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test-driven-development

test-driven-development

github.com/bobmatnycTesting & quality78395 installsUpdated 15w ago
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About test-driven-development

test-driven-development is a skill that provides TDD practices for developers and coding agents across programming languages. It organizes work into red, green, and refactor phases, with patterns for test structure, mocks, coverage, and avoiding fragile tests.

Key features

  1. 01Red-green-refactor workflow
  2. 02Arrange-Act-Assert and Given-When-Then patterns
  3. 03Test naming and language examples
  4. 04Guidance on mocks and test doubles
  5. 05Coverage practices and anti-patterns

Use cases

  1. 01Develop a feature by writing its test first
  2. 02Reproduce a bug with a failing test before fixing it
  3. 03Refactor while checking that behavior is preserved
  4. 04Test API contracts and business logic

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/bobmatnyc/claude-mpm-skills --skill test-driven-development

After installing, type/test-driven-developmentin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

metadata.json
references/
anti-patterns.md
examples.md
integration.md
philosophy.md
workflow.md

Details

From the project README

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):

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):

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:

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

def get_user_stub(user_id):
    return User(id=user_id, name="Test User")

Mock: Verifies interactions

mock_service = Mock()
service.process_payment(payment_data)
mock_service.process_payment.assert_called_once_with(payment_data)

Fake: Working implementation (simplified)

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

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