.NET application testing 101: best practices

For companies relying on .NET applications, a robust testing strategy is not just another technical convention. Done properly, testing minimizes system downtime and crashes, facilitates future product delivery, and drives a better end-user experience.

The modern .NET ecosystem has all the tools for efficient testing proceeding (unit, integration, and others). Whether building cloud-based solutions or maintaining legacy applications, with appropriate testing practices, you transform your workflow and product.

This article will cover:

• The selection of a right application testing framework to align with specific project requirements
• The role of using mocking libraries
• The techniques of generating test data
• The optimization of the test’s readability by using assertion libraries
• And, additionally, Docker integration into the testing pipeline

In this detailed overview, we’ll provide actionable insights for implementing and optimizing testing strategies for your .NET projects to ensure both reliability and scalability.

.NET application testing dive-in: the right testing framework

The table below illustrates the comparison of the most popular testing frameworks, their benefits & shortfalls, as well as their key features:

This table is a quick overview to help you identify the framework that suits your unique project’s requirements. And now, let’s get into detail.

NUnit

NUnit is a long-established and widely adopted framework that offers extensive features and extensibility.

Pros:

• Offers rich, extensive attributes for versatility in diverse testing scenarios
• Supports custom test runners and extensions
• Integrates seamlessly with popular IDEs and CI/CD pipelines
• Strong community with ample tech resources and support

Cons:

• Advanced features are not so beginner-friendly
• Reflection-based approach may cause performance overhead in large test suites

Code example:

[TestFixture]

public class CalculatorNUnitTests

{

   [Test]

   public void Add_ShouldReturnCorrectSum()

   {

       var calculator = new Calculator();

       var result = calculator.Add(2, 3);

       Assert.AreEqual(5, result);

   }

}

xUnit

xUnit takes a modern, minimalist approach, primarily focusing on simplicity and efficiency.

Pros:

• Designed with simplified syntax and conventions that minimize boilerplate code
• Supports parallel test execution at both method and class levels 
• Extensible with custom runners, data providers, and plugins
• Ensures isolation by running test individually in their own instance, to minimize test dependency 

Cons:

• Omits some NUnit features (e.g. [TestCase]) and replaces them with own alternatives – for example, either [Theory] or [InlineData] to provide similar functionality
• Smaller community (but growing) 

Code example:

public class CalculatorXUnitTests

{

   [Fact]

   public void Add_ShouldReturnCorrectSum()

   {

       var calculator = new Calculator();

       var result = calculator.Add(2, 3);

       Assert.Equal(5, result);

   }

}

MSTest

MSTest is a Microsoft default app testing framework, particularly suited for legacy .NET projects.

Pros:

• Bundled with Visual Studio, which eliminates additional setup
• Conveniently straightforward and easy-to-use for basic testing scenarios

Cons:

• Offers fewer advanced features (for example, parameterized tests)
• Smaller ecosystem and less active community than the previous two

Code example:

[TestClass]

public class CalculatorMSTestTests

{

   [TestMethod]

   public void Add_ShouldReturnCorrectSum()

   {

       var calculator = new Calculator();

       var result = calculator.Add(2, 3);

       Assert.AreEqual(5, result);

   }

}

TUnit

TUnit is a cutting-edge testing framework perfectly aligned for modern .NET 8 and beyond.

Pros:

• Supports both Native AOT and trimming to build high-performance applications
• Eliminates reflection by using source generators to deliver faster runtime

Bonus points: TUnit aligns with modern .NET 8+ for a future-ready design

Cons:

• Lacks compatibility (third-party tools, CI/CD pipelines, and more)
• Limited support due to its relatively recent introduction

Code example:

public class CalculatorTUnitTests

{

   [Test] 

   public async Task Add_ShouldReturnCorrectSum()

   {

       var calculator = new Calculator();

       var result = calculator.Add(2, 3);

       await Assert.That(result).IsEqualTo(5);

   }

}

.NET application testing tools: key practices to know

Mocking dependencies

Among other important practices, when writing unit tests, it’s essential to isolate the system under test.

Moq library

Pros:

• Simple and intuitive syntax for straightforward mock creation and management
• Strong community and extensive technical documentation

On the other hand, Moq has scarce support for dependencies without interfaces (non-interface dependencies). It works best with virtual methods and interfaces. 

Code example:

public class MoqTests

{

   [Fact]

   public void Moq_Example()

   {

       var mockRepository = new Mock<IRepository>();

       mockRepository

           .Setup(repo => repo.GetById(1))

           .Returns(new User { Id = 1, Name = "John" });

       var service = new UserService(mockRepository.Object);

       var result = service.GetUserById(1);

       Assert.Equal("John", result.Name);

   }

}

NSubstitute library

Pros:

• Readable syntax
  • NSubstitute provides human-readable syntax, which makes it intuitive for mocking 
  • Its API is straightforward, which means sensibly less boilerplate code 
• Flexible mocks
  • NSubstitute provides robust support for flexible argument matching
  • This facilitates precise control over behaviors based on varying inputs

Cons:

• Performance considerations
  • May introduce a slight performance overhead in large test suites 
• Limitations for non-virtual members
  • Requires only virtual members for substitutes; non-virtual/internal cannot be mocked
  • This limitation may require designing classes with interfaces or careful extra consideration
• Lack of strict mocking
  • Doesn’t support strict mocking, which means unexpected interactions may even go unnoticed
  • Stricter verification might require manual checks

Code example:

public class NSubstituteTests

{

   [Fact]

   public void NSubstitute_Example()

   {

       var repository = Substitute.For<IRepository>();

       repository.GetById(1).Returns(new User { Id = 1, Name = "John" });

       var service = new UserService(repository);

       var result = service.GetUserById(1);

       Assert.Equal("John", result.Name);

   }

}

FakeItEasy library

Pros:

• Minimalistic and straightforward API.
• Will generate dummy objects with defaults to minimize the need for additional manual configuration and streamline the process

Cons:

• May lack advanced features 
• Cannot mock static methods or non-virtual class members

Code example:

public class FakeItEasyTests

{

   [Fact]

   public void FakeItEasy_Example()

   {

       var repository = A.Fake<IRepository>();

       A.CallTo(() => repository.GetById(1))

           .Returns(new User { Id = 1, Name = "John" });

       var service = new UserService(repository);

       var result = service.GetUserById(1);

       Assert.Equal("John", result.Name);

   }

}

Choosing the right one

By selecting the right mocking library, you streamline unit testing and ensure the isolation of dependencies:

• Moq will be well-suited for many use cases, in particular when working with interfaces
• Go for NSubstitute when readability and argument flexibility are your top priorities
• Opt for FakeItEasy when simplicity and sensible defaults are more critical than advanced features

Generating realistic test data

Generating realistic test data is vital to ensure an expected application behavior in different testing scenarios. Manually creating test data can be quite tedious and error-prone.

Several libraries in the .NET ecosystem significantly streamline this process automating generating test data. Moving further, we’ll explore these tools.

Bogus

Bogus, a popular library, provides different data types, including names, addresses, dates, and more.

Pros:

• Rich capabilities: generates diverse data types
• High customization: allows tailoring to specific project needs for realistic test data
• Multi-locale support: provides localization for testing internationalized applications

Cons:

• Challenges with hierarchical data: to generate more complex, nested models, it requires extra setup
• Effort for complex models: customizing intricate domain structures can be quite time-consuming

Code example:

public class BogusExample

{

   [Fact]

   public void Bogus_UserGeneration()

   {

       var faker = new Faker<User>()

           .RuleFor(u => u.Id, f => f.IndexFaker + 1)

           .RuleFor(u => u.Name, f => f.Name.FullName())

           .RuleFor(u => u.Email, f => f.Internet.Email());

       List<User> users = faker.Generate(5);

       Assert.Equal(5, users.Count);

   }

}

AutoFixture

AutoFixture automates the process of creating testing objects by generating parameterized instances.

Pros:

• Easy Integration: seamlessly works with popular testing frameworks (NUnit, xUnit)
• High customization: easily adapts object creation to needs with flexible property settings

Cons:

• A steeper learning curve: extensive features may require more time to be fully comprehended
• Setup complexity: high customization can add configuration overhead

Code example:

public class AutoFixtureExample

{

   [Fact]

   public void AutoFixture_UserCreation()

   {

       var fixture = new Fixture();

       var user = fixture.Create<User>();

       Assert.NotNull(user);

       Assert.NotEqual(0, user.Id);   // Some random ID

   }

}

Assertion libraries

Assertions, another testing fundamental, are substantial to confirm actual and expected outputs are aligned. The built-in A s s e rt offers a simplified, dependency-free way to perform these checks for straightforward testing needs.

For more sophisticated scenarios, FluentAssertions and Shouldly provide improved readability and features. These libraries can support complex assertions and enhance test clarity, thus making them ideal for creating better maintainable and sophisticated test cases.

FluentAssertions

FluentAssertions provides a simple, fluent syntax that makes the tests more readable and expressive.

Pros:

• Supports both custom assertions and complex object comparisons 
• Allows assertions that resemble natural language, thus improving test readability and maintainability
• Provides detailed error messages on failures, thus enhancing issue identification and resolution

Cons:

• Adds an extra dependency beyond built-in assertion tools in standard testing frameworks.
• Version 8 has introduced a commercial license for commercial use (non-commercial use remains free); version 7 will receive critical fixes but lacks long-term updates

Code example:

public class FluentAssertionsExample

{

   [Fact]

   public void FluentAssertions_Test()

   {

       var calculator = new Calculator();

       var result = calculator.Add(2, 3);

       result.Should().Be(5);

       var user = new User { Name = "John" };

       user.Should().NotBeNull().And.Subject.As<User>().Name.Should().Be("John");

   }

}

Shouldly

Shouldly is another popular assertion library mainly focused on readability.

Pros:

• Simple and expressive syntax that resembles natural language for readable test assertions 
• Clear, concise error messages clearly indicate expected and actual outcomes

Cons:

• Offers fewer advanced features and options for customization 

Code example:

public class ShouldlyExample

{

   [Fact]

   public void Shouldly_Test()

   {

       var calculator = new Calculator();

       var result = calculator.Add(2, 3);

       result.ShouldBe(5);

       var user = new User { Name = "John" };

       user.Name.ShouldBe("John");

   }

}

Docker for integration testing: real databases in action

Integration testing is introduced to verify that different application modules function together as expected. Real databases are among the most prevalent scenarios, but still, integration testing can target other elements (message brokers, caching systems, and more).

Testing whether a complex EF Core LINQ expression can be translated into SQL syntax is a common challenge. This requires real databases rather than relying on an in-memory EF provider or mocks.

Docker eases this process by providing an isolated, disposable environment that mimics production settings.

Testcontainers for .NET applications

Testcontainers, a popular library, is used for managing Docker containers when covering integration tests: 

• It allows software developers to define and control Docker containers directly within the code
• The containers are destroyed automatically after each test to prevent any interference

Multiple containers, including databases, can be orchestrated simultaneously to simulate complex scenarios. The library integrates with CI pipelines, thereby providing a consistent and reproducible testing environment across stages. 

Key features:

• Automatically starts and stops Docker containers for tests.
• Provides already preconfigured setups for various popular databases (MS SQL, PostgreSQL, and more)  
• Provides a simple API for configuration

Code example:

public class MsSqlTestcontainerTests

{

   [Fact]

   public async Task DatabaseIntegrationTest_ShouldPerformExpectedOperations()

   {

       await using var container = new MsSqlBuilder()

           .Build();

       await container.StartAsync();

       // Use the container's connection string for testing

       var connectionString = container.GetConnectionString();

       await using var connection = new SqlConnection(connectionString);

       await connection.OpenAsync();

       // Example logic: Create a table, insert data, and verify it

       var command = connection.CreateCommand();

       command.CommandText = "CREATE TABLE TestTable (Id INT PRIMARY KEY, Name NVARCHAR(100));";

       await command.ExecuteNonQueryAsync();

       command.CommandText = "INSERT INTO TestTable (Id, Name) VALUES (1, 'TestName');";

       await command.ExecuteNonQueryAsync();

       command.CommandText = "SELECT Name FROM TestTable WHERE Id = 1;";

       var result = (string)await command.ExecuteScalarAsync();

       // Assert the expected value

       Assert.Equal("TestName", result);

   }

}

How we can help

With the right practices – testing frameworks, mocking libraries, and more – you ensure high-quality outcomes. And with Abto Software’s .NET engineers who possess the knowledge and experience to adopt these practices, you’re closer to success.

So, why not work with professionals?

Our services:

• .NET development
• ASP.NET development
• Web development
• Mobile development
• Cloud services
• Custom product software development

Our expertise:

• .NET application testing
• ASP.NET application testing

And everything in between! 

Written by Yurii Pelekh, Software Architect at Abto Software