Test Driven Traps, part 2

The Story of a Unit in Unit Tests

In the previous part of this article, you could see some bad, though popular, test samples. But I’m not a professional critic (also known as a troll, or a hater), to grumble about without having anything constructive to say. Years of TDD have taught me more than just how bad the things can go. There are many simple but effective tricks, that can make you test-life much easier.

Imagine this: you have a booking system for a small conference room in a small company. By some strange reason, it has to deal with off-line booking. People post their booking requests to some frontend, and once a week you get a text file with working hours of the company, and all the bookings (for what day, for how long, by whom, submitted at what point it time) in random order. Your system should produce a calendar for the room, according to some business rules (first come, first served, only in office business hours, that sort of things).

As part of the analysis, we have a clearly defined input data, and expected outcomes, with examples. Beautiful case for TDD, really. Something that sadly never happens in the real life.

Our sample test data looks like this:

class TestData {
    static final String INPUT_FIRST_LINE = "0900 1730\n";
    static final String FIRST_BOOKING    = "2011-03-17 10:17:06 EMP001\n" +
                                           "2011-03-21 09:00 2\n";
    static final String SECOND_BOOKING   = "2011-03-16 12:34:56 EMP002\n" +
                                           "2011-03-21 09:00 2\n";
    static final String THIRD_BOOKING    = "2011-03-16 09:28:23 EMP003\n" +
                                           "2011-03-22 14:00 2\n";
    static final String FOURTH_BOOKING   = "2011-03-17 10:17:06 EMP004\n" +
                                           "2011-03-22 16:00 1\n";
    static final String FIFTH_BOOKING    = "2011-03-15 17:29:12 EMP005\n" +
                                           "2011-03-21 16:00 3";

    static final String INPUT_BOOKING_LINES =
                                            FIRST_BOOKING +
                                            SECOND_BOOKING +
                                            THIRD_BOOKING +
                                            FOURTH_BOOKING +
                                            FIFTH_BOOKING;

    static final String CORRECT_INPUT = INPUT_FIRST_LINE + INPUT_BOOKING_LINES;

    static final String CORRECT_OUTPUT = "2011-03-21\n" +
                                         "09:00 11:00 EMP002\n" +
                                         "2011-03-22\n" +
                                         "14:00 16:00 EMP003\n" +
                                         "16:00 17:00 EMP004\n" +
                                         "";
}

So now we start with a positive test:

BookingCalendarGenerator bookingCalendarGenerator =  new BookingCalendarGenerator();

@Test
public void shouldPrepareBookingCalendar() {
    //when
    String calendar = bookingCalendarGenerator.generate(TestData.CORRECT_INPUT);

    //then
    assertEquals(TestData.CORRECT_OUTPUT, calendar);
}

It looks like we have designed a BookingCalendarGenerator with a “generate” method. Fair enough. Lets add some more tests. Tests for the business rules. We get something like this:

    @Test
    public void noPartOfMeetingMayFallOutsideOfficeHours() {
        //given
        String tooEarlyBooking = "2011-03-16 12:34:56 EMP002\n" +
                                 "2011-03-21 06:00 2\n";

        String tooLateBooking = "2011-03-16 12:34:56 EMP002\n" +
                                "2011-03-21 20:00 2\n";

        //when
        String calendar = bookingCalendarGenerator.generate(TestData.INPUT_FIRST_LINE + tooEarlyBooking + tooLateBooking);

        //then
        assertTrue(calendar.isEmpty());
    }

    @Test
    public void meetingsMayNotOverlap() {
        //given
        String firstMeeting = "2011-03-10 12:34:56 EMP002\n" +
                              "2011-03-21 16:00 1\n";

        String secondMeeting = "2011-03-16 12:34:56 EMP002\n" +
                               "2011-03-21 15:00 2\n";

        //when
        String calendar = bookingCalendarGenerator.generate(TestData.INPUT_FIRST_LINE + firstMeeting + secondMeeting);

        //then
        assertEquals("2011-03-21\n" +
                     "16:00 17:00 EMP002\n", calendar);
    }

    @Test
    public void bookingsMustBeProcessedInSubmitOrder() {
        //given
        String firstMeeting = "2011-03-17 12:34:56 EMP002\n" +
                              "2011-03-21 16:00 1\n";

        String secondMeeting = "2011-03-16 12:34:56 EMP002\n" +
                               "2011-03-21 15:00 2\n";

        //when
        String calendar = bookingCalendarGenerator.generate(TestData.INPUT_FIRST_LINE + firstMeeting + secondMeeting);

        //then
        assertEquals("2011-03-21\n15:00 17:00 EMP002\n", calendar);
    }

    @Test
    public void orderingOfBookingSubmissionShouldNotAffectOutcome() {
        //given
        List shuffledBookings = newArrayList(TestData.FIRST_BOOKING, TestData.SECOND_BOOKING,
                TestData.THIRD_BOOKING, TestData.FOURTH_BOOKING, TestData.FIFTH_BOOKING);
        shuffle(shuffledBookings);
        String inputBookingLines = Joiner.on("\n").join(shuffledBookings);

        //when
        String calendar = bookingCalendarGenerator.generate(TestData.INPUT_FIRST_LINE + inputBookingLines);

        //then
        assertEquals(TestData.CORRECT_OUTPUT, calendar);
    }

That’s pretty much all. But what if we get some rubbish as the input. Or if we get an empty string? Let’s design for that:

    @Test(expected = IllegalArgumentException.class)
    public void rubbishInputDataShouldEndWithException() {
        //when
        String calendar = bookingCalendarGenerator.generate("rubbish");

        //then exception is thrown
    }

    @Test(expected = IllegalArgumentException.class)
    public void emptyInputDataShouldEndWithException() {
        //when
        String calendar = bookingCalendarGenerator.generate("");

        //then exception is thrown
    }

IllegalArgumentException is fair enough. We don’t need to handle it in any more fancy way. We are done for now. Let’s finally write the class under the test: BookingCalendarGenerator.

And so we do. And it comes out, that the whole thing is a little big for a single method. So we use the power of Extract Method pattern. We group code fragments into different methods. We group methods and data those operate on, into classes. We use the power of Object Oriented programming, we use Single Responsibility Principle, we use composition (or decomposition, to be precise) and we end up with a package like this:

We have one public class, and several package-scope classes. Those package scope classes clearly belong to the public one. Here’s a class diagram for clarity:

Those aren’t stupid data-objects. Those are full fledged classes. With behavior, responsibility, encapsulation. And here’s a thing that may come to our Test Driven minds: we have no tests for those classes. We have only for the public class. That’s bad, right? Having no tests must be bad. Very bad. Right?

Wrong.

We do have tests. We fire up our code coverage tool and we see: 100% methods and classes. 95% lines. Not bad (I’ll get to that 5% of uncertainty in the next post).

But we have only a single unit test class. Is that good?

Well, let me put some emphasis, to point the answer out:

It’s a UNIT test. It’s called a UNIT test for a reason!

The unit does not have to be a single class. The unit does not have to be a single package. The unit is up to you to decide. It’s a general name, because your sanity, your common sense, should tell you where to stop.

So we have six classes as a unit, what’s the big deal? How about if somebody wants to use one of those classes, apart from the rest. He would have no tests for it, right?

Wrong. Those classes are package-scope, apart from the one that’s actually called in the test. This package-scope thing tells you: “Back off. Don’t touch me, I belong to this package. Don’t try to use me separately, I was design to be here!”.

So yeah, if a programmer takes one of those out, or makes it public, he would probably know, that all the guarantees are voided. Write your own tests, man.

How about if somebody wants to add some behavior to one of those classes, I’ve been asked. How would he know he’s not breaking something?

Well, he would start with a test, right? It’s TDD, right? If you have a change of requirements, you code this change as a test, and then, and only then, you start messing with the code. So you are safe and secure.

I see people writing test-per-class blindly, without giving any thought to it, and it makes me cry. I do a lot of pair-programming lately, and you know what I’ve found? Java programmers in general do not use package-scope. Java programmers in general do not know, that protected means: for me, all my descendants, and EVERYONE in the same package. That’s right, protected is more than package-scope, not less a single bit. So if Java programmers do not know what a package-scope really is, and that’s, contrary to Groovy, is the default, how could they understand what a Unit is?

How high can I get?

Now here’s an interesting thought: if we can have a single test for a package, we could have a single test for a package tree. You know, something like this:

We all know that packages in Java are not really tree-like, that the only thing those have with the directory structure is by a very old convention, and we know that the directory structure is there only to solve the collision-of-names problem, but nevertheless, we tend to use packages, like if the name.after.the.dot had some meaning. Like if we could hide one package inside another. Or build layers of lasagne with them.

So is it O.K. to have a single test class for a tree of packages?

Yes it is.

But if so, where is the end to that? Can we go all the way up in the package tree, to the entry point of our application? Those… those would be integration tests, or functional tests, perhaps. Could we do that? Would that be good?

The answer is: it would. In a perfect world, it would be just fine. In our shitty, hanging-on-the-edge-of-a-knife, world, it would be insane. Why? Because functional, end-to-end test are slow. So slow. So horribly slow, that it makes you wanna throw them away and go some place where you would not have to be always waiting for something. A place of total creativity, constant feedback, and lightning fast safety.

And you’re back to unit testing.

There are even some more reasons. One being, that it’s hard to test all flows of the application, testing it end-to-end. You should probably do that for all the major flows, but what about errors, bad connections, all those tricky logic parts that may throw up at one point or another. No, sometimes it would be just too hard, to set up the environment for integration test like that, so you end up testing it with unit tests anyway.

The second reason is, that though functional tests do not pour concrete over your code, do not inhibit your creativity by repeating you algorithm in the test case, they also give no safety for refactoring. When you had a package with a single public class, it was quite obvious what someone can safely do, and what he cannot. When you have something enclosed in a library, or a plugin, it’s still obvious. But if you have thousands of public classes, and you are implementing a new feature, you are probably going to use some of them, and you would like to know that they are fine.

So, no, in our world, it doesn’t make sense to go with functional tests only. Sorry. But it also doesn’t make sense to create a test per class. It’s called the UNIT test, for a reason. Use that.

You May Also Like

Integration testing custom validation constraints in Jersey 2

I recently joined a team trying to switch a monolithic legacy system into set of RESTful services in Java. They decided to use latest 2.x version of Jersey as a REST container which was not a first choice for me, since I’m not a big fan of JSR-* specs. But now I must admit that JAX-RS 2.x is doing things right: requires almost zero boilerplate code, support auto-discovery of features and prefers convention over configuration like other modern frameworks. Since the spec is still young, it’s hard to find good tutorials and kick-off projects with some working code. I created jersey2-starter project on GitHub which can be used as starting point for your own production-ready RESTful service. In this post I’d like to cover how to implement and integration test your own validation constraints of REST resources.

Custom constraints

One of the issues which bothers me when coding REST in Java is littering your class model with annotations. Suppose you want to build a simple Todo list REST service, when using Jackson, validation and Spring Data, you can easily end up with this as your entity class:

@Document
public class Todo {
    private Long id;
    @NotNull
    private String description;
    @NotNull
    private Boolean completed;
    @NotNull
    private DateTime dueDate;

    @JsonCreator
    public Todo(@JsonProperty("description") String description, @JsonProperty("dueDate") DateTime dueDate) {
        this.description = description;
        this.dueDate = dueDate;
        this.completed = false;
    }
    // getters and setters
}

Your domain model is now effectively blured by messy annotations almost everywhere. Let’s see what we can do with validation constraints (@NotNulls). Some may say that you could introduce some DTO layer with own validation rules, but it conflicts for me with pure REST API design, which stands that you operate on resources which should map to your domain classes. On the other hand - what does it mean that Todo object is valid? When you create a Todo you should provide a description and due date, but what when you’re updating? You should be able to change any of description, due date (postponing) and completion flag (marking as done) - but you should provide at least one of these as valid modification. So my idea is to introduce custom validation constraints, different ones for creation and modification:

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForCreation.Validator.class)
public @interface ValidForCreation {
    //...
    class Validator implements ConstraintValidator<ValidForCreation, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && todo.getDescription() != null
                && todo.getDueDate() != null;
        }
    }
}

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForModification.Validator.class)
public @interface ValidForModification {
    //...
    class Validator implements ConstraintValidator<ValidForModification, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && (todo.getDescription() != null || todo.getDueDate() != null || todo.isCompleted() != null);
        }
    }
}

And now you can move validation annotations to the definition of a REST endpoint:

@POST
@Consumes(APPLICATION_JSON)
public Response create(@ValidForCreation Todo todo) {...}

@PUT
@Consumes(APPLICATION_JSON)
public Response update(@ValidForModification Todo todo) {...}

And now you can remove those NotNulls from your model.

Integration testing

There are in general two approaches to integration testing:

  • test is being run on separate JVM than the app, which is deployed on some other integration environment
  • test deploys the application programmatically in the setup block.

Both of these have their pros and cons, but for small enough servoces, I personally prefer the second approach. It’s much easier to setup and you have only one JVM started, which makes debugging really easy. You can use a generic framework like Arquillian for starting your application in a container environment, but I prefer simple solutions and just use emdedded Jetty. To make test setup 100% production equivalent, I’m creating full Jetty’s WebAppContext and have to resolve all runtime dependencies for Jersey auto-discovery to work. This can be simply achieved with Maven resolved from Shrinkwrap - an Arquillian subproject:

    WebAppContext webAppContext = new WebAppContext();
    webAppContext.setResourceBase("src/main/webapp");
    webAppContext.setContextPath("/");
    File[] mavenLibs = Maven.resolver().loadPomFromFile("pom.xml")
                .importCompileAndRuntimeDependencies()
                .resolve().withTransitivity().asFile();
    for (File file: mavenLibs) {
        webAppContext.getMetaData().addWebInfJar(new FileResource(file.toURI()));
    }
    webAppContext.getMetaData().addContainerResource(new FileResource(new File("./target/classes").toURI()));

    webAppContext.setConfigurations(new Configuration[] {
        new AnnotationConfiguration(),
        new WebXmlConfiguration(),
        new WebInfConfiguration()
    });
    server.setHandler(webAppContext);

(this Stackoverflow thread inspired me a lot here)

Now it’s time for the last part of the post: parametrizing our integration tests. Since we want to test validation constraints, there are many edge paths to check (and make your code coverage close to 100%). Writing one test per each case could be a bad idea. Among the many solutions for JUnit I’m most convinced to the Junit Params by Pragmatists team. It’s really simple and have nice concept of JQuery-like helper for creating providers. Here is my tests code (I’m also using builder pattern here to create various kinds of Todos):

@Test
@Parameters(method = "provideInvalidTodosForCreation")
public void shouldRejectInvalidTodoWhenCreate(Todo todo) {
    Response response = createTarget().request().post(Entity.json(todo));

    assertThat(response.getStatus()).isEqualTo(BAD_REQUEST.getStatusCode());
}

private static Object[] provideInvalidTodosForCreation() {
    return $(
        new TodoBuilder().withDescription("test").build(),
        new TodoBuilder().withDueDate(DateTime.now()).build(),
        new TodoBuilder().withId(123L).build(),
        new TodoBuilder().build()
    );
}

OK, enough of reading, feel free to clone the project and start writing your REST services!

I recently joined a team trying to switch a monolithic legacy system into set of RESTful services in Java. They decided to use latest 2.x version of Jersey as a REST container which was not a first choice for me, since I’m not a big fan of JSR-* specs. But now I must admit that JAX-RS 2.x is doing things right: requires almost zero boilerplate code, support auto-discovery of features and prefers convention over configuration like other modern frameworks. Since the spec is still young, it’s hard to find good tutorials and kick-off projects with some working code. I created jersey2-starter project on GitHub which can be used as starting point for your own production-ready RESTful service. In this post I’d like to cover how to implement and integration test your own validation constraints of REST resources.

Custom constraints

One of the issues which bothers me when coding REST in Java is littering your class model with annotations. Suppose you want to build a simple Todo list REST service, when using Jackson, validation and Spring Data, you can easily end up with this as your entity class:

@Document
public class Todo {
    private Long id;
    @NotNull
    private String description;
    @NotNull
    private Boolean completed;
    @NotNull
    private DateTime dueDate;

    @JsonCreator
    public Todo(@JsonProperty("description") String description, @JsonProperty("dueDate") DateTime dueDate) {
        this.description = description;
        this.dueDate = dueDate;
        this.completed = false;
    }
    // getters and setters
}

Your domain model is now effectively blured by messy annotations almost everywhere. Let’s see what we can do with validation constraints (@NotNulls). Some may say that you could introduce some DTO layer with own validation rules, but it conflicts for me with pure REST API design, which stands that you operate on resources which should map to your domain classes. On the other hand - what does it mean that Todo object is valid? When you create a Todo you should provide a description and due date, but what when you’re updating? You should be able to change any of description, due date (postponing) and completion flag (marking as done) - but you should provide at least one of these as valid modification. So my idea is to introduce custom validation constraints, different ones for creation and modification:

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForCreation.Validator.class)
public @interface ValidForCreation {
    //...
    class Validator implements ConstraintValidator<ValidForCreation, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && todo.getDescription() != null
                && todo.getDueDate() != null;
        }
    }
}

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForModification.Validator.class)
public @interface ValidForModification {
    //...
    class Validator implements ConstraintValidator<ValidForModification, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && (todo.getDescription() != null || todo.getDueDate() != null || todo.isCompleted() != null);
        }
    }
}

And now you can move validation annotations to the definition of a REST endpoint:

@POST
@Consumes(APPLICATION_JSON)
public Response create(@ValidForCreation Todo todo) {...}

@PUT
@Consumes(APPLICATION_JSON)
public Response update(@ValidForModification Todo todo) {...}

And now you can remove those NotNulls from your model.

Integration testing

There are in general two approaches to integration testing:

  • test is being run on separate JVM than the app, which is deployed on some other integration environment
  • test deploys the application programmatically in the setup block.

Both of these have their pros and cons, but for small enough servoces, I personally prefer the second approach. It’s much easier to setup and you have only one JVM started, which makes debugging really easy. You can use a generic framework like Arquillian for starting your application in a container environment, but I prefer simple solutions and just use emdedded Jetty. To make test setup 100% production equivalent, I’m creating full Jetty’s WebAppContext and have to resolve all runtime dependencies for Jersey auto-discovery to work. This can be simply achieved with Maven resolved from Shrinkwrap - an Arquillian subproject:

    WebAppContext webAppContext = new WebAppContext();
    webAppContext.setResourceBase("src/main/webapp");
    webAppContext.setContextPath("/");
    File[] mavenLibs = Maven.resolver().loadPomFromFile("pom.xml")
                .importCompileAndRuntimeDependencies()
                .resolve().withTransitivity().asFile();
    for (File file: mavenLibs) {
        webAppContext.getMetaData().addWebInfJar(new FileResource(file.toURI()));
    }
    webAppContext.getMetaData().addContainerResource(new FileResource(new File("./target/classes").toURI()));

    webAppContext.setConfigurations(new Configuration[] {
        new AnnotationConfiguration(),
        new WebXmlConfiguration(),
        new WebInfConfiguration()
    });
    server.setHandler(webAppContext);

(this Stackoverflow thread inspired me a lot here)

Now it’s time for the last part of the post: parametrizing our integration tests. Since we want to test validation constraints, there are many edge paths to check (and make your code coverage close to 100%). Writing one test per each case could be a bad idea. Among the many solutions for JUnit I’m most convinced to the Junit Params by Pragmatists team. It’s really simple and have nice concept of JQuery-like helper for creating providers. Here is my tests code (I’m also using builder pattern here to create various kinds of Todos):

@Test
@Parameters(method = "provideInvalidTodosForCreation")
public void shouldRejectInvalidTodoWhenCreate(Todo todo) {
    Response response = createTarget().request().post(Entity.json(todo));

    assertThat(response.getStatus()).isEqualTo(BAD_REQUEST.getStatusCode());
}

private static Object[] provideInvalidTodosForCreation() {
    return $(
        new TodoBuilder().withDescription("test").build(),
        new TodoBuilder().withDueDate(DateTime.now()).build(),
        new TodoBuilder().withId(123L).build(),
        new TodoBuilder().build()
    );
}

OK, enough of reading, feel free to clone the project and start writing your REST services!