A builder class is made up of two main things:. In the simplified example above though, using a builder is very clear to read as setting each piece of the object state is spelled out for you. So this is great for unit tests, because we always want them to be clear to read. If arranging the state for several unit tests is a bit messy or complicated, then have a go at using the fluent builder pattern. The state under test becomes very clear to read. In some cases, using the fluent builder pattern in unit tests can help to prevent code duplication, because a single method on the builder could encapsulate a lot of state-setup code that can be written once and used by many tests.
This state-setup code is hidden away behind methods with clear names, which is all you need to know when reading a unit test to understand what is being tested. You are not limited to using Set methods on the builder, and the Build method is not limited to only calling a constructor.
Arranging the state of the object may also involve calling methods that add objects to child collections, or void-parameterless methods that update the objects state in some way. If the project you are testing already provides a fluent builder, you might be able to use that, otherwise add one to the unit test project. There are quite a few ways of tackling tests for units dealing with databases. Some of which are frowned upon though, such as pointing directly to the production database.
I would not recommend you do that. The easiest way of testing with databases is made possible if the unit your are testing uses an ORM. LightSpeed, for example, provides an IUnitOfWork that connects to a database and provides collections of objects that you work with directly using C.
Each collection is like a table, and each object is a record. The objects contain properties that map to columns in the table. By simply faking or mocking the IUnitOfWork, you can completely remove the need to connect to an actual database while running the unit tests.
When running the unit tests, the unit will fetch those objects and function in the same way as though it was interacting with a database. These are frameworks that aid in mocking databases, so that again you can test queries without actually connecting to a database. The main remaining option is to resort to setting up and connecting to a test database.
I personally find that this is a good path to take though, especially when raw database queries are involved.
Once this is done, the tests will:. This means that each new feature is tested individually on its own. A problematic feature i. In the ideal case, testers are just creating new tests that are added to an existing test suite. Testers themselves do not run tests manually. The test suite is run by the build server. In summary, testing should be something that happens all the time behind the scenes by the build server.
Developers should learn the result of the test for their individual feature after minutes of committing code. Testers should create new tests and refactor existing ones, instead of actually running tests.
If you are a seasoned developer, you will spend always some time to structure new code in your mind before implementing it. There are several philosophies regarding code design and some of them are so significant that have their own Wikipedia entry. Some examples are:. The first one is arguably the most important one as it forces you to have a single source of truth for code that is reused across multiple features.
Depending on your own programming language you may also have access to several other best practices and recommended design patterns. You might even have special guidelines that are specific to your team.
Yet, for some unknown reason several developers do not apply the same principles to the code that holds the software tests.
I have seen projects which have well designed feature code, but suffer from tests with huge code duplication, hardcoded variables, copy-paste segments and several other inefficiencies that would be considered inexcusable if found on the main code.
Treating test code as a second class citizen makes no sense, because in the long run all code needs maintenance. Tests will need to be updated and refactored in the future. Their variables and structure will need to change. If you write tests without thinking about their design you are creating additional technical debt that will be added to the one already present in the main code. Try to design your tests with the same attention that you give to the feature code.
All common refactoring techniques should be used on tests as well. As a starting point. If you employ tools for static analysis, source formatting or code quality then configure them to run on test code, too. One of the goals of testing is to catch regressions. One of the best ways to enforce this is to write a test for the fix either unit or integration or both. They correct the code and fix the bug straight away. For some strange reason a lot of developers assume that writing tests is only valuable when you are adding a new feature only.
This could not be further from the truth. I would even argue that software tests that stem from actual bugs are more valuable than tests which are added as part of new development. After all you never know how often a new feature will break in production maybe it belongs to non-critical code that will never break.
The respective software test is good to have but its value is questionable. On the other hand the software test that you write for a real bug is super valuable. Not only it verifies that your fix is correct, but also ensures that your fix will always be active even if refactorings happen in the same area.
If you join a legacy project that has no tests this is also the most obvious way to start getting value from software testing. Rather than attempting to guess which code needs tests, you should pay attention to the existing bugs and try to cover them with tests.
After a while your tests will have covered the critical part of the code, since by definition all tests have verified things that break often. One of my suggested metrics embodies the recording of this effort. The only case where it is acceptable to not write tests is when bugs that you find in production are unrelated to code and instead stem from the environment itself.
A misconfiguration to a load balancer for example is not something that can be solved with a unit test. In summary, if you are unsure on what code you need to test next, look at the bugs that slip into production.
TDD stands for Test Driven Development and like all methodologies before it, it is a good idea on paper until consultants try to convince a company that following TDD blindly is the only way forward.
At the time or writing this trend is slowly dying but I decided to mention it here for completeness as the enterprise world is especially suffering from this anti-pattern. One of the core tenets of TDD is always following option 1 writing tests before the implementation code.
Writing tests before the code is a good general practice but is certainly not always the best practice. Writing tests before the implementation code implies that you are certain about your final API, which may or may not be the case. Maybe you have a clear specification document in front of you and thus know the exact signatures of the code methods that need to be implemented. But in other cases you might want to just experiment on something, do a quick spike and work towards a solution instead of a solution itself.
For a more practical example, it would be immature for a startup to follow blindly TDD. If you work in a startup company you might write code that will change so fast that TDD will not be a big help. Writing tests after the implementation code, is a perfectly valid strategy in that case.
Writing no tests at all option 4 is also a valid strategy. As we have seen in anti-pattern 4 there is code that never needs testing. The obsession of TDD zealots on writing tests first no matter the case, has been a huge detriment to the mental health of sane developers.
At this point I would like to admit that several times I have personally implemented code like this:. If you work in a fortune company, surrounded by business analysts and getting clear specs on what you need to implement, then TDD might be helpful.
On the other hand if you are just playing with a new framework at your house during the weekend and want to understand how it works, then feel free to not follow TDD. A professional developer is one who knows the tools of the trade.
You might need to spend extra time at the beginning of a project to learn about the technologies you are going to use. Web frameworks are coming out all the time and it always pays off to know all the capabilities that can be employed in order to write effective and concise code.
You should treat software tests with the same respect. Because several developers treat tests as something secondary see also Anti-pattern 9 they never sit down to actually learn what their testing framework can do.
Copy-pasting testing code from other projects and examples might seem to work at first glance, but this is not the way a professional should behave. Unfortunately this pattern happens all too often.
You should spend some time to learn what your testing framework can do. For example try to find how it can work with:. If you are also working on the stereotypical web application you should do some minimal research to understand what are the best practices regarding. There is no need to re-invent the wheel. The sentence applies to testing code as well.
Maybe there are some corner cases where your main application is indeed a snowflake and needs some in-house utility for the core code. But I can bet that your unit and integration tests are not special themselves and thus writing custom testing utilities is a questionable practice. Even though I mention this as the last anti-pattern, this is the one that forced me to write this article.
A more common occurrence is meeting people who are against a specific type of testing usually either unit or integration like we have seen in anti-patterns 1 or 2. When I find people like this, it is my hobby to probe them with questions and understand their reasons behind hating tests.
And always, it boils down to anti-patterns. They previously worked in companies where tests were slow Anti pattern 7 , or needed constant refactoring Antipattern 5. If you are one of those people I truly feel for you. I know how hard it is to work in a company that has bad habits. Bad experiences of testing in the past should not clutter your judgment when it comes to testing your next greenfield project.
Try to look objectively at your team and your project and see if any of the anti-patterns apply to you. If yes, then you are simply testing in the wrong way and no amount of tests will make your application better. Try to find them! Go back to contents , contact me via email or find me at Twitter if you have a comment. Codepipes Blog A technical blog by Kostis Kapelonis. Software Testing Anti-patterns 21 Apr Introduction There are several articles out there that talk about testing anti-patterns in the software development process.
Terminology Unfortunately, testing terminology has not reached a common consensus yet. Some good starting points are: The forgotten layer of the test automation pyramid Mike Cohn The Test Pyramid Martin Fowler Google Testing blog Google The Practical Test Pyramid Ham Vocke The testing pyramid deserves a whole discussion on its own, especially on the topic of the amount of tests needed for each category.
Software Testing Anti-Pattern List Having unit tests without integration tests Having integration tests without unit tests Having the wrong kind of tests Testing the wrong functionality Testing internal implementation Paying excessive attention to test coverage Having flaky or slow tests Running tests manually Treating test code as a second class citizen Not converting production bugs to tests Treating TDD as a religion Writing tests without reading documentation first Giving testing a bad reputation out of ignorance Anti-Pattern 1 - Having unit tests without integration tests This problem is a classic one with small to medium companies.
Usually lack of integration tests is caused by any of the following issues: The company has no senior developers. The team has only junior developers fresh out of college who have only seen unit tests Integration tests existed at one point but were abandoned because they caused more trouble than their worth.
Unit tests were much more easy to maintain and so they prevailed. But why are integration tests essential in the first place? Anti-Pattern 2 - Having integration tests without unit tests This is the inverse of the previous anti-pattern. Integration tests are slow The second big issue with integration tests apart from their complexity is their speed.
Integration tests are harder to debug than unit tests The last reason why having only integration tests without any unit tests is an anti-pattern is the amount of time spent to debug a failed test. Quick summary of why you need unit tests This is the longest section of this article, but I consider it very important.
In summary while in theory you could only have integration tests, in practice Unit tests are easier to maintain Unit tests can easily replicate corner cases and not-so-frequent scenarios Unit tests run much faster than integration tests Broken unit tests are easier to fix than broken integration tests If you only have integration tests, you waste developer time and company money. Anti-Pattern 3 - Having the wrong kind of tests Now that we have seen why we need both kinds of tests unit and integration , we need to decide on how many tests we need from each category.
In this contrived example you would need: Lots and lots of unit tests for the mathematical equations. Here is the breakdown of tests for this project: Unit tests dominate in this example and the shape is not a pyramid.
Screenplay uses the idea of actors, tasks and goals to express tests in business terms, rather than in terms of interactions with the system. In Screenplay, you describe tests in terms of an actor who has goals. The Ports and Adapters design strives to make sure you are using the Single Responsibility Principle so that an object should do only one thing and have only one reason to change.
Of course, this is not easy to do, but the more you strive to do this when creating UI automation, the better off you will be. It's a tiny application with full-stack acceptance tests that can run in milliseconds. Its purpose is to illustrate the essential techniques to achieve this in any system. Presenter First is a modification of the model-view-controller MVC way of organizing code and development behaviors to create completely tested software using a test-driven development TDD approach.
I first learned of this pattern when interviewing Seb Rose SebRose , one of the contributors to the Cucumber project and author of the book Cucumber for Java. He mentioned that if you draw out the MVC pattern as blocks and arrows, you can see that the view, which is your UI, has well-defined channels of communication with the model and the controller.
You can also set your model and controller to mimic all sorts of odd behaviors, like a network going down. I was feeling pretty good about my list until I interviewed Seretta Gamba , author of the newly released book A Journey through Test Automation Patterns, where she and her co-author Dorothy Graham cover 86 patterns!
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