Testing and quality
Learn how to use AI to improve testing efficiency and quality, and explore best practices for AI-assisted test case generation, test code writing, test optimization, and more.
Learn AI-driven testing using Sequential Thinking
The application of AI in testing involves multiple aspects, usingStructured thinking methodsCan help you systematically master:
Overview of test types
Quickly understand test types and provide background knowledge for AI practice.
Unit testing
Test a single function or component, with fast feedback and high coverage.
Integration testing
Test the collaboration of multiple modules and verify interfaces and data flows.
E2E testing
End-to-end testing, simulating real user interactions.
Performance testing
Test system performance and load capacity.
Best practices for AI in testing
Use AI to improve testing efficiency and quality, with AI-assisted practices across the full process from test case generation to test automation.
AI-assisted test case generation
Use AI to generate unit test cases
Describe the function’s behavior to AI and have it generate complete test cases:
Prompt template:
I need to generate unit test cases for the following function:
// utils/calculateTotal.ts
export function calculateTotal(items: Item[]): number {
if (!items || items.length === 0) return 0
return items.reduce((sum, item) => {
if (item.price && item.quantity) {
return sum + item.price * item.quantity
}
return sum
}, 0)
}
interface Item {
price?: number
quantity?: number
}
Please use Jest/Vitest to generate test cases, including:
- Normal case tests
- Boundary case tests (empty array, null, undefined)
- Exceptional case tests (missing price or quantity)
- Organize tests using describe and it
- Use clear test descriptionsAI-generated test case examples
// utils/calculateTotal.test.ts
import { describe, it, expect } from 'vitest'
import { calculateTotal } from './calculateTotal'
describe('calculateTotal', () => {
it('should return 0 for empty array', () => {
expect(calculateTotal([])).toBe(0)
})
it('should return 0 for null or undefined', () => {
expect(calculateTotal(null as any)).toBe(0)
expect(calculateTotal(undefined as any)).toBe(0)
})
it('should calculate total for valid items', () => {
const items = [
{ price: 10, quantity: 2 },
{ price: 5, quantity: 3 }
]
expect(calculateTotal(items)).toBe(35) // 10*2 + 5*3 = 35
})
it('should ignore items without price', () => {
const items = [
{ price: 10, quantity: 2 },
{ quantity: 3 }
]
expect(calculateTotal(items)).toBe(20)
})
it('should ignore items without quantity', () => {
const items = [
{ price: 10, quantity: 2 },
{ price: 5 }
]
expect(calculateTotal(items)).toBe(20)
})
it('should handle zero price or quantity', () => {
const items = [
{ price: 0, quantity: 2 },
{ price: 10, quantity: 0 }
]
expect(calculateTotal(items)).toBe(0)
})
})AI-generated integration test scenarios
Prompt:
I need to generate integration test scenarios for the user registration API:
API: POST /api/users/register
Request body: { email, password, name }
Response: { id, email, name, createdAt }
Please generate test cases including:
- Successful registration scenario
- Email already exists scenario
- Insufficient password strength scenario
- Missing required field scenario
- Use the test database
- Clean up test dataAI generates the E2E test flow
Prompt: I need to generate E2E tests for the shopping cart flow: User flow: 1. Visit the homepage 2. Search for products 3. Add product to cart 4. View cart 5. Checkout 6. Fill in order information 7. Submit order Please use Playwright to generate complete E2E test code, including: - Page navigation - Element locators - User interactions - Assertion checks - Error handling
TDD practice basics
Keep the core concepts and focus on showing how AI assists TDD. Using AI can quickly generate test cases, implementation code, and refactoring suggestions.
Red
Write failing tests and define the expected behavior
Green
Write the minimal implementation to make the tests pass
Refactoring (Refactor)
Optimize code and keep tests passing
AI-assisted TDD
AI can help at every stage of TDD: generating test cases, rapid implementation, and refactoring suggestions. See the "AI-assisted TDD practice" section above for detailed examples and Prompt templates.
Basics of testing tools
Keep the introduction to core tools and focus on showing how AI helps with tool selection.
Jest
JavaScript testing framework with built-in assertions and mocks
Vitest
Fast test framework, native Vite support, TypeScript friendly
Playwright
E2E testing framework with multi-browser support
AI-assisted tool selection
Use AI to choose the right testing tools based on the project's needs. Describe the project characteristics to AI (Next.js, TypeScript, need E2E testing, etc.), and it will recommend the right combination of tools and configuration plan.
Quality assurance basics
Keep the core concepts, and focus on showing how AI helps quality assurance.
Test strategy
- • Test pyramid: a large number of unit tests + a moderate number of integration tests + a small number of E2E tests
- • Prioritize critical paths: prioritize testing core business logic
- • Boundary testing: Test boundary conditions and exceptional cases
Code coverage
- • Line coverage: proportion of lines of code executed
- • Branch coverage: Proportion of executed code branches
- • Goal: Key code 80%+, overall 60%+
AI-assisted quality assurance
AI can analyze test strategies, generate quality reports, and identify uncovered code paths. Refer to the sections above on "AI-assisted coverage analysis" and "AI-driven test automation" for detailed examples and Prompt templates.
Practical examples
Through real code examples, learn how to use AI to improve testing efficiency and quality.
AI-generated test cases
Complete test case generation example (Prompt + result):
// 1. Provide requirements to AI
Prompt: "Generate unit tests for the calculateTotal function, including normal cases, boundary cases, and exception cases..."
// 2. Test cases generated by AI
describe('calculateTotal', () => {
it('should return 0 for empty array', () => {
expect(calculateTotal([])).toBe(0)
})
it('should calculate total for valid items', () => {
const items = [
{ price: 10, quantity: 2 },
{ price: 5, quantity: 3 }
]
expect(calculateTotal(items)).toBe(35)
})
// ... more test cases
})AI-optimized test code
Example of test code optimization (before and after optimization):
// Each test calls the real API
describe('UserService', () => {
it('should fetch user', async () => {
const user = await fetchUser('1') // real API call
expect(user.id).toBe('1')
})
it('should update user', async () => {
const user = await fetchUser('1') // repeated call
await updateUser('1', { name: 'New' })
expect(user.name).toBe('New')
})
})// AI suggestion: use Mock instead of the real API
vi.mock('./api', () => ({
fetchUser: vi.fn().mockResolvedValue({ id: '1', name: 'Test' }),
updateUser: vi.fn().mockResolvedValue({ id: '1', name: 'New' })
}))
describe('UserService', () => {
it('should fetch user', async () => {
const user = await fetchUser('1')
expect(user.id).toBe('1')
})
it('should update user', async () => {
await updateUser('1', { name: 'New' })
expect(updateUser).toHaveBeenCalledWith('1', { name: 'New' })
})
})AI analysis coverage
Coverage analysis and supplementary recommendation examples:
// AI coverage report
Coverage: 65%
Uncovered code:
- utils/validation.ts: 45%
- Error handling branch of validateEmail is untested
- Boundary cases of validatePassword are untested
AI-suggested test case additions:
it('should return false for invalid email', () => {
expect(validateEmail('invalid')).toBe(false)
expect(validateEmail('invalid@')).toBe(false)
expect(validateEmail('@domain.com')).toBe(false)
})Learning outcomes
After completing this chapter, you will:
- 1Understand the overview of test types (unit tests, integration tests, E2E tests, performance tests) and their applicable scenarios
- 2Master how to use AI to generate test cases (unit tests, integration tests, E2E test case generation)
- 3Able to use AI to assist with test code writing (test framework syntax, mock data generation, test data preparation)
- 4Able to use AI to analyze and optimize test performance (performance bottleneck analysis, test execution speed optimization, test refactoring)
- 5Master the methods of AI-assisted coverage analysis (coverage report analysis, identifying uncovered code paths, suggesting additional test cases)
- 6Can use AI-driven test automation (CI/CD configuration generation, test report analysis, test failure root cause prediction)
- 7Master AI-assisted TDD practices (test case generation, minimal implementation code generation, refactoring suggestions)