Test Coverage

Test Coverage Analysis

Comprehensive test coverage analysis skill for measuring coverage, identifying gaps, and improving test quality.

Core Capabilities

Coverage Measurement

Calculate and report code coverage metrics:

Line Coverage:

• Percentage of lines executed by tests
• Target: > 80%
• Critical code paths: > 95%

Branch Coverage:

• Percentage of branches (if/else) tested
• Target: > 70%
• Catches edge cases line coverage misses

Function Coverage:

• Percentage of functions called by tests
• Target: > 90%
• Quick indicator of test breadth

Running coverage:

# Python with pytest-cov
pytest --cov=src --cov-report=html --cov-report=term-missing

# Python with coverage.py
coverage run -m pytest
coverage report -m
coverage html

# JavaScript with Jest
jest --coverage

Gap Identification

Find untested code areas:

Completely Untested Files:

• Files with 0% coverage
• Often forgotten modules
• Priority: New features, critical paths

Partially Tested Functions:

• Functions with some but not all branches tested
• Missing edge cases
• Error handling paths

Untested Code Patterns:

# Show lines not covered
coverage report --show-missing

# List files below threshold
coverage report --fail-under=80

# JSON report for parsing
coverage json -o coverage.json

Test Quality Assessment

Evaluate test effectiveness beyond coverage:

Test-to-Code Ratio:

• Lines of test / Lines of source
• Target: 1:1 to 2:1
• Low ratio may indicate insufficient testing

Assertion Density:

• Assertions per test function
• Target: > 1 per test
• Single assertion per concept (ideally)

Test Independence:

• Tests should not depend on each other
• No shared mutable state
• Proper setup/teardown

Test Clarity:

• Descriptive test names
• Clear arrange/act/assert structure
• Documented test purpose

Coverage Analysis Workflow

Full Coverage Analysis

1. Run test suite: Execute all tests with coverage
2. Generate reports: Create HTML and terminal reports
3. Identify gaps: Find untested files and lines
4. Prioritize: Rank gaps by risk and importance
5. Recommend tests: Suggest specific tests to add

Quick Coverage Check

For rapid assessment:

1. Run coverage on changed files only
2. Compare to baseline coverage
3. Flag regressions
4. Report delta coverage

Coverage Report Format

Summary Report

Coverage Summary
================
Total Coverage: 78.5%
Target: 80.0%
Status: BELOW TARGET

By Component:
┌────────────────┬──────────┬────────┬─────────┐
│ Component      │ Lines    │ Missed │ Coverage│
├────────────────┼──────────┼────────┼─────────┤
│ api/           │ 450      │ 45     │ 90%     │
│ services/      │ 820      │ 180    │ 78%     │
│ repositories/  │ 320      │ 96     │ 70%     │
│ utils/         │ 150      │ 60     │ 60%     │
└────────────────┴──────────┴────────┴─────────┘

Gap Analysis

Critical Gaps (Priority: High)
==============================
1. services/payment.py (45% coverage)
   - process_payment(): Lines 45-78 untested
   - refund_transaction(): Completely untested
   - Error handling: 0% coverage

2. repositories/user_repo.py (62% coverage)
   - delete_user(): Untested
   - bulk_update(): Partial coverage

Test Recommendations

Recommended Tests
=================

1. test_payment_processing.py
   - test_successful_payment()
   - test_payment_insufficient_funds()
   - test_payment_network_error()
   - test_refund_full_amount()
   - test_refund_partial_amount()

2. test_user_repository.py
   - test_delete_user_success()
   - test_delete_user_not_found()
   - test_bulk_update_all_fields()
   - test_bulk_update_partial()

Test Types and Strategies

Unit Tests

Coverage focus:

• Individual functions/methods
• Edge cases and boundaries
• Error conditions

Best practices:

• Fast execution (< 100ms each)
• No external dependencies
• Use mocks/stubs for isolation

Integration Tests

Coverage focus:

• Component interactions
• Database operations
• API endpoints

Best practices:

• Test real integrations
• Use test databases/containers
• Clean up after tests

End-to-End Tests

Coverage focus:

• User workflows
• Critical paths
• System behavior

Best practices:

• Selective coverage (key flows)
• Realistic test data
• Stable test environment

Coverage Configuration

Python (pytest-cov)

# pytest.ini or pyproject.toml
[tool.pytest.ini_options]
addopts = "--cov=src --cov-report=term-missing --cov-fail-under=80"

[tool.coverage.run]
branch = true
source = ["src"]
omit = ["tests/*", "*/__pycache__/*"]

[tool.coverage.report]
exclude_lines = [
    "pragma: no cover",
    "if TYPE_CHECKING:",
    "raise NotImplementedError",
]

JavaScript (Jest)

{
  "jest": {
    "collectCoverage": true,
    "coverageThreshold": {
      "global": {
        "branches": 70,
        "functions": 80,
        "lines": 80,
        "statements": 80
      }
    },
    "coveragePathIgnorePatterns": [
      "/node_modules/",
      "/tests/"
    ]
  }
}

Prioritization Framework

Critical (Must Test)

• Payment/financial operations
• Authentication/authorization
• Data validation
• Security-sensitive code
• Core business logic

Important (Should Test)

• User-facing features
• Data transformations
• External integrations
• Error handling paths

Lower Priority

• Utility functions
• Configuration loading
• Logging code
• Debug/development code

Common Coverage Issues

False Sense of Security

Problem: High coverage but weak tests Solution: Review assertion quality, test mutations

Coverage Gaming

Problem: Tests that touch code without verifying behavior Solution: Require meaningful assertions, code review

Untestable Code

Problem: Code that's difficult to test Solution: Refactor for testability, dependency injection

Integration

Coordinate with other skills:

• code-quality skill: For test code quality
• refactoring skill: For improving testability
• security-scanning skill: For security test coverage