_version_service.py** (629 statements, 0%)
1. **orchestration/advanced_orchestrator.py** (338 statements, 0%)
1. **services/health_metrics.py** (356 statements, 0%)
1. **mcp/dashboard.py** (354 statements, 0%)
1. **services/dependency_monitor.py** (291 statements, 0%)

**Impact**: These 5 modules = **1,968 statements**. Covering 50% would add **~6% to overall coverage**.

### Phase 2: Core Workflow Testing

Focus on the critical path that users actually use:

1. **managers/test_manager.py** (944 lines, 18% coverage → target 60%)
1. **core/workflow_orchestrator.py** (633 lines, 15% coverage → target 60%)
1. **managers/hook_manager.py** (critical functionality, improve coverage)

### Phase 3: Agent System Testing

Leverage the agent system's specialized test creation capabilities:

- **TestCreationAgent** - Can generate tests automatically
- **TestSpecialistAgent** - Handles complex test scenarios
- **AgentCoordinator** - Routes test generation to appropriate agents

## Improved Crackerjack Workflow for Test Generation

### 1. Leverage Existing Test Creation Agents

- Use `TestCreationAgent` and `TestSpecialistAgent` to auto-generate meaningful tests
- Configure agents to target 0% coverage modules first
- Set minimum coverage threshold per module (aim for 60-80% per module rather than 42% overall)

### 2. Create New Crackerjack Test Generation Command

```bash
python -m crackerjack --generate-tests --target-coverage 42 --focus-zero-coverage
```

- Automatically identifies 0% coverage modules
- Generates comprehensive test suites using AI agents
- Validates tests pass before committing

### 3. Implement Smart Test Prioritization

- Sort modules by: `(statements_count * (1 - coverage_percent))`
- Focus on high-value targets first
- Skip trivial modules (< 50 statements)

### 4. Test Quality Patterns to Implement

#### Bad Pattern (Current):

```python
def test_import():
    from module import Class

    assert Class is not None  # BAD - adds no value
```

#### Good Pattern (Target):

```python
def test_actual_functionality():
    obj = Class(config)
    result = obj.process_data(test_input)
    assert result.status == "success"
    assert len(result.items) == expected_count
```

### 5. Workflow Improvements

- Add `--test-generation` mode to AI agent workflow
- Create test templates for common patterns (services, managers, agents)
- Use property-based testing (Hypothesis) for complex logic
- Generate fixtures automatically from existing code patterns

### 6. Execution Order

1. Run coverage analysis to identify gaps
1. Generate tests for top 5 zero-coverage modules
1. Run tests and verify they increase coverage
1. Use AI agent to fix any failing tests
1. Iterate until 42% threshold is reached

### 7. Specific Module Targeting Priority

- **Priority 1**: services/tool_version_service.py (629 statements)
- **Priority 2**: orchestration/advanced_orchestrator.py (338 statements)
- **Priority 3**: services/health_metrics.py (356 statements)
- **Priority 4**: mcp/dashboard.py (354 statements)
- **Priority 5**: managers/test_manager.py (improve from 18% to 60%)

## Expected Outcome

This approach will efficiently reach 42% coverage by focusing on high-impact modules with meaningful tests rather than trivial import checks.

**Coverage Math**:

- Current: 2,829 statements covered (17.32%)
- Need: 6,859 statements covered (42%)
- Gap: 4,030 additional statements needed
- Strategy: Target high-value modules first for maximum efficiency
