SKILL.md
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Does the code under test depend on external infrastructure?
(database, HTTP service, file system, message broker)
|
+-- YES --> Is the infrastructure behavior critical to correctness?
| |
| +-- YES --> Does it need the full application stack (middleware, auth, routing)?
| | |
| | +-- YES --> E2E / Functional Test
| | | (WebApplicationFactory or Playwright)
| | |
| | +-- NO --> Integration Test
| | (WebApplicationFactory or Testcontainers)
| |
| +-- NO --> Unit Test with test doubles
| (mock the infrastructure boundary)
|
+-- NO --> Is this pure logic (calculations, transformations, validation)?
|
+-- YES --> Unit Test (no test doubles needed)
|
+-- NO --> Unit Test with test doubles
(mock collaborator interfaces)
Concrete Criteria by Test Type
Test Type
Infrastructure
Speed
Scope
When to Use
Unit
None (mocked/faked)
<10ms per test
Single class/method
Pure logic, domain rules, value objects, transformations, validators
Integration
Real (DB, HTTP)
100ms-5s per test
Multiple components
Repository queries, API contract verification, serialization round-trips, middleware behavior
E2E / Functional
Full stack
1-30s per test
Entire request pipeline
Critical user flows, auth + routing + middleware combined, cross-cutting concern verification
Cost-Benefit Guidance
- Prefer unit tests for business logic. They run fast, pinpoint failures precisely, and have no infrastructure requirements.
- Use integration tests to verify infrastructure boundaries work correctly. A repository unit test with a mocked
DbContextproves nothing about actual SQL generation -- use a real database via Testcontainers.
- Use E2E tests sparingly for critical paths only. They are slow, brittle, and expensive to maintain. Cover the happy path and one or two critical failure scenarios.
- The testing pyramid is a guideline, not a rule. Some applications (CRUD APIs with minimal logic) benefit from more integration tests than unit tests. Match the strategy to the application's complexity profile.
Test Organization
Project Naming Convention
Mirror the src/ project structure under tests/ with a suffix indicating test type:
MyApp/
src/
MyApp.Domain/
MyApp.Application/
MyApp.Api/
MyApp.Infrastructure/
tests/
MyApp.Domain.UnitTests/
MyApp.Application.UnitTests/
MyApp.Api.IntegrationTests/
MyApp.Api.FunctionalTests/
MyApp.Infrastructure.IntegrationTests/
*.UnitTests-- isolated tests, no external dependencies
*.IntegrationTests-- real infrastructure (database, HTTP, file system)
*.FunctionalTests-- full application stack viaWebApplicationFactory
See [skill:dotnet-add-testing] for creating these projects with proper package references and build configuration.
Test Class Organization
One test class per production class. Place test files in a namespace that mirrors the production namespace:
// Production: src/MyApp.Domain/Orders/OrderService.cs
// Test: tests/MyApp.Domain.UnitTests/Orders/OrderServiceTests.cs
namespace MyApp.Domain.UnitTests.Orders;
public class OrderServiceTests
{
// Group by method, then by scenario
}
For large production classes, split test classes by method:
// OrderService_CreateTests.cs
// OrderService_CancelTests.cs
// OrderService_RefundTests.cs
Test Naming Conventions
Use the Method_Scenario_ExpectedBehavior pattern. This reads naturally in test explorer output and makes failures self-documenting:
public class OrderServiceTests
{
[Fact]
public void CalculateTotal_WithDiscountCode_AppliesPercentageDiscount()
{
// ...
}
[Fact]
public void CalculateTotal_WithExpiredDiscount_ThrowsInvalidOperationException()
{
// ...
}
[Fact]
public async Task SubmitOrder_WhenInventoryInsufficient_ReturnsOutOfStockError()
{
// ...
}
}
Alternative naming styles (choose one per project and stay consistent):
Style
Example
Method_Scenario_Expected
CalculateTotal_EmptyCart_ReturnsZero
Should_Expected_When_Scenario
Should_ReturnZero_When_CartIsEmpty
Given_When_Then
GivenEmptyCart_WhenCalculatingTotal_ThenReturnsZero
Arrange-Act-Assert Pattern
Every test follows the AAA structure. Keep each section clearly separated:
[Fact]
public async Task CreateOrder_WithValidItems_PersistsAndReturnsOrder()
{
// Arrange
var repository = new FakeOrderRepository();
var service = new OrderService(repository);
var request = new CreateOrderRequest
{
CustomerId = "cust-123",
Items = [new OrderItem("SKU-001", Quantity: 2, UnitPrice: 29.99m)]
};
// Act
var result = await service.CreateAsync(request);
// Assert
Assert.NotNull(result);
Assert.Equal("cust-123", result.CustomerId);
Assert.Single(result.Items);
Assert.True(repository.SavedOrders.ContainsKey(result.Id));
}
Guideline: If you cannot clearly label the three sections, the test may be doing too much. Split into multiple tests.
Test Doubles: When to Use What
Terminology
Double Type
Behavior
State Verification
Use When
Stub
Returns canned data
No
You need a dependency to return specific values so the code under test can proceed
Mock
Verifies interactions
Yes (interaction)
You need to verify that the code under test called a dependency in a specific way
Fake
Working implementation
Yes (state)
You need a lightweight but functional substitute (in-memory repository, in-memory message bus)
Spy
Records calls for later assertion
Yes (interaction)
You need to verify calls happened without prescribing them upfront
Decision Guidance
Do you need to verify HOW a dependency was called?
|
+-- YES --> Do you need a working implementation too?
| |
| +-- YES --> Spy (record calls on a fake)
| +-- NO --> Mock (NSubstitute / Moq)
|
+-- NO --> Do you need the dependency to DO something realistic?
|
+-- YES --> Fake (in-memory implementation)
+-- NO --> Stub (return canned values)
Example: Stub vs Mock vs Fake
// STUB: Returns canned data -- verifying the code under test's logic
var priceService = Substitute.For<IPriceService>();
priceService.GetPriceAsync("SKU-001").Returns(29.99m); // canned return
var total = await calculator.CalculateTotalAsync(items);
Assert.Equal(59.98m, total); // assert on the result, not the call
// MOCK: Verifies interaction -- ensuring a side effect happened
var emailSender = Substitute.For<IEmailSender>();
await orderService.CompleteAsync(order);
await emailSender.Received(1).SendAsync( // assert on the call
Arg.Is<string>(to => to == order.CustomerEmail),
Arg.Any<string>(),
Arg.Any<string>());
// FAKE: In-memory implementation -- realistic behavior without infrastructure
public class FakeOrderRepository : IOrderRepository
{
public Dictionary<Guid, Order> Orders { get; } = new();
public Task<Order?> GetByIdAsync(Guid id, CancellationToken ct = default)
=> Task.FromResult(Orders.GetValueOrDefault(id));
public Task SaveAsync(Order order, CancellationToken ct = default)
{
Orders[order.Id] = order;
return Task.CompletedTask;
}
}
When to Prefer Fakes Over Mocks
- Domain-heavy applications: Fakes give more realistic behavior for complex interactions. An in-memory repository catches bugs that mocks miss (e.g., duplicate key violations).
- Overuse of mocks is a test smell. If a test has more mock setup than actual assertions, consider whether a fake would be clearer and more maintainable.
- Integration boundaries are better tested with real infrastructure via [skill:dotnet-integration-testing] than with mocks. A mocked
DbContextdoes not verify that your LINQ translates to valid SQL.
Testing Anti-Patterns
1. Testing Implementation Details
// BAD: Breaks when refactoring internals
repository.Received(1).GetByIdAsync(Arg.Is<Guid>(id => id == orderId));
repository.Received(1).SaveAsync(Arg.Any<Order>());
// ... five more Received() calls verifying the exact call sequence
// GOOD: Test the observable outcome
var result = await service.ProcessAsync(orderId);
Assert.Equal(OrderStatus.Completed, result.Status);
2. Excessive Mock Setup
// BAD: Mock setup is longer than the actual test
var repo = Substitute.For<IOrderRepository>();
var pricing = Substitute.For<IPricingService>();
var inventory = Substitute.For<IInventoryService>();
var shipping = Substitute.For<IShippingService>();
var notification = Substitute.For<INotificationService>();
var audit = Substitute.For<IAuditService>();
// ... 20 lines of .Returns() setup
// BETTER: Use a builder or fake that encapsulates setup
var fixture = new OrderServiceFixture()
.WithOrder(testOrder)
.WithPrice("SKU-001", 29.99m);
var result = await fixture.Service.ProcessAsync(testOrder.Id);
3. Non-Deterministic Tests
Tests must not depend on system clock, random values, or external network. Inject abstractions:
// BAD: Uses DateTime.UtcNow directly
public bool IsExpired() => ExpiresAt < DateTime.UtcNow;
// GOOD: Inject TimeProvider (.NET 8+)
public bool IsExpired(TimeProvider time) => ExpiresAt < time.GetUtcNow();
// In test
var fakeTime = new FakeTimeProvider(new DateTimeOffset(2025, 6, 15, 0, 0, 0, TimeSpan.Zero));
Assert.True(order.IsExpired(fakeTime));
Key Principles
- Test behavior, not implementation. Assert on observable outcomes (return values, state changes, published events), not internal method calls.
- One logical assertion per test. Multiple
Assertcalls are fine if they verify one logical concept (e.g., all properties of a returned object). Multiple unrelated assertions indicate the test should be split.
- Keep tests independent. No test should depend on another test's execution or ordering. Use fresh fixtures for each test.
- Name tests so failures are self-documenting. A failing test name should tell you what broke without reading the test body.
- Match test type to risk. High-risk code (payments, auth) deserves integration and E2E coverage. Low-risk code (simple mapping) needs only unit tests.
- **Use
TimeProviderfor time-dependent logic** (.NET 8+). It is the framework-provided abstraction; do not create customIClockinterfaces.
Agent Gotchas
- Do not mock types you do not own. Mocking
HttpClient,DbContext, or framework types leads to brittle tests that do not reflect real behavior. UseWebApplicationFactoryor Testcontainers instead -- see [skill:dotnet-integration-testing].
- Do not create test projects without checking for existing structure. Run [skill:dotnet-project-analysis] first; duplicating test infrastructure causes build conflicts.
- **Do not use
Thread.Sleepin tests.** UseTask.Delaywith a cancellation token, or better, useFakeTimeProvider.Advance()to control time deterministically.
- Do not test private methods directly. If a private method needs its own tests, it should be extracted into its own class. Test through the public API.
- Do not hard-code connection strings in integration tests. Use Testcontainers for disposable infrastructure or
WebApplicationFactoryfor in-process testing -- see [skill:dotnet-integration-testing].