Software Testing Strategy

Software Testing Strategy

Purpose

Strategic guidance for designing effective test suites: what to test, where to test it, how to structure it. Use tdd-enforcement for tactical test-first workflow.

Iron Laws

1. Fast Feedback - Unit tests in milliseconds, integration in seconds, full e2e under 30 minutes
2. Deterministic - No random inputs, no real clocks, no network timing. Every run identical.
3. Test Behavior, Not Implementation - Verify what code does, not how it does it
4. Test at Appropriate Level - Don't use e2e for business logic, don't mock everything in unit tests
5. Tests Are Production Code - Same quality standards: readability, maintainability, simplicity
6. Risk-Based Coverage - Focus on critical paths and edge cases, not percentage targets

The Testing Pyramid

Unit (70%): Business logic, algorithms, validations. No I/O. Hundreds/thousands of tests.

Integration (20%): Component interactions, database queries, API contracts. Real dependencies.

E2E (10%): Critical user journeys only. Top 20% of journeys = 80% of business value.

Architecture for Testability

Problem: Logic tangled with I/O requires heavy mocking and slow tests.

Solution: Separate decisions from effects (see writing-code skill for full pattern).

# Decision (pure, fast unit test)
def users_needing_reminder(users, cutoff_date):
    return [u for u in users if u.expires_at <= cutoff_date and not u.reminded]

# Effect (thin orchestration, integration test)
def send_reminders():
    users = db.find_all()
    to_remind = users_needing_reminder(users, today() + 7.days)
    email.send_batch(generate_emails(to_remind))

Result: More logic in pure functions = more fast unit tests = testing pyramid economics.

Test Design Patterns

AAA Pattern (Arrange-Act-Assert)

def test_withdrawing_more_than_balance_raises_error():
    account = Account(balance=100)          # Arrange
    with pytest.raises(InsufficientFundsError):
        account.withdraw(150)               # Act + Assert

Test Builder Pattern

const admin = new UserBuilder().withRoles('admin').build();
const minor = new UserBuilder().withAge(17).build();

Use for complex object creation. Provides defaults, fluent interface, reusability.

Test Doubles

Rule: Mock external systems, not your own components. Test state, not interactions.

Parameterized Tests

@pytest.mark.parametrize("input,expected", [
    ("Hello World", "hello-world"),
    ("HELLO WORLD", "hello-world"),
    ("Hello, World!", "hello-world"),
])
def test_slugify(input, expected):
    assert slugify(input) == expected

Anti-Patterns

Test Level Selection

Legacy Code Testing

Characterization Tests

When you don't know what code should do, capture what it currently does:

def test_legacy_calculator_current_behavior():
    calc = LegacyCalculator()
    assert calc.calculate(5, "A") == 47.50  # Document current behavior

Finding Seams

Add injection points for tests:

# Before: Hard to test
def process(order)
  gateway = PaymentGateway.new(ENV['KEY'])
  gateway.charge(order.amount)
end

# After: Testable via injection
def process(order, gateway: PaymentGateway.new(ENV['KEY']))
  gateway.charge(order.amount)
end

Test Quality Checklist

• Names describe behavior, not implementation
• Tests are isolated (no shared state)
• Setup is clear and minimal
• Assertions are simple and focused
• Critical paths have multiple test cases
• Edge cases covered
• Error paths tested
• No complex logic in tests
• Tests run fast at appropriate level

Key Takeaways

1. Testing pyramid 70/20/10 - Unit base, integration middle, e2e top
2. Test behavior, not implementation - Tests survive refactoring
3. Risk-based coverage - Focus on critical paths, not percentages
4. Separate decisions from effects - Enables fast unit tests (see writing-code skill)
5. Mock external systems only - Test state, not interactions
6. Zero tolerance for flaky tests - Fix immediately or delete