So, a few solutions come to scene in the last few years. The most famous I believe it’s Flutter, it covers mobile and desktop, but also web. But it’s not the only one! JetBrains released Compose for Desktop, which targets macOS, Linux and Windows. It’s a port of Android’s Compose for Desktop, what makes this a great alternative for multiplatform apps. If we add Kotlin Multiplatform to this equation for creating Business Logic that can also run on iOS, Kotlin seems like a great starting point for fully native desktop and mobile apps.

Web-based multiplatfom solutions are hungry for resources. Native apps are more resource-efficient, load faster, work better in offline mode.

Similar to the previous article, I will explore the development process of a Linux app using Kotlin Compose, and also will run that app on macOS. Take into consideration that Kotlin Compose is yet an experimental feature.

System Requirements

The only requirement for developing apps using Compose for Desktop, is Kotlin 1.4.20 or newer. A Java Runtime Environment is of course required for this JVM language, and even Kotlin can run on JRE 7 (for example) it’s recommended to use an as new as possible Java Virtual Machine, for example JVM 11 or 13.

At the time of this post there is a bug in JDK 14 that doesn’t allow to generate a Debian package in Linux. If you are using Linux, please switch to either JDK 11 (LTS) or JDK 15.

IntelliJ IDE, made by JetBrains, supports creating Kotlin Compose apps out-of-the-box. Two flavours are available:

• Desktop
• Multiplatform

Desktop targets macOS, Linux and Windows using Compose, while Multiplatform adds Android support.

In this tutorial, a desktop-only app will be created.

Getting Started

When the IDE finished starting up the project, all dependencies are downloaded and the index is updates, a single Main.kt file will be present in your source folder. The entry point of the app is a main function that returns a Window.

A simple Compose app may look like

@ExperimentalAnimationApi
fun main() = Window(title = "Hello, Compose!") {
    MaterialTheme {
        Column(
            horizontalAlignment = Alignment.CenterHorizontally,
            verticalArrangement = Arrangement.Center,
            modifier = Modifier.padding(32.dp).fillMaxWidth().fillMaxHeight()
        ) {
            Card {
                var expanded by remember { mutableStateOf(false) }
                Column(
                    horizontalAlignment = Alignment.CenterHorizontally,
                    verticalArrangement = Arrangement.Center,
                    modifier = Modifier.clickable { expanded = !expanded }) {
                    Image(
                        bitmap = imageResource("drawable/kotlin.png"),
                        alignment = Alignment.Center,
                        modifier = Modifier.padding(32.dp).preferredWidth(128.dp).preferredHeight(128.dp)
                    )
                    AnimatedVisibility(expanded) {
                        Column {
                            Text(
                                text = "Hello, Compose!",
                                style = MaterialTheme.typography.h2
                            )
                        }
                    }
                }
            }
        }
    }
}

Distribution

Packaging an application can be a little tricky, you can run the app everywhere using a gradle o maven task, but you can only create a package, a distributable installation file, in the same architecture of the target package. In other words, there is no “cross packaging”. You cannot create a Debian compatible -deb- file from macOS. So, in order to cover all the available flavours, you will need access to Windows, macOS and Debian.

Which, if you have a macOS machine, it’s pretty easy to archive using VirtualBox or any other Virtual Machine.

The package task generates a distributable file for the current platform. There are other related tasks, but I couldn’t successfully run any of the on a platform different that the current on.

$ ./gradlew package

> Task :packageDmg
WARNING: Using incubator modules: jdk.incubator.jpackage
The distribution is written to build/compose/binaries/main/dmg/DesktopApp-1.0.0.dmg

BUILD SUCCESSFUL in 11s
5 actionable tasks: 3 executed, 2 up-to-date

• msi (Microsoft Installer) for Windows
• deb (Debian package) for Debian/Ubuntu compatible
• dmg (Disk Image File) for macOS

Artefacts

The very simple app that you see in this post needs 80MB of disk space, and generates a DMG file of nearly 42MB. Where only 1MB belongs to this application (assets and compiled code). The rest is just Kotlin libraries (coroutines, stdlib, material design, etc).

/Applications/DesktopApp.app/Contents/app
kimi@Kimis-Mac-mini /A/D/C/app> ls -la
total 37024
drwxr-xr-x  38 kimi  admin     1216 Mar 23 14:34 ./
drwxr-xr-x   8 kimi  admin      256 Mar 23 14:34 ../
-rw-r--r--   1 kimi  admin   104427 Mar 23 14:34 DesktopApp-1.0.0.jar
-rw-r--r--   1 kimi  admin     1522 Mar 23 14:34 DesktopApp.cfg
drwxr-xr-x   3 kimi  admin       96 Mar 23 14:34 META-INF/
-rw-r--r--   1 kimi  admin     1522 Mar 23 14:34 MainKt$main$1$1$1$1$1$1.class
-rw-r--r--   1 kimi  admin     9533 Mar 23 14:34 MainKt$main$1$1$1$1$2$1.class
-rw-r--r--   1 kimi  admin    15698 Mar 23 14:34 MainKt$main$1$1$1$1.class
-rw-r--r--   1 kimi  admin     9692 Mar 23 14:34 MainKt$main$1$1.class
-rw-r--r--   1 kimi  admin     2157 Mar 23 14:34 MainKt$main$1.class
-rw-r--r--   1 kimi  admin     1292 Mar 23 14:34 MainKt.class
-rw-r--r--   1 kimi  admin   208635 Mar 23 14:34 animation-core-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin   201364 Mar 23 14:34 animation-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin    17536 Mar 23 14:34 annotations-13.0.jar
-rw-r--r--   1 kimi  admin    15414 Mar 23 14:34 desktop-jvm-0.2.0-build132.jar
drwxr-xr-x   4 kimi  admin      128 Mar 23 14:34 drawable/
-rw-r--r--   1 kimi  admin   822462 Mar 23 14:34 foundation-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin   357370 Mar 23 14:34 foundation-layout-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin  1488745 Mar 23 14:34 kotlin-stdlib-1.4.20.jar
-rw-r--r--   1 kimi  admin   191485 Mar 23 14:34 kotlin-stdlib-common-1.4.20.jar
-rw-r--r--   1 kimi  admin    22355 Mar 23 14:34 kotlin-stdlib-jdk7-1.4.20.jar
-rw-r--r--   1 kimi  admin    16233 Mar 23 14:34 kotlin-stdlib-jdk8-1.4.20.jar
-rw-r--r--   1 kimi  admin   196243 Mar 23 14:34 kotlinx-collections-immutable-jvm-0.3.jar
-rw-r--r--   1 kimi  admin  1672388 Mar 23 14:34 kotlinx-coroutines-core-jvm-1.4.1.jar
-rw-r--r--   1 kimi  admin    10884 Mar 23 14:34 kotlinx-coroutines-swing-1.4.1.jar
-rw-r--r--   1 kimi  admin  1261868 Mar 23 14:34 material-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin   674505 Mar 23 14:34 material-icons-core-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin   584609 Mar 23 14:34 runtime-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin    19435 Mar 23 14:34 runtime-dispatch-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin    56960 Mar 23 14:34 runtime-saved-instance-state-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin   248772 Mar 23 14:34 skiko-jvm-0.1.18.jar
-rw-r--r--   1 kimi  admin  8553451 Mar 23 14:34 skiko-jvm-runtime-macos-x64-0.1.18.jar
-rw-r--r--   1 kimi  admin  1378337 Mar 23 14:34 ui-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin    38650 Mar 23 14:34 ui-geometry-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin   304483 Mar 23 14:34 ui-graphics-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin   311880 Mar 23 14:34 ui-text-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin    81156 Mar 23 14:34 ui-unit-desktop-0.2.0-build132.jar
-rw-r--r--   1 kimi  admin    11744 Mar 23 14:34 ui-util-desktop-0.2.0-build132.jar

It may seems to much, but, remember that this application embeds a Java Runtime and a lot of libraries that make your live easier developing in Kotlin.

In comparison to Electron.js + React.js I believe that the artefact size is similar, but there is a huge improvement in running a Kotlin / JVM app.

Most of these apps where written in Java, others in Node.js and a few in Kotlin. And most (if not all) of them, shared a single missing point. Static Code Analysis.

Submit an app that makes you comfortable to put in production.

Static Code Analysis

So what is Static Code Analysis and why it’s important for production-ready software development.

Static Code Analysis, a.k.a. Source Code Analysis, is a type of analysis that addresses weaknesses that may lead to vulnerabilities. It automates a task that can be done in a deep code review, but also allows a much richer analysis. For example, duplicate code detection, coverage and quality of unit tests, bad practices, known vulnerabilities, etc.

There is such thing as Dynamic Code Analysis, in contrast to Static, and the main different is when this analysis is done. Is Dynamic the analysis is done after the program runs (during testing, for example) and in Static it is done before (unit testing and source code).

The best thing about Static Code Analysis is that it’s super easy to integrate in your development processes, either in a CI (Continuous Delivery) or a Git Hook (pre-push, for example).

Straight to the point

We will see in this post how to add a Maven task for a Java project, and do some Static Code Analysis using SonarQube Community Edition. No fancy hardware is needed, no cloud computing or VPS, just your machine which should be able to run SonarQube locally using Docker.

Adding SonarQube to a Maven project

First of all we will add the Jacoco and Sonar plugins to the project’s pom.xml.

<plugin>
    <groupId>org.sonarsource.scanner.maven</groupId>
    <artifactId>sonar-maven-plugin</artifactId>
    <version>3.8.0.2131</version>
</plugin>
<plugin>
    <groupId>org.jacoco</groupId>
    <artifactId>jacoco-maven-plugin</artifactId>
    <version>0.8.6</version>
</plugin>

Also, we will add Maven Compiler Plugin (if it’s not already present)

<plugin>
    <groupId>org.apache.maven.plugins</groupId>
    <artifactId>maven-compiler-plugin</artifactId>
    <version>3.8.1</version>
</plugin>

At the project’s level we will add a profile.

<profiles>
    <profile>
        <id>coverage</id>
        <activation>
            <activeByDefault>true</activeByDefault>
        </activation>
        <build>
            <plugins>
                <plugin>
                    <groupId>org.jacoco</groupId>
                    <artifactId>jacoco-maven-plugin</artifactId>
                    <executions>
                        <execution>
                            <id>prepare-agent</id>
                            <goals>
                                <goal>prepare-agent</goal>
                            </goals>
                        </execution>
                        <execution>
                            <id>report</id>
                            <goals>
                                <goal>report</goal>
                            </goals>
                        </execution>
                    </executions>
                </plugin>
            </plugins>
        </build>
    </profile>
</profiles>

Starting SonarQube

SonarQube will perform static code analysis based on some output files that Maven will produce when running a specific task, but prior to that, we need a working SonarQube Server.

Fortunately, that can be done easily using Docker. In case you don’t have Docker installed in your machine, follow this guide if you are under Linux, or this one if you are on Windows or macOS.

Then pull the latest SonarQube image, and bind the internal port 9000 to your local machine port 9000.

docker run -d --name sonarqube -e SONAR_ES_BOOTSTRAP_CHECKS_DISABLE=true -p 9000:9000 sonarqube:latest

Once it completes successfully, open your browser and login into http://localhost:9090 with the default credentials:

• login: admin
• password: admin

Create a new application and register for a Project ID and a Project Token. For more information about this, check this quick guide.

Putting all together

Once your application is created in SonarQube dashboard, and you have a valid token, run the following maven task.

mvn clean verify sonar:sonar 
  -Dsonar.projectKey=<ProjectID> \
  -Dsonar.host.url=http://localhost:9000 \
  -Dsonar.login=<ProjectToken>

Where <ProjectID> and <ProjectToken> where just created. When the target finished executing, you will see the link to your project’s report on the output.

ANALYSIS SUCCESSFUL, you can browse http://localhost:9000/dashboard?id=com.project

You will see in your project’s dashboard information about your code quality similar to the one in the following screenshots.

Project File:  Basic SysInfo