Test Driven Development

Test-Driven Development

Invariant Principles

1. Failure Proves Testing - Test passing immediately proves nothing. Only watching failure proves test detects what it claims.
2. Order Creates Trust - Tests-first answer "what should this do?" Tests-after answer "what does this do?" Fundamentally different questions.
3. Minimal Sufficiency - Write exactly enough code to pass. YAGNI violations compound into untested complexity.
4. Deletion Over Adaptation - Code written before tests is contaminated. Keeping "as reference" means testing after. Delete means delete.

Violating the letter of the rules is violating the spirit of the rules.

Inputs

Outputs

When to Use

Always:

• New features
• Bug fixes
• Refactoring
• Behavior changes

Exceptions (ask your human partner):

• Throwaway prototypes
• Generated code
• Configuration files

Thinking "skip TDD just this once"? Stop. That's rationalization.

The Iron Law

NO PRODUCTION CODE WITHOUT FAILING TEST FIRST

Code before test? Delete. Start over. No "reference," no "adapting," no looking at it.

Reasoning Schema

Red-Green-Refactor

RED: Write Failing Test

One behavior. Clear name. Real code (mocks only if unavoidable).

const result = await retryOperation(operation);

expect(result).toBe('success'); expect(attempts).toBe(3); });

Clear name, tests real behavior, one thing
</Good>

<Bad>
```typescript
test('retry works', async () => {
  const mock = jest.fn()
    .mockRejectedValueOnce(new Error())
    .mockRejectedValueOnce(new Error())
    .mockResolvedValueOnce('success');
  await retryOperation(mock);
  expect(mock).toHaveBeenCalledTimes(3);
});

Vague name, tests mock not code

Verify RED: Watch It Fail

MANDATORY. Never skip.

npm test path/to/test.test.ts

Confirm:

• Fails (not errors)
• Failure message expected
• Fails because feature missing (not typos)

Test passes? Testing existing behavior. Fix test. Test errors? Fix error, re-run until it fails correctly.

GREEN: Minimal Code

Simplest code to pass. No features, no refactoring, no "improvements."

Verify GREEN: Watch It Pass

MANDATORY.

npm test path/to/test.test.ts

Confirm:

• Test passes
• Other tests still pass
• Output pristine (no errors, warnings)

Test fails? Fix code, not test. Other tests fail? Fix now.

REFACTOR: Clean Up

After green only. Remove duplication, improve names, extract helpers. Keep tests green. Don't add behavior.

Repeat

Next failing test for next feature. The cycle continues until all behavior is implemented.

Good Tests

Evidence Requirements

Why Order Matters

"I'll write tests after to verify it works"

Tests written after code pass immediately. Passing immediately proves nothing:

• Might test wrong thing
• Might test implementation, not behavior
• Might miss edge cases you forgot
• You never saw it catch the bug

Test-first forces you to see the test fail, proving it actually tests something.

"I already manually tested all the edge cases"

Manual testing is ad-hoc. You think you tested everything but:

• No record of what you tested
• Can't re-run when code changes
• Easy to forget cases under pressure
• "It worked when I tried it" does not equal comprehensive

Automated tests are systematic. They run the same way every time.

"Deleting X hours of work is wasteful"

Sunk cost fallacy. The time is already gone. Your choice now:

• Delete and rewrite with TDD (X more hours, high confidence)
• Keep it and add tests after (30 min, low confidence, likely bugs)

The "waste" is keeping code you can't trust. Working code without real tests is technical debt.

"TDD is dogmatic, being pragmatic means adapting"

TDD IS pragmatic:

• Finds bugs before commit (faster than debugging after)
• Prevents regressions (tests catch breaks immediately)
• Documents behavior (tests show how to use code)
• Enables refactoring (change freely, tests catch breaks)

"Pragmatic" shortcuts = debugging in production = slower.

"Tests after achieve the same goals"

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 does not equal TDD. You get coverage, lose proof tests work.

Anti-Patterns

All mean: Delete code. Start over with TDD.

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.

Common Rationalizations

Self-Check

Before marking complete:

• Every function has test
• Watched each test fail before implementing
• Failed for expected reason (feature missing, not typo)
• Wrote minimal code to pass
• All tests pass, output pristine
• Tests use real code (mocks only if unavoidable)
• Edge cases and errors covered

If ANY unchecked: Skipped TDD. Start over.

When Stuck

Bug Fix Pattern

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' };
  }
  // ...existing logic
}

Verify GREEN

$ npm test
PASS

REFACTOR Extract validation for multiple fields if needed.

Never fix bugs without test.

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, avoid common pitfalls:

Test Speed & Scope

Fast tests enable tight red-green-refactor cycles. Slow tests break flow and discourage re-running.

Design for speed:

• Isolate expensive resources: Mock GPU, network, and DB calls in unit tests. Real resources belong in integration tests only.
• Smallest possible inputs: 4x4 matrices, not 1024x1024. Save large inputs for performance/integration tests.
• Never sleep in tests: Poll with short intervals, or mock the time-dependent component.
• Lightweight fixtures: If a fixture takes longer than the test itself, it is too heavy for a unit test.

Apply marks proactively when writing new tests. A test that calls a GPU kernel is a GPU test even if it is fast today. Common marks: slow, gpu/hardware, network/external, integration, smoke.

Scope test runs to changes: If src/auth/login.py changed, run tests/test_login.py, not the entire suite. Run the full suite once at the end of a work unit, not after every edit.

Final Rule

Production code -> test exists and failed first
Otherwise -> not TDD

No exceptions without your human partner's permission.