Open IMS Core does’t have standard way to define connection to MRF (Media Resource Function) on Mr interface.In IMS Mr interface is based on SIP and is similar to ISC used by Application Server (AS). Because of that we can define MRF as IMS AS and just add Wildcard PSI that has trigger on that AS. That […]
<!--:en-->TouK on GitHub Part 1<!--:-->
TouK sponsorem Confitura 2011 (dawniej Javarsovia)
You May Also Like
33rd Degree day 2 review
- byJakub Nabrdalik
- March 25, 2012
There were two workshops going on through the day, one about JEE6 and another about parallel programming in Java. I was considering both, but decided to go for presentations instead. Being on the Spring side of the force, I know just as much JEE as I need, and with fantastic GPars (which has Fork/Join, actors, STM , and much more), I won't need to go back to Java concurrency for a while.
GEB - Very Groovy browser automation
Luke Daley works for Gradleware, and apart from being cheerful Australian, he's a commiter to Grails, Spock and a guy behind Geb, a browser automation lib using WebDriver, similar to Selenium a bit (though without IDE and other features).I have to admit, there was a time where I really hated Selenium. It just felt so wrong to be writing tests that way, slow, unproductive and against the beauty of TDD. For years I've been treating frontend as a completely different animal. Uncle Bob once said at a Ruby conference: "I'll tell you what my solution to frontend tests is: I just don't". But then, you can only go so far with complex GUIs without tests, and once I've started working with Wicket and its test framework, my perspective changed. If Wicked has one thing done right, it's the frontend testing framework. Sure tests are slow, on par with integration tests, but it is way better than anything where the browser has to start up front, and I could finally do TDD with it.
Working with Grails lately, I was more than eager to learn a proper way to do these kind of tests with Groovy.
GEB looks great. You build your own API for every page you have, using CSS selectors, very similar to jQuery, and then write your tests using your own DSL. Sounds a bit complicated, but assuming you are not doing simple HTML pages, this is probably the way to go fast. I'd have to verify that on a project though, since with frontend, too many things look good on paper and than fall out in code.
The presentation was great, Luke managed to answer all the questions and get people interested. On a side note, WebDriver may become a W3C standard soon, which would really easy browser manipulation for us. Apart from thing I expected Geb to have, there are some nice surprises like working with remote browsers (e.g. IE on remote machine), dumping HTML at the end of the test and even making screenshots (assuming you are not working with headless browser).
Micro services - Java, the Unix Way
Concurrency without Pain in Pure Java
Smarter Testing with Spock
What's new in Groovy 2.0?
Scala for the Intrigued
BOF: Beautiful failures
If you want the slides, you can find them here.
You can find my review from the last day in here.
Integration testing custom validation constraints in Jersey 2
- byPiotr Jagielski
- October 26, 2013
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!
NextBeer, a sample OpenApi application for T-Mobile
- byJakub Nabrdalik
- May 22, 2012