DDevelopment & Design

OVal – validate your models quickly and effortlessly!

Some time ago one of the projects at work required me to validate some Java POJOs. Theses were my model classes and I’ve been creating them from incoming WebService requests. One would say that XSD would be sufficient for the task, for parts of this va…Some time ago one of the projects at work required me to validate some Java POJOs. Theses were my model classes and I’ve been creating them from incoming WebService requests. One would say that XSD would be sufficient for the task, for parts of this va…

Some time ago one of the projects at work required me to validate some Java POJOs. Theses were my model classes and I’ve been creating them from incoming WebService requests. One would say that XSD would be sufficient for the task, for parts of this validations – sure, it would. But there were some advanced rules XSD would not handle, or would render the schema document very complicated.

Rules I needed to express were like:

  • person’s first_name and last_name should be of appropriate length – between 2 and 20, and additionally one could pass a zero-length string just to remove the previous value
  • state field should consist only defined values – as in dictionary value – this one would be completable with XSD’s enumerations, but would require often changing schema files and redistributing them to interested parties :(

The library I’ve decided to use for this task is OVal and it came out really nice! Read on to find out the details!

Oval is quite mature library that allows POJO validation, but is not JSR303 (bean validation) implementation. It has converters that enable it to understand those annotations, but I’m not sure about the compatibility.

I’ve tried only a subset of the available checks, among which were:

  • NotNull
  • NotEmpty
  • Length

There are many more, and their attributes give interesting ways to configure the validation process. But using them was rather easy and did not require to much brainstorming. What I really needed were custom checks. And in this area OVal shows it’s strength. Implementing a check is really easy.

I needed an annotation that would check a field against some values in a dictionary. If field’s value was in the given set, than the validation would succeed, if not, an exception would be thrown. To accomplish this task it is required to implement two classes: annotation class and check class – called by the validation engine on a given field.

Let’s start with our new annotation:

 

In the above snippet I’ve defined a check-annotation, that would be used like this:

 

You can pass file – containing dictionary values for this field. There is also message field in the annotation which is an error message returned by the validation engine of failed check – pretty handy. And can be expressed in .properties file as:

 

Placeholder, like context, will be replaced with correct values supplied by the validation engine.

Annotating a field is not enough. It is also needed to create a validator for this kind of check. The name of the class is already defined in DictionaryValue annotation, it is called DictionaryValueCheck and I’ve done this check this way:

 

What this basically does is:

  1. when file is set – read dictionary content from the file into map
  2. upon check request just lookup value in dictionary parsed from the input file

And that’s it!

For me Oval is really great tool. With it at ones disposal it is extremely easy to create any imaginable validation you need. This library is really easy to use and offers lots of handy features.

But perhaps I’m reinventing the wheel and all this can be done easily with some other library? Share Your opinion!

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DDevelopment & Design

Thought static method can’t be easy to mock, stub nor track? Wrong!

No matter why, no matter is it a good idea. Sometimes one just wants to check or it's necessary to be done. Mock a static method, woot? Impossibru!

In pure Java world it is still a struggle. But Groovy allows you to do that really simple. Well, not groovy alone, but with a great support of Spock.

Lets move on straight to the example. To catch some context we have an abstract for the example needs. A marketing project with a set of offers. One to many.

import spock.lang.Specification

class OfferFacadeSpec extends Specification {

    OfferFacade facade = new OfferFacade()

    def setup() {
        GroovyMock(Project, global: true)
    }

    def 'delegates an add offer call to the domain with proper params'() {
        given:
            Map params = [projId: projectId, name: offerName]

        when:
            Offer returnedOffer = facade.add(params)

        then:
            1 * Project.addOffer(projectId, _) >> { projId, offer -> offer }
            returnedOffer.name == params.name

        where:
            projectId | offerName
            1         | 'an Offer'
            15        | 'whasup!?'
            123       | 'doskonała oferta - kup teraz!'
    }
}
So we test a facade responsible for handling "add offer to the project" call triggered  somewhere in a GUI.
We want to ensure that static method Project.addOffer(long, Offer) will receive correct params when java.util.Map with user form input comes to the facade.add(params).
This is unit test, so how Project.addOffer() works is out of scope. Thus we want to stub it.

The most important is a GroovyMock(Project, global: true) statement.
What it does is modifing Project class to behave like a Spock's mock. 
GroovyMock() itself is a method inherited from Specification.  The global flag is necessary to enable mocking static methods.
However when one comes to the need of mocking static method, author of Spock Framework advice to consider redesigning of implementation. It's not a bad advice, I must say.

Another important thing are assertions at then: block. First one checks an interaction, if the Project.addOffer() method was called exactly once, with a 1st argument equal to the projectId and some other param (we don't have an object instance yet to assert anything about it).
Right shit operator leads us to the stub which replaces original method implementation by such statement.
As a good stub it does nothing. The original method definition has return type Offer. The stub needs to do the same. So an offer passed as the 2nd argument is just returned.
Thanks to this we can assert about name property if it's equal with the value from params. If no return was designed the name could be checked inside the stub Closure, prefixed with an assert keyword.

Worth of  mentioning is that if you want to track interactions of original static method implementation without replacing it, then you should try using GroovySpy instead of GroovyMock.

Unfortunately static methods declared at Java object can't be treated in such ways. Though regular mocks and whole goodness of Spock can be used to test pure Java code, which is awesome anyway :)No matter why, no matter is it a good idea. Sometimes one just wants to check or it's necessary to be done. Mock a static method, woot? Impossibru!

In pure Java world it is still a struggle. But Groovy allows you to do that really simple. Well, not groovy alone, but with a great support of Spock.

Lets move on straight to the example. To catch some context we have an abstract for the example needs. A marketing project with a set of offers. One to many.

import spock.lang.Specification

class OfferFacadeSpec extends Specification {

    OfferFacade facade = new OfferFacade()

    def setup() {
        GroovyMock(Project, global: true)
    }

    def 'delegates an add offer call to the domain with proper params'() {
        given:
            Map params = [projId: projectId, name: offerName]

        when:
            Offer returnedOffer = facade.add(params)

        then:
            1 * Project.addOffer(projectId, _) >> { projId, offer -> offer }
            returnedOffer.name == params.name

        where:
            projectId | offerName
            1         | 'an Offer'
            15        | 'whasup!?'
            123       | 'doskonała oferta - kup teraz!'
    }
}
So we test a facade responsible for handling "add offer to the project" call triggered  somewhere in a GUI.
We want to ensure that static method Project.addOffer(long, Offer) will receive correct params when java.util.Map with user form input comes to the facade.add(params).
This is unit test, so how Project.addOffer() works is out of scope. Thus we want to stub it.

The most important is a GroovyMock(Project, global: true) statement.
What it does is modifing Project class to behave like a Spock's mock. 
GroovyMock() itself is a method inherited from Specification.  The global flag is necessary to enable mocking static methods.
However when one comes to the need of mocking static method, author of Spock Framework advice to consider redesigning of implementation. It's not a bad advice, I must say.

Another important thing are assertions at then: block. First one checks an interaction, if the Project.addOffer() method was called exactly once, with a 1st argument equal to the projectId and some other param (we don't have an object instance yet to assert anything about it).
Right shit operator leads us to the stub which replaces original method implementation by such statement.
As a good stub it does nothing. The original method definition has return type Offer. The stub needs to do the same. So an offer passed as the 2nd argument is just returned.
Thanks to this we can assert about name property if it's equal with the value from params. If no return was designed the name could be checked inside the stub Closure, prefixed with an assert keyword.

Worth of  mentioning is that if you want to track interactions of original static method implementation without replacing it, then you should try using GroovySpy instead of GroovyMock.

Unfortunately static methods declared at Java object can't be treated in such ways. Though regular mocks and whole goodness of Spock can be used to test pure Java code, which is awesome anyway :)