A Practical Guide to Unit, Integration and Acceptance Testing in C#

🎯 Why Testing Should Not Be an Afterthought

Postponing testing until the majority of the application is fully implemented introduces multiple risks:

Incorrectly designed classes might influence the implementation of other components, making late fixes expensive
Testing multiple modules together increases the complexity exponentially due to the combination of possible execution paths
Identifying bugs becomes harder when many modules are tested as a group
Any change in a shared module forces you to rewrite all its related tests

Testing each module separately is far more efficient. However, unit testing alone is not sufficient because some issues emerge only when modules interact. This is why a structured multi-stage testing strategy is needed.

🧱 The Three Layers of Software Testing

✅ Unit Tests

Focused on individual methods or classes
Free from dependencies like databases or external services
Aim to cover all possible execution paths
Fast, deterministic and suitable for automation

Because each module has a limited number of paths, unit testing can and should aim for full coverage.

🔗 Integration Tests

Executed after all unit tests pass
Validate the interactions between modules
Do not need to be exhaustive, since unit tests already verify correctness at the module level
Focus on common and edge-case interaction patterns

For example, if a module interaction pattern expects an array input, tests should be written for:

A typical array
A null array
An empty array
A very large array

This ensures compatibility between module behavior and actual integration usage.

🎯 Acceptance Tests

Executed at the end of each sprint or before release
Verify both functional and non-functional requirements
Include functional tests (what the app does) and performance tests (how well it performs)

Acceptance tests validate the final product against business expectations and help ensure the UI and performance meet real-world standards.

🤖 Automating Unit and Integration Tests

Automation is essential in modern CI/CD workflows. Automated tests:

Run quickly and repeatedly after each change
Reduce the risk of regression
Allow faster and safer releases
Provide documentation and confidence during refactoring

As bugs are discovered, new tests are added to cover them. Over time, this builds a more robust and self-defending codebase.

🧪 Writing Unit and Integration Tests in Practice

Most platforms offer tooling to simplify testing. In .NET, you typically use frameworks like MSTest, xUnit or NUnit, supported by Visual Studio’s integrated test runner.

🧱 Structure of a Test

Each test includes three main stages:

Test Preparation:
Set up the shared environment such as fake services, mock dependencies or test data
Test Execution:
Call the method under test and compare results using assertions like Assert.Equal(x, y)
Tear-Down:
Clean up the environment so tests remain isolated

🧪 Using Mocks

Unit tests avoid using real dependencies
Classes or interfaces are mocked to simulate interactions
Mock libraries (like Moq in .NET) help simulate method calls and verify behaviors
For example:

var mock = new Mock<IMyService>();
mock.Setup(m => m.GetData()).Returns(fakeData);

Mocks allow testing class A independently of class B even if A depends on B.

To maximize testability:

Inject dependencies via interfaces
Avoid static global instances in public fields
Use dependency injection to isolate behavior

🧪 Acceptance Testing: Functional and Performance

✔️ Functional Testing

Verifies that the software does what stakeholders expect
Usually bypasses the UI by injecting inputs directly into backend logic
In ASP.NET Core, use tools like Microsoft.AspNetCore.Mvc.Testing with AngleSharp for efficient functional test automation

These tests are sometimes called subcutaneous tests, as they operate just beneath the user interface.

🧪 UI Testing: When and Why

UI tests are expensive and fragile:

Difficult to automate
Break easily with small UI changes
Time-consuming to maintain

Use tools like Selenium IDE during manual tests to record repeatable test sessions but rely on automation only for stable UI sections.

🚀 Performance Testing

Performance tests simulate load on a staging environment that mimics production. They help:

Verify response times under normal and high loads
Discover bottlenecks
Decide between optimizing code or upgrading infrastructure

Fake loads should reflect real usage patterns, ideally extracted from production logs. You can monitor:

Memory consumption
I/O throughput
Execution times of critical methods

These insights help you scale wisely and prepare the application for real-world usage.

🧾 Summary

A solid testing strategy in C# involves:

Writing complete unit tests that isolate and verify internal logic
Adding integration tests that confirm inter-module cooperation
Running acceptance tests that verify functionality and performance

When done right, testing adds confidence, reduces bugs and enables agility during development. Use automation wisely to support continuous improvement and release with confidence.