If you thought writing tests for your app was fun, wait until you try writing tests for the very frameworks that power your tests! Yes, this is meta – and it's also a ton of fun. In this tutorial, we’ll show you how to contribute to testing frameworks by adding or improving their test cases. You’ll learn what makes a good test in the context of a testing library, why edge cases matter more than you think, and how to help ensure the framework doesn’t break down the road.

By the end of this tutorial, you’ll have experience with one of the most valuable (and sometimes overlooked) tasks in open-source projects: boosting the reliability of tools that countless developers rely on. Let’s dive in!

Step 1: Understanding the Structure of Test Suites in Testing Libraries

Before you start writing tests, it’s important to understand how testing frameworks are tested themselves. Most testing frameworks like Mocha, Jest, or smaller niche tools have their own suite of tests to ensure that their features work as expected. These test suites often serve as both quality assurance and documentation, showing how the framework is supposed to behave.

Anatomy of a Test Suite:

Here’s what you’ll generally find in a testing library’s test suite:

1. Unit Tests: Just like in any other project, unit tests focus on testing individual functions or methods in isolation. In a testing framework, these tests ensure that the core functionalities (like asserting values or throwing errors) behave correctly.

2. Integration Tests: These tests verify that different parts of the framework work together as expected. For example, integration tests might check if a test runner correctly handles multiple test files or if it outputs results in the right format.

3. Edge Case Tests: This is where things get fun. Testing frameworks need to be prepared for all sorts of weird and unexpected inputs. Edge case tests ensure that the framework doesn’t crash or misbehave when given unusual inputs, like massive amounts of data, circular references, or empty files.

4. Mock and Stub Tests: Many testing frameworks rely heavily on mocks and stubs to simulate external systems or dependencies. These tests ensure that the mocking and stubbing features work as expected, providing users with accurate and flexible tools.

Example: Mocha's Test Suite

Let’s take Mocha as an example. If you browse through Mocha’s repository, you’ll find a folder called test. This is where all the tests live, and inside, you’ll see various files that cover different aspects of the framework. There’s usually a test.js file that serves as the main entry point for running tests, and each module or feature of the framework gets its own set of tests.

Understanding this structure is crucial because when you start adding new tests, you’ll need to know where to place them and how they fit into the bigger picture.

Step 2: Adding New Test Cases for Features That Might Be Under-Tested

One of the easiest ways to start contributing to a testing framework is by improving its test coverage. Coverage refers to how much of the codebase is covered by tests. You’d be surprised how often important parts of a testing library are under-tested, especially in smaller frameworks or lesser-known plugins.

How to Find Under-Tested Features:

1. Look for Coverage Reports: Many open-source projects include a coverage report that shows which parts of the codebase have tests and which parts don’t. If the project uses a tool like Istanbul, you can find a coverage report in the repository, usually in a coverage folder. This report will give you a breakdown of how much of each file is covered by tests.

2. Check for Untested Edge Cases: Even if a feature is tested, there might be edge cases that haven’t been covered. For example, a test might check that a function works with standard inputs, but what happens if the input is null or undefined? What if the input is an array of arrays? Adding tests for these edge cases can significantly improve the framework’s reliability.

3. Explore Open Issues: Sometimes, maintainers will open issues asking for more tests to be written for specific features. Look for issues tagged with test coverage or needs tests. These are great opportunities for first-time contributors because the maintainer has already identified the problem – you just need to write the tests!

Step 3: Using TDD (Test-Driven Development) When Adding Features

Test-Driven Development (TDD) is a methodology where you write tests before writing the actual code. While this approach can feel a bit backward at first, it forces you to think through the feature you’re building and ensures that your code is thoroughly tested from the start.

How TDD Works:

1. Write the Test First: Before writing any new code, think about how the feature should behave and write a test that checks for this behavior. For example, if you’re adding a new assertion method to a framework, your test should verify that this method behaves as expected under different conditions.

2. Run the Test (It Should Fail): After writing the test, run it. Since you haven’t written the actual code yet, the test should fail. This is expected! The idea is that you’re defining what "success" looks like by writing the test first.

3. Write the Code: Now, write the code to make the test pass. This step is where you implement the feature or fix the bug, keeping the test in mind as your goal.

4. Run the Test Again (It Should Pass): Once you’ve written the code, run the test again. This time, it should pass. If it doesn’t, you’ll need to debug your code until the test passes successfully.

5. Refactor (If Necessary): After the test passes, you can refactor your code to make it cleaner or more efficient, knowing that the test will catch any issues introduced during refactoring.

Example: Adding a New Assertion Method

Let’s say you’re contributing to a testing framework and want to add a new assertion method called toBeEven(). Using TDD, you’d start by writing a test that checks if the toBeEven() method works as expected:

it('should assert that a number is even', () => {
  expect(4).toBeEven();
  expect(5).not.toBeEven();
});

You’d then run the test, see it fail (because toBeEven() doesn’t exist yet), and proceed to implement the method:

expect.extend({
  toBeEven(received) {
    const pass = received % 2 === 0;
    if (pass) {
      return {
        message: () => `expected ${received} not to be even`,
        pass: true,
      };
    } else {
      return {
        message: () => `expected ${received} to be even`,
        pass: false,
      };
    }
  },
});

Finally, you’d run the test again and see it pass. Congrats – you’ve just added a new feature using TDD!

Step 4: Writing Meaningful Test Assertions (Because Nobody Likes Flaky Tests)

Flaky tests are the worst. They pass sometimes, fail other times, and generally cause headaches for developers. One of the most important skills you can develop as a contributor to testing frameworks is writing solid, reliable test assertions that don’t flake out.

How to Write Reliable Assertions:

1. Be Specific: Make sure your assertions are as specific as possible. Instead of asserting that something "exists" or is "truthy," assert exactly what you expect the value to be. For example, if you’re testing an array, don’t just assert that the array has items – assert that the array has the exact number of items you expect.

   expect(array.length).toBe(3);
   expect(array).toContain('item');
   

2. Avoid Race Conditions: Race conditions can cause flaky tests, especially when testing asynchronous code. Make sure your tests account for any delays or timing issues by using proper asynchronous handling, like async/await or callbacks.

3. Use Mock Data for Consistency: Whenever possible, use mock data or fixtures in your tests to ensure consistency. Relying on real data can introduce variability that causes tests to pass sometimes and fail other times. By mocking the data, you have full control over the test environment.

Step 5: How to Test Edge Cases (And Why They Matter More Than You Think)

Testing edge cases is one of the most valuable things you can do for a testing framework. Edge cases are the weird, unexpected scenarios that developers might not think to test but that can break a framework if they’re not handled properly.

Why Edge Cases Matter:

1. Unusual Inputs: Testing frameworks need to handle all sorts of unusual inputs. For example, what happens if a test file is completely empty? Or if the input to a test is a circular reference? These scenarios might seem unlikely, but they can cause a framework to crash if they’re not handled properly.

2. Boundary Conditions: Boundary conditions are values at the extreme ends of the input range. For example, if a test framework allows users to set a timeout for their tests, you should test what happens when the timeout is 0 or a negative number.

3. Performance Under Stress: Sometimes, edge cases involve performance. What happens if a user runs thousands of tests at once? Does the framework slow down or crash? Testing for performance edge cases ensures that the framework remains reliable even under heavy loads.

Example: Testing Circular References

Circular references can cause all sorts of issues in a testing framework, especially if the framework tries to serialize or clone objects with circular references. Here’s an example of how you might test for this edge case:

it('should handle circular references without crashing', () => {
  const obj = {};
  obj.self = obj;

  expect(() => {
    myFramework.serialize(obj);
  }).not.toThrow();
});

This test ensures that the framework doesn’t crash when it encounters a circular reference – a rare but important edge case.

Improving Test Coverage Like a Pro

By the end of this tutorial, you’ll have a solid understanding of how to contribute to testing frameworks by adding and improving test cases. You’ve learned how to structure your tests, how to use TDD to add new features, and how to write reliable assertions and edge case tests. Now, it’s time to put that knowledge into practice.

Find a testing framework you want to contribute to, check the coverage report, and look for opportunities to add tests. Remember, every test you write makes the framework more reliable and helps developers catch issues early. You’re making the software world a better place, one test case at a time!