How can you write better unit tests?

Unit tests should always be tested in isolation and should be independent. Good unit tests are the ones which are not actually interacting with an actual integration, but instead to a mocked version of it. They should not cause any side effects and should not access any database, a global state or a file system. It is always advisable to segregate the unit tests on the basis of a single behaviour they are wanting to test.

The first step towards writing the unit test is to write testable code. If you are a beginner, you will find it difficult to write the complete unit tests for your method. You will refactor your method so that it would be easier to write unit tests. This will result in better code. Slowly you will learn to write better testable code and unit tests. Writing unit tests not only helps you eliminate bugs, but also makes you a better programmer. Your code will have very few bugs, if any. This reduces the bug cycles and results in timely delivery.

Each unit test should focus on testing a single piece of functionality. Avoid testing multiple scenarios in a single test, as it makes it harder to pinpoint the cause of failures.

Certainly, I'll keep it concise. Writing effective unit tests is crucial. Focus on specific aspects, use meaningful test names, set up and tear down as needed, and regularly review and refactor tests for maintainability and relevance. It's an ongoing skill that improves with practice. ???

A *~musical~* way I can think about unit testing is how I check each part of my violin ??. For ex: - Pegs: Making sure that my pegs are just the right amount of loose so that it will not uncoil when tuning my strings or be so tight that I am unable to turn them. - Bridge: Ensuring that the bridge of my violin is standing upright on the body so that it will not collapse when I'm tuning and won't defile the sound when playing. - etc. These would be some 'unit tests' for tuning my instrument. Essentially, each test focuses on one component of a functionality. (This way, my integration test can be responsible for testing the tuning or playing aspect; how all of the components play together.)

Unit tests help us to ensure something is working as designed, following the code's flow. Because of that, you need to see the method to test as a process: Input - Data, Dependencies and everything to make sure the method will be called properly. Operation - Which method are we covering and how do we call it? Output - What am I expecting as result (in success/failure scenarios)? When creating unit tests, under the assumption you have a project that followed Single Responsibility principle, each class with functionality should have its own file with tests in it. If there are dependencies shared by multiple classes, consider introducing helpers to allocate those and reuse them across your tests.

Absolutely, structuring unit tests using the AAA pattern is like following a recipe for a delicious dish ???. It keeps things organized and makes our tests easy to understand. ?? I remember a time when I didn't follow this pattern, and my tests were all over the place. It was like trying to cook without any instructions – chaotic and confusing. ?? But once I started using AAA, it was like adding clear steps to a recipe. You know exactly what you need, what to do with it, and what the final result should be. It made writing and maintaining tests a breeze. ??? So, I totally agree that the AAA pattern should always be your go-to structure for unit tests. It's like having a well-organized kitchen for our code! ??????

Here are some additional tips for structuring your unit tests: - Use descriptive names for your test functions. - Keep your test functions short and focused. - Avoid using global variables in your tests. - Use mocks or stubs to isolate the code under test. - Run your unit tests frequently to catch bugs early.

Personally I prefer to follow Given-When-Then (GWT)?since it makes it clear in what condition what we expect from what action.

Naming unit tests used to be a bit of a puzzle for me ??. I remember the days when I'd name them something like "test_case_1" not very helpful, right? ??♂? Then I realized that clear test names are like giving your tests a superpower. ??♂? It's all about making your intentions crystal clear. When you come back to these tests months later, you want to instantly understand what they're testing and why. So, yes, I totally agree with the format that mentioned. Something like "test_[method]_[input]_[output]." It's like putting labels on your tests: "Hey, here's what this test is checking, and here's what it should do."??? This simple change made my testing life so much easier. It's like having a map that guides you through the jungle! ?????

I concur with Mohammad's entry that Given-When-Then is a superb pattern for naming your tests and test steps. Testing frameworks that drive a live user interface (such as Capybara and Selenium) have various options for interoperability with the Given-When-Then pattern, such that literal text and labels in your UI can dependably and exactly correspond to the strings you've used to write your test steps and name the related functions. Where these can be generalized and variable, you can use regular expressions for highly robust naming schema in coordination with your UI.

Here are some tips for naming your unit tests: - Use a consistent naming convention. This will make it easier to find and organize your tests. - Start the test name with the word test. - Include the name of the method or function being tested. - Include the input and output values, if relevant. - Be as specific as possible. For example, instead of just saying test_palindrome, you could say test_isPalindrome_evenLength_true. Here are some examples of good unit test names: - test_isPalindrome_evenLength_true - test_add_two_numbers_positive - test_subtract_two_numbers_negative - test_sort_list_ascending - test_check_login_credentials_valid I hope these tips help you to name your unit tests in a way that is clear, concise, and informative.

??Software code is highly testable code if it??: ??Has a great deal of conditional/DEBUG output statements that display intermediate answers/results ??Is #repeatable. When the same inputs give the #same outputs, every time. (This gets very tricky with #AI output sometimes.) ??Is #morphable. The code should allow a tester to test all blocks of code by varying only the program #inputs. ??Is highly #readable. The tester must know your thinking. In-line comments are highly recommended for this, along with code syntax that is #descriptive. ??Has a great Software Requirements Specification #document; the tester has concrete #rules to test against. ??Follows industry coding #practices. #softwaredevelopment #engineering #coding

Always start with the output you need, then inputs; only after you’ve created the test in this way you can finally start the implementation. This will make your APIs cleaner as you are always thinking in terms of inputs/outputs, and a natural byproduct of following this pattern is that your code becomes more testable. Remember that your tests should be behavior tests, not methods or implementation details (this also comes naturally if you follow the input/output pattern above).

I know, making my code testable is like preparing a dish for a cooking competition. ?? We want everything neatly organized and ready to be tasted, or in our case, tested. ?? I remember when I used to write code that was tightly coupled to databases, external services, and a million other things. Testing that was a nightmare! ?? But then, I started following some of these principles you mentioned. I started breaking down my code into smaller, focused functions, like bite-sized pieces. ?? Each function had a single job, and that made it so much easier to test. I also got into the habit of using interfaces and abstractions to hide the nitty-gritty details of how things worked. It's like putting a lid on a pot while you cook.

Here are some additional tips that you may find helpful: - Use a unit testing framework to help you write and run your tests. - Document your code and tests so that other developers can understand them. - Use a continuous integration (CI) server to automatically run your tests every time you make a change to your code. By following these tips, you can write testable code that is easier to maintain and debug. This will help you to improve the quality of your software and reduce the risk of bugs.

Testing is a critical aspect of software engineering. For testing, code should be testable. Below are some factors to consider for writing testable code: - Single Responsibility Principle: Each function or class should have a single purpose - Modularity: Break code into independent modules to aid in DRYness (Don't Repeat Yourself) - Avoid global state: Global variables are complex to test - Use dependency injection: By injecting dependencies, you can substitute them during testing - Avoid hidden side-effects: Side-effects lead to inconsistent results during testing - Mocking external services: Mocks replicate the behavior of real objects. They make testing external services simpler Tests should be consistent, repeatable, and deterministic

Assertions are one of the most important aspects of writing automated test cases and they might not always mean comparing outputs. Assertions may be of various natures:- 1. Comparing actual output of a function/method to expected output. 2. Verifying if correct method or dependency was called or not from within the function in test. 3. Checking if correct arguments were passed in dependencies, nested methods 4. Checking correct exceptions/errors are thrown in negative test cases 5. Testing performance of a method (though this may fall under performance testing in most of the cases). Always use assertion frameworks (for e.g. Hamcrest in java) in cases like when checking:- - Large JSONs, objects - Order of elements in a list - Contains check

- Use specific and expressive assertion methods. - Provide descriptive and informative failure messages. - Avoid using too many or too few assertions in one test. - Avoid testing irrelevant or trivial aspects of your code. - Avoid using logic or calculations in your assertions. - Use a continuous integration (CI) server to automatically run your assertions every time you make a change to your code.

Certainly, maintaining unit tests is crucial. When I make changes, I revisit tests, addressing failures promptly. I also review tests for duplication, complexity, and readability, ensuring they remain clear and efficient. Organizing tests into suites and using coverage and analysis tools keeps things tidy and reveals areas needing attention. Maintaining tests ensures code health and a smooth development experience. ??

To enhance the unit test code, consider adding comments that explain the purpose of each test section. By doing so, the code becomes more descriptive and accessible for other developers. With clear comments indicating the function of each section, the test becomes self-documenting. It enables developers to swiftly grasp the test's objective, the values used in the test, and the expected outcome. This practice promotes better collaboration and understanding among team members, leading to more efficient code maintenance and troubleshooting.

To enhance the unit test code, consider adding comments that explain the purpose of each test section. By doing so, the code becomes more descriptive and accessible for other developers. With clear comments indicating the function of each section, the test becomes self-documenting. It enables developers to swiftly grasp the test's objective, the values used in the test, and the expected outcome. This practice promotes better collaboration and understanding among team members, leading to more efficient code maintenance and troubleshooting.

The sad fact is that unit tests, like most tests, prove very little and do almost nothing to enhance the bug-safety and integrity of your code. That doesn't mean they are useless! Tests are important basically as specs, and to serve as live code examples of your modules and objects in action. You should write comprehensive unit tests, but you should *not* rely on them to ensure the safety of your code from bugs at runtime. For that, you should rely on a good strong typing system. The best of these exist in type-safe languages like OCaml and Standard ML, but you can find library-level typing solutions in other languages that will help with this as well (Sorbet in Ruby, Flow in JavaScript). Typing, rather than tests, proves code safety.