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test-driven-development skill

/universal/testing/test-driven-development

This skill teaches test-driven development patterns across languages, accelerating reliable features, safer refactors, and clearer contracts through

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---
name: test-driven-development
description: Comprehensive TDD patterns and practices for all programming languages, eliminating redundant testing guidance per agent.
license: Apache-2.0
compatibility: claude-code
metadata:
  updated_at: 2025-10-30T17:00:00Z
tags: [testing, tdd, best-practices, quality-assurance]
progressive_disclosure:
  entry_point:
    summary: "Comprehensive TDD patterns and practices for all programming languages, eliminating redundant testing guidance per agent."
    when_to_use: "When writing tests, implementing test-driven-development, or ensuring code quality."
    quick_start: "1. Review the core concepts below. 2. Apply patterns to your use case. 3. Follow best practices for implementation."
  references:
    - anti-patterns.md
    - examples.md
    - integration.md
    - philosophy.md
    - workflow.md
---
# Test-Driven Development (TDD)

Comprehensive TDD patterns and practices for all programming languages. This skill eliminates ~500-800 lines of redundant testing guidance per agent.

## When to Use

Apply TDD for:
- New feature implementation
- Bug fixes (test the bug first)
- Code refactoring (tests ensure behavior preservation)
- API development (test contracts)
- Complex business logic

## TDD Workflow (Red-Green-Refactor)

### 1. Red Phase: Write Failing Test
```
Write a test that:
- Describes the desired behavior
- Fails for the right reason (not due to syntax errors)
- Is focused on a single behavior
```

### 2. Green Phase: Make It Pass
```
Write the minimum code to:
- Pass the test
- Not introduce regressions
- Follow existing patterns
```

### 3. Refactor Phase: Improve Code
```
While keeping tests green:
- Remove duplication
- Improve naming
- Simplify logic
- Extract functions/classes
```

## Test Structure Patterns

### Arrange-Act-Assert (AAA)
```
// Arrange: Set up test data and conditions
const user = createTestUser({ role: 'admin' });

// Act: Perform the action being tested
const result = await authenticateUser(user);

// Assert: Verify the outcome
expect(result.isAuthenticated).toBe(true);
expect(result.permissions).toContain('admin');
```

### Given-When-Then (BDD Style)
```
Given: A user with admin privileges
When: They attempt to access protected resource
Then: Access is granted with appropriate permissions
```

## Test Naming Conventions

### Pattern: `test_should_<expected_behavior>_when_<condition>`

**Examples:**
- `test_should_return_user_when_id_exists()`
- `test_should_raise_error_when_user_not_found()`
- `test_should_validate_email_format_when_creating_account()`

### Language-Specific Conventions

**Python (pytest):**
```python
def test_should_calculate_total_when_items_added():
    # Arrange
    cart = ShoppingCart()
    cart.add_item(Item("Book", 10.00))
    cart.add_item(Item("Pen", 1.50))

    # Act
    total = cart.calculate_total()

    # Assert
    assert total == 11.50
```

**JavaScript (Jest):**
```javascript
describe('ShoppingCart', () => {
  test('should calculate total when items added', () => {
    const cart = new ShoppingCart();
    cart.addItem({ name: 'Book', price: 10.00 });
    cart.addItem({ name: 'Pen', price: 1.50 });

    const total = cart.calculateTotal();

    expect(total).toBe(11.50);
  });
});
```

**Go:**
```go
func TestShouldCalculateTotalWhenItemsAdded(t *testing.T) {
    // Arrange
    cart := NewShoppingCart()
    cart.AddItem(Item{Name: "Book", Price: 10.00})
    cart.AddItem(Item{Name: "Pen", Price: 1.50})

    // Act
    total := cart.CalculateTotal()

    // Assert
    if total != 11.50 {
        t.Errorf("Expected 11.50, got %f", total)
    }
}
```

## Test Types and Scope

### Unit Tests
- **Scope:** Single function/method
- **Dependencies:** Mocked
- **Speed:** Fast (< 10ms per test)
- **Coverage:** 80%+ of code paths

### Integration Tests
- **Scope:** Multiple components
- **Dependencies:** Real or test doubles
- **Speed:** Moderate (< 1s per test)
- **Coverage:** Critical paths and interfaces

### End-to-End Tests
- **Scope:** Full user workflows
- **Dependencies:** Real (in test environment)
- **Speed:** Slow (seconds to minutes)
- **Coverage:** Core user journeys

## Mocking and Test Doubles

### When to Mock
- External APIs and services
- Database operations (for unit tests)
- File system operations
- Time-dependent operations
- Random number generation

### Mock Types

**Stub:** Returns predefined data
```python
def get_user_stub(user_id):
    return User(id=user_id, name="Test User")
```

**Mock:** Verifies interactions
```python
mock_service = Mock()
service.process_payment(payment_data)
mock_service.process_payment.assert_called_once_with(payment_data)
```

**Fake:** Working implementation (simplified)
```python
class FakeDatabase:
    def __init__(self):
        self.data = {}

    def save(self, key, value):
        self.data[key] = value

    def get(self, key):
        return self.data.get(key)
```

## Test Coverage Guidelines

### Target Coverage Levels
- **Critical paths:** 100%
- **Business logic:** 95%+
- **Overall project:** 80%+
- **UI components:** 70%+

### What to Test
- ✅ Business logic and algorithms
- ✅ Edge cases and boundary conditions
- ✅ Error handling and validation
- ✅ State transitions
- ✅ Public APIs and interfaces

### What NOT to Test
- ❌ Framework internals
- ❌ Third-party libraries
- ❌ Trivial getters/setters
- ❌ Generated code
- ❌ Configuration files

## Testing Best Practices

### 1. One Assertion Per Test (When Possible)
```python
# Good: Focused test
def test_should_validate_email_format():
    assert is_valid_email("[email protected]") is True

# Avoid: Multiple unrelated assertions
def test_validation():
    assert is_valid_email("[email protected]") is True
    assert is_valid_phone("123-456-7890") is True  # Different concept
```

### 2. Test Independence
```python
# Good: Each test is self-contained
def test_user_creation():
    user = create_user("[email protected]")
    assert user.email == "[email protected]"

# Avoid: Tests depending on execution order
shared_user = None

def test_create_user():
    global shared_user
    shared_user = create_user("[email protected]")

def test_update_user():  # Depends on previous test
    shared_user.name = "Updated"
```

### 3. Descriptive Test Failures
```python
# Good: Clear failure message
assert result.status == 200, f"Expected 200, got {result.status}: {result.body}"

# Avoid: Unclear failure
assert result.status == 200
```

### 4. Test Data Builders
```python
# Good: Reusable test data creation
def create_test_user(**overrides):
    defaults = {
        'email': '[email protected]',
        'name': 'Test User',
        'role': 'user'
    }
    return User(**{**defaults, **overrides})

# Usage
admin = create_test_user(role='admin')
guest = create_test_user(email='[email protected]')
```

## Testing Anti-Patterns to Avoid

### ❌ Testing Implementation Details
```python
# Bad: Tests internal structure
def test_user_storage():
    user = User("[email protected]")
    assert user._internal_cache is not None  # Implementation detail
```

### ❌ Fragile Tests
```python
# Bad: Breaks with harmless changes
assert user.to_json() == '{"name":"John","email":"[email protected]"}'

# Good: Tests behavior, not format
data = json.loads(user.to_json())
assert data['name'] == "John"
assert data['email'] == "[email protected]"
```

### ❌ Slow Tests in Unit Test Suite
```python
# Bad: Real HTTP calls in unit tests
def test_api_integration():
    response = requests.get("https://api.example.com/users")  # Slow!
    assert response.status_code == 200
```

### ❌ Testing Everything Through UI
```python
# Bad: Testing business logic through UI
def test_calculation():
    browser.click("#input1")
    browser.type("5")
    browser.click("#input2")
    browser.type("3")
    browser.click("#calculate")
    assert browser.find("#result").text == "8"

# Good: Test logic directly
def test_calculation():
    assert calculate(5, 3) == 8
```

## Quick Reference by Language

### Python (pytest)
```python
# Setup/Teardown
@pytest.fixture
def database():
    db = create_test_database()
    yield db
    db.cleanup()

# Parametrized tests
@pytest.mark.parametrize("input,expected", [
    ("[email protected]", True),
    ("invalid-email", False),
])
def test_email_validation(input, expected):
    assert is_valid_email(input) == expected
```

### JavaScript (Jest)
```javascript
// Setup/Teardown
beforeEach(() => {
  database = createTestDatabase();
});

afterEach(() => {
  database.cleanup();
});

// Async tests
test('should fetch user data', async () => {
  const user = await fetchUser(1);
  expect(user.name).toBe('John');
});
```

### Go
```go
// Table-driven tests
func TestEmailValidation(t *testing.T) {
    tests := []struct {
        input    string
        expected bool
    }{
        {"[email protected]", true},
        {"invalid-email", false},
    }

    for _, tt := range tests {
        result := IsValidEmail(tt.input)
        if result != tt.expected {
            t.Errorf("IsValidEmail(%s) = %v, want %v",
                tt.input, result, tt.expected)
        }
    }
}
```

## TDD Benefits Realized

- **Design Improvement:** Tests drive better API design
- **Documentation:** Tests serve as executable documentation
- **Confidence:** Refactoring becomes safe
- **Debugging:** Tests isolate issues quickly
- **Coverage:** Ensures comprehensive test coverage
- **Regression Prevention:** Catches bugs before deployment

## Related Skills

When using Test Driven Development, these skills enhance your workflow:
- **systematic-debugging**: Debug-first methodology when tests fail unexpectedly
- **react**: Testing React components, hooks, and context
- **django**: Testing Django models, views, and forms
- **fastapi-local-dev**: Testing FastAPI endpoints and dependency injection

[Full documentation available in these skills if deployed in your bundle]

Overview

This skill provides a compact, language-agnostic Test-Driven Development (TDD) guide with patterns, examples, and practical rules you can apply across projects. It consolidates Red-Green-Refactor workflow, test structure, test types, mocking guidance, coverage targets, and anti-patterns to eliminate redundant testing advice. Use it to standardize test design and speed up reliable development across teams and languages.

How this skill works

The skill inspects common testing scenarios and prescribes focused actions: write a failing test (Red), implement the minimal code to pass it (Green), then clean the design while keeping tests green (Refactor). It presents concrete patterns like Arrange-Act-Assert and Given-When-Then, naming conventions, language-specific snippets, and recommendations for unit, integration, and end-to-end tests. It also guides when to mock, coverage targets, what to test or skip, and anti-patterns to avoid.

When to use it

  • Implementing a new feature to drive design via tests
  • Fixing a bug by reproducing it with a failing test first
  • Refactoring code while ensuring behavior is preserved
  • Designing APIs and contracts with testable expectations
  • Validating complex business logic or state transitions

Best practices

  • Follow Red-Green-Refactor: failing test, minimal pass, then refactor
  • Name tests descriptively: test_should_<expected>_when_<condition>
  • Prefer one focused assertion per test to isolate failures
  • Keep tests independent and deterministic; avoid shared state
  • Mock external systems for unit tests; use real integrations only in integration/E2E tests
  • Write clear failure messages and reusable test data builders

Example use cases

  • Add a payment feature: write contract tests for edge cases, then implement minimal code
  • Refactor legacy module: create unit tests first to lock behavior, then refactor safely
  • Build an API: test endpoints and response contracts before shipping
  • Fix intermittent bug: reproduce it with a focused test that fails consistently
  • Create CI pipeline: enforce coverage targets for critical paths and business logic

FAQ

How granular should unit tests be?

Unit tests should target a single function or method and cover edge cases; mock external dependencies so tests run fast and deterministic.

When should I avoid mocking?

Avoid mocking when verifying integration behavior between components or when tests should validate real interactions in integration or end-to-end suites.