| name | test-data-strategy |
| description | Plan comprehensive test data management including synthetic data generation, data anonymization, versioning, and environment-specific strategies. |
| allowed-tools | Read, Write, Glob, Grep, Task, WebSearch, WebFetch |
Test Data Strategy
When to Use This Skill
Use this skill when:
- Test Data Strategy tasks - Working on plan comprehensive test data management including synthetic data generation, data anonymization, versioning, and environment-specific strategies
- Planning or design - Need guidance on Test Data Strategy approaches
- Best practices - Want to follow established patterns and standards
Overview
Effective test data management ensures tests have the right data at the right time while protecting sensitive information and maintaining data quality across environments.
Test Data Types
| Type | Source | Use Case | Privacy Risk |
|---|---|---|---|
| Synthetic | Generated | Unit/Integration tests | None |
| Subset | Production sample | Performance testing | Medium |
| Masked | Anonymized production | Realistic scenarios | Low |
| Production Clone | Full copy | Pre-prod validation | High |
| Baseline | Curated reference | Regression testing | Low |
Test Data Strategy Template
# Test Data Strategy: [Project Name]
## 1. Data Requirements
### By Test Level
| Level | Data Source | Volume | Refresh |
|-------|-------------|--------|---------|
| Unit | Synthetic | Minimal | On-demand |
| Integration | Synthetic/Subset | Moderate | Per run |
| System | Masked production | Realistic | Weekly |
| Performance | Scaled synthetic | Production-like | Per release |
### By Feature Area
| Feature | Critical Data | Volume Required | Sensitivity |
|---------|---------------|-----------------|-------------|
| Authentication | User accounts | 1000 | High |
| Payments | Transactions | 10000 | High |
| Reporting | Historical data | 1M records | Medium |
## 2. Data Generation Strategy
### Synthetic Data Tools
- **Unit Tests**: AutoFixture, Bogus
- **Integration**: TestContainers + Seed
- **Performance**: Bulk generators
### Generation Rules
| Entity | Key Fields | Generation Logic |
|--------|------------|------------------|
| User | Email | `{guid}@test.example.com` |
| Order | Amount | `Random(1, 10000)` |
| Date | Timestamp | `Random(now-1y, now)` |
## 3. Data Anonymization
### PII Fields
| Field | Original | Anonymization Method |
|-------|----------|---------------------|
| Name | John Smith | Faker generated |
| Email | john@acme.com | `hash@domain.test` |
| Phone | 555-123-4567 | `555-xxx-xxxx` |
| SSN | 123-45-6789 | `xxx-xx-xxxx` |
| Address | 123 Main St | Faker address |
| DOB | 1985-03-15 | Shift by random days |
### Anonymization Rules
- Preserve data relationships
- Maintain referential integrity
- Keep statistical properties
- Remove unique identifiers
## 4. Environment Strategy
### Dev Environment
- Source: 100% synthetic
- Refresh: On-demand
- Volume: Minimal
### QA Environment
- Source: Masked production subset
- Refresh: Weekly
- Volume: 10% of production
### Staging Environment
- Source: Masked production clone
- Refresh: Before each release
- Volume: 100% of production
### Performance Environment
- Source: Scaled synthetic
- Refresh: Before performance runs
- Volume: 150% of production
## 5. Data Versioning
### Baseline Management
- Version baseline data sets
- Track data schema changes
- Maintain backward compatibility
- Document data dependencies
### Refresh Procedures
1. Trigger: [Manual/Scheduled/Event]
2. Source: [Production/Backup/Generator]
3. Transform: [Anonymization steps]
4. Load: [Target environment]
5. Validate: [Verification checks]
## 6. Compliance Requirements
### GDPR Compliance
- [ ] No real EU citizen data in non-prod
- [ ] Right to erasure supported
- [ ] Data minimization applied
- [ ] Consent tracking anonymized
### HIPAA Compliance
- [ ] PHI fully de-identified
- [ ] Safe Harbor method applied
- [ ] Audit logs maintained
- [ ] Access controls verified
Synthetic Data Generation (.NET)
Using Bogus
using Bogus;
public class TestDataGenerator
{
public static Faker<Customer> CustomerFaker => new Faker<Customer>()
.RuleFor(c => c.Id, f => f.Random.Guid())
.RuleFor(c => c.FirstName, f => f.Person.FirstName)
.RuleFor(c => c.LastName, f => f.Person.LastName)
.RuleFor(c => c.Email, (f, c) => f.Internet.Email(c.FirstName, c.LastName))
.RuleFor(c => c.Phone, f => f.Phone.PhoneNumber())
.RuleFor(c => c.DateOfBirth, f => f.Date.Past(50, DateTime.Now.AddYears(-18)))
.RuleFor(c => c.Address, f => new Address
{
Street = f.Address.StreetAddress(),
City = f.Address.City(),
State = f.Address.StateAbbr(),
Zip = f.Address.ZipCode()
});
public static Faker<Order> OrderFaker(Customer customer) => new Faker<Order>()
.RuleFor(o => o.Id, f => f.Random.Guid())
.RuleFor(o => o.CustomerId, customer.Id)
.RuleFor(o => o.OrderDate, f => f.Date.Recent(30))
.RuleFor(o => o.Total, f => f.Finance.Amount(10, 1000))
.RuleFor(o => o.Status, f => f.PickRandom<OrderStatus>());
}
Using AutoFixture
using AutoFixture;
using AutoFixture.Xunit2;
public class CustomerTests
{
[Theory, AutoData]
public void CreateCustomer_WithValidData_Succeeds(Customer customer)
{
// AutoFixture generates valid Customer automatically
var result = _service.Create(customer);
Assert.True(result.IsSuccess);
}
[Theory, AutoData]
public void ProcessOrder_CalculatesCorrectTotal(
[Frozen] Customer customer,
Order order,
List<OrderItem> items)
{
// Frozen ensures customer is reused
// Order and items are auto-generated
order.Items = items;
var total = _calculator.Calculate(order);
Assert.Equal(items.Sum(i => i.Quantity * i.Price), total);
}
}
Seeding Test Databases
public class TestDatabaseSeeder
{
public static async Task SeedAsync(AppDbContext context)
{
// Clear existing data
await context.Database.ExecuteSqlRawAsync("DELETE FROM Orders");
await context.Database.ExecuteSqlRawAsync("DELETE FROM Customers");
// Generate test data
var customers = TestDataGenerator.CustomerFaker.Generate(100);
await context.Customers.AddRangeAsync(customers);
foreach (var customer in customers)
{
var orders = TestDataGenerator.OrderFaker(customer).Generate(5);
await context.Orders.AddRangeAsync(orders);
}
await context.SaveChangesAsync();
}
}
Data Anonymization Techniques
| Technique | Description | Use Case |
|---|---|---|
| Substitution | Replace with fake data | Names, emails |
| Shuffling | Rearrange within column | Salaries, dates |
| Masking | Partial hiding | SSN (xxx-xx-1234) |
| Generalization | Reduce precision | Age ranges, zip prefix |
| Nulling | Remove entirely | Unnecessary fields |
| Tokenization | Replace with token | Cross-reference needs |
| Hashing | One-way transform | Identifiers |
.NET Anonymization Example
public class DataAnonymizer
{
public Customer Anonymize(Customer source)
{
return new Customer
{
Id = source.Id, // Preserve for relationships
FirstName = _faker.Person.FirstName,
LastName = _faker.Person.LastName,
Email = $"{Guid.NewGuid():N}@test.example.com",
Phone = MaskPhone(source.Phone),
SSN = "xxx-xx-" + source.SSN.Substring(7, 4),
DateOfBirth = ShiftDate(source.DateOfBirth),
Address = new Address
{
Street = _faker.Address.StreetAddress(),
City = source.Address.City, // Preserve geography
State = source.Address.State,
Zip = source.Address.Zip.Substring(0, 3) + "00"
}
};
}
private string MaskPhone(string phone)
{
// Keep area code, mask rest
return Regex.Replace(phone, @"(\d{3})\d{3}(\d{4})", "$1-xxx-$2");
}
private DateTime ShiftDate(DateTime date)
{
// Shift by random days within ±30
return date.AddDays(_random.Next(-30, 30));
}
}
Test Data Patterns
Builder Pattern
public class CustomerBuilder
{
private Customer _customer = new();
public CustomerBuilder WithName(string first, string last)
{
_customer.FirstName = first;
_customer.LastName = last;
return this;
}
public CustomerBuilder WithPremiumStatus()
{
_customer.IsPremium = true;
_customer.PremiumSince = DateTime.Now.AddYears(-1);
return this;
}
public CustomerBuilder WithOrders(int count)
{
_customer.Orders = TestDataGenerator.OrderFaker(_customer).Generate(count);
return this;
}
public Customer Build() => _customer;
}
// Usage
var customer = new CustomerBuilder()
.WithName("Test", "User")
.WithPremiumStatus()
.WithOrders(5)
.Build();
Object Mother Pattern
public static class TestCustomers
{
public static Customer ValidCustomer() => new()
{
Id = Guid.NewGuid(),
FirstName = "Test",
LastName = "User",
Email = "test@example.com",
Status = CustomerStatus.Active
};
public static Customer PremiumCustomer() => new()
{
Id = Guid.NewGuid(),
FirstName = "Premium",
LastName = "User",
Email = "premium@example.com",
IsPremium = true,
Status = CustomerStatus.Active
};
public static Customer InactiveCustomer() => new()
{
Id = Guid.NewGuid(),
Status = CustomerStatus.Inactive
};
}
Integration Points
Inputs from:
- Data model → Test data structure
- Privacy requirements → Anonymization rules
test-strategy-planningskill → Data volume needs
Outputs to:
- Test automation → Data fixtures
performance-test-planningskill → Load data- Environment provisioning → Seed scripts