Cross-platform mobile apps – possible or not?

What is Titanium and how it works. Titanium is an open-source solution for cross-platform, almost-native mobile app development. It has its own MVC, JavaScript and XML-based framework Alloy. Titanium is based on assumption, that each app can be divided into two parts: UI, which is platform-specific part and application core – business logic, common to all […]What is Titanium and how it works. Titanium is an open-source solution for cross-platform, almost-native mobile app development. It has its own MVC, JavaScript and XML-based framework Alloy. Titanium is based on assumption, that each app can be divided into two parts: UI, which is platform-specific part and application core – business logic, common to all […]

blog-product-titanium1

What is Titanium and how it works.

Titanium is an open-source solution for cross-platform, almost-native mobile app development. It has its own MVC, JavaScript and XML-based framework Alloy. Titanium is based on assumption, that each app can be divided into two parts: UI, which is platform-specific part and application core – business logic, common to all platforms. So, inside the app, we have native UI components and JavaScript interpreted logic, communicating with each other.

If you want to write your app in titanium, you only need to know JavaScript and learn to call Titanium API for UI components. Alloy, on the other hand, is more fun, because you have to write views in XML, model and controllers in JavaScript (+ Titanium API mentioned before) and styles in something called Titanium StyleSheets, which is CSS+JSON hybrid. I must admit, the language is not an obstacle for anybody who ever did web development, or any kind of script and markup languages. It’s easy to start working with this framework.

Beginnings.

To work with Titanium, you will need Titanium Studio – an Eclipse-based IDE adapted to write and deploy Titanium apps into various platforms and stores – AppStore, Google Play etc. It has a direct access to Appcelerator Titanium Marketplace, where you can download e.g. sample applications, widgets and plugins – paid for or free of charge.

After downloading Titanium Studio and necessary SDK’s I downloaded sample code called Kitchen Sink – an example, showing possibilities of Titanium Alloy framework. I chose a device and… it worked! After (very few ;-) years of programming I get used to difficult beginnings, long configurations before the first launch (whether regarding a web app, mobile app or any kind of desktop/command line app), but Appcelerator did a great job preparing IDE and integrating it with simulators, emulators etc. After the first success I played with Alloy for a few days and here comes my conclusions.

What is great about Titanium.

1. Simplicity. Apps can be build from small files and can be developed very fast. Everybody knows basics of XML and JavaScript, so you can start writing your apps straight away.

2. Architecture. Alloy framework is very well designed. It allows installing plugins, widgets, or even native modules in a convenient way. “Convention over configuration” makes this process faster – all you need to do is put the downloaded widget into the “widget” directory and add a dependency into config.json file.

3. GitTio is a search engine that indexes all Titanium modules and Alloy widgets. It is something similar to Cocoa Controls for iOS, but more comprehensive, because it automatically finds new modules in GitHub and indexes them. GitTio provides Command Line Interface, which facilitates installing and managing widgets.

What is not-so-great about Titanium.

1. There is not such thing as “one app to rule them all”. Mobile platforms have different controls, components and UI elements. The same things are implemented by different solutions. The more complex the app gets, the more platform dedicated code needs to be written. After all, I end up writing views and controllers for each platform separately.

2. Even if you can write one view for each platform, you probably shouldn’t do it. There is one thing I have not mentioned yet – User Experience. It is extremely different for each mobile OS. Android users are used to “back” and “menu” buttons, iOS users are using navigation bar, some OS’s are using swipe moves to navigate between window. Therefore, a universal app for all platforms is doubtful idea to start with.

3. Cross-platform idea stops working when you want to use external module. There are “iOS-only” modules or “iOS and Android” modules. Very rarely, they may also include mobileweb.

What is totally not-great about Titanium.

1. Titanium is still young. It develops really fast. A lot of things have bugs, while at the same time, a lot of features get deprecated. When you find a tutorial from 2011, you may never be sure whether it’s up to date. Differences between close versions (like 3.1.3 and 3.2) sometimes force re-writing the whole view or using another widget.

2. Titanium and Titanium Alloy are two different worlds. Having got used to the beautiful Alloy MVC code I tried downloading a widget written in “plain Titanium”. This was a lot of code with a completely different approach and not so easy to integrate with Alloy. Then I found out, that I don’t have “631 Titanium modules” (gitt.io), but “178 Alloy Widgets”, so I had to found widget with similar functionality, written in Alloy. Another “little” bump on the road.

So what?

With some experience with Titanium and some experience with PhoneGap, I don’t think it is possible to write a good cross-platform app. It is hard even when you try to do this for iOS and Android only, but we have also Bada, Tizen, Firefox OS and new OS’s are developed as we speak – Ubuntu Touch, Sailfish OS and some more. Also, it is always good to have mobile web version of the app. But, even if a cross-platform app would be possible to write…

You shouldn’t do this. When you write a native app, you can learn user habits and good practises for each platform. When you write one app for every platform, you probably break about a million good-UX rules. But, if you are desperate and want to do this anyway…

It won’t save you a lot of time. When you write cross-platform apps, you have to deal with OS-specific quirks, you sometimes get native-code errors (good luck with Objective-C errors without any iOS knowledge) and it is not too difficult to miss some crucial things (while testing on 9 devices at the time).

Of course, in some cases, cross-platform apps can be a good solution. Nevertheless, in my opinion, it is not the universal solution for mobile app development.

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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!