test-driven-development

name	test-driven-development
description	Use when implementing any feature or bugfix, before writing implementation code
domain	development
author	oyi77
license	Apache-2.0
subdomain	software-development
tags	["coding","driven","software-engineering","test","testing"]
version	1.0.0

persona: name: "Domain Expert" title: "Master of Test Driven Development" expertise: ['Specialized Knowledge', 'Best Practices', 'Industry Standards'] philosophy: "Excellence through expertise." credentials: ['Industry leader', 'Practiced expert', 'Thought leader'] principles: ['Quality first', 'Continuous improvement', 'Evidence-based decisions', 'Customer focus']

Test-Driven Development (TDD)

World-Class Expert Persona

Kent Beck - Creator of Test-Driven Development and Extreme Programming

• Credentials: Author of "Test-Driven Development by Example", "Extreme Programming Explained", pioneered TDD methodology
• Expertise: Test-first development, evolutionary design, refactoring, agile practices, software craftsmanship
• Philosophy: "I'm not a great programmer; I'm just a good programmer with great habits" - TDD is the habit that makes good programmers great
• Core Principles:
  • Red-Green-Refactor is sacred - never skip steps
  • Tests are specifications, not afterthoughts
  • Small steps prevent big mistakes
  • Confidence comes from passing tests, not clever code
  • Design emerges from refactoring, not upfront planning
  • If it's hard to test, the design is wrong

Overview

Write the test first. Watch it fail. Write minimal code to pass.

Anti-Rationalization Table

Rationalization	Reality
"I'll figure it out as I go"	A structured approach saves time and reduces errors. Follow the workflow in this skill rather than improvising.
"I already know this topic"	Familiarity breeds shortcuts. Use the checklist to verify you haven't missed critical steps.
"This doesn't apply to my situation"	The patterns here generalize across contexts. Adapt, don't skip — the underlying principles hold.
"One more tool will fix it"	Adding complexity rarely solves process gaps. Master the core workflow first.

When to Use

Trigger phrases:

• "test driven development"

• "New features"

• "Bug fixes"

• "Refactoring"

• New features

• Bug fixes

• Refactoring

Exceptions:

• Throwaway prototypes
• Generated code

The Iron Law

NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST

Write code before test? Delete it. Start over.

Red-Green-Refactor

• Configure before, bugfix, code, development, driven settings before first use

RED: Write Failing Test

Write minimal test showing expected behavior.

test('retries 3 times', async () => {
  let attempts = 0;
  const op = () => { attempts++; return attempts >= 3 ? 'ok' : fail(); };
  expect(await retry(op)).toBe('ok');
  expect(attempts).toBe(3);
});

Requirements: One behavior, clear name, real code

GREEN: Minimal Code

Write simplest code to pass the test.

• No "while I'm here" improvements
• Just make it pass

REFACTOR: Clean Up

• Improve code structure
• Keep tests passing
• Don't add new behavior if (i === 2) throw e; } } throw new Error('unreachable'); }

Just enough to pass
</Good>

<Bad>
```typescript
async function retryOperation<T>(
  fn: () => Promise<T>,
  options?: {
    maxRetries?: number;
    backoff?: 'linear' | 'exponential';
    onRetry?: (attempt: number) => void;
  }
): Promise<T> {
  // YAGNI
}

Over-engineered

Don't add features, refactor other code, or "improve" beyond the test.

Verify GREEN

• Run tests
• Confirm passes
• Fix code, not test

REFACTOR

After green: remove duplication, improve names

Repeat

Next failing test for next feature.

Good Tests

• Minimal: One thing per test
• Clear: Name describes behavior
• Shows intent: Demonstrates desired API

"Tests after achieve the same goals - it's spirit not ritual"

No. Tests-after answer "What does this do?" Tests-first answer "What should this do?"

Tests-after are biased by your implementation. You test what you built, not what's required. You verify remembered edge cases, not discovered ones.

Tests-first force edge case discovery before implementing. Tests-after verify you remembered everything (you didn't).

30 minutes of tests after ≠ TDD. You get coverage, lose proof tests work.

Common Rationalizations

Excuse	Reality
"Too simple to test"	Simple code breaks. Test takes 30 seconds.
"I'll test after"	Tests passing immediately prove nothing.
"Tests after achieve same goals"	Tests-after = "what does this do?" Tests-first = "what should this do?"
"Already manually tested"	Ad-hoc ≠ systematic. No record, can't re-run.
"Deleting X hours is wasteful"	Sunk cost fallacy. Keeping unverified code is technical debt.
"Keep as reference, write tests first"	You'll adapt it. That's testing after. Delete means delete.
"Need to explore first"	Fine. Throw away exploration, start with TDD.
"Test hard = design unclear"	Listen to test. Hard to test = hard to use.
"TDD will slow me down"	TDD faster than debugging. Pragmatic = test-first.
"Manual test faster"	Manual doesn't prove edge cases. You'll re-test every change.
"Existing code has no tests"	You're improving it. Add tests for existing code.

Red Flags - STOP and Start Over

• Code before test
• Test after implementation
• Test passes immediately
• Can't explain why test failed
• Tests added "later"
• Rationalizing "just this once"
• "I already manually tested it"
• "Tests after achieve the same purpose"
• "It's about spirit not ritual"
• "Keep as reference" or "adapt existing code"
• "Already spent X hours, deleting is wasteful"
• "TDD is dogmatic, I'm being pragmatic"
• "This is different because..."

All of these mean: Delete code. Start over with TDD.

Example: Bug Fix

Bug: Empty email accepted

RED

test('rejects empty email', async () => {
  const result = await submitForm({ email: '' });
  expect(result.error).toBe('Email required');
});

Verify RED

$ npm test
FAIL: expected 'Email required', got undefined

GREEN

function submitForm(data: FormData) {
  if (!data.email?.trim()) {
    return { error: 'Email required' };
  }
  // ...
}

Verify GREEN

$ npm test
PASS

REFACTOR Extract validation for multiple fields if needed.

Verification Checklist

Before marking work complete:

• Every new function/method has a test
• Watched each test fail before implementing
• Each test failed for expected reason (feature missing, not typo)
• Wrote minimal code to pass each test
• All tests pass
• Output pristine (no errors, warnings)
• Tests use real code (mocks only if unavoidable)
• Edge cases and errors covered

Can't check all boxes? You skipped TDD. Start over.

When Stuck

Problem	Solution
Don't know how to test	Write wished-for API. Write assertion first. Consult your human partner.
Test too complicated	Design too complicated. Simplify interface.
Must mock everything	Code too coupled. Use dependency injection.
Test setup huge	Extract helpers. Still complex? Simplify design.

Debugging Integration

Bug found? Write failing test reproducing it. Follow TDD cycle. Test proves fix and prevents regression.

Never fix bugs without a test.

Testing Anti-Patterns

When adding mocks or test utilities, read @testing-anti-patterns.md to avoid common pitfalls:

• Testing mock behavior instead of real behavior
• Adding test-only methods to production classes
• Mocking without understanding dependencies

Final Rule

Production code → test exists and failed first
Otherwise → not TDD

When to Use

• Implementing any feature
• Fixing any bug
• Before writing implementation code

When NOT to Use

• Exploratory work
• Quick prototyping
• When test infrastructure isn't available

Quick Reference

• Write test first, watch it fail
• Write minimal code to pass
• Refactor
• No exceptions without explicit approval

Common Mistakes

• Writing tests after code
• Not watching test fail first
• Writing too much code to pass test
• Skipping refactoring step
• Not using the testing-anti-patterns guide

Red Flags

• Code changes are made without running the existing test suite
• Agent does not handle error cases or edge conditions
• Watch for shortcuts and skipped steps

Verification

After completing this skill, confirm:

• All existing tests pass after code changes are applied
• Error handling covers documented failure modes and edge cases
• All required outputs generated
• Success criteria met

Process

1. Analyze the task requirements
2. Apply domain expertise
3. Verify output quality