test-data-generation

name	test-data-generation
description	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.
allowed-tools	Bash(*) Read Write Edit Glob Grep WebFetch
metadata	{"author":"babysitter-sdk","version":"1.0.0","category":"test-data-management","backlog-id":"SK-015"}

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..()
});


 users = faker..(generateUser, { :  });

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 = {}) {
     .({ : count },  .(overrides));
  }

  
   () {
     .({ : , ...overrides });
  }

   () {
     .({ : , ...overrides });
  }
}


 user = .();
 admin = .({ :  });
 users = .();

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(),
  : faker..(),
  : ,
  : associations. || profileFactory.()
}));


 user = userFactory.();
 admin = userFactory.({ :  });
 usersWithProfiles = userFactory.(, {}, {
  : { : profileFactory.() }
});

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()
        }
      })
    )
  );

  
   products =  .(
    .({ :  }, 
      prisma..({
        : {
          : faker..(),
          : faker..(),
          : (faker..()),
          : faker..().(),
          : faker..()
        }
      })
    )
  );

  
   ( user  users) {
     orderCount = faker..({ : , :  });
     ( i = ; i < orderCount; i++) {
       prisma..({
        : {
          : user.,
          : faker..([, , , ]),
          : (faker..({ : , :  })),
          : {
            : faker..(products, { : , :  }).( ({
              : p.,
              : faker..({ : , :  }),
              : p.
            }))
          }
        }
      });
    }
  }

  .();
}

()
  .(.)
  .( 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),
    :  (),
    :  (),
    :  (),
    :  (),
    :  () 
  },

  
  : {
    : [],
    : [],
    : .({ :  },  i)
  }
};


 () {
   testCases = [];

   ( [field, config]  .(schema)) {
     (config. === ) {
      testCases.(
        { [field]: , : config. ?  :  },
        { [field]: .(config. + ), :  },
        { [field]: .(config.), :  }
      );
    }
     (config. === ) {
      testCases.(
        { [field]: config. - , :  },
        { [field]: config., :  },
        { [field]: config., :  },
        { [field]: config. + , :  }
      );
    }
  }

   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').(ssn).());
     faker..();
  },

  
  :  ({
    : faker..(),
    : faker..(),
    : faker..(),
    : faker..()
  })
};


 () {
   records.( ({
    ...record,
    : anonymize.(record.),
    : anonymize.(),
    : anonymize.(record.),
    : record. ? anonymize.(record.) : ,
    : anonymize.()
  }));
}

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 =  ({ : [locale] });
     .({ : count },  ({
      : code,
      : localFaker..(),
      : localFaker..(),
      : localFaker..(),
      : localFaker..()
    }));
  });
}

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

1. Use seeds - Enable reproducible test data
2. Factories over inline - Use factory patterns for maintainability
3. Realistic but safe - Data should look real but not match real people
4. Boundary coverage - Include edge cases in test data
5. Cleanup - Implement data cleanup strategies
6. Performance - Generate data in batches for large datasets
7. 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 handling
• e2e-test-suite.js - E2E test data setup
• api-testing.js - API test data generation
• environment-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