how to write a unit test in c#

✨ Shield now has support for  Avalonia UI

Next Generation Obfuscator

Code analyzer to find vulnerabilities

Decentralized secret manager for applications

Monitor code exceptions and secure error reporting

Stay up to date with the latest changes and improvements

Open source tools

Documentation

Explore the documentation for each of our products and take your applications to the next level

Ensures the integrity of your application dependencies

Analyze your .NET source code for trojan source vulnerabilities

Unit Testing with C# and .NET (Full Guide)

Jun 2, 2023 | C# , .NET

In this section, we’ll explore the world of unit testing in C# and .NET, learn what unit testing is, why it’s important, and the landscape of testing frameworks and tools available to developers.

What is Unit Testing?

Unit testing is the process of verifying the correctness of individual units of code, typically methods or functions, in isolation from the rest of the system. This ensures that each unit performs as expected and helps to catch potential bugs or issues early in the development process.

Unit tests are automated, self-contained, and focused on specific aspects of a unit. They should be easy to understand, maintain and execute, providing a solid foundation for any developer who wants to ensure the quality of their code.

Importance of Unit Testing in Software Development

Unit testing is a crucial practice in modern software development. Its importance can’t be overstated, since it:

• Ensures functionality: It verifies that each unit of code works as expected, avoiding bugs and other issues.
• Enhances maintainability: Well-written tests act as a safety net, allowing developers to refactor or change the code with confidence.
• Improves code quality: It encourages best practices like SOLID principles and makes developers better at writing more testable code.
• Accelerates development: Testing early and often, allows developers to detect and fix issues faster, reducing the overall time spent on debugging.
• Facilitates collaboration: Shared test suites give developers a common understanding of the code and enable smooth collaboration, and better communication.

C# and .NET Unit Test Landscape: Testing Frameworks and Tools

There are several testing frameworks and tools available for unit testing in C# and .NET, but the most popular ones are:

• xUnit : A modern, extensible testing framework that focuses on simplicity and ease of use. It is often considered the de facto choice for unit testing in .NET Core.
• NUnit : A widely used, well-established testing framework with a rich feature set and extensive plugin ecosystem. It has a long history and many legacy .NET projects use it.
• MSTest : The default testing framework provided by the Microsoft Visual Studio suite, offering tight integration with Visual Studio, and backed by Microsoft support.
• Moq : A powerful mocking library specifically designed for .NET, allowing developers to create mock objects for isolated testing of units that interact with external dependencies.

Each framework has its strengths and weaknesses, but in this article, we’ll focus on xUnit and Moq, popular choices among C# developers for unit testing.

Getting Started with xUnit: A Modern Testing Framework for C#

Now that we’re introduced to the landscape of C# unit testing, let’s dive into xUnit, learn its advantages, and set up our first unit test using the framework.

Why Choose xUnit over Other Testing Frameworks?

xUnit has emerged as a preferred choice in the .NET community for several reasons:

• Modernity : It was designed specifically for .NET Core, bringing a contemporary approach and new features to the table.
• Simplicity : xUnit emphasizes simplicity, making it easy to learn and use, even for developers new to unit testing.
• Extensibility : xUnit provides many extensibility points, such as its attributes, assertions, and conventions, allowing developers to tailor it to their needs.
• Strong community support : With broad adoption in the .NET community, xUnit has a wealth of resources, documentation, and answers to common questions.
• Integration : It boasts integrations with popular tools like Visual Studio, VSCode, ReSharper, and .NET CLI, streamlining the testing experience.

Given these advantages, we’ll show you how to get started with xUnit in the sections below.

Installing and Setting up xUnit in Your .NET Project

To get started with xUnit, follow these easy steps:

• Begin by creating a new .NET Core test project using your preferred method such as Visual Studio, JetBrains Rider, or the .NET CLI:
• Next, navigate to the project directory and then run the following command to restore the project dependencies:
• Finally, execute your first example test with the following command:

With setup complete, you’re now ready to write your own unit tests using xUnit!

Your First C# Unit Test Case with xUnit

In this section, we’ll walk through creating a simple unit test using xUnit. For our example, let’s say we have the following implementation of an Add method, inside a Calculator class:

To write a unit test for the Add method, create a new test class in your test project called CalculatorTests . Inside this class, add a method called Add_PositiveNumbers_ReturnsExpectedResult , decorated with the [Fact] attribute, as follows:

When running the tests with dotnet test , the test suite will now execute this test and provide a pass/fail result based on whether the method behaves as expected.

xUnit Test Attributes, Conventions, and Execution Flow

xUnit uses a variety of attributes and conventions in its execution flow:

• Fact : A [Fact] attribute indicates a method as a test case. The method should neither have any return type nor any input parameters.
• Theory : A [Theory] attribute signifies a data-driven test method, allowing multiple inputs, each of which results in a separate test execution.
• InlineData : [InlineData] attribute provides inline data for [Theory] tests, simplifying test data management.
• MemberData : [MemberData] allows sharing data across test methods by specifying a member from which to pull the test data.

Additionally, xUnit has an optional convention for test execution order control, which can be customized to control test execution flow according to specific requirements.

Now that we’ve covered the basics, we’re ready to move on to more advanced unit testing techniques with xUnit and C#.

Writing Effective and Maintainable C# Unit Tests

An essential aspect of unit testing is creating tests that are easy to understand, maintain, and extend. In this section, we’ll explore the anatomy of a well-structured test, apply SOLID principles in test design, encapsulate test setup and teardown, and more.

Anatomy of a Well-Structured Test: Arrange, Act, Assert

A good unit test follows the “Arrange, Act, Assert” pattern, which makes the code simple, easy-to-understand, and maintainable. To explain this pattern, let’s break it down:

• Arrange : Set up the test environment and instantiate the system under test or its dependencies. In practical terms, this might mean creating mock objects, setting up exception handlers, or initializing state.
• Act : Invoke the target method using the prepared environment.
• Assert : Check if the expected outcome equals the actual result. If not, the test fails. Try to keep your assertion count to one per test.

This pattern helps ensure that tests are logically organized and accessible, facilitating better test maintainability.

Applies SOLID Principles in Test Design

To ensure unit tests remain manageable, maintainable, and easy to understand, they should adhere to the SOLID principles, just like production code:

• Single Responsibility Principle (SRP) : Each test should focus on one specific unit or behavior. Avoid mixing multiple assertions in a single test, making it easier to comprehend and troubleshoot.
• Open/Closed Principle (OCP) : Ensure that tests are open for extension, meaning that adding new test cases doesn’t require modifying the existing ones.
• Liskov Substitution Principle (LSP) : When using test inheritance or shared fixtures, make sure the base classes or fixtures are replaceable by their derived types without compromising test integrity.
• Interface Segregation Principle (ISP) : If a test requires a specific interface, it should depend solely on that interface, rather than a larger, more complex one. This helps in narrowing down the dependencies and scope of the test.
• Dependency Inversion Principle (DIP) : Depend on abstractions, rather than concrete implementations. In tests, this means using mocking frameworks like Moq to isolate tests from the actual implementation of dependencies.

Encapsulating Test Setup and Teardown

In many testing scenarios, we need to perform setup or cleanup code before or after the test execution. xUnit supports encapsulating test setup and teardown code through:

• Constructor and IDisposable : In xUnit, the test class’s constructor is used for setup, and the IDisposable interface implementation is used for teardown. This is the most common and recommended approach.
• IAsyncLifetime : For async setup and teardown code, xUnit provides the IAsyncLifetime interface, which has InitializeAsync and DisposeAsync methods.

C# Unit Test Best Practices: Naming, Organization, and Granularity

To maintain clean and maintainable test code, it’s essential to pay attention to the organization and naming conventions. Some best practices include:

• Naming : Give your test method names descriptive titles that convey their purpose. Using a convention like MethodName_Scenario_ExpectedBehavior helps in understanding the test’s intent quickly.
• Organization : Group related tests in the same class or namespace, making it easier to locate relevant tests.
• Granularity : Aim to test a single behavior per test case. Smaller tests reduce the debugging effort if a test fails.
• Readability : Write clean and easy-to-understand tests, making it straightforward for developers to grasp the intention and expectations of a test.

Incorporating Test-Driven Development (TDD) in Your Workflow

Test-Driven Development (TDD) is a powerful development methodology that revolves around writing tests first, followed by the implementation. It follows a cyclical process of:

• Write a failing test
• Implement the functionality to pass the test
• Refactor the code while keeping the test green

TDD fosters better code quality, maintainability, and overall development efficiency, as the focus is on writing simple, clear, and tested code from the start.

Advanced xUnit Techniques for Robust Test Cases

Next, let’s expand our knowledge of xUnit and explore advanced techniques to create robust test cases.

Embracing Data-Driven Tests with InlineData and MemberData

xUnit’s [Theory] attribute allows creating data-driven tests, using [InlineData] or [MemberData] to supply input values:

• InlineData : Supplies inline data values directly in the test method attribute.
• MemberData : Specifies a member (property or method) that returns an enumeration of test data, which should return an object array for each test case.

Sharing Test Contexts Using Class and Collection Fixtures

In xUnit, test context sharing is achieved via fixtures, helping avoid code duplication and ensuring consistent setup/teardown.

• Class Fixture : Shares a single instance of a context across all tests in a class. To use a class fixture, create a class implementing the IClassFixture<T> interface, where T is the context type.
• Collection Fixture : Shares a context instance across multiple test classes, useful for resource-intensive setups. Create a collection definition class implementing the ICollectionFixture<T> interface, and then apply the [CollectionDefinition] attribute.

Skipping Tests and Conditional Test Execution in xUnit

Sometimes, we may want to skip tests or execute them conditionally, based on specific circumstances. xUnit provides options to facilitate this:

• Skipping tests : Use the Skip parameter on the [Fact] or [Theory] attributes to skip a test.
• Conditional test execution : The [ConditionalFact] and [ConditionalTheory] attributes let you conditionally execute tests, controlled by a boolean value, which can be obtained through a custom method or property.

Customizing Test Output: xUnit Loggers and Reporters

In some scenarios, you may want to customize test output to generate reports or logs in various formats. xUnit supports this through a system of loggers and reporters:

• Loggers : Implement the ITestOutputHelper interface to redirect test output to custom locations or append additional information.
• Reporters : Custom reporters can be created by implementing the IMessageSinkWithTypes interface, allowing for more fine-grained control over test output and formatting.

Tips for Dealing with Flaky and Non-deterministic Tests

Flaky tests can cause headaches and wasted time, as their pass/fail outcome may change depending on external factors or timing. Some tips for handling non-deterministic tests include:

• Mocking : Use mocking frameworks like Moq to replace external dependencies that might cause flakiness.
• Timeouts : Use timeouts to ensure tests don’t run indefinitely due to faulty synchronization mechanisms or long delays.
• Test stability : Make your tests resilient to minor changes in the system, ensuring consistency while still checking for correctness.
• Retry : Implement retry logic for tests that intermittently fail due to transient issues.

Introduction to Mocking and Moq for C# Unit Tests

In this part, we’ll introduce the concept of mocking, its benefits, and one of the most popular mocking libraries in the .NET ecosystem, Moq.

Understanding the Purpose of Mocking and Its Benefits

Mocking is the practice of creating “fake” implementations of objects or dependencies that a system under test interacts with. This allows developers to isolate their tests from the actual implementation, enabling increased control, stability, and isolation. The benefits of mocking include:

• Test isolation : Mocks allow for complete control of test behavior and avoid side effects caused by real implementations.
• Greater flexibility : With mocks, testing becomes more flexible by enabling edge cases or exceptional scenarios that might be difficult to reproduce with actual dependencies.
• Reduced complexity : Mocks let you focus on the behavior of the system under test, instead of dealing with the complexities of real-world dependencies.
• Speed : Mocking can significantly speed up test execution by reducing resource-intensive operations or network interactions.

Moq: A Powerful and Popular Mocking Library for .NET Developers

Moq is a popular and powerful .NET mocking library that provides a simple and intuitive API for creating and managing mock objects. Key features of Moq include:

• Strong typing : Moq leverages C#’s strong typing, providing compile-time checking of mocked method calls and behavior.
• Expressive API : Moq’s API is designed to be expressive and easy to use, allowing developers to specify expectations and behaviors with minimal code.
• LINQ querying : Moq supports LINQ queries, making it simple to define complex mock behaviors and expectations.
• Integration : Moq works seamlessly with popular testing frameworks, like xUnit, making it easier to create robust and maintainable unit tests.

Integrate Moq in Your .NET Project

To get started with Moq, follow these steps:

• Add the Moq NuGet package to your test project using your preferred method, such as Visual Studio, JetBrains Rider, or the .NET CLI:
• Add the using Moq; statement in your test classes where you plan to use mocks.
• Use Moq’s Mock<T> class to create and configure mock objects in your tests, where T is the interface or class being mocked.

Mastering Moq: Writing Isolated Unit Tests with Mock Objects

In this section, let’s dive into Moq, learn how to create and configure mock objects, set up expectations, responses, and return values, as well as verify interactions and behaviors.

Creating and Configuring Mock Objects with Moq

To create a mock object with Moq, instantiate a Mock<T> object, where T is the interface or class being mocked. Consider the following example with an IOrderService interface:

To create a mock object of this interface, use the following code:

Once you’ve created a mock object, you can configure its behavior and expectations using Moq’s methods, such as Setup , Returns , Throws , and more.

Setting up Expectations, Responses, and Return Values with Moq

Moq allows you to specify expectations and responses for your methods. Let’s explore a few common scenarios:

• Returns : To specify a return value for a mocked method, use the Returns method:
• Throws : To throw an exception when the mocked method is called, use the Throws method:
• Callbacks : If you wish to execute specific code when a mocked method is called, use the Callback method:

Verifying Interactions and Behaviors: Asserting Mock Calls

Another powerful feature of Moq is the ability to verify the interactions between the system under test and the mocked dependencies. To do this, use the Verify method:

In this example, we’re verifying that the PlaceOrder method was called exactly once with any Order object.

Going Beyond Basics: Moq Callbacks, Sequences, and Event Raising

Moq offers more advanced options for advanced scenarios:

• Callbacks : As already mentioned, you can use Callback to execute specific code when a mock method is called. You can even capture method arguments for further validation:
• Sequences : If a mocked method gets called multiple times, you can set up a sequence of responses or actions using the Sequence extension:
• Event Raising : Moq allows you to mock events and raise them from the mocked object:

Moq and xUnit Integration: Use Cases and Gotchas

Integrating Moq with xUnit is straightforward since they work well together. Both libraries emphasize simplicity and usability. However, there are potential pitfalls, such as:

• Test Fixture Lifetimes : When using shared test fixtures with Moq, be aware that the fixtures’ lifetime affects the state of your mock objects. Resetting or reconfiguring them might be necessary.
• Async/Await : If your tests involve asynchronous methods, be sure to setup and verify the mock objects’ behavior accordingly.

Enhancing Unit Tests with DI and Mocking Best Practices

Now that we are more acquainted with Moq, let’s explore best practices for combining Dependency Injection (DI) and mocking in our tests.

Embracing Dependency Injection for Greater Test Flexibility

Dependency Injection (DI) is a design pattern that promotes greater test flexibility. By injecting dependencies as constructor or method parameters rather than directly instantiating them, we achieve:

• Easier mocking : Mock objects can be injected more easily, leading to better test isolation.
• Reduced coupling : Dependencies are expressed explicitly, making code easier to understand and maintain.

Try to apply DI wherever possible, particularly when working with external dependencies, allowing you to work with Moq more effectively.

When to Use Mocks, Stubs, and Fakes in Your Tests

When dealing with dependencies in your tests, it’s essential to understand when to use each type:

• Mocks : Use mocks when you need to verify interactions or behavior between the system under test and its dependencies. Useful for asserting that specific methods were called, with particular parameters, or a certain number of times.
• Stubs : Use stubs when you need to provide fixed responses or data from a dependency without asserting the behavior. They’re excellent for supplying inputs and simulating state transitions.
• Fakes : Fakes are lightweight, in-memory implementations of dependencies that replicate their essential behavior. Use them when you need more control over the dependency’s behavior or state and when mocking or stubbing isn’t sufficient.

Striking a Balance: Effective Mock Usage for Maintainable Tests

Overusing mocks can lead to brittle tests that break easily and are hard to maintain. It’s essential to strike a balance between mocking and other techniques, like stubbing or fakes. Key tips include:

• Don’t over-mock : Only mock the necessary dependencies and avoid mocking everything.
• Mock only parts of a dependency : Sometimes, you can mock parts of a dependency rather than the whole object.
• Simplicity is key : Assess whether a mock is really necessary. Using simpler alternatives such as stubs or fakes can simplify your tests.

Building Modular Tests with Factories and Builders

To further enhance the maintainability of your tests, employ factories and builders to generate mock objects, test data, or instances of your system under test:

• Factories : Create factory methods or classes that instantiate or configure common objects used throughout your test suite. This encapsulates object creation and reduces code duplication.
• Builders : Use the builder pattern to construct complex objects by allowing the incremental setting of properties or configuration. This results in more readable and flexible test code.

Measuring and Improving Test Quality with Metrics

Finally, let’s discuss how to measure test quality and make improvements using metrics such as code coverage, test quality metrics, and handling edge cases.

The Importance of Code Coverage in C# Unit Tests

Code coverage is a valuable metric that helps you understand how well your tests exercise your production code. While it doesn’t provide a complete picture of test quality, it does offer insights into potential gaps in your test suite.

Aim for a reasonable, context-specific level of code coverage. Aiming for 100% coverage isn’t always practical or efficient. Instead, determine which parts of your code require more thorough testing and ensure that critical code paths are well-tested.

Leveraging Visual Studio and .NET CLI for Code Coverage Analysis

Visual Studio and .NET CLI support analyzing code coverage, enabling you to measure the coverage of your tests effortlessly:

• Visual Studio : The Visual Studio Enterprise edition provides built-in support for code coverage analysis, featuring an easy-to-use interface and results visualization. You can also use extensions like ReSharper or dotCover for code coverage analysis in other Visual Studio editions.
• .NET CLI : You can use the dotnet test command to generate code coverage reports in various formats (Cobertura, OpenCover, etc.) by installing a coverage tool like coverlet and analyzing results with an external tool like ReportGenerator.

Beyond Code Coverage: Test Quality Metrics and Heuristics

While code coverage is useful, it’s essential to measure other aspects of test quality, including:

• Test effectiveness : Evaluate how well your tests detect actual issues in your code. High-quality tests are better at detecting defects and minimizing false negatives or positives.
• Ease of maintenance : Assess how easy your tests are to understand, modify, and extend. High-quality tests promote maintainability, reducing the cost of development over time.
• Test execution time : Monitor the time it takes to run your tests. Slow tests can hinder development and feedback cycles, reducing overall productivity.

Consider these factors when evaluating the quality of your test suite and making improvements.

Handling Edge Cases and Corner Cases: Strategies for Comprehensive Testing

Lastly, it’s vital to consider edge cases and corner cases when designing your tests. These scenarios can lead to unexpected behavior or defects and should be tested thoroughly to ensure system stability. Some strategies for handling edge cases include:

• Boundary value analysis : Test inputs or conditions at the edges of acceptable ranges. These cases often reveal problems with edge conditions or limit checks.
• Equivalence class partitioning : Divide input data into groups or classes that are expected to behave similarly, testing each group with representative values. This can help you discover issues with specific input groups.
• Error conditions : Test various ways your code can fail or encounter errors, especially in handling exceptions and error reporting. Ensure that your code gracefully handles these scenarios.
• Performance limits : Identify performance or resource constraints and test accordingly. Find out how your system behaves under high load, limited memory, or other constrained conditions.
• User behavior : Finally, consider how users interact with your application and test any unusual usage patterns or inputs. Doing so can help you uncover issues that arise from unexpected user input or actions.

In conclusion, C# and .NET offer a rich ecosystem for unit testing, with a variety of powerful frameworks and libraries like xUnit and Moq. By following the principles, patterns, and best practices discussed in this article, you can develop comprehensive and maintainable unit tests that ensure the quality, stability, and reliability of your C# applications. Keep learning, practicing, and refining your unit testing skills to become an ever-more-effective developer.

You May Also Like

Top 5 Best C# Books for Beginners in 2024

Jun 17, 2024 | C#

Top 5 Best C# Books for Beginners in 2024 If you're considering diving into the world of programming with C#, you've made an excellent...

What’s new in .NET 9 Preview 4? All You Need To Know

Jun 4, 2024 | .NET

Overview of .NET 9 Preview 4 Ready to dive deep into the latest from the .NET ecosystem? In this section, we'll explore what .NET 9...

Hexagonal Architecture in .NET – Full Guide 2024

May 28, 2024 | .NET

Introduction to Hexagonal Architecture in .NET In this comprehensive guide, we'll walk you through everything you need to know about this...

Learn Parallel Programming with C# and .NET in 2024.

May 27, 2024 | .NET , C#

Learn Parallel Programming with C# and .NET can drastically improve your application's performance. With C# and .NET, you have powerful...

How to compare two objects in C#: A Guide for Developers

May 24, 2024 | C#

In this article, we'll walk through how to create a generic method that can compare the objects of any class, even those with nested...

Pagination in C#: Complete Guide with Easy Code Examples (2024)

Introduction to Pagination in C# Today, we're diving into pagination in C#. Imagine showing a library with thousands of books – you...

• Book V2 📙 (50% OFF!)
• Blazor WASM 🔥 (50% OFF!)
• ASP.NET Core Series
• GraphQL ASP.NET Core
• ASP.NET Core MVC Series
• Testing ASP.NET Core Applications
• EF Core Series
• HttpClient with ASP.NET Core
• Azure with ASP.NET Core
• ASP.NET Core Identity Series
• IdentityServer4, OAuth, OIDC Series
• Angular with ASP.NET Core Identity
• Blazor WebAssembly
• .NET Collections
• SOLID Principles in C#
• ASP.NET Core Web API Best Practices
• Top REST API Best Practices
• Angular Development Best Practices
• 10 Things You Should Avoid in Your ASP.NET Core Controllers
• C# Back to Basics
• C# Intermediate
• Design Patterns in C#
• Sorting Algorithms in C#
• Docker Series
• Angular Series
• Angular Material Series
• HTTP Series
• Our Editors
• Leave Us a Review
• Code Maze Reviews

Select Page

Introduction to Unit Testing With NUnit in C#

Posted by Code Maze | Mar 7, 2022 | 0

In this article, we are going to learn about unit testing with NUnit in C# through examples.

Testing is one of the essential parts of the software development cycle, and there are many different test types. We’ll concentrate our attention on programmatic tests, such as unit tests, functional tests, or integrational tests. 

We need a test framework that conveniently defines a single test case or a group of test cases and runs them to cover our code with tests.  NUnit is one of the testing frameworks available for .NET developers. It has convenient tools for writing tests and good documentation.

Before we start, let’s revise what unit tests are, and let’s talk about some best practices.

What is Unit Testing?

Unit test is an automated test written and run by the developer to ensure that a piece of an application behaves as intended. Usually, unit tests cover the smallest logic unit of an application, and it helps developers to be sure that the application’s pieces work correctly. 

A single unit test has a proper structure – well-known as triple A. Arrange, Act, Assert . It helps to identify what happens inside the test case. 

Let’s take a look at the test case where we have triple-A separation: 

This test case verifies that operator + correctly sums two operands a and b . To keep the assertion part as simple as possible, we should define the expected value in the Arrange part. 

The test case in our example verifies the result. But also, we can be interested in verifying a component interaction. We’ll have a look at how to test it later. 

Test Method Naming Convention

The most important part of the development and unit testing is a proper naming convention. The name of the unit test should reflect what we are trying to test and the conditions for the test case. 

Let’s take a look at one of the commonly used naming conventions:

[GivenX]_When[Y]_Then[Z]

It starts with an optional “Given” part that gives some context to the test, after which we describe some action that needs to be done in the “When” part. Finally, we describe what we expect to happen for a particular test case in the “Then” part of the method name.

Test Project and Files Naming Convention 

It’s common good practice to keep separate test projects for each business project inside the solution. So if our solution has a business project named Project.Business than test’s project name should be Project.Business.UnitTests .

We use a proper suffix to show the intention of tests. For functional tests, the name would be Project.Business.FunctionalTests .

We should keep the same structure that we have in our business project. Each class we cover with tests should have a test class in the test project named accordingly with Test suffix. 

NUnit Project Setup

Let’s define the simplest business logic class that we are going to test in this article. We are going to create a  NUnitProject project with a single Calculator class that has just one method, Divide . It’s enough for our purposes:

The next step would be to add a test project to the solution. We should rely on the naming convention and name it NUnitProject.UnitTests . It’s a simple class library. Also, we are going to add the reference from the main project to the testing project. 

Now it’s time to add the required NuGet packages. 

 Let’s run the command to install the NUnit package in the Test project:

dotnet add package NUnit

To be able to integrate with visual studio properly, we should also add the NUnit adapter package and Microsoft test SDK:

First Test Case 

Now when we have the test project ready, we can start covering the Calculator class with unit tests. 

Let’s define a simple test case to verify that the Divide method works properly:

To mark a method as a test case, we need to add a Test attribute. It tells the NUnit framework that it should run this method.

We can run all tests in a solution using Visual Studio with a few simple steps: 

TopMenu -> Tests -> Run All Tests , with a shortcut Ctrl R + T , o r from the console – navigate to the test project directory and run the command:

dotnet test

It’s a good approach to run our test methods with different arguments, without copy-pasting our test methods. We can define test method parameters by using the [TestCase] attribute.

The [TestCase] attribute allows us to provide params for the test method:

The [TestCase] attribute allows only constant values for params, but we can find ourselves in a situation where we need to create a value on the fly.

Providing a Source With the TestCaseSource Attribute

We can solve this by using the [TestCaseSource] attribute. It accepts the name of the static method or property, which provides values for the test method:

Now, we face the problem of creating a calculator instance inside each test method. NUnit provides a convenient way to execute a piece of code before all test methods or before each test method run. 

With the [Setup] attribute, we can execute a method before each test case run, and we can create a Calculator class instance inside this method:

We have another attribute that runs just once before all test cases run. It’s named OneTimeSetup . 

It depends on what kind of resources we are going to set up before test case execution. Sometimes we have a strict restriction to use a single instance of an object between all test cases and using the OneTimeSetup method to create such an object is the best option.

Also, we have replacements for the Setup attributes that we can use to execute code after the test case is finished. The attributes as TearDown and, accordingly, OneTimeTearDown give us such ability. 

Unit Test Metadata

In a huge project, we can end up with a very large number of unit tests. In that case, we can use additional metadata attributes to add information to our unit tests.

Later we can run tests relying on specific values provided by metadata attributes. 

Test framework can’t check git history and determine the author of a test. To do that, we need to mark the test method with the [Author] attribute:

Description

If the intention of the test case is not clear, it’s possible to provide additional descriptions to clarify what exactly is tested inside the test case. It’s helpful when we run tests automatically and give the test framework additional information to display in the log message :

In some cases, we need to verify that method works fast enough. We can use [MaxTime] attribute to specify a maximum time for a test case to succeed. When the method exceeds the defined time it fails with a proper explanation:

The [Category] attribute marks that test related to a specific feature, and it allows us to run a set of unit tests for the feature without running all other tests. 

In huge projects, this saves a lot of time to run just a few tests for a new feature instead of running thousands of existing tests:

NUnit provides a variety of tools for writing unit tests in C#. This test framework is pretty popular in the .NET community. In this article, we’ve learned how to use it to create unit tests and how to provide additional metadata for these tests.

Leave a reply Cancel reply

Your email address will not be published. Required fields are marked *

Web API Book

Check out our  Ultimate ASP.NET Core Web API – Second Edition ( SUMMER SALE – 50% OFF! ) and learn how to create a full production-ready ASP.NET Core API (.NET 8). Bonus materials (Security, Docker, and other bonus files) are included in the Premium package!

Unit Testing 101: Write your first unit test in C# with MSTest

Do you want to start writing unit tests and you don't know how to start? Were you asked to write some unit tests on a past interview? Let's see what is a unit test and how to write your first unit tests in C#.

What is a unit test?

The book The Art of Unit Testing defines a unit test as "an automated piece of code that invokes a unit of work in the system and then checks a single assumption about the behavior of that unit of work."

From the previous definition, a unit of work is any logic exposed through public methods. Often, a unit of work returns a value, changes the internals of the system, or makes an external invocation.

If that definition answers how to test public methods, we might ask: 'What about private methods?' Short answer: we don't test them. We test private methods when we call our code through its public methods.

In short, a unit test is code that invokes some code under test and verifies a given behavior of that code.

Why should we write unit tests?

Have you ever needed to change your code, but you were concerned about breaking something? I've been there too.

The main reason to write unit tests is to gain confidence. Unit tests allow us to make changes, with confidence that they will work. Unit tests allow change.

Unit tests work like a "safety net" to prevent us from breaking things when we add features or change our codebase.

In addition, unit tests work like a living documentation. The first end-user of our code is our unit tests. If we want to know what a library does, we should check its unit tests. Often, we will find not-documented features in the tests.

What makes a good unit test?

Now, we know what is a unit test and why we should write them. The next question we need to answer is: 'What makes a test a good unit test?' Let's see what all good unit tests have in common.

Our tests should run quickly. The longer our tests take to run, the less frequent we run them. And, if we don't run our tests often, we have doors opened to bugs.

Our tests should run in any order. Tests shouldn't depend on the output of previous tests to run. A test should create its own state and not rely upon the state of other tests.

Our tests should be deterministic. No matter how many times we run our tests, they should either fail or pass every time. We don't want our test to use random input, for example.

Our tests should validate themselves. We shouldn't debug our tests to make sure they passed or failed. Each test should determine the success or failure of the tested behavior. Imagine we have hundreds of tests and to make sure they pass, we have to debug every one of them. What's the point, then?

"It could be considered unprofessional to write code without tests" - Robert Martin, The Clean Coder

Let's write our first unit test

Let's write some unit tests for Stringie, a (fictional) library to manipulate strings with more readable methods.

One of Stringie methods is Remove() .  It removes chunks of text from an string. For example, Remove() receives a substring to remove. Otherwise it returns an empty string if we don't pass any parameters.

Here's the implementation of the Remove() method for the scenario without parameters.

Let's write some tests for the Remove() method. We can write a Console program to test these two scenarios.

However, these aren't real unit tests. They run quickly, but they don't run in any order and they don't validate themselves.

Where should we put our tests?

Let's create a new project. Let's add to the solution containing Stringie a new project of type "MSTest Test Project (.NET Core)". Since we're adding tests for the Stringie project, let's name our new test project Stringie.UnitTests .

It's my recommendation to put our unit tests in a test project named after the project they test. We can add the suffix "Tests" or "UnitTests". For example, if we have a library called MyLibrary , we should name our test project: MyLibrary.UnitTests .

In our new test project, let's add a reference to the Stringie project.

After adding the new test project, Visual Studio created a file UnitTest1.cs . Let's rename it! We are adding tests for the Remove() method, let's name this file: RemoveTests.cs .

One way of making our tests easy to find and group is to put our unit tests separated in files named after the unit of work or entry point of the code we're testing. Let's add the suffix "Tests". For a class MyClass , let's name our file: MyClassTests .

Now, let's see what's inside our RemoveTests.cs file.

It contains one normal class and method. However, they're annotated with two unusual attributes: [TestClass] and [TestMethod] . These attributes tell Visual Studio that our file contains unit tests to run.

The [TestClass] and [TestMethod] attributes belong to a project called MSTest. Microsoft Test Framework (MSTest) is an open source unit testing framework. MSTest comes installed with Visual Studio.

Unit testing frameworks help us to write and run unit tests. Also, they create reports with the results of our tests. Other common unit testing frameworks include NUnit and XUnit .

How should we name our tests?

Let's replace the name TestMethod1 with a name that follows a naming convention.

We should use naming conventions to show the feature tested and the purpose behind of our tests. Tests names should tell what they're testing. A name like TestMethod1 doesn't say anything about the code under test and the expected result.

One naming convention for our test names uses a sentence to tell what they're testing. Often these names start with the prefix "ItShould" follow by an action. For our Remove() method, it could be: "ItShouldRemoveASubstring" and "ItShouldReturnEmpty".

Another convention uses underscores to separate the unit of work, the test scenario and the expected behavior in our test names. If we follow this convention for our example tests, we name our tests: Remove_ASubstring_RemovesThatSubstring() and Remove_NoParameters_ReturnsEmpty() .

With this convention, we can read our test names out loud like this: "When calling Remove with a substring, then it removes that substring".

These names could look funny at first glance. We should use compact names in our code. However, when writing unit tests, readability is important. Every test should state the scenario under test and the expected result. We shouldn't worry about long test names.

Following the second naming convention, our tests look like this:

How should we write our tests?

Now, let's write the body of our tests.

To write our tests, let's follow the Arrange/Act/Assert (AAA) principle. Each test should contain these three parts.

In the Arrange part, we create input values to call the entry point of the code under test.

In the Act part, we call the entry point to trigger the logic being tested.

In the Assert part, we verify the expected behavior of the code under test.

Let's use the AAA principle to replace one of our examples with a real test. Also, let's use line breaks to visually separate the AAA parts.

We used the Assert class from MSTest to write the Assert part of our test. This class contains methods like AreEqual() , IsTrue() and IsNull() .

The AreEqual() method checks if the result from a test is equal to an expected value. In our test, we used it to verified the length of the transformed string. We expect it to be zero.

Let's use a known value in the Assert part instead of repeating the logic under test in the assertions. It's OK to hardcode some expected values in our tests. We shouldn't repeat the logic under test in our assertions. For example, we can use well-named constants for our expected values.

Here's an example of how not to write the Assertion part of our second test.

Notice how it uses the Substring() method in the Assert part to find the string without the Hello substring. A better alternative is to use the expected result in the AreEqual() method.

Let's rewrite our last test to use an expected value instead of repeating the logic being tested.

How can we run a test inside Visual Studio?

To run a test, let's right click on the [TestMethod] attribute of the test and use "Run Test(s)". Visual Studio will compile your solution and run the test you clicked on.

After the test runs, let's go to the "Test Explorer" menu. There we will find the list of tests. A passed test has a green icon. If we don't have the "Test Explorer", we can use the "View" menu in Visual Studio and click "Test Explorer" to display it.

That's a passing test! Hurray!

If the result of a test isn't what was expected, the Assertion methods will throw an AssertFailedException . This exception or any other unexpected exception flags a test as failed.

These are some of the most common Assertion methods in MSTest.

Voilà! That's how you write your first unit tests in C# with MSTest. Don't forget to follow naming conventions and use the Assert class when writing unit tests.

If you want to practice writing more test for Stringie, check my Unit Testing 101 repository over on GitHub.

In this repository, you will find two lessons. One lesson to write some unit tests and another lesson to fix some unit tests.

Happy testing!

QA Best Practices for More Efficient Software Testing

The Catch Block #71 - Conflict, Lambdas, Updating Tests, and Defaults

Using C# Named Arguments to Declutter Complex Tests

May we suggest a tag?

May we suggest an author.

Matthew Jones

Vladimir Vozar

Cesar Aguirre

Ram Hemasri

Joe Middour

Maverick Jones

• Retrace Full Lifecycle APM
• Prefix Real-time Code Profiling
• Self-Hosted Retrace APM & ELM
• Netreo IT Infrastructure Monitoring
• By Initiative Monitoring, Tracing and Logging Application Performance Monitoring
• By Role Engineering & DevOps Teams For SI's, MSP's and ADM
• By Technology Azure and AWS Monitoring Azure Monitoring
• By Language Integrates with your stack .NET
• Resources Explore blogs, e-books and more. Blog
• Technical It’s easy to get the help you need Documentation
• Start Free Trial

You Still Don’t Know How to Do Unit Testing (and Your Secret is Safe with Me)

What is Unit Testing, Tutorial and 14 Best Practices

When I started in this industry, only an  avant-garde  fringe unit wrote automated tests for their code.  Over the last 15 years, however, that number has exploded, and the practice has become mainstream.  But “mainstream” does not mean “universal.”  Plenty of folks still do not have comfort with or even exposure to the unit testing practice.  And yet, a form of peer pressure causes them to play that close to the vest.

So I reached out to these folks to say, “Hey, no worries.  You can learn, and you don’t even have to climb too steep of a hill.”  I’d like to revisit that approach again, here, today, and in the form of a blog post.

Let’s get started with unit testing in C#, assuming that you know absolutely nothing about it.

What Unit Testing Isn’t

First, let’s clear up any misconceptions by talking about what doesn’t count.  Not every test you could conceivably write qualifies as a unit test.

If you write code that stuffs things into a database or that reads a file from disk, you have not written a unit test.  Unit tests don’t deal with their environment and with external systems to the codebase.  If it you’ve written something that can fail when run on a machine without the “proper setup,” you haven’t written a unit test.

Unit tests also don’t count as other sorts of tests.  If you create some sort of test that throws thousands of requests for a service you’ve written, that qualifies as a smoke test and not a unit test.  Unit tests don’t generate random data and pepper your application with it in unpredictable sequences.  They’re not something that QA generally executes.

And, finally, unit tests don’t exercise multiple components of your system and how they act.  If you have a console application and you pipe input to it from the command line and test for output, you’re executing an end-to-end system test — not a unit test.

Make no mistake — tests that do these things add value.  They should be part of your general approach to code quality.  They just don’t fall under the heading of unit tests.

What Unit Testing Is

With that out of the way, let’s consider what actually does qualify.  Unit tests isolate and exercise specific  units  of your code.  Okay.  I’ll concede that I just punted by defining a term with a word in the term.  But the creators of the term left the designation deliberately vague, presumably to cross language boundaries.

In C#, you can think of a unit as a method.  You thus write a unit test by writing something that tests a method.  Oh, and it tests something specific about that method  in isolation .  Don’t create something called TestAllTheThings and then proceed to call every method in a namespace.

Write better code on your workstation, try Stackify’s free code profiler, Prefix . Prefix works with .NET, Java, PHP, Node.js, Ruby, and Python.

That’s really it — all there is to it.  You’ll notice that I haven’t mentioned a few things that might pop into your head, such as test-driven development (TDD), unit test frameworks , test runners, mocks, or other unit testing tools.  Let’s not get ahead of ourselves.  Forget TDD and mocks for another time, as those are separate topics.  And forget test runners and frameworks for now.  We will get to those, but they aren’t, strictly speaking, necessary to have a unit test.

Unit Testing Tutorial

A dead simple unit test.

For the rest of this post, I’m going to demonstrate unit testing with a hypothetical and fairly trivial calculator class.  For now, let’s just have it do the following:

That’s it.  We have a single class, Calculator, in a class library project.  Add looks pretty reliable at first glance, but so does all the code you write.  You still need to test it, if only to prove your rightness to others.

To do that, let’s add a new console project and give it a reference to the project containing calculator, like so.

Now, let’s do the following in the main of the Calculator Tester.

Congratulations!  You’ve just written one extremely clunky unit test!

Introducing a Unit Test Framework

I’m sure you can pick out the flaw in this approach.  While you might enjoy your newfound ability to verify that 5 + 6 does, indeed, return 11, you probably don’t want to create and run a new console project for each unit test that you write.

Now, you might think that you could create a method for each test and call it from the main in CalculatorTester.  That would improve things over creating a project for each test, but only pain waits down that road (more than a decade ago, I used to test this way, before ubiquitous test runners existed).  Adding a method and call for each test will prove laborious, and tracking the output will prove unwieldy.

Fortunately, you can do better.  Since one or two other people have tried unit testing before you picked it up, some enterprising folks built frameworks to make it easier.  Let’s take a look at how to do that.

First, I’m going to delete my short-lived CalculatorTester console project.  Next, I’ll right-click on the solution to add a project, and choose the “Unit Test Project Template” after selecting “Test.”

Add the project reference to Calculator again, and then take a look at the class it created for you, called “UnitTest1.”  We’ll do a little better with the naming later, but let’s write our first, real test.

Now, we’ve got an actual unit test! Click Ctrl-R, T to run it, and look what happens.

We can see that it ran, passed, and took 8 ms to execute.  Much better out of the box than our erstwhile console application, eh?

Anatomy of a Unit Test

Let’s do a brief post-mortem in the form of looking at the bits and pieces of this test.  But first, let’s do a bit of renaming.

First off, we have a class called “CalculatorTests,” indicating that it will contain tests for the calculator class.  (Other ways to conceptually organize your tests exist but consider that an advanced topic.)  It gets an attribute called “TestClass” to tell Visual Studio’s default test runner and framework, MSTest, that this class contains unit tests.

Then, we have a method now called “Adding_4_And_3_Should_Return_7.”  I’d say that title speaks for itself, and that’s kind of the idea.  We want to name our test methods in a very descriptive way that indicates our hypothesis as to what inputs should create what outputs.  Notice the TestMethod attribute above this method.  This tells MSTest to consider this a test method.  If you removed the attribute and re-ran the unit tests in the codebase, MSTest would ignore this method.  You need to decorate any test classes and test methods this way to make MSTest execute them.

Finally, consider the static method Assert.AreEqual.  Microsoft supplies a UnitTesting namespace with this Assert class in it.  You use this class’s various methods as the final piece in the MSTest puzzle.  Assertion passes and fails determine whether the test passes or fails as seen in the test runner.  (As an aside, if you generate an unhandled exception in the test, that constitutes a failure, and if you never assert anything, that constitutes a pass.)

The Importance of Unit Testing

Here are some reasons why every developer should make unit testing a mandatory practice:

• Catching Bugs Early : By writing unit tests, developers can identify bugs and errors in their code much earlier in the development cycle, before they propagate to other parts of the application. This can save time and money in the long run by reducing the cost of fixing bugs later in the development cycle.
• Improving Code Quality : Unit testing can help improve code quality by ensuring that each unit of code is functioning correctly and as expected. This helps to prevent errors and unexpected behavior in the application.
• Frequent Releases : By testing code in isolation, developers can quickly identify and fix issues, allowing for faster iteration and more frequent releases.
• Encouraging Good Programming Habits : Writing unit tests encourages good programming habits, such as writing code that is modular, easy to understand, and testable. This can help to improve the overall quality of the codebase.

Now that we’ve understood what unit testing is and why it’s important, let’s look into some unit testing best practices.

Unit Testing Best Practices

1. arrange, act, assert.

Let’s now consider another sort of unit test anatomy.  Here, I’m talking about the logical components of a good unit test.  The test that I’ve written has them in their absolute most basic form.  Perhaps not surprisingly, given the title of this section, those components are “arrange, act, assert.”

Lean heavily on the  scientific method  to understand the real idea here.  Consider your test as a hypothesis and your test run as an experiment.  In this case, we hypothesize that the add method will return 7 with inputs of 4 and 3.

To pull off this experiment, first, we  arrange  everything we need to run the experiment.  In this case, very little needs to happen.  We simply instantiate a calculator object.  In other, more complex cases, you may need to seed an object with some variable values or call a particular constructor.

With the arranging in place, we  act .  In this case, we invoke the add method and capture the result.  The “act” represents the star of the unit testing show.  All of the arrangings lead up to it, and everything afterward amounts to retrospection.

Finally, we  assert.   The invocation of the Assert class probably gave that one away.  But the  assert  concept in the unit test represents a general category of action that you cannot omit and have a unit test.  It asserts the hypothesis itself.  Asserting something represents the essence of testing.

2. Use Relevant and High-Quality Test Data

Test with data that is similar to the data that the application will handle in the production environment. This approach can help identify issues that may not be apparent with small or simplistic test data. You should ensure that the test data covers a variety of scenarios, including edge cases and invalid input. You should also consider using real-world data whenever possible. For example, if an application is designed to process financial transactions, the test data should include realistic transaction amounts, dates, and customer information.

When testing with representative data, it’s important to avoid hard-coding data values in the test cases. This approach can make the test cases brittle and difficult to maintain.

3. One Assert Per Test Method

I may catch some flak for this from unit-testing veterans of a certain testing philosophy, but so be it.  Not everyone will necessarily agree with this, but I believe you should shoot for one assert per test method.  Each test forms a hypothesis and asserts it.  (The contrarian viewpoint would argue that multiple asserts can represent a single hypothesis).

I won’t go so far as to say that no test should  ever  contain a number of assertions other than one.  But I will say that your unit test suite should have a test-to-assert ratio pretty darned near 1.

Unit testing newbies commonly make the mistake of testing all of the things in one test method.  After all, more testing is better, right?  This drives them to want to get the most bang for their buck with each test, asserting lots of stuff.

But, remember, hypothesis, experiment.  Think of reading the output of the test in the test runner.  If you assert 20 things, you still only see a single failure.  How will you know at a glance what went wrong — which of your 20 assertions failed?

4. Avoid Test Interdependence

Each test should handle its own setup and tear down.  The test runner will execute your stuff in whatever order it pleases and, depending on the specific runner you use (advanced topic), it might even execute them in parallel.

You, therefore, cannot count on the test suite or the class that you’re testing to maintain state in between tests.  But that won’t always make itself obvious to you.

If you have two tests, for instance, the test runner may happen to execute them in the same order each time.  Lulled into a false sense of security, you might come to rely on this.  Weeks later, when you add a third test, it upsets this mix and one of your tests starts failing intermittently because of the ordering.

This will confuse and infuriate you.  Avoid this interdependence at all costs.

5. Write Tests before Code

Writing tests before writing code is a practice called Test Driven Development (TDD). This approach can help ensure that the code is testable, meets requirements, and is more maintainable.

With TDD, you create test cases before writing the actual code, and then write the code to pass those tests. This approach can also help you identify any gaps in the requirements or logic before writing any code. Additionally, TDD can help teams avoid the cost of fixing defects and bugs later in the development cycle.

6. Keep It Short, Sweet, and Visible

I’ve trod this road before as well and felt the pain.  Resist the impulse to abstract test setup (the “arrange”) to other classes, and especially resist the impulse to abstract it into a base class.  I won’t say that you’ll  never  find this abstraction appropriate (though I’d argue base classes are never appropriate here), but look to avoid it.

The reasoning here is simple.  When a test fails, you want to understand what went wrong.  You thus want a test where all setup logic reveals itself to you at a glance.  If you have logic strewn all over the class or residing in different classes, you’ll have a defect treasure hunt on your hands.  That’s bad enough in prod code, but tests are supposed to help eliminate that.  Make it easy on yourself.

7. Use Headless Testing when Appropriate

Headless testing is a form of running tests without a user interface or browser window. This approach can be more efficient and reliable than running tests with a graphical interface, especially for tests that do not require visual interaction.

You can use tools such as PhantomJS or Headless Chrome to run tests in a headless environment. These tools can help reduce the overhead of running tests with a graphical interface and can allow tests to run more quickly and in a more consistent environment.

However, it’s important to note that not all tests are suitable for headless testing. Tests that involve visual interaction or rendering, such as tests for user interfaces or web page layout, may require a graphical interface to be properly tested. Therefore, you should carefully consider which tests are appropriate for headless testing and which require a graphical interface.

8. Test Positive and Negative Scenarios

It’s important to test both the expected outcomes and unexpected outcomes of a function or method. Negative tests are especially important to ensure that error handling and edge cases are handled correctly.

Developers should also test for boundary conditions, such as the minimum and maximum values of input variables. By testing both positive and negative scenarios, you can ensure that the code is robust and can handle unexpected situations.

9. Use Mock Objects when Necessary

Mock objects can be used to simulate dependencies, such as databases or web services, which can make testing more reliable and faster. By using mock objects, developers can isolate the code being tested and focus on the behavior of the unit being tested. This approach can also help avoid issues with external systems, such as network connectivity or performance.

10. Ensure Compliance with Industry Standards

Ensuring compliance with industry standards involves verifying that the application meets the requirements set by relevant regulations or standards, such as HIPAA or PCI-DSS. Compliance testing can help ensure that the application is secure and that sensitive data is protected.

You should first identify the relevant standards or regulations that apply to your application. You should then create test cases that cover all relevant requirements. For example, if the application is required to encrypt all sensitive data in transit and at rest, the test cases should verify that the encryption is implemented correctly.

It’s important to document the compliance testing process thoroughly. This documentation can be used to demonstrate compliance with regulators or auditors.

11. Ensure Tests are Repeatable

Tests should be repeatable, meaning that they produce the same result every time they are run. This approach helps ensure that the tests are reliable and can be used to detect regressions. To ensure repeatability, you should use deterministic tests that don’t depend on external factors, such as the current time or the state of the system.

12. Test for Security Vulnerabilities

This involves identifying and addressing potential security issues in the application and can help ensure that the application is secure and can handle potential attacks.

You should consider testing for common vulnerabilities, such as SQL injection, cross-site scripting, or buffer overflows, and also use techniques such as fuzz testing to uncover potential issues. Fuzz testing involves sending random or malformed input to the application to see how it responds. This approach can help you identify unexpected behavior that could be exploited by attackers.

It’s important to test for security vulnerabilities throughout the development process, not just at the end. By testing early and often, you can identify and address potential issues before they become more difficult and expensive to fix.

13. Recognize Test Setup Pain as a Smell

For my second to last best practice mention, I’ll get a bit philosophical.  Stick this one in the back of your head, but do not forget it.

When you first teach yourself to write unit tests, you’ll do so on toy codebases like my little calculator.  It’ll take some real-world experience and some notches on your belt before you hit this, but you will hit it.  And, when you do, remember my advice.

If you find that the “arrange” part of your unit test becomes cumbersome, stop what you’re doing.  One of the most undercover powerful things about unit tests is that they provide  excellent  feedback on the design of your code — specifically its modularity.  If you find yourself laboring heavily to get a class and method setup so that you can test it, you have a design problem.

When you create setup heavy tests, you create  brittle  tests.  Tests carry a maintenance weight, just like production code.  You thus want to avoid unwieldy tests like the plague — they’ll break and make you and everyone else hate them.  So instead of going nuts on the setup, take a critical look at your design.

14. Add Them to the Build

I’ll conclude the post with arguably the most important best practice.  Since you’re early in your unit testing journey, get started on this one immediately when you only have a single test in your codebase.

If your team has a continuous integration build, add your new unit test suite’s execution to the build.  If any tests fail, then the build fails.  No exceptions, no ifs, ands or buts.  Trust me on this one.  If unit test failures don’t stop your team’s progress, your team will eventually start ignoring the failures when the pressure to deliver mounts.  It’s not a question of if, but when.

Unit testing takes time to learn and even more time to master.  Getting to that mastery will seem incredibly onerous at first, but you won’t ever get there if you don’t go all in.  If you’re going to write ’em, make ’em count.

Since the topic of unit testing has grown in demand, I decided to write a  book about unit testing .

Related posts:

• Unit Test Frameworks for C#: The Pros and Cons of the Top 3
• How to Write Test Cases and Why They Are Like the Scientific Method
• The Ultimate Guide to Performance Testing and Software Testing: Testing Types, Performance Testing Steps, Best Practices, and More
• A Look at JUnit 5’s Core Features & New Testing Functionality
• Continuous Testing Requires Faster Feedback Loops

Improve Your Code with Retrace APM

Stackify's APM tools are used by thousands of .NET, Java, PHP, Node.js, Python, & Ruby developers all over the world. Explore Retrace's product features to learn more.

[email protected]

Get the latest news, tips, and guides on software development.

Join the community of 40,000 developers that subscribe to our newsletter.

Popular Posts

9 Laravel Best Practices for Building Better Websites

Distributed Tracing 101

Node.js Performance Monitoring

How to Optimize Website Performance

How to optimize your Python apps

Topics/keywords, latest posts.

Container Orchestration: A Comprehensive Guide

5 Top Benefits for Choosing React Native

How To Ensure a Successful Database Upgrade

Flutter vs React Native: An In-Depth Comparison

The Business Case for OpenTelemetry – APM for Modern Applications

Want to contribute to the stackify blog.

If you would like to be a guest contributor to the Stackify blog please reach out to [email protected]

Unit Testing in C#: Ensuring Code Quality

In the realm of software development, ensuring code quality is paramount to building robust and reliable applications. Unit testing, a fundamental practice in test-driven development (TDD), plays a crucial role in achieving this goal. By systematically testing individual units of code, developers can identify and rectify bugs and design flaws early in the development cycle. This blog post will delve into the world of unit testing in C# and explore its benefits, best practices, and code samples.

What is Unit Testing?

Unit testing is a software testing technique that focuses on testing individual units or components of a program to verify their correctness. In the context of C# development, a unit typically refers to a method or function. Unit tests are written to verify the behavior of these individual units and ensure they work as expected. These tests are automated, repeatable, and can be run frequently to catch bugs early in the development process.

Benefits of Unit Testing

1. bug detection and prevention.

One of the primary benefits of unit testing is early bug detection and prevention. By writing tests for each unit of code, developers can catch issues before they propagate to other parts of the system. This leads to better overall code quality and reduces the likelihood of encountering critical bugs in production.

2. Code Refactoring and Maintainability

Unit tests act as a safety net when refactoring code. By having a comprehensive test suite, developers can confidently modify code without the fear of breaking existing functionality. This facilitates code refactoring, which leads to cleaner, more maintainable code over time.

3. Improved Collaboration and Code Documentation

Unit tests serve as living documentation for the codebase. When new developers join a project, they can easily understand how individual units of code are supposed to behave by examining the associated unit tests. Additionally, writing tests forces developers to think about the expected behavior of their code, leading to better-designed interfaces and clearer specifications.

Unit Testing Frameworks in C#

C# provides several popular unit testing frameworks that simplify the process of writing and executing unit tests. Some of the prominent frameworks include MSTest, NUnit, and xUnit.net. These frameworks offer various features such as test discovery, assertions, and test runners that make unit testing in C# more efficient and manageable.

MSTest is the built-in unit testing framework in Visual Studio. It offers a simple and intuitive way to write tests and provides features like test initialization and cleanup. MSTest supports parallel test execution and integrates seamlessly with the Visual Studio IDE.

Sample code using MSTest:

NUnit is a widely used open-source unit testing framework for .NET. It offers a rich set of assertions, test fixtures, and attributes for organizing tests. NUnit supports data-driven testing, parallel test execution, and extensibility through custom attributes and extensions.

Sample code using NUnit:

3. xUnit.net

xUnit.net is another popular open-source unit testing framework that follows the principles of simplicity, extensibility, and test parallelization. It provides an extensive set of attributes, assertions, and test runners. xUnit.net encourages a data-driven approach to testing and promotes clean test code by removing unnecessary abstractions.

Sample code using xUnit.net:

Writing Unit Tests in C#

1. test class and test methods.

To write unit tests in C#, you create a separate test class that contains individual test methods. Each test method should focus on testing a specific unit of code and be independent of other tests. The [TestMethod] attribute in MSTest, [Test] attribute in NUnit, or [Fact] attribute in xUnit.net is used to mark a method as a test method.

2. Assertions and Expected Results

Assertions are used to verify the expected behavior of the unit being tested. They help ensure that the code under test produces the desired output. Common assertions include checking for equality, inequality, nullity, exceptions, and more. The testing frameworks provide various assertion methods to handle different scenarios.

3. Test Fixtures and Test Initialization

Test fixtures provide a way to share common setup and cleanup code across multiple tests. They are particularly useful when tests require the same set of objects or resources. The [TestFixture] attribute in NUnit and [TestClass] attribute in MSTest define a test fixture. Test initialization code can be placed in a setup method, executed before each test, and cleanup code in a teardown method, executed after each test.

Test-Driven Development (TDD) and Unit Testing

Test-Driven Development (TDD) is an iterative development approach that emphasizes writing tests before writing the production code. TDD works hand in hand with unit testing, as it helps drive the design and implementation of the code. TDD follows the red-green-refactor cycle, where tests are initially written and executed, then the code is written to make the tests pass, and finally, the code is refactored to improve its design and maintainability.

1. Red-Green-Refactor Cycle

In the red phase, tests are written for the desired behavior, but they fail because the code is not implemented yet. In the green phase, the minimum code necessary is written to make the tests pass. Once the tests pass, the code is refactored in the refactor phase to improve its structure without changing its behavior. This cycle repeats until the desired functionality is achieved.

2. Mocking and Dependency Injection

To isolate units of code during testing, it is common to use mocking frameworks and dependency injection. Mocking frameworks help create mock objects that simulate the behavior of external dependencies, allowing you to test individual units in isolation. Dependency injection enables the substitution of real dependencies with mocks or stubs, making unit testing more effective.

3. Test Coverage and Continuous Integration

Test coverage measures the extent to which the code is covered by tests. It is essential to have good test coverage to ensure that critical code paths are tested. Continuous Integration (CI) practices involve running unit tests automatically and regularly as part of the development process. CI tools like Jenkins, Travis CI, or Azure Pipelines can be configured to execute unit tests on every code commit, providing rapid feedback on code changes.

Best Practices for Effective Unit Testing

1. keep tests independent and isolated.

Unit tests should be independent and not rely on the state or order of other tests. Each test should set up its required state and clean up after itself. This ensures that tests can be run individually or in any order without causing interference or unexpected failures.

2. Test Naming Conventions and Readability

Well-named tests help developers understand their purpose and intent. Use descriptive names that clearly convey what aspect of the code is being tested and what the expected outcome is. Additionally, write tests that are easy to read and understand, making it simpler for developers to maintain and debug them in the future.

3. Maintain a Good Test Suite Structure

Organize your tests into logical groupings using test fixtures, namespaces, or test categories. This helps in locating and running specific sets of tests when needed. A well-structured test suite enables developers to navigate and manage tests efficiently.

4. Use Test Doubles for External Dependencies

When unit testing code that depends on external services or resources, such as databases or web APIs, it is crucial to use test doubles like mocks or stubs. Test doubles help simulate the behavior of the dependencies, allowing tests to focus on the unit under test and avoiding external dependencies during testing.

5. Continuous Integration and Automated Testing

Integrate unit testing into your development workflow by incorporating it into your CI process. Automated testing ensures that tests are executed consistently and frequently, providing early feedback on code changes and reducing the chances of introducing bugs.

Common Unit Testing Pitfalls and How to Avoid Them

1. writing fragile tests.

Fragile tests are tests that break frequently due to changes in unrelated code or implementation details. To avoid fragile tests, focus on testing behavior rather than implementation details. Use appropriate abstractions and avoid tightly coupling tests to specific code internals.

2. Neglecting Edge Cases

Unit tests should cover a wide range of scenarios, including edge cases and boundary conditions. Neglecting these cases can leave critical parts of the code untested, leading to potential issues in production. Ensure that your test suite includes tests for all possible inputs and corner cases.

3. Over-Testing or Under-Testing

Finding the right balance is crucial when it comes to unit testing. Over-testing can lead to excessive maintenance overhead and slow down development, while under-testing may result in incomplete coverage and increased risks. Use code coverage tools to monitor test coverage and ensure that critical code paths are adequately tested.

Unit testing is an essential practice for ensuring code quality and building reliable software applications. By systematically testing individual units of code, developers can catch bugs early, facilitate code refactoring, and improve collaboration within development teams. By following best practices and leveraging the rich unit testing frameworks available in C#, developers can elevate the quality of their code and enhance the software development process as a whole. Start incorporating unit testing in your C# projects today to reap the benefits of improved code quality and robustness.

Table of Contents

What is ASP.NET Identity in C#?

What is blazor in c#, how to optimize database queries in entity framework.

• Manage Email Subscriptions
• How to Post to DZone
• Article Submission Guidelines
• Manage My Drafts

Low-Code Development: Leverage low and no code to streamline your workflow so that you can focus on higher priorities.

DZone Security Research: Tell us your top security strategies in 2024, influence our research, and enter for a chance to win $!

Launch your software development career: Dive head first into the SDLC and learn how to build high-quality software and teams.

Open Source Migration Practices and Patterns : Explore key traits of migrating open-source software and its impact on software development.

• Test-Driven Development With The oclif Testing Library: Part One
• Implementing ROS Communication Patterns
• Alexa Skill With .NET Core
• Add Mule 4 Standalone Runtime as On-Premise Server in Anypoint Platform Runtime Manager
• Implementing Real-Time Credit Card Fraud Detection With Apache Flink on AWS
• The Scale, Speed, and Spend of Low Code: Benefits and Challenges of Low-Code Platforms
• 7 Linux Commands and Tips to Improve Productivity
• Threads, ThreadPools, and Executors: Multi-Thread Processing In Java

How to Write Unit Tests for a .NET Core Application

Learn how to write effective unit tests for a c# .net core application as part of tdd, or test-driven development..

Join the DZone community and get the full member experience.

Writing unit tests is a good software engineering practice. In this article, we will learn how to create a C# .NET Core application while adhering to the Test Driven Development (TDD) approach. In the TDD approach, before implementing a functionality, you write a unit test for it. For example, if you want to write a function to add two numbers, first you'll write a failed unit test and then implement the functionality to pass the test.

In this post, we'll create a Calculator application. To start, let's follow the folder structure as outlined below:

• CalculatorApp - Solution
• CalculatorApp.Services - Application project
• CalculatorApp.Services.Tests - Test project

You can use Visual Studio to create projects; however, in this post, I will use .NET Core commands to create my projects, add tests, and run tests. You can also use MSTest or NUnit to write unit tests, but in this example, I'll use xUnit and dotnet test to write and run my unit tests.

Let's start by opening a command shell and follow along:

Creating the Application Project

To start, you'll need to create a directory called CalculatorApp. Keep in mind that you can follow any naming convention you'd like for directories, but if you'd like to follow along with this post, I would recommend following the same directory name. So, let's create the CalculatorApp directory and navigate to it.

Inside the CalculatorApp directory, we are going to create a new solution by running the following command:

  dotnet new sln  

After successfully running the command, you should get the message "The Template Solution File was created successfully". Also inside the CalculatorApp directory, you will find a file named calculatorapp.sln.

Next, create a directory called CalculatorApp.Services. This directory will keep the application sources, i.e. all classes of the calculator application. Navigate to the Calculatorapp.Services directory and create a class library by running the following command:

  dotnet new classlib  

After successfully running this command, you should get the message "The Template Class Library was created successfully". You'll also find a file named calculatorapp.services.csproj inside the CalculatorApp.Services directory. Next, you need to add this class library project to the CalculatorApp solution. To do this, navigate back to the CalculatorApp directory, and run the command:

  dotnet sln add .\calculatorapp.services\calculatorapp.services.csproj  

After successfully running the command, you should get the message "Project added to the solution."

Inside the CalculatorApp.Services folder, you will find a class Class1  — rename it to Calculator and modify the class as shown in the listing below:

You'll notice in the above listing that the Add and Sub functions are not implemented. First, we will write a unit test and then implement these functionalities.

Creating the Test Project

To add test projects, create a directory called CalculatorApp.Services.Tests and navigate to the directory. In this directory, we will create an MS Test project by running the following command:

  dotnet new mstest  

This command creates the test project which uses MS Test as the test library. Once the test project is created, add the source project library in the test project. To do that, run the command:

  dotnet add reference ../CalculatorApp.Services/CalculatorApp.Services.csproj  

This command will add a reference of the CalculatorAppService project to the test project. After adding the reference, add the test project to the solution by navigating to the CalculatorApp root directory, and run the command:

  dotnet sln add .\CalculatorAppServices.tests\CalculatorAppServices.Tests.csproj

This command will add the test project to the solution. After successfully running the command, you should get the message "Project added to the solution."

Writing Unit Tests

So far, we've created the application source project and a test project. In the application source project, there are unimplemented functions. Now let us write tests for these functions.

In the Test project, I have renamed the file UnitTest1.cs to Calculator.Test.cs and the class name to CalculatorTest. In the constructor of CalculatorTest, we need to create an object of the Calculator class. This can be done as shown in the listing below:

Unit Test for the Add function

In the CalculatorTest class, add a unit test method to test the Add functionality, as shown in the listing below:

To run the test, navigate to the CalculatorApp.Services.Tests directory and execute the command:

You'll get a "test failed" output because the Add function is not implemented, as shown in the image below:

To pass the test, implement the Add function in the Calculator class as shown in the listing below:

To run the test now, navigate to the CalculatorApp.Services.Tests director and execute the command:

As output, you will get the "test passed" message as shown in the image below:

Now you have implemented the Add functionality while adhering to the TDD approach in a .NET Core application!

Unit Test for the Sub function

In the CalculatorTest class, add a unit test method to test the Sub functionality, as shown in the listing below:

Here, your test will fail because the Sub function is not implemented. You will get one failed test result, as shown in the image below:

To pass the test, implement the Sub function in the Calculator class as shown in the below listing:

Now run the test again by navigating to the CalculatorApp.Services.Tests directory and executing:

Now you'll find both tests passed, as seen here:

Now you have implemented Sub functionality while adhering to the TDD approach in a .NET Core application.

Wrapping Up

So far in this post, we've created a .NET Core Calculator application while adhering to the TDD approach. To create tests, we used the XUnit and dotnet tests. For your reference, here is the source code of both the Calculator class and its test class:

And that's how you write unit tests and then implement their functionalities. I hope this post helps you in getting started with writing unit tests for your next .NET Core application!

Published at DZone with permission of Dhananjay Kumar , DZone MVB . See the original article here.

Opinions expressed by DZone contributors are their own.

Partner Resources

• About DZone
• Send feedback
• Community research
• Advertise with DZone

CONTRIBUTE ON DZONE

• Become a Contributor
• Core Program
• Visit the Writers' Zone
• Terms of Service
• Privacy Policy
• 3343 Perimeter Hill Drive
• Nashville, TN 37211
• [email protected]

Let's be friends:

How to Write a Unit Test in C# That Checks for an Exception

Life is unpredictable. And unexpected things happen.

It’s the same with the code. There are places in the code where you need to use error handling to protect the rest of the code execution from bad inputs. Unit tests can be used to check for exceptions and to ensure that your code handles such exceptions the way you expect it to.

If you use the xUnit testing framework, you can check that the exception was thrown in two different ways:

• Assert.Throws
• Using try-catch block

This post will show you how to write unit tests for your C# code that checks for exceptions. It will also discuss why you want to write these unit tests.

Table of Contents

Should exceptions be unit tested?

Unit Testing is a way to test the smallest part of a program to see if it works and use it for troubleshooting. Unit tests are also a great way to refactor code and see which parts of a large application are currently working. When writing these tests, it’s important to make sure that they cover all of the bases. For example, one of the scenarios that occur in code is throwing exceptions.

Exceptions are a controversial topic. Some developers think they should be unit tested, while others see exceptions as anti-patterns to be avoided at all costs.

But you definitely should test that your code throws an exception when bad input happens. If you don’t test the exception cases, you will not cover all possible scenarios with your test suite. And that can lead to unexpected behavior in your code and bugs.

So how do you assert exceptions in unit testing with the xUnit framework?

Test for exceptions using Assert.Throws

When it comes to writing your code, it’s important to know whether or not it’s working. Assertions are a great way to do that. An assertion is a test that checks if something is true.

In this post, I will use the xUnit unit testing framework.

xUnit has an Assert.Throws method on the Assert class for testing that the expected exception occurs. The Assert.Throws method takes a function as a parameter, which will be called with the list of parameters to the method under test.

This is an example of throwing an exception:

As you can see, it very simple. You wrap your code into the Action and pass that to the Assert.Throws method.

Let’s see how this works when testing the production code. We want to test the DocumentWriter class. It has a method for writing paragraphs to the document.

Going back to the test class, the following test case checks that the Write method throws an exception.

Testing asynchronous code

In case you want to test the asynchronous method, you can use ThrowsAsync . The following test method provides an example.

In this case, you need to use Func , since the method’s return type is Task . This means that you are calling the async method.

Checking exception message

How to check an exception message in unit tests?

It is straightforward to check the exception message in unit tests. You just need to capture the thrown exception.

Test for exceptions using try-catch block

Assert.Throws is a preferred way to check for exceptions while using xUnit. But there is another way to achieve the same goal. In your unit test case, you can use a try-catch block.

Let me show you what I mean.

You use the try block to execute the code under test. If the method throws an exception, that will be covered by the catch block. If the Write method doesn’t work as the test code expects, the Assert.True(false, message) will be triggered, and the automated test fails.

Unit testing is an essential practice for any developer. It helps you find bugs and identify faulty code. Unit tests also help you maintain code quality and consistency. And you should also use them to check when exceptions happen in the code.

Kristijan Kralj

Recent Posts

Building Solid Foundations: Exploring SOLID Principles in C#

To build a clean architecture in C#, laying a solid foundation for your codebase is important. One of the fundamentals of clean architecture in C# is adherence to the SOLID principles, which serve as...

4 Amazing Benefits of Integration Testing (+ 4 Drawbacks, Sadly)

So you're working on a new software project and about to reach the testing phase. That's great news! But have you considered the different testing types you need to perform? One of them...

Unit Testing in C# — basics

Gabriel Kerekeš

This is a unit.

This is a test.

This test tests the functionality of the unit of code. That is why this test can also be called a unit test. Unit testing is the practice of writing extra code in addition to your normal (production) code, in order to verify the functionality of that code. This post will help you start out with unit testing in C#, it will introduce the absolute basics necessary for you to start writing your own unit tests and after going through it you will be able to write your own unit tests for e.g. your school assignment.

Unit testing frameworks

There are basically three main unit testing frameworks available in C#. There’s MSTest (v2), NUnit (3) and xUnit . You might think that choosing the right framework is overwhelming. However, the frameworks are very similar, so the choice doesn’t matter so much (generally). You’ve got a bunch of attributes to decorate your methods with and you simply write some code to do some testing.

In the past choosing the right framework was a bit harder, because there were larger differences in the features which each framework supported. Nowadays they have all gotten to pretty much the same level and as I said, they are very similar. In this post, I will show you the basics of MSTestv2 and also NUnit3 , so you can see for yourself what the differences between these frameworks are. I haven’t really worked with xUnit, that is why I am not going to concern myself with it.

First we need some code to test

I have prepared a very simple class called SortedCollection. SortedCollection has only a single property (or field, whatever you want to call it) and that is a List of integers called items . It has three constructors. One is the default constructor, which I could have removed but haven’t. The other two are constructors which initialize the items list. One creates a copy of a provided list and assigns it to the items property, the other transforms an array into a List (basically also copying the array items) and also assigns it to the items property. Both of these constructors also BubbleSort the items by calling the BubbleSort() method.

The BubbleSort() method simply sorts the items list using the simple sorting algorithm Bubble Sort. I have also overriden the ToString() method so that it would be easier to debug the code and to view the collection if I wished to do so. I am not going to paste the code here, you can take a look at it in this github repo .

Unit Test Project

Before I tried unit testing, the usual way of testing my code (school assignments mostly) was to write some code, which would test the current functionality, in to the main function of the program . The problem with this method is, that once you are done testing your code, you will either delete that code or comment it out and move on. You write new functionality and after a while your main function is bloated with commented code or the code is deleted . Either way, none of the code is actually being tested anymore. As code changes (which it does) you need a way to test it easily and consistently.

A unit test project is a special type of a project . It is a separate project from the production project. You can create it in Visual Studio by either creating a new project using the Unit Test project template or by right clicking a class or a method in code and choosing Create Unit Tests . This project then behaves as an independent project and the tests in it are run separately from the production project.

You can see from Fig. 1, that the unit test projects are separate projects . They contain their own files, their own dependencies (e.g. the project under test), their own build configurations, dlls and so on.

Creating The Project From Scratch

Note: Feel free to skip this section if you aren’t interested in doing stuff manually.

One way to create a unit test project is to create it by yourself. This can be done via right clicking the solution in the Solution Explorer and then choosing Add -> New Project . Here you can use the search bar on the right to look for “ Unit Test ”. You should look for the Unit Test Project (.Net Framework) project template.

The standard way of naming your project is [ProductionProjectName].UnitTests or simply something, which enables you to differentiate this project from the production project and also states that it is a unit test project.

After clicking the OK button you should have a new project in your solution explorer and there should also be one file.

Now since this is pretty much an empty project, we need to include all our dependencies . Let’s start by adding a reference to the MySortedCollection project. Right click References under the unit test project and select Add Reference… . In the dialog select Projects and check the check box next to MySortedCollection . Click OK and that is it. Now our unit test project is able to see our project under test.

Adding a Unit Testing Framework

Next we have to add a unit testing framework . Visual Studio is a bit sneaky and the project template already contains the MSTestV2 framework. So you can either use that or if you want to use another framework you should go through the following steps. Right click on the unit test project and choose Manage NuGet Packages…. Go to the Installed tab and delete both of the MSTest packages. Then navigate to the Browse tab and search for “NUnit” . You should install the package named simply “NUnit” . However you also need the package called NUnit3TestAdapter which enables Visual Studio to run your tests.

That is it. Your project is now ready . Don’t worry if this looks a bit too complicated, there is also an easier way of doing this.

Letting Visual Studio Create The Project

The easier way of creating a unit testing project is to right-click a function or a class in your production code and then selecting Create Unit Tests . You will get a dialog , which you can see in Fig. 4.

The dialog is pretty straightforward. The important part is the framework you want the project to contain. After clicking OK, Visual Studio will create a test project. The project will also contain a file with the name you have set in the dialog and there will be a single test method in the class. The best part about this is, that everything has already been setup for you . Both the production project and the framework of your choice have been added to the project as references. The only thing left is to write our first unit test .

Our First Unit Test

Let’s go ahead and create our first unit test. Below you can see both the MSTestV2 version and the NUnit3 version of the same test. As you can see, they aren’t really that different. The only difference in this case is that MSTestV2 uses the TestClass and TestMethod attributes to mark test classes/functions. Whereas NUnit3 uses the TestFixture and Test attributes. That’s it. Nothing else to it (for now).

So what does this test actually do? Well, let’s start with the basics. Each unit test should have three phases (or mostly they do). I have marked these phases in the code, this is just for the purposes of this post, it isn’t normal practice to include the comments. The first phase is Arrange . You setup everything you need for your unit test. You create your classes under test and some other classes you need for the test to actually run. Then comes the Act phase. This is the phase, when the thing you are testing happens . You call a method, create an object (if you are testing a constructor), assign a value to a property and so on. The third phase is the Assert phase. In this phase you compare expected results to the actual results you have received.

In the context of our example test the Arrange phase is the creation of a list of numbers. This list will be used to create our sorted collection in the Act phase. The act is the instantiation of our SortedCollection , since that is what we are testing. We are testing that the constructor, which takes a list of numbers, also sorts that list. Note: In the example I have also included the ToString() call in the act phase, which is probably wrong, but I realized this after creating the videos so I didn’t want to change it anymore. In the Assert phase we set the expected string and we Assert that the expected string is equal to the actual collection string. This basically compares the two strings. If they aren’t equal, the Assert.AreEqual() method throws an exception with a nice message explaining what has happened.

The Assert Class

Assert is a static class which contains some methods to help you make checks in your test code. The methods check your condition and if the condition fails, it’ll also make the test fail with a nice message to it. These methods are pretty straightforward so I will just mention a couple of them, without explaining them.

• Assert.AreEqual(object, object)
• Assert.AreEqual(double, double, epsilon) — this overload of the method is worth mentioning. It exists because of floating point arithmetic and its (im)precision. Epsilon is the maximum difference, which can be between the two numbers for them to be considered equal.
• Assert.IsTrue(bool) , Assert.IsFalse(bool)
• Assert.IsNull(object) , Assert.IsNotNull(object)
• Assert.ThrowsException(Action) — useful if you expect an excetion to be thrown

The Assert class is framework specific, but the classes don’t differ too much. There is also a special class for asserting collections — CollectionAssert . It contains some methods to compare two collections — compare with ignoring the order, with the exact same order, …. CollectionAssert is however beyond the scope of this post.

Running Unit Tests

Now that we have written our first unit test we should be able to run it somehow. Luckily running unit tests in visual studio (or in most other IDEs) is very straightforward. You can either right-click the unit test and select Run Test(s). This should start building the project and it should also open the Test Explorer window in Visual Studio. If the Test Explorer doesn’t open automatically, you can open by going to Test -> Windows -> Test Explorer or by pressing Ctrl + Alt + U.

After it has run you can see the results in the Test Explorer . The Test Explorer conveniently sorts your tests by namespace so it easy to navigate to them. You can see whether the test has failed or passed and if it has failed, you can see the output of the test by selecting it in the explorer. Also at the top of the Test Explorer you have some buttons which enable you to run different groups of tests (failed tests, not run tests, repeat last run, …). The tests can also be run by right-clicking them in the Test Explorer . Doing so runs all of the tests which belong to that tree.

Parametrized Unit Tests

So far we have learned how to write a simple unit test and how we can actually run it. Now we are going to learn a way of making our unit test a bit cleaner with less repeated code . Both of the frameworks covered in this post have the option of having parametrized tests . This means that you add parameters to your tests and then fill them accordingly.

For example, let’s say we have an addition function. This function takes two numbers as parameters and produces the sum as a result. If you were to write simple tests for this method, you could end up having three test methods. The first one would test that 2+2=4 , the scond one that -1+3=2 and the third one would test that double.NaN+2=double.NaN. Instead of all that code, you can write just one method, but with three parameters and three parameter sets (2, 2, 4) , (-1, 2, 1) , (double.NaN, 2, double.NaN) .

The great thing about the parametrized test is, that the test cases are treated as independent tests . You can see them as separate tests in the Test Explorer. If one of them fails, the other tests run anyways and you can see the failure messages for each failed test case.

In the context of our application I decided to test the Add() function this way. You can see the test in the code snippet below. The first parameter is the number I will be adding to my collection. The second parameter is the string I expect to get when I call ToString() on my collection after adding the number. Note: I have to say again, that the choice to use ToString() isn’t a very fortunate one.

Initializing Unit Tests

One more topic I am going to talk about in this tutorial is the initialization of your unit tests. While writing unit tests you might notice that in a class most of the tests start in the same way. You decide to refactor your code so you create an Initialize() method which contains the repeating lines and you call that function at the beginning of each test. However, there is a better way of refactoring this code.

Initialize Each Test

Both MSTest and NUnit provide you with an attribute which makes a method run before each test . In MSTest this attribute is TestInitialize and the method takes no parameters. In NUnit the attribute is SetUp and the method also doesn’t take any parameters. These methods are run before each test, which allows you to put various initialization code into them.

In the test code below, you can see our MSTestV2 version of test initialization. I have decided to factor out the creation of our collection into this method, because it was repeated in all of our tests. Be careful while applying refactoring like this, because it might make your code unreadable.

Initialize Only Once

There are also attributes available for methods, which should be run only once for each test class. The attribute in MSTest is ClassInitialize and MSTest also requires this method to have a given method signature , which you can see in the code snippet. In NUnit this feature is available via the OneTimeSetUp attribute and in this case, you don’t need any special signatures.

If you are wondering what you would use this for, think of singletons for example. All of your tests might need some kind of a singleton to be initialized in order to run properly. Creating the singleton is expensive though and takes about 200ms. If you have 100 tests in this class and you initialize the singleton before each test, your tests are going to run for 20 seconds (at least). By initializing the singleton only once, your 100 tests will run more than 19 seconds quicker.

Test Deinitialization

There also attributes for deinitializing your unit tests if you wish to do so. This might be useful for object disposal, resetting some variables etc. MSTestV2 has the TestCleanup and ClassCleanup attributes. NUnit3 uses TearDown and OneTimeTearDown . I am sure you can figure out which method is run when. Also you can notice once again, that the frameworks are very similar.

That is all you shall need to start writing your own unit tests. If you feel like you need to know more about unit test here are some topics you might want to search for:

• TDD — test driven development
• Integration Testing
• difference between unit tests and integration tests

Also I recommend you read this books on unit testing:

• The Art of Unit Testing: With Examples in .NET
• Test Driven Development: By Example

Good Luck and Have Fun unit testing ;)

Written by Gabriel Kerekeš

Text to speech

• TECHNOLOGIES
• An Interview Question

Explain Unit Testing in .NET API

• Jul 03, 2024
• Other Artcile

Explore effective strategies for unit testing in .NET API development. Learn essential techniques like test-driven development (TDD), utilizing NUnit or xUnit frameworks, mocking dependencies, and ensuring robustness through integration testing.

Introduction

Unit testing is a critical practice in software development, ensuring that individual components of an application work as intended. In the context of .NET API development, unit tests help maintain code quality, facilitate refactoring, and prevent bugs from reaching production. This article explores the fundamentals of unit testing in .NET API, covering essential tools, best practices, and a step-by-step guide to writing effective tests.

Why Unit Testing Matters?

• Code Quality: Unit tests ensure that your code behaves as expected, catching errors early in the development cycle.
• Refactoring Confidence: With a robust suite of tests, developers can refactor code without fear of introducing new bugs.
• Documentation: Tests serve as a form of documentation, demonstrating how the code is supposed to work.
• Reduced Debugging Time: Early detection of issues leads to faster debugging and overall reduced development time.

Setting Up Unit Testing in .NET  

Prerequisites.

Before diving into unit testing, ensure you have the following.

• .NET SDK: Install the latest version from the official .NET website.
• IDE: Visual Studio or Visual Studio Code.

Creating a .NET API Project

Start by creating a new .NET API project.

Adding a Unit Test Project

Add a new unit test project to your solution.

Writing Your First Unit Test

Step 1. Install Required Packages.

Ensure your test project has the necessary packages. Open MyApi.Tests.csproj and add.

Step 2. Create a Sample Controller.

In your API project, create a simple controller, WeatherForecastController.cs.

Step 3. Write a Unit Test for the Controller.

In your test project, add a test class for the controller, WeatherForecastControllerTests.cs.

Step 4. Run Your Tests.

Execute your tests using the following command.

Best Practices for Unit Testing

• Isolation: Each unit test should be independent, not relying on external systems like databases or APIs.
• Arrange, Act, Assert (AAA): Structure your tests into three sections: setup (arrange), execution (act), and verification (assert).
• Mocking Dependencies: Use mocking frameworks like Moq to isolate the unit under test by mocking external dependencies.
• Clear Naming Conventions: Name your tests clearly to reflect their purpose, such as MethodName_StateUnderTest_ExpectedBehavior.
• Test Coverage: Aim for high test coverage, but prioritize critical and complex code paths.

Advanced Topics

• Test-Driven Development (TDD): Test-Driven Development is a practice where tests are written before the actual code. This approach ensures that the codebase is always covered by tests and promotes better design decisions.
• Continuous Integration (CI): Integrate unit tests into your CI pipeline to ensure that every code change is automatically tested, providing immediate feedback to developers.

Unit testing is an indispensable practice in .NET API development, offering numerous benefits, including improved code quality, easier maintenance, and faster debugging. By following the steps and best practices outlined in this article, you can start writing effective unit tests for your .NET API projects, leading to more robust and reliable applications.

• .NET Framework
• API Testing
• Mocking Frameworks
• Test-Driven Development
• Unit Testing

DateTime in C#

This browser is no longer supported.

Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support.

Creating Unit Tests for ASP.NET MVC Applications (C#)

• 8 contributors

by Stephen Walther

Learn how to create unit tests for controller actions. In this tutorial, Stephen Walther demonstrates how to test whether a controller action returns a particular view, returns a particular set of data, or returns a different type of action result.

The goal of this tutorial is to demonstrate how you can write unit tests for the controllers in your ASP.NET MVC applications. We discuss how to build three different types of unit tests. You learn how to test the view returned by a controller action, how to test the View Data returned by a controller action, and how to test whether or not one controller action redirects you to a second controller action.

Creating the Controller under Test

Let's start by creating the controller that we intend to test. The controller, named the ProductController , is contained in Listing 1.

Listing 1 – ProductController.cs

The ProductController contains two action methods named Index() and Details() . Both action methods return a view. Notice that the Details() action accepts a parameter named Id.

Testing the View returned by a Controller

Imagine that we want to test whether or not the ProductController returns the right view. We want to make sure that when the ProductController.Details() action is invoked, the Details view is returned. The test class in Listing 2 contains a unit test for testing the view returned by the ProductController.Details() action.

Listing 2 – ProductControllerTest.cs

The class in Listing 2 includes a test method named TestDetailsView() . This method contains three lines of code. The first line of code creates a new instance of the ProductController class. The second line of code invokes the controller's Details() action method. Finally, the last line of code checks whether or not the view returned by the Details() action is the Details view.

The ViewResult.ViewName property represents the name of the view returned by a controller. One big warning about testing this property. There are two ways that a controller can return a view. A controller can explicitly return a view like this:

Alternatively, the name of the view can be inferred from the name of the controller action like this:

This controller action also returns a view named Details . However, the name of the view is inferred from the action name. If you want to test the view name, then you must explicitly return the view name from the controller action.

You can run the unit test in Listing 2 by either entering the keyboard combination Ctrl-R, A or by clicking the Run All Tests in Solution button (see Figure 1). If the test passes, you'll see the Test Results window in Figure 2.

Figure 01 : Run All Tests in Solution ( Click to view full-size image )

Figure 02 : Success! ( Click to view full-size image )

Testing the View Data returned by a Controller

An MVC controller passes data to a view by using something called View Data . For example, imagine that you want to display the details for a particular product when you invoke the ProductController Details() action. In that case, you can create an instance of a Product class (defined in your model) and pass the instance to the Details view by taking advantage of View Data .

The modified ProductController in Listing 3 includes an updated Details() action that returns a Product.

Listing 3 – ProductController.cs

First, the Details() action creates a new instance of the Product class that represents a laptop computer. Next, the instance of the Product class is passed as the second parameter to the View() method.

You can write unit tests to test whether the expected data is contained in view data. The unit test in Listing 4 tests whether or not a Product representing a laptop computer is returned when you call the ProductController Details() action method.

Listing 4 – ProductControllerTest.cs

In Listing 4, the TestDetailsView() method tests the View Data returned by invoking the Details() method. The ViewData is exposed as a property on the ViewResult returned by invoking the Details() method. The ViewData.Model property contains the product passed to the view. The test simply verifies that the product contained in the View Data has the name Laptop.

Testing the Action Result returned by a Controller

A more complex controller action might return different types of action results depending on the values of the parameters passed to the controller action. A controller action can return a variety of types of action results including a ViewResult , RedirectToRouteResult , or JsonResult .

For example, the modified Details() action in Listing 5 returns the Details view when you pass a valid product Id to the action. If you pass an invalid product Id -- an Id with a value less than 1 -- then you are redirected to the Index() action.

Listing 5 – ProductController.cs

You can test the behavior of the Details() action with the unit test in Listing 6. The unit test in Listing 6 verifies that you are redirected to the Index view when an Id with the value -1 is passed to the Details() method.

Listing 6 – ProductControllerTest.cs

When you call the RedirectToAction() method in a controller action, the controller action returns a RedirectToRouteResult . The test checks whether the RedirectToRouteResult will redirect the user to a controller action named Index .

In this tutorial, you learned how to build unit tests for MVC controller actions. First, you learned how to verify whether the right view is returned by a controller action. You learned how to use the ViewResult.ViewName property to verify the name of a view.

Next, we examined how you can test the contents of View Data . You learned how to check whether the right product was returned in View Data after calling a controller action.

Finally, we discussed how you can test whether different types of action results are returned from a controller action. You learned how to test whether a controller returns a ViewResult or a RedirectToRouteResult .

Was this page helpful?

Coming soon: Throughout 2024 we will be phasing out GitHub Issues as the feedback mechanism for content and replacing it with a new feedback system. For more information see: https://aka.ms/ContentUserFeedback .

Submit and view feedback for

Additional resources

• Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers
• Advertising & Talent Reach devs & technologists worldwide about your product, service or employer brand
• OverflowAI GenAI features for Teams
• OverflowAPI Train & fine-tune LLMs
• Labs The future of collective knowledge sharing
• About the company Visit the blog

Collectives™ on Stack Overflow

Find centralized, trusted content and collaborate around the technologies you use most.

Q&A for work

Connect and share knowledge within a single location that is structured and easy to search.

Get early access and see previews of new features.

How do you know what to test when writing unit tests? [closed]

Using C#, I need a class called User that has a username, password, active flag, first name, last name, full name, etc.

There should be methods to authenticate and save a user. Do I just write a test for the methods? And do I even need to worry about testing the properties since they are .Net's getter and setters?

• unit-testing
• This post will help with the narrowing the wider question: earnestengineer.blogspot.com/2018/03/… You can take these guidelines to focus your question –  Lindsay Morsillo Commented Jun 12, 2018 at 19:36
• Keep in mind passwords should not be stored as plaintext. –  Mr Anderson Commented Apr 16, 2019 at 15:26

36 Answers 36

Many great responses to this are also on my question: " Beginning TDD - Challenges? Solutions? Recommendations? "

May I also recommend taking a look at my blog post (which was partly inspired by my question), I have got some good feedback on that. Namely:

I Don’t Know Where to Start? Start afresh. Only think about writing tests when you are writing new code. This can be re-working of old code, or a completely new feature. Start simple. Don’t go running off and trying to get your head round a testing framework as well as being TDD-esque. Debug.Assert works fine. Use it as a starting point. It doesn’t mess with your project or create dependencies. Start positive. You are trying to improve your craft, feel good about it. I have seen plenty of developers out there that are happy to stagnate and not try new things to better themselves. You are doing the right thing, remember this and it will help stop you from giving up. Start ready for a challenge. It is quite hard to start getting into testing. Expect a challenge, but remember – challenges can be overcome. Only Test For What You Expect I had real problems when I first started because I was constantly sat there trying to figure out every possible problem that could occur and then trying to test for it and fix. This is a quick way to a headache. Testing should be a real YAGNI process. If you know there is a problem, then write a test for it. Otherwise, don’t bother. Only Test One Thing Each test case should only ever test one thing. If you ever find yourself putting “and” in the test case name, you’re doing something wrong.

I hope this means we can move on from "getters and setters" :)

• 2 "If you know there is a problem, then write a test for it. Otherwise, don’t bother." I would disagree with the way this is worded. I was under the impression that unit tests should cover all possible execution paths. –  Corin Blaikie Commented Sep 15, 2008 at 15:50
• 3 While some may advocate such things, I personally don't. A good 90% of my headache came from simply trying to do "everything". I say test for what you expect to happen (so you know you are getting the right values back) but don't try and figure it all out. YAGNI. –  Rob Cooper Commented Sep 15, 2008 at 16:17
• 4 I, too, advocate the "test your bugs" approach. If we all had infinite time and patience, we'd test every possible execution path. But we don't, so you have to spend your effort where it's going to have the greatest effect. –  Schwern Commented Oct 18, 2008 at 7:05

Test your code, not the language.

A unit test like:

is only useful if you are writing a compiler and there is a non-zero chance that your instanceof method is not working.

Don't test stuff that you can rely on the language to enforce. In your case, I'd focus on your authenticate and save methods - and I'd write tests that made sure they could handle null values in any or all of those fields gracefully.

• 1 Good Point on "Dont test the framework" - Something I got on too when new to this. +1'ed :) –  Rob Cooper Commented Sep 15, 2008 at 13:44

This got me into unit testing and it made me very happy

We just started to do unit testing. For a long time I knew it would be good to start doing it but I had no idea how to start and more importantly what to test.

Then we had to rewrite an important piece of code in our accounting program. This part was very complex as it involved a lot of different scenarios. The part I'm talking about is a method to pay sales and/or purchase invoices already entered into the accounting system.

I just didn't know how to start coding it, as there were so many different payment options. An invoice could be $100 but the customer only transferred $99. Maybe you have sent sales invoices to a customer but you have also purchased from that customer. So you sold him for $300 but you bought for $100. You can expect your customer to pay you $200 to settle the balance. And what if you sold for $500 but the customer pays you only $250?

So I had a very complex problem to solve with many possibilities that one scenario would work perfectly but would be wrong on an other type of invocie/payment combination.

This is where unit testing came to the rescue.

I started to write (inside the test code) a method to create a list of invoices, both for sales and purchases. Then I wrote a second method to create the actual payment. Normally a user would enter that information through a user interface.

Then I created the first TestMethod, testing a very simple payment of a single invoice without any payment discounts. All the action in the system would happen when a bankpayment would be saved to the database. As you can see I created an invoice, created a payment (a bank transaction) and saved the transaction to disk. In my asserts I put what should be the correct numbers ending up in the Bank transaction and in the linked Invoice. I check for the number of payments, the payment amounts, the discount amount and the balance of the invoice after the transaction.

After the test ran I would go to the database and double check if what I expected was there.

After I wrote the test, I started coding the payment method (part of the BankHeader class). In the coding I only bothered with code to make the first test pass. I did not yet think about the other, more complex, scenarios.

I ran the first test, fixed a small bug until my test would pass.

Then I started to write the second test, this time working with a payment discount. After I wrote the test I modified the payment method to support discounts.

While testing for correctness with a payment discount, I also tested the simple payment. Both tests should pass of course.

Then I worked my way down to the more complex scenarios.

1) Think of a new scenario

2) Write a test for that scenario

3) Run that single test to see if it would pass

4) If it didn't I'd debug and modify the code until it would pass.

5) While modifying code I kept on running all tests

This is how I managed to create my very complex payment method. Without unit testing I did not know how to start coding, the problem seemed overwhelming. With testing I could start with a simple method and extend it step by step with the assurance that the simpler scenarios would still work.

I'm sure that using unit testing saved me a few days (or weeks) of coding and is more or less guaranteeing the correctness of my method.

If I later think of a new scenario, I can just add it to the tests to see if it is working or not. If not I can modify the code but still be sure the other scenarios are still working correctly. This will save days and days in the maintenance and bug fixing phase.

Yes, even tested code can still have bugs if a user does things you did not think of or prevented him from doing

Below are just some of tests I created to test my payment method.

• 1 Found a bug in your unit test! You repeat this line instead of including a 2 in one of them: Assert.AreEqual(0, bankHeader.BankCashDetails[0].Payments[3].InvoiceHeader.Balance); –  Ryan Peschel Commented Oct 21, 2011 at 23:42
• 2 You say: "After the test ran I would go to the database and double check if what I expected was there." This is a good example of an integration test between components of your system - not an isolated unit test of a single piece of code. –  JTech Commented Mar 27, 2017 at 23:39
• 2 You also broke the rule of more than one Assert per test. –  Steve Commented Jan 4, 2018 at 17:07

If they really are trivial, then don't bother testing. Eg, if they are implemented like this;

If, on the other hand, you are doing something clever, (like encrypting and decrypting the password in the getter/setter) then give it a test.

The rule is that you have to test every piece of logic you write. If you implemented some specific functionality in the getters and setters I think they are worth testing. If they only assign values to some private fields, don't bother.

This question seems to be a question of where does one draw the line on what methods get tested and which don't.

The setters and getters for value assignment have been created with consistency and future growth in mind, and foreseeing that some time down the road the setter/getter may evolve into more complex operations. It would make sense to put unit tests of those methods in place, also for the sake of consistency and future growth.

Code reliability, especially while undergoing change to add additional functionality, is the primary goal. I am not aware of anyone ever getting fired for including setters/getters in the testing methodology, but I am certain there exists people who wished they had tested methods which last they were aware or can recall were simple set/get wrappers but that was no longer the case.

Maybe another member of the team expanded the set/get methods to include logic that now needs tested but didn't then create the tests. But now your code is calling these methods and you aren't aware they changed and need in-depth testing, and the testing you do in development and QA don't trigger the defect, but real business data on the first day of release does trigger it.

The two teammates will now debate over who dropped the ball and failed to put in unit tests when the set/gets morphed to include logic that can fail but isn't covered by a unit test. The teammate that originally wrote the set/gets will have an easier time coming out of this clean if the tests were implemented from day one on the simple set/gets.

My opinion is that a few minutes of "wasted" time covering ALL methods with unit tests, even trivial ones, might save days of headache down the road and loss of money/reputation of the business and loss of someone's job.

And the fact that you did wrap trivial methods with unit tests might be seen by that junior team mate when they change the trivial methods into non-trivial ones and prompt them to update the test, and now nobody is in trouble because the defect was contained from reaching production.

The way we code, and the discipline that can be seen from our code, can help others.

Another canonical answer. This, I believe, from Ron Jeffries:

Only test the code that you want to work.

Testing boilerplate code is a waste of time, but as Slavo says, if you add a side effect to your getters/setters, then you should write a test to accompany that functionality.

If you're doing test-driven development, you should write the contract (eg interface) first, then write the test(s) to exercise that interface which document the expected results/behaviour. Then write your methods themselves, without touching the code in your unit tests. Finally, grab a code coverage tool and make sure your tests exercise all the logic paths in your code.

Really trivial code like getters and setters that have no extra behaviour than setting a private field are overkill to test. In 3.0 C# even has some syntactic sugar where the compiler takes care of the private field so you don't have to program that.

I usually write lots of very simple tests verifying behaviour I expect from my classes. Even if it's simple stuff like adding two numbers. I switch a lot between writing a simple test and writing some lines of code. The reason for this is that I then can change around code without being afraid I broke things I didn't think about.

• Glad you made a good point of the KISS principle.. I often have tests that are literally like 2-3 lines of code, real small, simple tests. Easy to grok and hard to break :) +1'ed –  Rob Cooper Commented Sep 15, 2008 at 13:31

You should test everything. Right now you have getters and setters, but one day you might change them somewhat, maybe to do validation or something else. The tests you write today will be used tomorrow to make sure everything keeps on working as usual. When you write test, you should forget considerations like "right now it's trivial". In an agile or test-driven context you should test assuming future refactoring. Also, did you try putting in really weird values like extremely long strings, or other "bad" content? Well you should... never assume how badly your code can be abused in the future.

Generally I find that writing extensive user tests is on one side, exhausting. On the other side, though it always gives you invaluable insight on how your application should work and helps you throw away easy (and false) assumptions (like: the user name will always be less than 1000 characters in length).

For simple modules that may end up in a toolkit, or in an open source type of project, you should test as much as possible including the trivial getters and setters. The thing you want to keep in mind is that generating a unit test as you write a particular module is fairly simple and straight forward. Adding getters and setters is minimal code and can be handled without much thought. However, once your code is placed in a larger system, this extra effort can protect you against changes in the underlying system, such as type changes in a base class. Testing everthing is the best way to have a regression that is complete.

It doesn't hurt to write unit tests for your getters and setters. Right now, they may just be doing field get/sets under the hood, but in the future you may have validation logic, or inter-property dependencies that need to be tested. It's easier to write it now while you're thinking about it then remembering to retrofit it if that time ever comes.

• well, if your getters/setters need unit tests, there must be some logic associated with them, so that means logic must be written inside them, if they don't have any logic, no unit tests need to be written. –  Pop Catalin Commented Sep 15, 2008 at 13:20
• 2 His point is that logic may be added to them later. –  LegendLength Commented Mar 23, 2009 at 2:36

in general, when a method is only defined for certain values, test for values on and over the border of what is acceptable. In other words, make sure your method does what it's supposed to do, but nothing more . This is important, because when you're going to fail, you want to fail early.

In inheritance hierarchies, make sure to test for LSP compliance.

Testing default getters and setters doesn't seem very useful to me, unless you're planning to do some validation later on.

well if you think it can break, write a test for it. I usually don't test setter/getter, but lets says you make one for User.Name, which concatenate first and last name, I would write a test so if someone change the order for last and first name, at least he would know he changed something that was tested.

The canonical answer is "test anything that can possibly break." If you are sure the properties won't break, don't test them.

And once something is found to have broken (you find a bug), obviously it means you need to test it. Write a test to reproduce the bug, watch it fail, then fix the bug, then watch the test pass.

As I understand unit tests in the context of agile development, Mike, yes, you need to test the getters and setters (assuming they're publicly visible). The whole concept of unit testing is to test the software unit, which is a class in this case, as a black box . Since the getters and setters are externally visible you need to test them along with Authenticate and Save.

If the Authenticate and Save methods use the properties, then your tests will indirectly touch the properties. As long as the properties are just providing access to data, then explicit testing should not be necessary (unless you are going for 100% coverage).

I would test your getters and setters. Depending on who's writing the code, some people change the meaning of the getter/setter methods. I've seen variable initialization and other validation as part of getter methods. In order to test this sort of thing, you'd want unit tests covering that code explicitly.

Personally I would "test anything that can break" and simple getter (or even better auto properties) will not break. I have never had a simple return statement fail and therefor never have test for them. If the getters have calculation within them or some other form of statements, I would certainly add tests for them.

Personally I use Moq as a mock object framework and then verify that my object calls the surrounding objects the way it should.

You have to cover the execution of every method of the class with UT and check the method return value. This includes getters and setters, especially in case the members(properties) are complex classes, which requires large memory allocation during their initialization. Call the setter with some very large string for example (or something with greek symbols) and check the result is correct (not truncated, encoding is good e.t.c.)

In case of simple integers that also applies - what happens if you pass long instead of integer? That's the reason you write UT for :)

I wouldn't test the actual setting of properties. I would be more concerned about how those properties get populated by the consumer, and what they populate them with. With any testing, you have to weigh the risks with the time/cost of testing.

You should test "every non-trivial block of code" using unit tests as far as possible.

If your properties are trivial and its unlikely that someone will introduce a bug in it, then it should be safe to not unit test them.

Your Authenticate() and Save() methods look like good candidates for testing.

Ideally, you would have done your unit tests as you were writing the class. This is how you're meant to do it when using Test Driven Development. You add the tests as you implement each function point, making sure that you cover the edge-cases with test too.

Writing the tests afterwards is much more painful, but doable.

Here's what I'd do in your position:

• Write a basic set of tests that test the core function.
• Get NCover and run it on your tests. Your test coverage will probably be around 50% at this point.
• Keep adding tests that cover your edge-cases until you get coverage of around 80%-90%

This should give you a nice working set of unit tests that will act as a good buffer against regressions.

The only problem with this approach is that code has to be designed to be testable in this fashion. If you made any coupling mistakes early on, you won't be able to get high coverage very easily.

This is why it is really important to write the tests before you write the code. It forces you to write code that is loosely coupled.

Don't test obviously working (boilerplate) code. So if your setters and getters are just "propertyvalue = value" and "return propertyvalue" it makes no sense to test it.

Even get / set can have odd consequences, depending upon how they have been implemented, so they should be treated as methods.

Each test of these will need to specify sets of parameters for the properties, defining both acceptable and unacceptable properties to ensure the calls return / fail in the expected manner.

You also need to be aware of security gotchas, as an example SQL injection, and test for these.

So yes, you do need to worry about testing the properties.

I believe it's silly to test getters & setters when they only make a simple operation. Personally I don't write complex unit tests to cover any usage pattern. I try to write enough tests to ensure I have handled the normal execution behavior and as much error cases I can think of. I will write more unit tests as a response to bug reports. I use unit test to ensure the code meets the requirements and to make future modification easier. I feel a lot more willing to change code when I know that if I break something a test will fail.

I would write a test for anything that you are writing code for that is testable outside of the GUI interface.

Typically, any logic that I write that has any business logic I place inside another tier or business logic layer.

Then writing tests for anything that does something is easy to do.

First pass, write a unit test for each public method in your "Business Logic Layer".

If I had a class like this:

The first thing I would do before I wrote any code knowing that I had these actions to perform would be to start writing unit tests.

Write your tests to validate the code you've written to do something. If you iterating over a collection of things, and changing something about each of them, write a test that does the same thing and Assert that actually happened.

There's a lot of other approaches you can take, namely Behavoir Driven Development (BDD), that's more involved and not a great place to start with your unit testing skills.

So, the moral of the story is, test anything that does anything you might be worried about, keep the unit tests testing specific things that are small in size, a lot of tests are good.

Keep your business logic outside of the User Interface layer so that you can easily write tests for them, and you'll be good.

I recommend TestDriven.Net or ReSharper as both easily integrate into Visual Studio.

I would recommend writing multiple tests for your Authenticate and Save methods. In addition to the success case (where all parameters are provided, everything is correctly spelled, etc), it's good to have tests for various failure cases (incorrect or missing parameters, unavailable database connections if applicable, etc). I recommend Pragmatic Unit Testing in C# with NUnit as a reference.

As others have stated, unit tests for getters and setters are overkill, unless there's conditional logic in your getters and setters.

Whilst it is possible to correctly guess where your code needs testing, I generally think you need metrics to back up this guess. Unit testing in my view goes hand in hand with code-coverage metrics.

Code with lots of tests but a small coverage hasn't been well tested. That said, code with 100% coverage but not testing the boundry and error cases is also not great.

You want a balance between high coverage (90% minimum) and variable input data.

Remember to test for "garbage in"!

Also, a unit-test is not a unit-test unless it checks for a failure. Unit-tests that don't have asserts or are marked with known exceptions will simply test that the code doesn't die when run!

You need to design your tests so that they always report failures or unexpected/unwanted data!

It makes our code better... period!

One thing us software developers forget about when doing test driven development is the purpose behind our actions. If a unit test is being written after the production code is already in place, the value of the test goes way down (but is not completely lost).

In the true spirit for unit testing, these tests are not primarily there to "test" more of our code; or to get 90%-100% better code coverage. These are all fringe benefits of writing the tests first. The big payoff is that our production code ends be be written much better due to the natural process of TDD.

To help better communicate this idea, the following may be helpful in reading:

The Flawed Theory of Unit Tests Purposeful Software Development

If we feel that the act of writing more unit tests is what helps us gain a higher quality product, then we may be suffering from a Cargo Cult of Test Driven Development.

• I disagree with the assertion that unit tests don't have value after production code is already in place. Such assertions don't account for their utility in replicating error conditions found in production, or in the understanding of code inherited from a previous developer or team. –  Scott Lawrence Commented Sep 15, 2008 at 15:25
• I may have come across incorrectly. I didn't mean that unit tests don't have value after production code is in place. However, their value goes down. The biggest benefit to unit testing comes from the inherent magic that occurs when we let them drive our production development. –  Scott Saad Commented Sep 16, 2008 at 4:20

Not the answer you're looking for? Browse other questions tagged c# unit-testing tdd or ask your own question .

• The Overflow Blog
• Community Products Roadmap Update, July 2024
• Featured on Meta
• We spent a sprint addressing your requests — here’s how it went
• Upcoming initiatives on Stack Overflow and across the Stack Exchange network...
• Policy: Generative AI (e.g., ChatGPT) is banned
• The [lib] tag is being burninated
• What makes a homepage useful for logged-in users

Hot Network Questions

• Why should I meet my advisor even if I have nothing to report?
• Beer clip packaging
• Reduce the column padding in tabular environment
• Old SF story about someone who detonated an atomic bomb, sacrificing self to save society from an evil government
• GDPR Data Processor
• Can the U. S. Supreme Court decide on agencies, laws, etc., that are not in front of them for a decision?
• Don't make noise. OR Don't make a noise
• What do you call the male equivalent to Cougar (woman)?
• confidence intervals for proportions containing a theoretically impossible value (zero)
• What is meant by "I was blue ribbon" and "I broke my blue ribbon"?
• Explain why "Calf" is the answer to "Ice mass broken off a little lower?"
• Cliffhanger ending?
• Why does redirecting stderr interfere with bash's handling of $COLUMNS and the `checkwinsize` option?
• Airtight beaks?
• Should "as a ..." and "unlike ..." clauses refer to the subject?
• Align 3 tables neatly
• How does the temperature of the condenser impact an air conditioner's energy usage?
• What is the best translation of the phrase "Live a nice life"?
• Please explain the purpose of R3 and R4 in this ground isolating amplifier
• Are US enlisted personnel (as opposed to officers) required, or allowed, to disobey unlawful orders?
• Is it possible to "label" Segwit spendable output ScriptPubKeys with arbitrary bytes?
• Why does independent research from people without formal academic qualifications generally turn out to be a complete waste of time?
• I want to leave my current job during probation but I don't want to tell the next interviewer I am currently working
• Why does Paul's fight with Feyd-Rautha take so long?