Test Design Skill

A structured approach to designing tests that give confidence without excessive maintenance burden.

Core Philosophy

Test behavior, not implementation. Tests that couple to internal implementation details become fragile and refactor-resistant. Aim to test what the code does, not how it does it.

The best test is the one that fails when something breaks, and passes when everything works. Perfect coverage means nothing if tests don't catch real bugs.

Testing Pyramid

        ┌─────────┐
        │   E2E   │  ← Few, slow, high confidence
       ┌┴─────────┴┐
       │ Integration│ ← Some, medium speed
      ┌┴───────────┴┐
      │    Unit     │ ← Many, fast, granular
      └─────────────┘

Unit tests form the base — fast, isolated, cover individual functions. Integration tests verify components work together. E2E tests validate complete user journeys.

Test Case Design

Arrange-Act-Assert (AAA) Pattern

def test_withdraw_amount_exceeds_balance():
    # Arrange
    account = Account(balance=Decimal("100.00"))
    
    # Act
    result = account.withdraw(Decimal("150.00"))
    
    # Assert
    assert result.is_failed()
    assert account.balance == Decimal("100.00")  # unchanged

Given-When-Then (GWT) Pattern

Feature: Account Withdrawal

  Scenario: Withdrawal amount exceeds balance
    Given an account with balance $100
    When I withdraw $150
    Then the withdrawal is rejected
    And the balance remains $100

Test Categories

🔴 Happy Path Tests

• Verify the main success scenario works
• At least one per feature/function

🟡 Edge Case Tests

• Boundary values (0, -1, max integer)
• Empty/null inputs
• Rare but possible conditions

🟡 Error Case Tests

• Invalid inputs
• Missing dependencies
• Permission denied scenarios

🟢 Edge/Extreme Cases

• Very large inputs
• Very small inputs
• Unicode/special characters
• Concurrent access

Test Doubles (Mocks/Stubs/Fakes)

Type	Purpose	Use When
Dummy	Fill parameter lists	Never actually used
Stub	Provide predetermined responses	Test requires specific data
Spy	Record how something was called	Verify interactions
Mock	Pre-programmed expectations	Verify behavior + interactions
Fake	Working implementation (simplified)	Real impl too slow/complex

Rule: Prefer real objects over mocks when practical. Mocks hide integration problems.

Test Naming Convention

test_<unit>_<scenario>_<expected_result>

Examples:

• test_user_create_with_valid_input_succeeds
• test_user_create_with_duplicate_email_fails
• test_order_cancel_after_shipment_refunds_full_amount

Coverage Targets

Layer	Target	Purpose
Unit	70-80%	Core business logic
Integration	40-60%	Key flows work together
E2E	Critical paths only	User journeys

Note: Coverage is a guide, not a goal. 100% coverage with shallow tests is worse than 70% with meaningful assertions.

Test Execution

Unit Tests

Run frequently during development (every save).

# Go
go test ./...

# Python
pytest tests/unit/ -v

# TypeScript
npm test -- --coverage

Integration Tests

Run before PR, after unit tests pass.

# Start dependencies
docker-compose up -d

# Run integration suite
pytest tests/integration/ -v

E2E Tests

Run on CI against deployed environment.

# CI/CD pipeline
npm run test:e2e -- --specs=critical-paths

Test Data Management

Strategies

1. Factories/Fixtures — Create test data on demand
2. Seeded Data — Deterministic test datasets
3. Randomized Data — Fuzz testing with random inputs
4. Snapshot Testing — Verify serializable outputs

Best Practices

• Tests should be independent (no shared state)
• Each test should clean up after itself
• Use meaningful data, not magic values
• Avoid test interdependencies

File Structure

test-design/
├── SKILL.md
└── references/
    ├── test-case-templates.md
    ├── testing-pyramid.md
    ├── mocking-strategies.md
    ├── test-naming-conventions.md
    └── per-type/
        ├── unit-test-guide.md
        ├── integration-test-guide.md
        └── e2e-test-guide.md