Red-Green-Refactor Methodology

You are following the RED-GREEN-REFACTOR cycle for test-driven development. Every new feature, bug fix, or behavior change starts with a failing test.

The Cycle

1. RED Phase — Write a Failing Test

1. Understand the requirement — what specific behavior must exist?
2. Write one test asserting that behavior
3. Run the test — it MUST fail (red)
4. Verify the failure reason — not a syntax error, but a missing implementation

The test should be focused on ONE behavior, named descriptively, and use clear assertions.

Executable example (Jest):

// calculateTotal.test.js
const { calculateTotal } = require('./calculateTotal');

describe('calculateTotal', () => {
  it('should apply 10% discount when total exceeds 100', () => {
    const items = [{ price: 60 }, { price: 60 }]; // total = 120
    expect(calculateTotal(items)).toBe(108); // 120 * 0.90
  });
});

Running this now produces:

Cannot find module './calculateTotal'

— correct RED state.

---

2. GREEN Phase — Make the Test Pass

Write the minimum code needed to pass the test. Don't add anything extra.

// calculateTotal.js
function calculateTotal(items) {
  const total = items.reduce((sum, item) => sum + item.price, 0);
  return total > 100 ? total * 0.9 : total;
}
module.exports = { calculateTotal };

Run the test — it passes. GREEN achieved. Stop here; resist adding more logic.

---

3. REFACTOR Phase — Improve the Code

With a passing test as your safety net, clean up the implementation. Run tests after every change.

// calculateTotal.js — refactored for clarity
const DISCOUNT_THRESHOLD = 100;
const DISCOUNT_RATE = 0.9;

function calculateTotal(items) {
  const subtotal = items.reduce((sum, { price }) => sum + price, 0);
  return subtotal > DISCOUNT_THRESHOLD ? subtotal * DISCOUNT_RATE : subtotal;
}
module.exports = { calculateTotal };

Test still passes — GREEN maintained. Constants now communicate intent.

---

End-to-End Example: Adding a New Behavior

Next requirement: apply a 15% discount when total exceeds 200.

RED — write the failing test first:

it('should apply 15% discount when total exceeds 200', () => {
  const items = [{ price: 110 }, { price: 110 }]; // total = 220
  expect(calculateTotal(items)).toBe(187); // 220 * 0.85
});

GREEN — extend the implementation minimally:

function calculateTotal(items) {
  const subtotal = items.reduce((sum, { price }) => sum + price, 0);
  if (subtotal > 200) return subtotal * 0.85;
  if (subtotal > 100) return subtotal * 0.9;
  return subtotal;
}

REFACTOR — remove duplication with a tiered structure:

const DISCOUNT_TIERS = [
  { threshold: 200, rate: 0.85 },
  { threshold: 100, rate: 0.9 },
];

function calculateTotal(items) {
  const subtotal = items.reduce((sum, { price }) => sum + price, 0);
  const tier = DISCOUNT_TIERS.find(({ threshold }) => subtotal > threshold);
  return tier ? subtotal * tier.rate : subtotal;
}

Both tests pass — ready for the next cycle.

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Workflow Steps

1. Create or open the test file first
2. Write ONE failing test for the smallest testable unit
3. Implement minimally — just enough to pass
4. Refactor if needed — while tests stay green
5. Repeat for the next behavior

Decision Points

Write a new test when:

• Adding a new feature or behavior
• Fixing a bug (test the bug first, then fix it)
• Handling an edge case discovered during implementation

Don't write a test when:

• Pure refactoring (existing tests already cover the behavior)
• Non-functional changes (formatting, comments)
• Third-party library internals

Verification Checklist

• All new code has corresponding tests
• Tests fail when the feature is removed
• Tests pass consistently (not flaky)
• Code has been refactored for clarity
• No unnecessary code was added

Common Mistakes to Avoid

1. Writing tests after code — defeats the design benefit of TDD
2. Writing multiple tests at once — one test drives one change
3. Passing tests with hacks — the test should drive good design
4. Skipping the refactor phase — technical debt accumulates
5. Testing implementation details — test behavior, not internals

Integration with Other Skills

• test-patterns: Patterns for structuring tests
• anti-patterns: Common testing mistakes to avoid
• debugging/root-cause-analysis: When tests reveal unexpected failures