DDevelopment & Design

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.

Solution Architect @ TouK

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Test Driven Traps, part 1

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Classloader problem with Java 7 and WebServices in Grails

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DDevelopment & Design

Spock basics

Spock (homepage) is like its authors say 'testing and specification framework'. Spock combines very elegant and natural syntax with the powerful capabilities. And what is most important it is easy to use.

One note at the very beginning: I assume that you are already familiar with principles of Test Driven Development and you know how to use testing framework like for example JUnit.

So how can I start?


Writing spock specifications is very easy. We need basic configuration of Spock and Groovy dependencies (if you are using mavenized project with Eclipse look to my previous post: Spock, Java and Maven). Once we have everything set up and running smooth we can write our first specs (spec or specification is equivalent for test class in other frameworks like JUnit of TestNG).

What is great with Spock is fact that we can use it to test both Groovy projects and pure Java projects or even mixed projects.


Let's go!


Every spec class must inherit from spock.lang.Specification class. Only then test runner will recognize it as test class and start tests. We will write few specs for this simple class: User class and few tests not connected with this particular class.

We start with defining our class:
import spock.lang.*

class UserSpec extends Specification {

}
Now we can proceed to defining test fixtures and test methods.

All activites we want to perform before each test method, are to be put in def setup() {...} method and everything we want to be run after each test should be put in def cleanup() {...} method (they are equivalents for JUnit methods with @Before and @After annotations).

It can look like this:
class UserSpec extends Specification {
    User user
    Document document

    def setup() {
        user = new User()
        document = DocumentTestFactory.createDocumentWithTitle("doc1")
    }

    def cleanup() {

    }
}
Of course we can use field initialization for instantiating test objects:
class UserSpec extends Specification {
    User user = new User()
    Document document = DocumentTestFactory.createDocumentWithTitle("doc1")

    def setup() {

    }

    def cleanup() {

    }
}

What is more readable or preferred? It is just a matter of taste because according to Spock docs behaviour is the same in these two cases.

It is worth mentioning that JUnit @BeforeClass/@AfterClass are also present in Spock as def setupSpec() {...} and def cleanupSpec() {...}. They will be runned before first test and after last test method.


First tests


In Spock every method in specification class, expect setup/cleanup, is treated by runner as a test method (unless you annotate it with @Ignore).

Very interesting feature of Spock and Groovy is ability to name methods with full sentences just like regular strings:
class UserSpec extends Specification {
    // ...

    def "should assign coment to user"() {
        // ...
    }
}
With such naming convention we can write real specification and include details about specified behaviour in method name, what is very convenient when reading test reports and analyzing errors.

Test method (also called feature method) is logically divided into few blocks, each with its own purpose. Blocks are defined like labels in Java (but they are transformed with Groovy AST transform features) and some of them must be put in code in specific order.

Most basic and common schema for Spock test is:
class UserSpec extends Specification {
    // ...

    def "should assign coment to user"() {
        given:
            // do initialization of test objects
        when:
            // perform actions to be tested
        then:
            // collect and analyze results
    }
}

But there are more blocks like:
  • setup
  • expect
  • where
  • cleanup
In next section I am going to describe each block shortly with little examples.

given block

This block is used to setup test objects and their state. It has to be first block in test and cannot be repeated. Below is little example how can it be used:
class UserSpec extends Specification {
    // ...

    def "should add project to user and mark user as project's owner"() {
        given:
            User user = new User()
            Project project = ProjectTestFactory.createProjectWithName("simple project")
        // ...
    }
}

In this code given block contains initialization of test objects and nothing more. We create simple user without any specified attributes and project with given name. In case when some of these objects could be reused in more feature methods, it could be worth putting initialization in setup method.

when and then blocks

When block contains action we want to test (Spock documentation calls it 'stimulus'). This block always occurs in pair with then block, where we are verifying response for satisfying certain conditions. Assume we have this simple test case:
class UserSpec extends Specification {
    // ...

    def "should assign user to comment when adding comment to user"() {
        given:
            User user = new User()
            Comment comment = new Comment()
        when:
            user.addComment(comment)
        then:
            comment.getUserWhoCreatedComment().equals(user)
    }

    // ...
}

In when block there is a call of tested method and nothing more. After we are sure our action was performed, we can check for desired conditions in then block.

Then block is very well structured and its every line is treated by Spock as boolean statement. That means, Spock expects that we write instructions containing comparisons and expressions returning true or false, so we can create then block with such statements:
user.getName() == "John"
user.getAge() == 40
!user.isEnabled()
Each of lines will be treated as single assertion and will be evaluated by Spock.

Sometimes we expect that our method throws an exception under given circumstances. We can write test for it with use of thrown method:
class CommentSpec extends Specification {
    def "should throw exception when adding null document to comment"() {
        given:
            Comment comment = new Comment()
        when:
            comment.setCommentedDocument(null)
        then:
            thrown(RuntimeException)
    }
}

In this test we want to make sure that passing incorrect parameters is correctly handled by tested method and that method throws an exception in response. In case you want to be certain that method does not throw particular exception, simply use notThrown method.


expect block

Expect block is primarily used when we do not want to separate when and then blocks because it is unnatural. It is especially useful for simple test (and according to TDD rules all test should be simple and short) with only one condition to check, like in this example (it is simple but should show the idea):
def "should create user with given name"() {
    given:
        User user = UserTestFactory.createUser("john doe")
    expect:
        user.getName() == "john doe"
}



More blocks!


That were very simple tests with standard Spock test layout and canonical divide into given/when/then parts. But Spock offers more possibilities in writing tests and provides more blocks.


setup/cleanup blocks

These two blocks have the very same functionality as the def setup and def cleanup methods in specification. They allow to perform some actions before test and after test. But unlike these methods (which are shared between all tests) blocks work only in methods they are defined in. 


where - easy way to create readable parameterized tests

Very often when we create unit tests there is a need to "feed" them with sample data to test various cases and border values. With Spock this task is very easy and straighforward. To provide test data to feature method, we need to use where block. Let's take a look at little the piece of code:

def "should successfully validate emails with valid syntax"() {
    expect:
        emailValidator.validate(email) == true
    where:
        email }

In this example, Spock creates variable called email which is used when calling method being tested. Internally feature method is called once, but framework iterates over given values and calls expect/when block as many times as there are values (however, if we use @Unroll annotation Spock can create separate run for each of given values, more about it in one of next examples).

Now, lets assume that we want our feature method to test both successful and failure validations. To achieve that goal we can create few parameterized variables for both input parameter and expected result. Here is a little example:

def "should perform validation of email addresses"() {
    expect:
        emailValidator.validate(email) == result
    where:
        email         result }
Well, it looks nice, but Spock can do much better. It offers tabular format of defining parameters for test what is much more readable and natural. Lets take a look:
def "should perform validation of email addresses"() {
    expect:
        emailValidator.validate(email) == result
    where:
        email           | result
        "WTF"           | false
        "@domain"       | false
        "foo@bar.com"   | true
        "a@test"        | false
}
In this code, each column of our "table" is treated as a separate variable and rows are values for subsequent test iterations.

Another useful feature of Spock during parameterizing test is its ability to "unroll" each parameterized test. Feature method from previous example could be defined as (the body stays the same, so I do not repeat it):
@Unroll("should validate email #email")
def "should perform validation of email addresses"() {
    // ...
}
With that annotation, Spock generate few methods each with its own name and run them separately. We can use symbols from where blocks in @Unroll argument by preceding it with '#' sign what is a signal to Spock to use it in generated method name.


What next?


Well, that was just quick and short journey  through Spock and its capabilities. However, with that basic tutorial you are ready to write many unit tests. In one of my future posts I am going to describe more features of Spock focusing especially on its mocking abilities.