Primitives and its wrapped types compatibility

IntroductionHow often do you think about possible changes in your API? Do you consider that something required could become optional in future? How about compatibility of such change? One of this changes is going from primitive (e. g. int) to its wrapp…

Introduction

How often do you think about possible changes in your API? Do you consider that something required could become optional in future? How about compatibility of such change? One of this changes is going from primitive (e. g. int) to its wrapped type (e. g. Integer). Let’s check it out.

API – first iteration

Let’s start with simple DTO class Dep in our public API.

public class Dep {
    private int f1;

public int getF1(){
return f1;
}

public void setF1(int f1){
this.f1 = f1;
}

// other fields and methods omitted
}

f1 is obligatory field that never will be null.

Let’s use it in Main class:

public class Main {
    public static void main(String... args) {
        Dep dep = new Dep();
        dep.setF1(123);
        System.out.println(dep.getF1());
    }
}

compile it:

$ javac depInt/Dep.java
$ javac -cp depInt main/Main.java

and run:

$ java -cp depInt:main Main
123

It works.

API – obligatory field become optional

Now suppose our business requirements have changed. f1 is not longer obligatory and we want possibility to set it to null.

So we provide next iteration of Dep class where f1 field has type Integer.

public class Dep {
    private Integer f1;

public Integer getF1(){
return f1;
}

public void setF1(Integer f1){
this.f1 = f1;
}

// other fields and methods omitted
}

We compile only the new Dep class because we do not want to change the Main class:

$ javac depInteger/Dep.java

and run it with old Main:

$ java -cp depInteger:main Main
Exception in thread "main" java.lang.NoSuchMethodError: Dep.setF1(I)V
    at Main.main(Main.java:4)

Wow! It does not work…

Why does it not work?

We can use javap tool to investigate Main class.

$ javap -c main/Main.class
Compiled from "Main.java"
public class Main {
  public Main();
    Code:
       0: aload_0
       1: invokespecial #1                  // Method java/lang/Object."<init>":()V
       4: return

public static void main(java.lang.String…);
Code:
0: new #2 // class Dep
3: dup
4: invokespecial #3 // Method Dep.”<init>”:()V
7: astore_1
8: aload_1
9: bipush 123
11: invokevirtual #4 // Method Dep.setF1:(I)V
14: getstatic #5 // Field java/lang/System.out:Ljava/io/PrintStream;
17: aload_1
18: invokevirtual #6 // Method Dep.getF1:()I
21: invokevirtual #7 // Method java/io/PrintStream.println:(I)V
24: return
}

The most important are 11th and 18th instructions of main method. Main lookups for methods which use int (I in method signature).

Next let’s compile the Main class with Dep which has f1 of type Integer:

javac -cp depInteger main/Main.java

and use javap on this class:

$ javap -c main/Main.class
Compiled from "Main.java"
public class Main {
  public Main();
    Code:
       0: aload_0
       1: invokespecial #1                  // Method java/lang/Object."<init>":()V
       4: return

public static void main(java.lang.String…);
Code:
0: new #2 // class Dep
3: dup
4: invokespecial #3 // Method Dep.”<init>”:()V
7: astore_1
8: aload_1
9: bipush 123
11: invokestatic #4 // Method java/lang/Integer.valueOf:(I)Ljava/lang/Integer;
14: invokevirtual #5 // Method Dep.setF1:(Ljava/lang/Integer;)V
17: getstatic #6 // Field java/lang/System.out:Ljava/io/PrintStream;
20: aload_1
21: invokevirtual #7 // Method Dep.getF1:()Ljava/lang/Integer;
24: invokevirtual #8 // Method java/io/PrintStream.println:(Ljava/lang/Object;)V
27: return
}

Now we see the difference. The main method:

  • converts int to Integer in instruction 11th,
  • invokes method setF1 which takes parameter of type Integer (Ljava/lang/Integer;) in instruction 14th,
  • invokes method getF1 which returns Integer in instruction 21st.

These differences do not allow us to use the Main class with Dep without recompilation if we change f1.

How about Groovy?

We have GroovyMain class which do the same as Main class written in Java.

class GroovyMain {
    static void main(String... args) {
        Dep dep = new Dep(f1: 123)
        println(dep.f1)
    }
}

We will compile GroovyMain class only with Dep which uses int:

$ groovyc -cp lib/groovy-all-2.4.5.jar:depInt -d main main/GroovyMain.groovy

It runs great as expected with int:

$ java -cp lib/groovy-all-2.4.5.jar:depInt:main GroovyMain
123

but with Integer… It works the same!

$ java -cp lib/groovy-all-2.4.5.jar:depInteger:main GroovyMain
123

Groovy is immune to such change.

With CompileStatic

But what if we compile groovy with CompileStatic annotation? This annotation instructs groovy compiler to compile class with type checking and should produce bytecode similar to javac output.

GroovyMainCompileStatic class is GroovyMain class with only CompileStatic annotation:

import groovy.transform.CompileStatic

@CompileStatic
class GroovyMainCompileStatic {
static void main(String… args) {
Dep dep = new Dep(f1: 123)
println(dep.f1)
}
}

When we compile this with Dep with int field:

$ groovyc -cp lib/groovy-all-2.4.5.jar:depInt -d main main/GroovyMainCompileStatic.groovy

then of course it works:

$ java -cp lib/groovy-all-2.4.5.jar:depInt:main GroovyMainCompileStatic
123

but with Dep with Integer field it fails like in Java:

$ java -cp lib/groovy-all-2.4.5.jar:depInteger:main GroovyMainCompileStatic
Exception in thread "main" java.lang.NoSuchMethodError: Dep.setF1(I)V
    at GroovyMainCompileStatic.main(GroovyMainCompileStatic.groovy:6)

Conclusion

Change from primitive to its wrapped java type is not compatible change. Bytecode which uses dependent class assumes that there will be method which consumes or returns e. g. int and cannot deal with the same class which provides such method with Integer in place of int.

Groovy is much more flexible and could handle it, but only if we do not use CompileStatic annotation.

The source code is available here.

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Sample for lift-ng: Micro-burn 1.0.0 released

During a last few evenings in my free time I've worked on mini-application called micro-burn. The idea of it appear from work with Agile Jira in our commercial project. This is a great tool for agile projects management. It has inline tasks edition, drag & drop board, reports and many more, but it also have a few drawbacks that turn down our team motivation.

Motivation

From time to time our sprints scope is changing. It is not a big deal because we are trying to be agile :-) but Jira's burndowchart in this situation draw a peek. Because in fact that chart shows scope changes not a real burndown. It means, that chart cannot break down an x-axis if we really do more than we were planned – it always stop on at most zero.

Also for better progress monitoring we've started to split our user stories to technical tasks and estimating them. Original burndowchart doesn't show points from technical tasks. I can find motivation of this – user story almost finished isn't finished at all until user can use it. But in the other hand, if we know which tasks is problematic we can do some teamwork to move it on.

So I realize that it is a good opportunity to try some new approaches and tools.

Tools

I've started with lift framework. In the World of Single Page Applications, this framework has more than simple interface for serving REST services. It comes with awesome Comet support. Comet is a replacement for WebSockets that run on all browsers. It supports long polling and transparent fallback to short polling if limit of client connections exceed. In backend you can handle pushes in CometActor. For further reading take a look at Roundtrip promises

But lift framework is also a kind of framework of frameworks. You can handle own abstraction of CometActors and push to client javascript that shorten up your way from server to client. So it was the trigger for author of lift-ng to make a lift with Angular integration that is build on top of lift. It provides AngularActors from which you can emit/broadcast events to scope of controller. NgModelBinders that synchronize your backend model with client scope in a few lines! I've used them to send project state (all sprints and thier details) to client and notify him about scrum board changes. My actor doing all of this hard work looks pretty small:

Lift-ng also provides factories for creating of Angular services. Services could respond with futures that are transformed to Angular promises in-fly. This is all what was need to serve sprint history:

And on the client side - use of service:


In my opinion this two frameworks gives a huge boost in developing of web applications. You have the power of strongly typing with Scala, you can design your domain on Actors and all of this with simplicity of node.js – lack of json trasforming boilerplate and dynamic application reload.

DDD + Event Sourcing

I've also tried a few fresh approaches to DDD. I've organize domain objects in actors. There are SprintActors with encapsulate sprint aggregate root. Task changes are stored as events which are computed as a difference between two boards states. When it should be provided a history of sprint, next board states are computed from initial state and sequence of events. So I realize that the best way to keep this kind of event sourcing approach tested is to make random tests. This is a test doing random changes at board, calculating events and checking if initial state + events is equals to previously created state:



First look

Screenshot of first version:


If you want to look at this closer, check the source code or download ready to run fatjar on github.During a last few evenings in my free time I've worked on mini-application called micro-burn. The idea of it appear from work with Agile Jira in our commercial project. This is a great tool for agile projects management. It has inline tasks edition, drag & drop board, reports and many more, but it also have a few drawbacks that turn down our team motivation.

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!

How to automate tests with Groovy 2.0, Spock and Gradle

This is the launch of the 1st blog in my life, so cheers and have a nice reading!

y u no test?

Couple of years ago I wasn't a big fan of unit testing. It was obvious to me that well prepared unit tests are crucial though. I didn't known why exactly crucial yet then. I just felt they are important. My disliking to write automation tests was mostly related to the effort necessary to prepare them. Also a spaghetti code was easily spotted in test sources.

Some goodies at hand

Now I know! Test are crucial to get a better design and a confidence. Confidence to improve without a hesitation. Moreover, now I have the tool to make test automation easy as Sunday morning... I'm talking about the Spock Framework. If you got here probably already know what the Spock is, so I won't introduce it. Enough to say that Spock is an awesome unit testing tool which, thanks to Groovy AST Transformation, simplifies creation of tests greatly.

An obstacle

The point is, since a new major version of Groovy has been released (2.0), there is no matching version of Spock available yet.

What now?

Well, in a matter of fact there is such a version. It's still under development though. It can be obtained from this Maven repository. We can of course use the Maven to build a project and run tests. But why not to go even more "groovy" way? XML is not for humans, is it? Lets use Gradle.

The build file

Update: at the end of the post is updated version of the build file.
apply plugin: 'groovy'
apply plugin: 'idea'

def langLevel = 1.7

sourceCompatibility = langLevel
targetCompatibility = langLevel

group = 'com.tamashumi.example.testwithspock'
version = '0.1'

repositories {
mavenLocal()
mavenCentral()
maven { url 'http://oss.sonatype.org/content/repositories/snapshots/' }
}

dependencies {
groovy 'org.codehaus.groovy:groovy-all:2.0.1'
testCompile 'org.spockframework:spock-core:0.7-groovy-2.0-SNAPSHOT'
}

idea {
project {
jdkName = langLevel
languageLevel = langLevel
}
}
As you can see the build.gradle file is almost self-explanatory. Groovy plugin is applied to compile groovy code. It needs groovy-all.jar - declared in version 2.0 at dependencies block just next to Spock in version 0.7. What's most important, mentioned Maven repository URL is added at repositories block.

Project structure and execution

Gradle's default project directory structure is similar to Maven's one. Unfortunately there is no 'create project' task and you have to create it by hand. It's not a big obstacle though. The structure you will create will more or less look as follows:
<project root>

├── build.gradle
└── src
├── main
│ ├── groovy
└── test
└── groovy
To build a project now you can type command gradle build or gradle test to only run tests.

How about Java?

You can test native Java code with Spock. Just add src/main/java directory and a following line to the build.gradle:
apply plugin: 'java'
This way if you don't want or just can't deploy Groovy compiled stuff into your production JVM for any reason, still whole goodness of testing with Spock and Groovy is at your hand.

A silly-simple example

Just to show that it works, here you go with a basic example.

Java simple example class:

public class SimpleJavaClass {

public int sumAll(int... args) {

int sum = 0;

for (int arg : args){
sum += arg;
}

return sum;
}
}

Groovy simple example class:

class SimpleGroovyClass {

String concatenateAll(char separator, String... args) {

args.join(separator as String)
}
}

The test, uhm... I mean the Specification:

class JustASpecification extends Specification {

@Unroll('Sums integers #integers into: #expectedResult')
def "Can sum different amount of integers"() {

given:
def instance = new SimpleJavaClass()

when:
def result = instance.sumAll(* integers)

then:
result == expectedResult

where:
expectedResult | integers
11 | [3, 3, 5]
8 | [3, 5]
254 | [2, 4, 8, 16, 32, 64, 128]
22 | [7, 5, 6, 2, 2]
}

@Unroll('Concatenates strings #strings with separator "#separator" into: #expectedResult')
def "Can concatenate different amount of integers with a specified separator"() {

given:
def instance = new SimpleGroovyClass()

when:
def result = instance.concatenateAll(separator, * strings)

then:
result == expectedResult

where:
expectedResult | separator | strings
'Whasup dude?' | ' ' as char | ['Whasup', 'dude?']
'2012/09/15' | '/' as char | ['2012', '09', '15']
'nice-to-meet-you' | '-' as char | ['nice', 'to', 'meet', 'you']
}
}
To run tests with Gradle simply execute command gradle test. Test reports can be found at <project root>/build/reports/tests/index.html and look kind a like this.


Please note that, thanks to @Unroll annotation, test is executed once per each parameters row in the 'table' at specification's where: block. This isn't a Java label, but a AST transformation magic.

IDE integration

Gradle's plugin for Iintellij Idea

I've added also Intellij Idea plugin for IDE project generation and some configuration for it (IDE's JDK name). To generate Idea's project files just run command: gradle idea There are available Eclipse and Netbeans plugins too, however I haven't tested them. Idea's one works well.

Intellij Idea's plugins for Gradle

Idea itself has a light Gradle support built-in on its own. To not get confused: Gradle has plugin for Idea and Idea has plugin for Gradle. To get even more 'pluginated', there is also JetGradle plugin within Idea. However I haven't found good reason for it's existence - well, maybe excluding one. It shows dependency tree. There is a bug though - JetGradle work's fine only for lang level 1.6. Strangely all the plugins together do not conflict each other. They even give complementary, quite useful tool set.

Running tests under IDE

Jest to add something sweet this is how Specification looks when run with jUnit  runner under Intellij Idea (right mouse button on JustASpecification class or whole folder of specification extending classes and select "Run ...". You'll see a nice view like this.

Building web application

If you need to build Java web application and bundle it as war archive just add plugin by typing the line
apply plugin: 'war'
in the build.gradle file and create a directory src/main/webapp.

Want to know more?

If you haven't heard about Spock or Gradle before or just curious, check the following links:

What next?

The last thing left is to write the real production code you are about to test. No matter will it be Groovy or Java, I leave this to your need and invention. Of course, you are welcome to post a comments here. I'll answer or even write some more posts about the subject.

Important update

Spock version 0.7 has been released, so the above build file doesn't work anymore. It's easy to fix it though. Just remove last dash and a word SNAPSHOT from Spock dependency declaration. Other important thing is that now spock-core depends on groovy-all-2.0.5, so to avoid dependency conflict groovy dependency should be changed from version 2.0.1 to 2.0.5.
Besides oss.sonata.org snapshots maven repository can be removed. No obstacles any more and the build file now looks as follows:
apply plugin: 'groovy'
apply plugin: 'idea'

def langLevel = 1.7

sourceCompatibility = langLevel
targetCompatibility = langLevel

group = 'com.tamashumi.example.testwithspock'
version = '0.1'

repositories {
mavenLocal()
mavenCentral()
}

dependencies {
groovy 'org.codehaus.groovy:groovy-all:2.0.5'
testCompile 'org.spockframework:spock-core:0.7-groovy-2.0'
}

idea {
project {
jdkName = langLevel
languageLevel = langLevel
}
}