Test data generation
Skill a5c-ai/babysitter/library/specializations/qa-testing-automation/skills/test-data-generation
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Synthetic test data generation and management using Faker.js and similar tools. Generate realistic test data, create data factories, implement database seeding, and manage test data anonymization.
SKILL.md
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test-data-generation
You are test-data-generation - a specialized skill for synthetic test data generation and management, providing capabilities for creating realistic, reproducible test data.
Overview
This skill enables AI-powered test data management including:
- Generating realistic test data with Faker.js
- Creating data factories and builders
- Database seeding scripts
- Test data anonymization and masking
- Generating boundary value test data
- Configuring data cleanup strategies
- Creating deterministic test data with seeds
- Integration with ORM factories (Fishery, Factory Bot)
Prerequisites
- Node.js or Python environment
- Faker library installed (@faker-js/faker or faker-python)
- Database access for seeding operations
- Optional: ORM (Prisma, Sequelize, SQLAlchemy) for factory integration
Capabilities
1. Basic Data Generation
Generate realistic test data with Faker.js:
import { faker } from '@faker-js/faker';
// Generate user data
const generateUser = () => ({
id: faker.string.uuid(),
email: faker.internet.email(),
firstName: faker.person.firstName(),
lastName: faker.person.lastName(),
phone: faker.phone.number(),
address: {
street: faker.location.streetAddress(),
city: faker.location.city(),
state: faker.location.state(),
zipCode: faker.location.zipCode(),
country: faker.location.country()
},
company: faker.company.name(),
jobTitle: faker.person.jobTitle(),
avatar: faker.image.avatar(),
createdAt: faker.date.past(),
updatedAt: faker.date.recent()
});
// Generate multiple users
const users = faker.helpers.multiple(generateUser, { count: 100 });
2. Data Factory Pattern
Create reusable data factories:
import { faker } from '@faker-js/faker';
// User Factory
class UserFactory {
static defaults = {
id: () => faker.string.uuid(),
email: () => faker.internet.email(),
firstName: () => faker.person.firstName(),
lastName: () => faker.person.lastName(),
role: () => 'user',
isActive: () => true,
createdAt: () => faker.date.past()
};
static create(overrides = {}) {
const defaults = Object.fromEntries(
Object.entries(this.defaults).map(([key, fn]) => [key, fn()])
);
return { ...defaults, ...overrides };
}
static createMany(count, overrides = {}) {
return Array.from({ length: count }, () => this.create(overrides));
}
// Trait methods
static admin(overrides = {}) {
return this.create({ role: 'admin', ...overrides });
}
static inactive(overrides = {}) {
return this.create({ isActive: false, ...overrides });
}
}
// Usage
const user = UserFactory.create();
const admin = UserFactory.admin({ firstName: 'Admin' });
const users = UserFactory.createMany(50);
3. Fishery Factory (TypeScript)
Using Fishery for typed factories:
import { Factory } from 'fishery';
import { faker } from '@faker-js/faker';
interface User {
id: string;
email: string;
firstName: string;
lastName: string;
role: 'user' | 'admin';
profile: Profile;
}
interface Profile {
bio: string;
avatar: string;
}
const profileFactory = Factory.define<Profile>(() => ({
bio: faker.person.bio(),
avatar: faker.image.avatar()
}));
const userFactory = Factory.define<User>(({ associations, sequence }) => ({
id: faker.string.uuid(),
email: faker.internet.email(),
firstName: faker.person.firstName(),
lastName: faker.person.lastName(),
role: 'user',
profile: associations.profile || profileFactory.build()
}));
// Usage
const user = userFactory.build();
const admin = userFactory.build({ role: 'admin' });
const usersWithProfiles = userFactory.buildList(10, {}, {
associations: { profile: profileFactory.build() }
});
4. Database Seeding
Seed databases with test data:
// seed.js - Database seeding script
import { PrismaClient } from '@prisma/client';
import { faker } from '@faker-js/faker';
const prisma = new PrismaClient();
async function seed() {
// Set seed for reproducibility
faker.seed(12345);
// Clear existing data
await prisma.order.deleteMany();
await prisma.product.deleteMany();
await prisma.user.deleteMany();
// Create users
const users = await Promise.all(
Array.from({ length: 50 }, () =>
prisma.user.create({
data: {
email: faker.internet.email(),
name: faker.person.fullName(),
password: faker.internet.password()
}
})
)
);
// Create products
const products = await Promise.all(
Array.from({ length: 100 }, () =>
prisma.product.create({
data: {
name: faker.commerce.productName(),
description: faker.commerce.productDescription(),
price: parseFloat(faker.commerce.price()),
sku: faker.string.alphanumeric(8).toUpperCase(),
inStock: faker.datatype.boolean()
}
})
)
);
// Create orders
for (const user of users) {
const orderCount = faker.number.int({ min: 1, max: 5 });
for (let i = 0; i < orderCount; i++) {
await prisma.order.create({
data: {
userId: user.id,
status: faker.helpers.arrayElement(['pending', 'processing', 'shipped', 'delivered']),
total: parseFloat(faker.commerce.price({ min: 10, max: 500 })),
items: {
create: faker.helpers.arrayElements(products, { min: 1, max: 5 }).map(p => ({
productId: p.id,
quantity: faker.number.int({ min: 1, max: 3 }),
price: p.price
}))
}
}
});
}
}
console.log('Seeding complete!');
}
seed()
.catch(console.error)
.finally(() => prisma.$disconnect());
5. Boundary Value Generation
Generate edge case test data:
import { faker } from '@faker-js/faker';
const boundaryValues = {
// String boundaries
strings: {
empty: '',
singleChar: 'a',
maxLength: 'a'.repeat(255),
unicode: '日本語テスト',
emoji: '🎉🚀💡',
specialChars: '<script>alert("xss")</script>',
sqlInjection: "'; DROP TABLE users; --",
whitespace: ' spaces ',
newlines: 'line1\nline2\rline3'
},
// Number boundaries
numbers: {
zero: 0,
negative: -1,
maxInt: Number.MAX_SAFE_INTEGER,
minInt: Number.MIN_SAFE_INTEGER,
decimal: 0.1 + 0.2, // Famous floating point issue
infinity: Infinity,
nan: NaN
},
// Date boundaries
dates: {
epochStart: new Date(0),
farPast: new Date('1900-01-01'),
farFuture: new Date('2100-12-31'),
leapYear: new Date('2024-02-29'),
endOfMonth: new Date('2024-01-31'),
timezoneEdge: new Date('2024-03-10T02:30:00') // DST transition
},
// Array boundaries
arrays: {
empty: [],
single: [1],
large: Array.from({ length: 10000 }, (_, i) => i)
}
};
// Generate boundary test cases
function generateBoundaryTestCases(schema) {
const testCases = [];
for (const [field, config] of Object.entries(schema)) {
if (config.type === 'string') {
testCases.push(
{ [field]: '', expected: config.required ? 'error' : 'success' },
{ [field]: 'a'.repeat(config.maxLength + 1), expected: 'error' },
{ [field]: 'a'.repeat(config.maxLength), expected: 'success' }
);
}
if (config.type === 'number') {
testCases.push(
{ [field]: config.min - 1, expected: 'error' },
{ [field]: config.min, expected: 'success' },
{ [field]: config.max, expected: 'success' },
{ [field]: config.max + 1, expected: 'error' }
);
}
}
return testCases;
}
6. Data Anonymization
Anonymize production data for testing:
import { faker } from '@faker-js/faker';
import crypto from 'crypto';
const anonymize = {
// Consistent anonymization (same input = same output)
email: (email) => {
const hash = crypto.createHash('md5').update(email).digest('hex').slice(0, 8);
return `user_${hash}@example.com`;
},
// Full replacement
name: () => faker.person.fullName(),
// Partial masking
phone: (phone) => phone.replace(/\d(?=\d{4})/g, '*'),
// Format preservation
creditCard: (cc) => {
const last4 = cc.slice(-4);
return `****-****-****-${last4}`;
},
// Consistent fake data
ssn: (ssn) => {
faker.seed(crypto.createHash('md5').update(ssn).digest('hex'));
return faker.string.numeric('###-##-####');
},
// Address anonymization
address: () => ({
street: faker.location.streetAddress(),
city: faker.location.city(),
state: faker.location.state(),
zip: faker.location.zipCode()
})
};
// Anonymize dataset
function anonymizeDataset(records) {
return records.map(record => ({
...record,
email: anonymize.email(record.email),
name: anonymize.name(),
phone: anonymize.phone(record.phone),
creditCard: record.creditCard ? anonymize.creditCard(record.creditCard) : null,
address: anonymize.address()
}));
}
7. Multi-Locale Support
Generate data in different locales:
import { faker, Faker } from '@faker-js/faker';
import { de, fr, ja, es } from '@faker-js/faker';
// German locale
const fakerDE = new Faker({ locale: [de] });
const germanUser = {
name: fakerDE.person.fullName(),
address: fakerDE.location.streetAddress(),
city: fakerDE.location.city()
};
// Japanese locale
const fakerJA = new Faker({ locale: [ja] });
const japaneseUser = {
name: fakerJA.person.fullName(),
address: fakerJA.location.streetAddress(),
city: fakerJA.location.city()
};
// Generate test data for multiple locales
const locales = { de, fr, ja, es };
function generateMultiLocaleData(count = 10) {
return Object.entries(locales).flatMap(([code, locale]) => {
const localFaker = new Faker({ locale: [locale] });
return Array.from({ length: count }, () => ({
locale: code,
name: localFaker.person.fullName(),
email: localFaker.internet.email(),
phone: localFaker.phone.number(),
address: localFaker.location.streetAddress()
}));
});
}
8. Deterministic Data with Seeds
Create reproducible test data:
import { faker } from '@faker-js/faker';
// Set global seed for reproducibility
faker.seed(12345);
// Generate same data every time
const user1 = faker.person.fullName(); // Always same name
const user2 = faker.person.fullName(); // Always same name
// Reset seed for new sequence
faker.seed(12345);
const user1Again = faker.person.fullName(); // Same as user1
// Environment-based seeding
const testSeed = process.env.TEST_SEED || Date.now();
faker.seed(testSeed);
console.log(`Using seed: ${testSeed}`);
MCP Server Integration
This skill can leverage the following MCP servers for enhanced capabilities:
| Server | Description | Installation |
|---|---|---|
| funsjanssen/faker-mcp | Faker.js MCP Server | GitHub |
Best Practices
- Use seeds - Enable reproducible test data
- Factories over inline - Use factory patterns for maintainability
- Realistic but safe - Data should look real but not match real people
- Boundary coverage - Include edge cases in test data
- Cleanup - Implement data cleanup strategies
- Performance - Generate data in batches for large datasets
- Validation - Validate generated data matches expected schema
Process Integration
This skill integrates with the following processes:
test-data-management.js- All phases of test data handlinge2e-test-suite.js- E2E test data setupapi-testing.js- API test data generationenvironment-management.js- Environment data seeding
Output Format
When executing operations, provide structured output:
{
"operation": "generate",
"dataType": "users",
"count": 100,
"seed": 12345,
"locale": "en",
"schema": {
"id": "uuid",
"email": "email",
"name": "fullName"
},
"outputFile": "./test-data/users.json",
"statistics": {
"generated": 100,
"uniqueEmails": 100,
"executionTime": "45ms"
}
}
Error Handling
- Validate schema before generation
- Handle large dataset memory constraints
- Provide seed information for debugging
- Log generation failures with context
- Support partial data generation recovery
Constraints
- Never use real personal data as seeds
- Ensure generated emails don't match real domains
- Avoid generating data that could pass as real credentials
- Respect data privacy regulations (GDPR, etc.)
- Document seed values for test reproducibility