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We wanted to share some of what we have learned, both about testing in general, and about testing with XCTest. Note that some of the model classes and methods in this article have been renamed, because the project is not in the App Store yet.

With this article, we hope to shed some light on when XCTest is a good option, and when you might want to pick something else. We tried to link to the other articles in this issue where it makes sense. Why We Are Testing As the article about bad practices in testing mentions, many people believe that "the only time a test will give value back is when we want to change our code. But it is also important to remember that even when writing the first version of any code, most of the time will be spent changing code — as the project evolves, more and more features get added, and we realize that behavior needs to change slightly here and there.

So even though you're not yet working on version 1. We are still finishing the initial version of our framework, and have just recently passed 1, test cases with more than 10 man months of effort spent on the project. Even though we had a clear vision of the project's architecture, we've still had to change and adapt the code along the way.

The ever-growing set of test cases have helped us do this. They have given us a level of comfort with the quality of our code, and at the same time given us the ability to refactor and change the code while knowing that we didn't break things. And we have been able to actually run our code from day one; we didn't have to wait for all the pieces to be in place. Tests are grouped into classes that subclass from XCTestCase. Each method that has a name starting with test is a test.

Because tests are simply classes and methods, we can add property and helper methods to the class, as we see fit. In order to be able to reuse code, we have a common superclass, TestCase, for all our test classes. This class subclasses from XCTestCase. All our test classes subclass from our TestCase. We also put shared helper methods into the TestCase class. And we even have properties on it that get pre-populated for each test.

But which class and method being tested should be obvious by simply looking at the test. The "testThatIt" style shifts the focus to the desired outcome, which, in most cases, is more difficult to understand at first glance. There is a test case class for each production code class, and one is named after the other, e.

If a class gets a bit bigger, we use categories to split up the test by topics. The given section sets up the environment for the test by creating model objects or bringing the system under test to a certain state. The when section contains the code we want to test.

In most cases, this is only one method call. In the then section, we check the result of our action: Did we get the desired output? Was the object changed? This section consists mainly of assertions. For faster visual scanning, we even put the words "given," "when," and "then" as comments on top of their respective sections. This way, the method being tested immediately sticks out. Reusable Code Over time, we noticed that we repeated some code again and again in our tests, like waiting for an asynchronous operation to finish, or setting up an in-memory Core Data stack.

To avoid code duplication, we began to gather all these useful snippets into a common base class for all our tests. It turned out that this is not only useful as a collection of utility methods. The test base class can run its own -setUp and -tearDown methods to set up the environment. We use this mostly to initialize Core Data stacks for testing, to reseed our deterministic NSUUID which is one of those small things that makes debugging a lot easier , and to set up background magic to simplify asynchronous testing.

Another useful pattern we started using recently is to implement delegate protocols directly in our XCTestCase classes. This way, we don't have to awkwardly mock the delegate. Instead, we can interact with the tested class in a fairly direct way. Mocking Our mocking framework is OCMock. As described in the article about mocking in this issue, a mock is an object that returns a prepared answer for method calls.

We use mocks for all dependencies of an object. This way, we can test the behavior of a class in isolation. The obvious disadvantage is that changes in a class don't automatically lead to failing unit tests for other classes that depend on it. But this is remedied by the fact that we also have integration tests, which test all the classes together. It is important not to 'over-mock,' which is the habit of mocking every object except for the one being tested.

When we started, we got into this habit at times, and we even mocked rather simple objects that were used as input to methods. Now we use many objects just the way they are, without mocking them. As part of our common superclass for all test classes, we also added a - void verifyMockLater: id mock; method. This makes using mocks even more convenient. But at the end of the day, our apps need state. Without state, most apps would be pretty pointless.

But managing state is the source of a lot of bugs, because managing state is very complex. We made our code a lot easier to work on by isolating the state. A few classes contain state, while most are stateless. In addition to the code, testing got a whole lot easier, too. For example, we have a class, EventSync, that is responsible for sending local changes to our server.

It needs to keep track of which local objects have changes that need to get pushed to the server, and which changes are currently being pushed. We can send multiple changes at once, but we don't want to send the same change twice. We also had interdependencies between objects to keep track of.

If A has a relationship to B, and B has local changes, we need to wait for those local changes to be pushed first, before we can send the changes of A. We have a UserSyncStrategy that has a -nextRequest method that generates the next request. This request will send local changes to the server. The class itself is stateless, though. Or rather: All its state is encapsulated inside an UpstreamObjectSync class, which keeps track of all the user objects that have local changes, and for which we have running requests.

There is no state outside this class. This way, it was easy for us to have one set of tests for the UpstreamObjectSync. They check that this class manages the state correctly. That reduced the test complexity a lot, even more so because we were syncing many different kind of objects, and our different classes were all stateless and able to reuse the UpstreamObjectSync class. Core Data Our code relies heavily on Core Data. Since we need our tests to be isolated from one another, we have to bring up a clean Core Data stack for each test case, and then tear it down afterward.

We need to be sure that we don't reuse the store from one test case for the next test. All of our code is centered around two managed object contexts: one that the user-interface uses and that is tied to the main queue, and one that we use for synchronization and that has its own private queue. We didn't want to repeat creating managed object contexts inside every test that needs them.

Hence, inside our shared TestCase superclass' -setUp method, we create this set of two managed object contexts. This makes each individual test a lot easier to read. A test that needs a managed object context can simply call self. But we implemented our own -performGroupedBlock: on top of -performBlock:, in order to solve the isolation problem. More about this under our section about testing asynchronous code. Merging Multiple Contexts We have two contexts in our code.

In production, we rely heavily on being able to merge from one context to another by means of -mergeChangesFromContextDidSaveNotification:. At the same time, we are using a separate persistent store coordinator for each context. Both contexts can then access the same SQLite store with minimal contention. But for testing, we had to change this. We wanted to be able to use an in-memory store. Using an on-disk SQLite store for testing does not work, because there are race conditions associated with deleting the store on disk.

The test method will return without giving the completionHandler block a chance to be called. This is serviceable. When we instantiate a test expectation, the testing framework expects that it will be fulfilled at some point in the future. Our test code fulfills the expectation in the completion block with a call to the XCTestExpectation method fulfill. This takes the place of setting a flag like responseHasArrived in the previous example. Then we tell the test framework to wait with a timeout for its expectations to be fulfilled via the XCTestCase method waitForExpectationsWithTimeout:handler:.

If not, then the test will live a sad, lonely, unfulfilled existence… until it goes out of scope. And by living a sad, lonely, unfulfilled existence, I mean that the expectation fails the test upon timing out. Remember that a failing result is not the sign of a bad test; an indeterminate result is.

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Many web browsers, such as Internet Explorer 9, include a download manager. Stand-alone download managers also are available, including the Microsoft Download Manager. In this case, you will have to download the files individually. You would have the opportunity to download individual files on the "Thank you for downloading" page after completing your download. Files larger than 1 GB may take much longer to download and might not download correctly.

You might not be able to pause the active downloads or resume downloads that have failed. Prior to expectations, testing any code that had an async component to it either required a webwork of code that itself probably needed testing, or more sanely, the use of a third-party testing library e.

Though expectations were late to the party, those genius developers over at Apple added them in a graceful, intuitive way that made them seem like they had been a part of the test family for generations. Using expectations, however, we just add a few lines of code:. With the expectation set on the first line, we can safely run our method. Until fulfill is called the test method is considered finished, so our method has plenty of time to launch its query and return an array.

Then we hit our assertion and call fulfill whether the assertion is true or not. Modern apps have become network dependent, lightning fast UI beasts, which means a lot of the grunt work is done asynchronously - either waiting for a network response, or shoved to a background thread. Expectations offer an intuitive way to test these methods, while giving you one less reason to avoid building tests into your apps.

What if I didn't bring a completion handler to this testing party? Expectations work perfectly for async functions that have a completion handler of some type. How can we test these without resorting to adding a block just for the purpose of testing? Put Grand Central Dispatch back in its cave and sit around the warm glow of expectations yet again! The team at Apple has done a great job in making expectations an intuitive way to test async operations.

Integrating them into your testing process is painless, while those who are just starting out with testing will probably assume that XCTestExpectation has been there since day one.

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