version: "1.0.1" name: test-data-generation description: > Generate realistic, consistent test data using factories, fixtures, and fake data libraries. Use for test data, fixtures, mock data, faker, test builders, and seed data generation.

Test Data Generation

Table of Contents

• Overview
• When to Use
• Quick Start
• Reference Guides
• Best Practices

Overview

Test data generation creates realistic, consistent, and maintainable test data for automated testing. Well-designed test data reduces test brittleness, improves readability, and makes it easier to create diverse test scenarios.

When to Use

• Creating fixtures for integration tests
• Generating fake data for development databases
• Building test data with complex relationships
• Creating realistic user inputs for testing
• Seeding test databases
• Generating edge cases and boundary values
• Building reusable test data factories

Quick Start

Minimal working example:

// tests/factories/userFactory.js
const { faker } = require("@faker-js/faker");
class UserFactory {
  static build(overrides = {}) {
    return {
      id: faker.string.uuid(),
      email: faker.internet.email(),
      firstName: faker.person.firstName(),
      lastName: faker.person.lastName(),
      age: faker.number.int({ min: 18, max: 80 }),
      phone: faker.phone.number(),
      address: {
        street: faker.location.streetAddress(),
        city: faker.location.city(),
        state: faker.location.state(),
        zip: faker.location.zipCode(),
        country: "USA",
      },
      role: "user",
      isActive: true,
      createdAt: faker.date.past(),
      ...overrides,
    };
  }
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Best Practices

✅ DO

• Use faker libraries for realistic data
• Create reusable factories for common objects
• Make factories flexible with overrides
• Generate unique values where needed (emails, IDs)
• Use builders for complex object construction
• Create fixtures for integration test setup
• Generate edge cases (empty strings, nulls, boundaries)
• Keep test data deterministic when possible

❌ DON'T

• Hardcode test data in multiple places
• Use production data in tests
• Generate truly random data for reproducible tests
• Create overly complex factory hierarchies
• Ignore data relationships and constraints
• Generate massive datasets for simple tests
• Forget to clean up generated data
• Use the same test data for all tests