Creating an iOS framework with… Kotlin

🇫🇷 Parlez-vous Français ? You can read a French Version of this post on our blog at Xebia France.
Kotlin/Native is a new Kotlin dialect which supports compiling code in an executable form that can be run on the targeted system, without needing for a JVM. The Kotlin/Native compiler, named Konan, interfaces with the LLVM compiler infrastructure in order to support a number of targets, such as Linux, macOS, iOS, Web Assembly and others.
First announced in April, Kotlin/Native has now reached v0.6, published in February 2018. Since its version 0.5 Kotlin/Native introduces a new target, which can particularly be useful for iOS projects, that is iOS frameworks.
In this article, we’ll see how to create an iOS framework using Kotlin code. Our library will actually do nothing too fancy, but it’ll be a great starting point for future evolutions.
Please note that to complete this tutorial you will need a machine running macOS and Xcode 9.2.

How Konan works

As mentioned above, Konan interfaces with the LLVM backend compiler in order to support a number of targets, such as Linux, macOS, iOS, Web Assembly and others. The LLVM compiler takes as input an intermediate representation (IR, or LLVM-IR) and generates machine code (or, better, object code) for a number of supported CPU architectures (such as ARM, x86 and many others).
In other words, Konan will compile Kotlin code to LLVM-IR and LLVM will take care of the rest, by compiling LLVM-IR down to ARM (or other CPUs).
Kotlin and LLVM

Before we start: Gradle

In order to complete this tutorial, you’ll need to install Gradle first. If you’ve never stumbled on it, Gradle is the main build tool in the JVM environment and it is used by the vast majority of Android projects. With Gradle, we’ll be able to define dependencies, and define tasks that will take care of compiling our project. Also, and foremost, gradle is easily extendable via plugins, and we’ll actually use one of them to help us creating the tasks we need to create our framework.
The easiest way to install Gradle is via Homebrew:

Project Setup

We then create a new project folder, for instance “MyProject”.
We can now open the shell inside “MyProject” and run

This operation will create the basic configuration for our project.

Now, we’ll need to add the following resources to “MyProject”:
  • An empty file
  • A folder, named “myframework”, which will contain code and properties for our library
  • Inside the “myframework” folder, we’ll be adding:
    • A tree of folders as follows: src/main/kotlin/fr/xebia/myframework
    • Another empty build.gradle file
The result should now be as follows:

This structure follows the conventions of most Java and Kotlin projects and allows us to prepare our project to host other subprojects in the future in case we need it (and we sure will in a further post).

Configuring the environment

Now we’ll be setting the basic properties of our environment.
The settings.gradle file should reference reference the modules of the project we’re building. In our case, it’s “myframework”, so we’ll add to the file the following line:

The root build.gradle file will contain the main configuration used throughout our project and subproject. In particular, we’ll set the kotlin_version to be used (1.2.21) and the version of the compiler (0.6). We also set which repositories will be used by our build script, i.e. jCenter.

Configuring the “myframework” subproject

Let’s open the build.gradle contained in the “myframework” subproject. This file instructs Konan on what and how it will need to handle the compilation.
In particular, via the apply plugin directive, we’ll define the plugin to be used in our context: ‘konan’, which is of course the plugin used for easily interfacing with the Kotlin/Native compiler.
Also, we’ll instruct our script about its repository: i.e., maven, and its dependency, I.e. the kotlin-native-gradle-plugin.

Finally, we’ll add to the same build.gradle file the directives for creating the iOS framework. We’ll be targeting iPhone and the iPhone Simulator, which are based on two different architectures, namely ARM for the iPhone and x86 for the Simulator. We’re also setting, in the framework parameters, the output file name of our task: ‘MyKotlinFramework’.

Here, we’ll also indicate which folder contains our source code, in our case “src/main/kotlin”.
Not much else to see here, apart from enabling the debugging mode, via the enableDebug true line.

Adding some source code

Now it’s finally the time to add some Kotlin code.

As you clearly understand, this code doesn’t do much, but it’s enough to try out the basic functionalities of Kotlin/Native.


That’s pretty much all. We just need to compile our project by running grade.
Before doing this, let’s just run

This should output a number of tasks preconfigured by Gradle. Among them, the compileKonan task, compileKonanMyKotlinFrameworkIphone, compileKonanMyKotlinFrameworkIphone_sim are automatically created by the konan plugin applied in the build.gradle file: as the names say, they will compile code and produce frameworks for iPhone and iPhone simulator.

We can now run

and wait for the project to compile. Please note that Gradle will also take care of automatically downloading the Kotlin/Native compiler for us – even though this’ll take a while.

When the compilation is finished (it may take a little while at the time of writing), verify the contents of the folder myframework/build/konan/bin/iphone_sim: they should contain three files:
  • MyKotlinFramework.framework
  • MyKotlinFramework.framework.dSYM
  • MyKotlinFramework.kt.bc
What are those three files?
The first one is, of course the framework we’ve just produced. The second file, having the dSYM extension, contains the information needed to debug our framework with an lldb debugger, such as the one provided by Xcode. Last, the .kt.bc file is the bitcode file of our program. In other words, it is the binary form of the LLVM Intermediate Representation of our code.

Integrating in an iOS application

In order to try how the framework runs in our iOS app, let’s add it to the “Embedded Binaries” section of our target.
Embedded Binaries Section
Then, in our Swift code, we’ll just need to import the library and use the bar() method of our Foo class. As you’ll see, please note that Konan prefixes all your classes with the trigram of your framework output name. In our case, MyKotlinFramework. In our case, the Foo class will become visible in Objective-C and Swift as MKFFoo.

The complete code of this tutorial is available at this GitHub repo.

Where to go from here?

Needless to say, this is just the beginning. Thanks to Kotlin/Native 0.6 it is now easy to share code between iOS and Android, by using the Multiplatform DSL. This will allow for a more effective reuse of your business logic between your mobile apps, no matter the platform.


Huge thanks to my colleagues at Xebia France for reviewing this article, in particular Sergio Dos Santos, Benjamin Lacroix, Michaël Ohayon and Julien Datour.

Kotlin/Native 0.5 and iOS

Kotlin Native interoperability is rapidly evolving and the latest iteration, version 0.5, brings support for calling Kotlin code from Swift and Objective-C.

Also, iPhone Simulator is now supported out of the box. Just run

to compile the Kotlin bridge for the iOS Simulator platform libs and runtime. The command will take about 1 hour to complete on a recent MacBook Pro.

Also, the samples have been adapted and you will now be able to try out the features straight on your simulator.

And that’s pretty neat.

Running a Kotlin/Native iOS app in the Simulator

Update: since Kotlin/Native 0.5, the following article is now outdated. I’ll be keeping its content for reference.

Kotlin Native 0.4 is out since the beginning of November and, with it, some nice sample iOS demo apps to be run into your favourite iOS device. That sounds amazing, even for some hardcore Swift fans like me. Yet, there’s a catch: the sample apps can only run on a real iOS device but not in the Simulator. Sure, that’s just an unsignificant drawback compared to what the Kotlin Native team achieved so far. Still, I’m a huge fan of the iOS Simulator, as it’s by far the fastest way to do some quick testing of an app while doing a pretty good job in mimicking the behaviour of an app on a real device.

So, as a way to understand the Kotlin Native project, I decided to try supporting the Simulator on a Kotln Native iOS app.

In order to do this, I started from the UIKit project sample found in the samples dir of the main repo and tried to make it run in the sim.

Continue reading Running a Kotlin/Native iOS app in the Simulator

Leveraging Swift Code Coverage with Xcode 7

French speakers: the original version of this article is actually French, and you can read it on Xebia’s excellent blog.

Also, this article is the text version of the talk “Leveraging Xcode Code Coverage”, presented at the Mobile Optimized conference in Minsk, whose slides are available here.

One of the WWDC 2015 announcements that surprised interested us the most has definitely been the support for code coverage for the Swift language.
In this article we will understand the advantages of the new code coverage functionality introduced in Xcode 7 and how to integrate such KPI in our daily work.

Code coverage is a metric that measures the value of our tests by identifying what code is executed when running them and, above all, what portions of our project are untested.

How it works?

The production of code coverage information is done in two passes:

  1. At compile time, the compiler prepares the files for analysis
  2. At runtime, the lines of code affected by the tests are annotated in a specific file

Xcode code coverage before June 2015

Before WWDC 2015, only the Objective-C code coverage was supported by Apple’s tools, while Swift had been left behind. Also, the Objective-C support was sometimes inconsistent and required a few tricks to get the information.

How did it work?

The procedure necessary to retrieve the information was a variant of the one used by gcov, included in the gcc tools. Two settings had to be added to the Build Settings:

  1. Generate test coverage files, which corresponds to the -ftest-coverage gcc flag
  2. Instrument program flow, corresponding to -fprofile-arcs

The former allows the creation of the .gcno files, which contain the information needed to build the execution graph and reconstruct the line numbers.

The latter, Instrument program flow, deals with the creation oft the .gcda files, which contain the number of transitions on different arcs of the graph and other summary information.

In order to force the generation of these command line data, it was possible to use the following command:

Exploiting the data

A number of tools for reading and exporting reports exist, but in particular, we used the following:

  • Coverstory, a GUI tool to read files “.gcda” and “.gcno”
  • gcovr translates these files Cobertura XML format
  • lcov generates a visual report in a navigable HTML
  • and, especially, Slather.


Slather, developed by the SF-based company Venmo, exports the code coverage data in a number of different formats, including Gutter JSON, Cobertura XML, HTML and plain text. In addition, it integrates easily with other platforms, such as Jenkins, Travis CI, Circle CI and coveralls.

As said, one of the major assets of Slather is its ease of configuration and integration within a continuous integration system. Slather is open source, and available here at Venmo’s GitHub repo.


A recent tool for collecting Swift coverage information is Swiftcov, developed by the guys at Realm. Swiftcov makes heavy use of LLDB breakpoints to detect which lines are affected by the execution of our tests.

Code coverage after June 2015

During the WWDC 2015 keynote, Apple announced that Xcode 7 would introduce support of code coverage for our beloved Swift.

How does it work?

A completely new format has been introduced, named profdata, thus making
gcov legacy – at least for what concerns projects developed with Apple’s development tools.

In other words, starting from the very first beta of Xcode 7, profdata is intended to replace completely gcov for both Swift and Objective-C.

In order to enable the setting, from Xcode 7, you will need to access the “scheme” setting and, in the “Test” tab, to tick the “Gather coverage data” checkbox.

Access the scheme editor, select the "Test" tab and enable the "Gather coverage data" checkbox

As for the command line, xcodebuild now ships with a new parameter, -enableCodeCoverage, which can be used as follows:

Once the tests run, coverage information is immediately available in Xcode, on the right side of the code editor (see image below) and, in particular, in the “Report Navigator”.

Inline code coverage information
Inline code coverage information
Code coverage information in the Report Navigator
The new Report Navigator

The Report Navigator shows in detail which classes are covered by our tests and, by expanding the selection, which methods are actually used.

Exploiting the data

Apple’s work hasn’t only consisted in enhancing Xcode but, also, in extending the features of the   llvm-cov command line tool, which allows working with .profdata format.

The llvm-cov show command, for instance, allows exporting plain text coverage information and outputs annotated source code files, which can be easily read and processed.

Slather (returns)

A recent Pull Request allows Slather to work with profdata files and convert them to other formats, thus enabling the integration with the other platforms supported by the tool.

Xcode Server

If you are thinking about setting up an automated integration system, aside from the excellent Jenkins, Travis or Circle CI, it is perhaps time to start taking into consideration Xcode Server, which is part of the OS X Server bundle, distributed free of charge by Apple.

With the new version of Xcode bots and Xcode Server, it is now possible to support code coverage values ​​and to display the results in a Web browser. The reports are also available in the “Big Screen” presentation, useful for presenting your content in a simplified yet effective overview.

In order to enable this workflow, you could follow the steps below:

  1. Install OS X server
  2. Enable “Xcode” and “Websites” services
  3. Create a new project and assign a Source Control Manager to it (such as git)
  4. In Xcode, create an Xcode bot under “Product > Create Bot”
  5. Select the frequency of integration and enable code coverage (see image below) next to the caption “Code Coverage”.
  6. Launch an integration
  7. Open the web browser at the host indicated by your instance of Mac OS.
Xcode Bot creation panel
Xcode Bot creation panel


Code coverage is very useful to keep under control your code base health status. Although it can not replace your developer confidence in well designed, well structured apps, this metric can help write better code by encouraging you to give yourself concrete goals day by day.

Also, and finally, the new tools offered by Apple can now allow you to keep under control these values ​​in minutes, with a simple and immediate configuration.

Some opinions about Calabash-iOS

For what concerns iOS my colleagues and I have been using Calabash-iOS for a year now, with mixed feelings.
Here is a totally subjective opinion about Pros and Cons of Calabash-iOS


  • Conciseness of the Gherkin language
  • Capability of querying webviews with CSS selectors
  • Access to all the object property values via Ruby
  • built-in Jenkins-Ready output (xml and HTML test reports, mainly)
  • Performance (on <= iOS 6)
  • It does not uniquely rely on accessibilityIdentifiers (as KIF does)
  • Actively mantained


  • It’s not an Apple-backed project : functionalities change significantly from OS to OS
  • Test fail randomly under certain circumstances and, in particular, when dealing with repeated scrolling on a UIScrollView (due to a poor implementation of the scroll/swipe functions)
  • On iOS 7, it relies on UIAutomation, thus…
  • …terrible performance on iOS 7 (see above)
  • Once again, quite a Pain-in-the-ass to make it work on iOS 7
  • Finding the good query for your element usually requires much trial-and-error via the calabash-ios console (Frank provides a nice UI tool for that task, but it’s not merged into Calabash-iOS yet)

Truth to be told, at this stage, the performance impact of relying on UIAutomation is deal breaker for me, so, on the next project we’ll be using KIF, which appears to be also used in some Google projects.

How to resolve “Unable to start status bar server” when launching GHUnit Tests from command line after upgrading to XCode 5

After upgrading to XCode 5 my Jenkins Continuous Integration machine over at Xebia stopped executing command-line GHUnit tests under some apparently random conditions. The console output was as follows:

The reason of the exception looks pretty much the same I had to deal with some months ago (and solved in a previous post).

Well, it turns out that after the XCode upgrade, after quitting an iOS 5.x or iOS 6.x simulator instance, the SpringBoard daemon (along with many others) does not get removed, thus preventing our test target to instantiate a status bar. Interestingly enough, this behaviour does not occur when quitting an iOS 7.0 simulator.

That said, in order to fix the issue, I added the following line to the script:

The complete script is available at this public gist.

Introducing SMWheelControl

Today I am proud to announce the availability of a new Pod for iOS which will be included in my forthcoming app.


SMWheelControl is an iOS control allowing the selection of an item from a 360° spinning wheel with a smooth inertial rotation.

The code, released under the BSD 3-clause license, is loosely based on the tutorial “How To Create a Rotating Wheel Control with UIKit” published on this Ray Wenderlich’s post by Cesare Rocchi

As usual, you can insert it into your podfile by adding

Some howto follows.


Initialization and data source

Instantiate the control with a classical - (id)initWithFrame:(CGRect)rect and add a target as you usually do with a control, e.g.:

Then add a dataSource:

and implement the following methods (the dataSource should conform to the SMWheelControlDataSource):

For instance:

When the wheel ends snapping to the closest slice, if you added a target, then it will receive the event UIControlEventValueChanged, and the selector you specified will be executed.

About the Builder Pattern in Objective-C

When dealing with complex object creation in an iOS application you may feel the need for a cleaner and more fluent approach.

During my latest development my colleague @alexiskinsella set up a pattern based on providers in order to mimic the factory behaviour we often find in languages such as Java.

Recently, in the occasion of a side project, I am studying a slightly different approach, based on this article by Matthias Wessendorf.

What I am willing to do is an image builder which creates UIImages on which a GPUImageFilter is applied.

The result I came to is as follows:

The Builder itself (implementation)

The Configuration object (header)

 Using a Builder with an inline Configuration

This should make for a quite readable code with a reduced number of lines of code in the method that invokes the builder.