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Vibe Coding · 课时

使用人工智能添加测试

在用户发现问题之前捕获故障

使用人工智能添加测试 是 CoddyKit 上的免费 Vibe Coding 课时。 这是第 1 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 Vibe Coding 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Vibe Coding 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

Why Tests Save Your App

You vibe-coded an app. It works today. But next week you ask AI to add a feature, and something else silently breaks. Tests are tiny programs that check your app still does the right thing.

Think of tests as a safety net: every time you change code, they re-run and shout if anything broke. With AI, you don't even have to write them by hand — you describe what should happen and let the AI generate the tests.

What a Test Actually Looks Like

A test calls your code with some input and checks the output is what you expect. If it isn't, the test fails and points at the problem.

Here's a real, runnable example: a function plus a check.

function add(a, b) {
  return a + b;
}

// a tiny hand-made 'test'
function expectEqual(actual, expected, label) {
  if (actual === expected) console.log('PASS: ' + label);
  else console.log('FAIL: ' + label + ' (got ' + actual + ')');
}

expectEqual(add(2, 3), 5, 'adds two numbers');
expectEqual(add(-1, 1), 0, 'handles negatives');

Let AI Write the Tests

You rarely write tests from scratch anymore. You paste your function into Cursor, Claude Code, or Copilot and ask for tests. The key is telling the AI which cases matter: normal input, weird input, and edge cases (empty, zero, negative, huge).

Here is a prompt you can copy.

Here is my function:

function discount(price, percent) {
  return price - (price * percent / 100);
}

Write tests using Vitest. Cover:
- a normal case (100 at 20%)
- 0% discount
- 100% discount
- a negative price (should it even be allowed?)
Use describe/it/expect. Keep it short.

Test Runners: The Tool That Runs Tests

You don't run tests by hand. A test runner finds all your test files, runs them, and prints a clean PASS/FAIL report. For JavaScript the popular ones are Vitest and Jest.

Ask your AI tool to set one up — it knows the commands and config so you don't have to memorize them.

Set up Vitest in this project. Add the dependency, a "test" script in package.json, and a sample test file so I can run `npm test` and see it pass.

Anatomy of a Real Test File

Most JS tests share the same shape: describe groups related tests, it (or test) is one case, and expect checks a value. AI generates this pattern constantly, so it pays to recognize it.

This is what the AI typically hands back.

import { describe, it, expect } from 'vitest';
import { discount } from './pricing';

describe('discount', () => {
  it('takes 20% off 100', () => {
    expect(discount(100, 20)).toBe(80);
  });

  it('returns full price at 0%', () => {
    expect(discount(100, 0)).toBe(100);
  });
});

Tests as a Spec for the AI

Here's a power move: write the tests first, then ask AI to make them pass. The tests become a precise description of what you want, with zero ambiguity.

This flips the workflow — instead of describing behavior in fuzzy words, you describe it in checkable code.

These tests describe a function I want. Write the `slugify` function so ALL of these pass:

import { slugify } from './slug';
expect(slugify('Hello World')).toBe('hello-world');
expect(slugify('  Spaced  Out ')).toBe('spaced-out');
expect(slugify('A/B & C')).toBe('a-b-c');

Return only the function.

Don't Trust Tests That Always Pass

AI sometimes writes tests that can't fail — they assert something trivially true, or they re-implement the bug. A passing test that proves nothing is worse than no test.

Quick check: temporarily break your function on purpose. If the test still passes, it's a fake test. Ask the AI to make it actually verify the behavior.

// Suspicious: this passes no matter what discount() returns
it('works', () => {
  const result = discount(100, 20);
  expect(typeof result).toBe('number'); // too weak!
});

// Better: checks the actual value
it('takes 20% off 100', () => {
  expect(discount(100, 20)).toBe(80);
});

Cover the Edge Cases

Bugs hide in the unusual inputs: empty strings, zero, negative numbers, missing values, very large lists. AI is great at brainstorming these if you ask.

Use a prompt that pushes for the weird cases on purpose.

List the edge cases I should test for this function, then write a test for each:

function averageScore(scores) {
  return scores.reduce((a, b) => a + b, 0) / scores.length;
}

Think about: empty array, one item, negatives, non-numbers. What should happen for each?

Run Tests Automatically (CI)

The real win: tests run on every change, automatically. When you push to GitHub, a service like GitHub Actions re-runs your whole test suite. If something broke, you find out in minutes — not from an angry user.

You don't have to learn the YAML config. Ask your AI to write it.

Create a GitHub Actions workflow that runs `npm install` and `npm test` on every push and pull request. Use Node 20. Put it in .github/workflows/test.yml.

A Sensible Testing Rhythm

You don't need 100% coverage to benefit. A practical rhythm for vibe coders:

  • Test the logic that matters — pricing, auth, data parsing, anything users feel.
  • Skip trivial UI glue at first.
  • Add a test every time you fix a bug so it never comes back.

Ask AI: What are the 5 most important things to test in this app? and start there.

Reading the Test Report

When tests fail, the runner tells you exactly what it expected vs. what it got. Don't panic — copy that whole report to your AI and ask it to fix the code or the test (you decide which is wrong).

My test failed with this output:

FAIL  src/pricing.test.js
  discount > takes 20% off 100
  expected 80 but got 120

Here is the discount function: <paste it>
Is the function wrong or the test wrong? Fix the right one and explain.

Quick Check

You ask AI for tests and every single one passes immediately — even after you intentionally break the function. What's the most likely problem?

Recap: Tests Are Your Safety Net

You learned why tests matter when AI is changing your code, what a test looks like, and how to let AI write them for you. Key habits:

  • Tell the AI which cases matter, especially edge cases.
  • Use a runner like Vitest and run tests on every change with CI.
  • Verify tests can actually fail — break the code on purpose.
  • Add a test whenever you fix a bug.

Next up: keeping your AI-generated code secure.

常见问题解答

「使用人工智能添加测试」课时是免费的吗？

是的 — 「使用人工智能添加测试」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Vibe Coding 课程的其余内容，请升级到 CoddyKit PRO。 Vibe Coding 课程共包含 4 节课。

「使用人工智能添加测试」这节课中我会学到什么？

在用户发现问题之前捕获故障 你通过在浏览器中直接运行的动手代码来练习 Vibe Coding，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Vibe Coding 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Vibe Coding 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 1 节课，共 4 节。

「使用人工智能添加测试」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Vibe Coding 课中编写并运行代码吗？

能。每节 Vibe Coding 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

此课程中的所有课时

  1. 使用人工智能添加测试
  2. 人工智能代码安全基础
  3. 保持代码可维护
  4. 性能与成本
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