Unit Testing

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last updated: 2017-08

Mobile apps have unique problems that desktop and web-based applications don't have to worry about. Mobile users will differ by the devices that they use, by network connectivity, by the availability of services, and a range of other factors. Therefore, mobile apps should be tested as they will be used in the real world in order to improve their quality, reliability, and performance. There are many types of testing that should be performed on an app, including unit testing, integration testing, and user interface testing, with unit testing being the most common form of testing.

A unit test takes a small unit of the app, typically a method, isolates it from the remainder of the code, and verifies that it behaves as expected. Its goal is to check that each unit of functionality performs as expected, so that errors don't propagate throughout the app. Detecting a bug where it occurs is more efficient that observing the effect of a bug indirectly at a secondary point of failure.

Unit testing has the greatest effect on code quality when it's an integral part of the software development workflow. As soon as a method has been written, unit tests should be written that verify the behavior of the method in response to standard, boundary, and incorrect cases of input data, and that check any explicit or implicit assumptions made by the code. Alternatively, with test driven development, unit tests are written before the code. In this scenario, unit tests act as both design documentation and functional specifications.

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Note: Unit tests are very effective against regression – that is, functionality that used to work but has been disturbed by a faulty update.

Unit tests typically use the arrange-act-assert pattern:

  • The arrange section of the unit test method initializes objects and sets the value of the data that is passed to the method under test.
  • The act section invokes the method under test with the required arguments.
  • The assert section verifies that the action of the method under test behaves as expected.

Following this pattern ensures that unit tests are readable and consistent.

Dependency Injection and Unit Testing

One of the motivations for adopting a loosely-coupled architecture is that it facilitates unit testing. One of the types registered with Autofac is the OrderService class. The following code example shows an outline of this class:

public class OrderDetailViewModel : ViewModelBase  
{  
    private IOrderService _ordersService;  

    public OrderDetailViewModel(IOrderService ordersService)  
    {  
        _ordersService = ordersService;  
    }  
    ...  
}

The OrderDetailViewModel class has a dependency on the IOrderService type which the container resolves when it instantiates a OrderDetailViewModel object. However, rather than create an OrderService object to unit test the OrderDetailViewModel class, instead, replace the OrderService object with a mock for the purpose of the tests. Figure 10-1 illustrates this relationship.

Figure 10-1: Classes that implement the IOrderService interface

This approach allows the OrderService object to be passed into the OrderDetailViewModel class at runtime, and in the interests of testability, it allows the OrderMockService class to be passed into the OrderDetailViewModel class at test time. The main advantage of this approach is that it enables unit tests to be executed without requiring unwieldy resources such as web services, or databases.

Testing MVVM Applications

Testing models and view models from MVVM applications is identical to testing any other classes, and the same tools and techniques – such as unit testing and mocking, can be used. However, there are some patterns that are typical to model and view model classes, that can benefit from specific unit testing techniques.

💡 Tip: Test one thing with each unit test. Don't be tempted to make a unit test exercise more than one aspect of the unit's behavior. Doing so leads to tests that are difficult to read and update. It can also lead to confusion when interpreting a failure.

The eShopOnContainers mobile app uses xUnit to perform unit testing, which supports two different types of unit tests:

  • Facts are tests that are always true, which test invariant conditions.
  • Theories are tests that are only true for a particular set of data.

The unit tests included with the eShopOnContainers mobile app are fact tests, and so each unit test method is decorated with the [Fact] attribute.

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Note: xUnit tests are executed by a test runner. To execute the test runner, run the eShopOnContainers.TestRunner project for the required platform.

Testing Asynchronous Functionality

When implementing the MVVM pattern, view models usually invoke operations on services, often asynchronously. Tests for code that invokes these operations typically use mocks as replacements for the actual services. The following code example demonstrates testing asynchronous functionality by passing a mock service into a view model:

[Fact]  
public async Task OrderPropertyIsNotNullAfterViewModelInitializationTest()  
{  
    var orderService = new OrderMockService();  
    var orderViewModel = new OrderDetailViewModel(orderService);  

    var order = await orderService.GetOrderAsync(1, GlobalSetting.Instance.AuthToken);  
    await orderViewModel.InitializeAsync(order);  

    Assert.NotNull(orderViewModel.Order);  
}

This unit test checks that the Order property of the OrderDetailViewModel instance will have a value after the InitializeAsync method has been invoked. The InitializeAsync method is invoked when the view model's corresponding view is navigated to. For more information about navigation, see Navigation.

When the OrderDetailViewModel instance is created, it expects an OrderService instance to be specified as an argument. However, the OrderService retrieves data from a web service. Therefore, an OrderMockService instance, which is a mock version of the OrderService class, is specified as the argument to the OrderDetailViewModel constructor. Then, when the view model's InitializeAsync method is invoked, which invokes IOrderService operations, mock data is retrieved rather than communicating with a web service.

Testing INotifyPropertyChanged Implementations

Implementing the INotifyPropertyChanged interface allows views to react to changes that originate from view models and models. These changes are not limited to data shown in controls – they are also used to control the view, such as view model states that cause animations to be started or controls to be disabled.

Properties that can be updated directly by the unit test can be tested by attaching an event handler to the PropertyChanged event and checking whether the event is raised after setting a new value for the property. The following code example shows such a test:

[Fact]  
public async Task SettingOrderPropertyShouldRaisePropertyChanged()  
{  
    bool invoked = false;  
    var orderService = new OrderMockService();  
    var orderViewModel = new OrderDetailViewModel(orderService);  

    orderViewModel.PropertyChanged += (sender, e) =>  
    {  
        if (e.PropertyName.Equals("Order"))  
            invoked = true;  
    };  
    var order = await orderService.GetOrderAsync(1, GlobalSetting.Instance.AuthToken);  
    await orderViewModel.InitializeAsync(order);  

    Assert.True(invoked);  
}

This unit test invokes the InitializeAsync method of the OrderViewModel class, which causes its Order property to be updated. The unit test will pass, provided that the PropertyChanged event is raised for the Order property.

Testing Message-based Communication

View models that use the MessagingCenter class to communicate between loosely-coupled classes can be unit tested by subscribing to the message being sent by the code under test, as demonstrated in the following code example:

[Fact]  
public void AddCatalogItemCommandSendsAddProductMessageTest()  
{  
    bool messageReceived = false;  
    var catalogService = new CatalogMockService();  
    var catalogViewModel = new CatalogViewModel(catalogService);  

    Xamarin.Forms.MessagingCenter.Subscribe<CatalogViewModel, CatalogItem>(  
        this, MessageKeys.AddProduct, (sender, arg) =>  
    {  
        messageReceived = true;  
    });  
    catalogViewModel.AddCatalogItemCommand.Execute(null);  

    Assert.True(messageReceived);  
}

This unit test checks that the CatalogViewModel publishes the AddProduct message in response to its AddCatalogItemCommand being executed. Because the MessagingCenter class supports multicast message subscriptions, the unit test can subscribe to the AddProduct message and execute a callback delegate in response to receiving it. This callback delegate, specified as a lambda expression, sets a boolean field that's used by the Assert statement to verify the behavior of the test.

Testing Exception Handling

Unit tests can also be written that check that specific exceptions are thrown for invalid actions or inputs, as demonstrated in the following code example:

[Fact]  
public void InvalidEventNameShouldThrowArgumentExceptionText()  
{  
    var behavior = new MockEventToCommandBehavior  
    {  
        EventName = "OnItemTapped"  
    };  
    var listView = new ListView();  

    Assert.Throws<ArgumentException>(() => listView.Behaviors.Add(behavior));  
}

This unit test will throw an exception, because the ListView control does not have an event named OnItemTapped. The Assert.Throws<T> method is a generic method where T is the type of the expected exception. The argument passed to the Assert.Throws<T> method is a lambda expression that will throw the exception. Therefore, the unit test will pass provided that the lambda expression throws an ArgumentException.

💡 Tip: Avoid writing unit tests that examine exception message strings. Exception message strings might change over time, and so unit tests that rely on their presence are regarded as brittle.

Testing Validation

There are two aspects to testing the validation implementation: testing that any validation rules are correctly implemented, and testing that the ValidatableObject<T> class performs as expected.

Validation logic is usually simple to test, because it is typically a self-contained process where the output depends on the input. There should be tests on the results of invoking the Validate method on each property that has at least one associated validation rule, as demonstrated in the following code example:

[Fact]  
public void CheckValidationPassesWhenBothPropertiesHaveDataTest()  
{  
    var mockViewModel = new MockViewModel();  
    mockViewModel.Forename.Value = "John";  
    mockViewModel.Surname.Value = "Smith";  

    bool isValid = mockViewModel.Validate();  

    Assert.True(isValid);  
}

This unit test checks that validation succeeds when the two ValidatableObject<T> properties in the MockViewModel instance both have data.

As well as checking that validation succeeds, validation unit tests should also check the values of the Value, IsValid, and Errors property of each ValidatableObject<T> instance, to verify that the class performs as expected. The following code example demonstrates a unit test that does this:

[Fact]  
public void CheckValidationFailsWhenOnlyForenameHasDataTest()  
{  
    var mockViewModel = new MockViewModel();  
    mockViewModel.Forename.Value = "John";  

    bool isValid = mockViewModel.Validate();  

    Assert.False(isValid);  
    Assert.NotNull(mockViewModel.Forename.Value);  
    Assert.Null(mockViewModel.Surname.Value);  
    Assert.True(mockViewModel.Forename.IsValid);  
    Assert.False(mockViewModel.Surname.IsValid);  
    Assert.Empty(mockViewModel.Forename.Errors);  
    Assert.NotEmpty(mockViewModel.Surname.Errors);  
}

This unit test checks that validation fails when the Surname property of the MockViewModel doesn't have any data, and the Value, IsValid, and Errors property of each ValidatableObject<T> instance are correctly set.

Summary

A unit test takes a small unit of the app, typically a method, isolates it from the remainder of the code, and verifies that it behaves as expected. Its goal is to check that each unit of functionality performs as expected, so that errors don't propagate throughout the app.

The behavior of an object under test can be isolated by replacing dependent objects with mock objects that simulate the behavior of the dependent objects. This enables unit tests to be executed without requiring unwieldy resources such as web services, or databases.

Testing models and view models from MVVM applications is identical to testing any other classes, and the same tools and techniques can be used.

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