Common Unit Testing Mistakes and How to Avoid Them

Testing small parts of code is essential to ensure the code is good and works well.

By testing smaller units, it also helps to avoid issues down the line when there’s hundreds, if not thousands, of lines of code.

But this testing can annoy and confuse people if it is not done well. In this article, we will talk about common mistakes in this testing and ways to improve it.

We will also see how reviewing tests with colleagues and following suitable methods can help overcome any challenges.

What is Unit Testing?

A unit test checks the smallest part of the code on its own. This could be a function, method, or even just one line of code. It's like examining a single puzzle piece.

Making these tests small is good because they show how the code works in tiny pieces. It's like looking at a picture up close.

Plus, when tests are little, they can be done quickly – even a lot of them in just one second.

Another benefit is that it is also easier to fix any issues if the batch being tested is smaller.

Unit Testing Mistakes and How to Avoid Them :-

Unit testing can be prone to mistakes, leading to suboptimal results. Let’s look at some of the most common things that can go wrong and how you can avoid that.

Not Keeping Your Tests Up to Date

The fast pace of technological progress is evident, and this means that tests conducted months ago might not apply anymore.

It's crucial to run tests regularly since changes in requirements and code can cause difficulties not matching what they should test.

The tests should also evolve as the code evolves to reflect the changes. Neglecting test updates can lead to false or misleading results.

Solution: Running tests regularly is essential. Changes to requirements and code can cause tests to become misaligned with what they're supposed to test. It's crucial to run tests, preferably using automated unit testing. You should also be sure they stay in sync with the requirements.

Test Quantity

One of the main mistakes in unit testing is not finding the right balance. Testing every single line of code can be exhaustive and time-consuming while testing too few parts might miss critical defects.

Focusing on testing the most important functionalities and edge cases is essential.

Solution: Use techniques such as code coverage analysis and risk assessment to identify which parts of your code need the most testing. Prioritize testing for complex functions, error-prone areas, and user-facing features.

Writing Fragile Tests

One of the main issues with unit testing is creating poor-quality tests. These tests may not be straightforward, complicated, or match each other.

This makes tests challenging to grasp, change, or apply again. Additionally, it can bring mistakes or issues into your code that can lessen its quality and trustworthiness.

Solution: To create practical tests, give your trials, test cases, and test data names that explain what they're used for. Also, stick to a clear structure like the AAA pattern: Arrange, Act, and Assert.

Use testing tools that fit your project, like Jest, Mocha, or Jasmine. Have precise and accurate statements for your checks (but not too many or too few).

Add comments and explanations to clarify the test's goal without repeating the code's content. This approach helps in producing meaningful and maintainable tests.

Testing Bad Data

Using incorrect or inappropriate data for testing can result in misleading outcomes. Such examples are false positives or negatives or unimportant results.

For example, conducting tests using null values could obscure real errors or distinctive scenarios.

Likewise, performing tests with excessively similar, highly random, or overly predetermined data could diminish the effectiveness and transparency of your testing processes.

Solution: It's vital to employ practical and inclusive data that encompasses various situations and inputs. To do this, use data generators or factories to produce and control your test data dynamically, preventing repetition.

Testing Wrong Data

A significant pitfall in unit testing is checking incorrect aspects or evaluating something that isn't a unit.

Evaluating non-unit components like database queries, web service calls, or user interfaces leads to unreliable, sluggish tests that rely on external elements.

This misalignment can compromise the effectiveness of your tests.

Solution: For testing a unit effectively, employ mocks, stubs, or fakes. These techniques simulate the unit's dependencies, creating a controlled environment that isolates the unit from the larger system. This isolation aids in accurate and focused testing.

No Peer Reviews

Skipping test reviews means missing out on sharing best practices and raises the chance of test bugs. Code reviews elevate the quality of unit tests in your team.

Solution: Conduct code reviews directly, whether in person or via screen sharing, for optimal results. Written comments alone aren't as impactful; interactive discussions are crucial for meaningful exchange.

Creating Logical Tests

Putting logic into unit tests complicates their readability and upkeep and increases the risk of errors.

If your unit test contains logic, it suggests that you might not be creating proper unit tests.

Solution: Limit the number of assertions in each test. If you have too many assertions, maintenance becomes challenging. This might indicate that you're dealing with a test suite rather than a single test in the test method. If this happens, break the test method into multiple tests.

Writing Tests for Coverage

A common error people make while crafting unit tests is focusing solely on achieving high code coverage.

Coverage is a valuable metric, much like Lines of Code give insight into function complexity.

However, it's essential to recognize that code coverage alone doesn't guarantee comprehensive testing.

Solution: View coverage as a tool to identify what's not covered rather than solely measuring what is covered. It's more about finding gaps and assessing if they require attention.

For a meaningful metric, focus on the precision of your tests.

In essence, prioritize hitting the critical paths with all potential variations rather than attempting to cover every single code path.

This approach ensures a more thorough examination of your code's behavior.

Conclusion :-

Unit testing is a powerful tool for maintaining code quality, but it's essential to avoid common mistakes that can undermine its effectiveness.

By striking the right balance between testing coverage, focusing on behavior, and incorporating best practices, developers can ensure that their unit tests contribute significantly to the reliability and robustness of their software applications.