How to use shouldSayTooManyInvocations method of org.mockitousage.stacktrace.PointingStackTraceToActualInvocationTest class

Mockito mock works when we mock the objects loosely.

Here is the change i have made to make it work:

when(controlWfDefTypeService.getDqCntlWfDefnTypCd(any(DqCntlWfDefn.class))
    .thenReturn(dqCntlWfDefnTyp);

Instead of passing the object of the Mock class, I passed the class with the Matcher any() and it works.

In addition to whummer's and shachar's answers:

If you're a lucky JUnit 5 user, let me recommend you JUnit 5 extensions for AWS*, a few JUnit 5 extensions that could be useful for testing AWS-related code. These extensions can be used to inject clients for AWS service clients provided by tools like localstack (or the real ones). Both AWS Java SDK v 2.x and v 1.x are supported.

*I maintain this library

If you really don't have a choice for refactoring you can mock/stub everything in the super method call e.g.

    class BaseService {

        public void validate(){
            fail(" I must not be called");
        }

        public void save(){
            //Save method of super will still be called.
            validate();
        }
    }

    class ChildService extends BaseService{

        public void load(){}

        public void save(){
            super.save();
            load();
        }
    }

    @Test
    public void testSave() {
        ChildService classToTest = Mockito.spy(new ChildService());

        // Prevent/stub logic in super.save()
        Mockito.doNothing().when((BaseService)classToTest).validate();

        // When
        classToTest.save();

        // Then
        verify(classToTest).load();
    }

Well, the common approach to data storage in Java is, as you noted, not at all very object-oriented. This is in and of itself neither bad nor good: "object-orientedness" is neither an advantage nor disadvantage, it's just one of many paradigms, that sometimes helps with good architecture design (and sometimes not).

The reason DAOs in Java aren't usually object-oriented is exactly what you want to achieve – relaxing your dependency on the database. In a better-designed language, that allowed for multiple inheritances, this, of course, can be done very elegantly in an object-oriented way, but with Java, it just seems to be more troublesome than it is worth.

In a broader sense, the non-OO approach helps decouple your application-level data from the way it is stored. This is more than (non-)dependency on the specifics of a particular database, but also the storage schemas, which is especially important when using relational databases (don't get me started on ORM): you can have a well-designed relational schema seamlessly translated into the application OO model by your DAO.

So, what most DAOs are in Java nowadays are essentially what you mentioned in the beginning – classes, full of static methods. One difference is that, instead of making all the methods static, it is better to have a single static "factory method" (probably, in a different class), that returns a (singleton) instance of your DAO, which implements a particular interface, used by application code to access the database:

public interface GreatDAO {
    User getUser(int id);
    void saveUser(User u);
}
public class TheGreatestDAO implements GreatDAO {
   protected TheGreatestDAO() {}
   ... 
}
public class GreatDAOFactory {
     private static GreatDAO dao = null;
     protected static synchronized GreatDao setDAO(final GreatDAO d) {
         final GreatDAO old = dao;
         dao = d;
         return old;
     }
     public static synchronized GreatDAO getDAO() {
         return dao == null ? dao = new TheGreatestDAO() : dao;
     }
}

public class App {
     void setUserName(final int id, final String name) {
          final GreatDAO dao =  GreatDAOFactory.getDao();
          final User u = dao.getUser(id);
          u.setName(name);
          dao.saveUser(u);
     }
}

Why do it this way as opposed to static methods? Well, what if you do decide to switch to a different database? Naturally, you'd create a new DAO class, implementing the logic for your new storage. If you were using static methods, you would now have to go through all your code, accessing the DAO, and change it to use your new class, right? This could be a huge pain. And what if then you change your mind and want to switch back to the old DB?

With this approach, all you need to do is to change the GreatDAOFactory.getDAO() and make it create an instance of a different class, and all your application code will be using the new database without any changes.

In real life, this is often done without any changes to the code at all: the factory method gets the implementation class name via a property setting, and instantiates it using reflection, so, all you need to do to switch implementations is to edit a property file. There are actually frameworks – like spring or guice – that manage this "dependency injection" mechanism for you, but I won't go into details, first, because it is really beyond the scope of your question, and also, because I am not necessarily convinced that the benefit you get from using those frameworks is worth the trouble integrating with them for most applications.

Another (probably, more likely to be taken advantage of) benefit of this "factory approach" as opposed to "static" is testability. Imagine that you are writing a unit test that should test the logic of your App class independently of any underlying DAO. You don't want it to use any real underlying storage for several reasons (speed, having to set it up, and clean up afterwards, possible collisions with other tests, the possibility of polluting test results with problems in DAO, unrelated to App, which is actually being tested, etc.).

To do this, you want a test framework, like Mockito, that allows you to "mock out" the functionality of any object or method, replacing it with a "dummy" object, with predefined behavior (I'll skip the details, because, this again is beyond the scope). So, you can create this dummy object replacing your DAO, and make the GreatDAOFactory return your dummy instead of the real thing by calling GreatDAOFactory.setDAO(dao) before the test (and restoring it after). If you were using static methods instead of the instance class, this would not be possible.

One more benefit, which is kinda similar to switching databases I described above is "pimping up" your DAO with additional functionality. Suppose that your application becomes slower as the amount of data in the database grows, and you decide that you need a cache layer. Implement a wrapper class, that uses the real DAO instance (provided to it as a constructor parameter) to access the database, and caches the objects it reads in memory so that they can be returned faster. You can then make your GreatDAOFactory.getDAO instantiate this wrapper, for the application to take advantage of it.

(This is called "delegation pattern" … and seems like a pain in the butt, especially when you have lots of methods defined in your DAO: you will have to implement all of them in the wrapper, even to alter behavior of just one. Alternatively, you could simply subclass your DAO, and add caching to it this way. This would be a lot less boring coding upfront, but may become problematic when you do decide to change the database, or, worse, to have an option of switching implementations back and forth.)

One equally broadly used (but, in my opinion, inferior) alternative to the "factory" method is making the dao a member variable in all classes that need it:

public class App {
   GreatDao dao;
   public App(final GreatDao d) { dao = d; }
}

This way, the code that instantiates these classes needs to instantiate the DAO object (which could still use the factory) and provide it as a constructor parameter. The dependency injection frameworks I mentioned above, usually do something similar to this.

This provides all the benefits of the "factory method" approach, that I described earlier, but, as I said, is not as good in my opinion. The disadvantages here are having to write a constructor for each of your app classes, doing the same exact thing over, and over, also not being able to instantiate the classes easily when needed, and some lost readability: with a large enough code base, a reader of your code, not familiar with it, will have hard time understanding which actual implementation of the DAO is used, how it is instantiated, whether it is a singleton, a thread-safe implementation, whether it keeps state, or caches anything, how the decisions on choosing a particular implementation are made etc.

First Mock your Worker with Mockito (just as you did). Also mock your ChildService. Then:

@Test
public void shouldUseChildService() {
  ArgumentCaptor<Callable> callableCaptor = ArgumentCaptor.forClass(Callable.class);
  ArgumentCaptor<Consumer> consumerCaptor = ArgumentCaptor.forClass(Consumer.class);

  parentService.doAction();

  verify(worker).execute(callableCaptor.capture(), consumerCaptor.capture());
  callableCaptor.getValue().call(); //this will execute whatever was captured
  consumerCaptor.getValue().accept(null);//this will execute whatever was captured

  // now verify that childService::listClients and childService::refreshObjects have been called
}

I finally figured it out...

Sometimes, asking a question can give you a better approach to your problems :p

The problem is I was linking the validators to the list before they were mocked. The validators was then null and no reference could be updated when the MockitAnnotations.initMocks(this) was called.

Moreover, to avoid iterator problems on List, I had to use @Spy instead of @Mock.

Here is the final solution:

@Mock
private EsmRegexValidator regexValidator;

@Mock
private EsmFormNotNullValidator notNullValidator;

@Mock
private EsmFormDataTypeValidator dataValidator;

@InjectMocks
private EsmFormValidatorManager validatorManager;

@Spy
private List<IEsmFormValidator> validators = new ArrayList<IEsmFormValidator>();

@Mock
private ColumnDTO columnDTO;

@Before
public void init() {

    MockitoAnnotations.initMocks(this);

    validators.add(notNullValidator);
    validators.add(regexValidator);
    validators.add(dataValidator);

    Mockito.when(columnDTO.getTitle()).thenReturn("Mock title");
    Mockito.when(columnDTO.getName()).thenReturn("Mock name");
}

You don't normally set properties on your mocked objects; instead, you do some specific thing when it's invoked.

when(slingHttpRequest.getAttribute("search")).thenReturn(someObject);

One way could be to avoid being too restrictive on your arguments in order to provide all the expected results with only one thenReturn call.

For example let's say that I want to mock this method:

public String foo(String firstArgument, Object obj) {
    return "Something";
}

You could then mock it by providing as many results as you want like below:

// Mock the call of foo of any String to provide 3 results
when(mock.foo(anyString(), anyObject())).thenReturn("val1", "val2", "val3");

Calls to foo with any parameters will provide respectively "val1", "val2", then any subsequent calls will provide "val3".

In case you do care about passed values but don't want to depend on call sequence you can use thenAnswer to provide an answer that matches with the second argument like you currently do but with 3 different thenReturn. Assuming that you have overridden the method equals(Object o).

when(mock.foo(anyString(), anyObject())).thenAnswer(
    invocation -> {
        Object argument = invocation.getArguments()[1];
        if (argument.equals(new ARequest(1, "A"))) {
            return new AResponse(1, "passed");
        } else if (argument.equals(new ARequest(2, "2A"))) {
            return new AResponse(2, "passed");
        } else if (argument.equals(new BRequest(1, "B"))) {
            return new BResponse(112, "passed");
        }
        throw new InvalidUseOfMatchersException(
            String.format("Argument %s does not match", argument)
        );
    }
);

Or simply, using the methods anyString and eq as argument marchers. Assuming that you have overridden the method equals(Object o).

when(service.foo(anyString(), eq(new ARequest(1, "A"))))
    .thenReturn(new AResponse(1, "passed"));
when(service.foo(anyString(), eq(new ARequest(2, "2A"))))
    .thenReturn(new AResponse(2, "passed"));
when(service.foo(anyString(), eq(new BRequest(1, "B"))))
    .thenReturn(new BResponse(112, "passed"));

Wiremock provides a simulator for HTTP-based APIs while Mockito provides the mock implementation of the method/object.

If we are using Mockito to mock HTTP-based method, it means we are trying to return the object/response without testing any code to invoke REST service, getting HTTP response and deserializing the same.

If we use the Wiremock, we will able to test close to reality as it will test invocation of REST call as well as deserialization of the response.

https://www.linkedin.com/pulse/what-difference-between-stub-mock-virtual-service-wojciech-bulaty/ is one good article to read, of course not by me :-)