Co-Pilot / 辅助式
更新于 a month ago

test-driven-development

Oobra
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obra/superpowers/skills/test-driven-development
74
Agent 评分

💡 摘要

一个严格的测试驱动开发方法指南和执行者,要求在任何实现代码之前编写并看到测试失败。

🎯 适合人群

学习最佳实践的初级开发人员在团队中强制执行代码质量的高级工程师建立团队工作流程的技术负责人对抗技术债务的独立开发者

🤖 AI 吐槽:这个技能是个TDD狂热分子,如果你在写测试前瞥了一眼编辑器,它都会让你删掉整个代码库。

安全分析低风险

该技能作为流程指南,不涉及代码执行、网络或文件系统访问,直接安全风险极低。主要风险是间接的:其教条式执行可能迫使开发人员以TDD纯粹性为名绕过安全审查流程。缓解措施:确保安全需求首先作为失败的测试被捕获。


name: test-driven-development description: Use when implementing any feature or bugfix, before writing implementation code

Test-Driven Development (TDD)

Overview

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

Core principle: If you didn't watch the test fail, you don't know if it tests the right thing.

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

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 A FAILING TEST FIRST

Write code before the test? Delete it. Start over.

No exceptions:

  • Don't keep it as "reference"
  • Don't "adapt" it while writing tests
  • Don't look at it
  • Delete means delete

Implement fresh from tests. Period.

Red-Green-Refactor

digraph tdd_cycle { rankdir=LR; red [label="RED\nWrite failing test", shape=box, style=filled, fillcolor="#ffcccc"]; verify_red [label="Verify fails\ncorrectly", shape=diamond]; green [label="GREEN\nMinimal code", shape=box, style=filled, fillcolor="#ccffcc"]; verify_green [label="Verify passes\nAll green", shape=diamond]; refactor [label="REFACTOR\nClean up", shape=box, style=filled, fillcolor="#ccccff"]; next [label="Next", shape=ellipse]; red -> verify_red; verify_red -> green [label="yes"]; verify_red -> red [label="wrong\nfailure"]; green -> verify_green; verify_green -> refactor [label="yes"]; verify_green -> green [label="no"]; refactor -> verify_green [label="stay\ngreen"]; verify_green -> next; next -> red; }

RED - Write Failing Test

Write one minimal test showing what should happen.

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

Requirements:

  • One behavior
  • Clear name
  • Real code (no mocks unless unavoidable)

Verify RED - Watch It Fail

MANDATORY. Never skip.

npm test path/to/test.test.ts

Confirm:

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

Test passes? You're testing existing behavior. Fix test.

Test errors? Fix error, re-run until it fails correctly.

GREEN - Minimal Code

Write simplest code to pass the test.

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

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.

Good Tests

| Quality | Good | Bad | |---------|------|-----| | Minimal | One thing. "and" in name? Split it. | test('validates email and domain and whitespace') | | Clear | Name describes behavior | test('test1') | | Shows intent | Demonstrates desired API | Obscures what code should do |

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" ≠ 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 - 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. Ask 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

No exceptions without your human partner's permission.

五维分析
清晰度9/10
创新性3/10
实用性8/10
完整性10/10
可维护性7/10
优缺点分析

优点

  • 强制执行纪律严明、高置信度的开发周期
  • 清晰解释了TDD规则背后的原理
  • 提供了具体的示例和反模式
  • 包含完整性的验证清单

缺点

  • 极其教条的语气可能会疏远务实的开发人员
  • 缺乏对探索性编码或原型设计的灵活性
  • 假设了特定的项目结构(例如 npm test)
  • 没有实际的代码执行或分析,仅是流程指导

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