Is AspectJ Still Useful for Android? Part 2

In the first part of this post, I showed some ways that AspectJ would be useful in android development when it comes to testing. This final part demonstrates one way of incorporating AspectJ, and how I manage to make the aspect weaving somewhat configurable in the build process.

Android + AspectJ

A search on the internet will show that there are various ways of integrating AspectJ into the Android build process, including doing it manually or using a gradle plugin. I have been using the android-gradle-aspectj plugin for the last few years, since it has some useful features and the author seems to keep it maintained fairly well.

A basic setup for this plugin requires adding it to the buildscript repositories and dependencies blocks. I have this in build.gradle in the project root directory.

buildscript {
  repositories {
    mavenCentral()
  }
  dependencies {
    classpath 'com.android.tools.build:gradle:x.x.x'
    classpath 'com.archinamon:android-gradle-aspectj:x.x.x'
  }
}

Then apply the plugin where required, so in the module build.gradle:

apply plugin: 'com.archinamon.aspectj'

or

plugins {
    id 'com.android.application'
    id 'com.archinamon.aspectj'
}

This should be enough to run a simple case, such as the example from the first post. Please see the plugin documentation for more advanced configurations.

To verify that the aspect has been compiled and weaved during the build process, you can check:

  • the aspectj directory in the module build directory, containing the compiled aspect class files
  • some log files generated by the plugin in the module build directory, ajc-transform.log and ajc-compile.log
  • the build output log for the AspectJ plugin tasks, compile[Build variant]Aspectj and transformClassesWithAspectjFor[Build variant].

Determining When to Use Aspects or Not

If we’re only using aspects for testing, most of the time we don’t want the aspect code to be incorporated into the build process. An easy way to determine when to weave the aspect code or not is to use a Boolean condition.
For instance, in the aspect file include a Boolean condition in the pointcut to determine whether the advice will apply or not:

pointcut myPointcut(): if (aspectjEnabled) && ... // the rest of the pointcut

Here the Boolean value ‘aspectjEnabled‘ is used as a flag that will determine whether the aspect code will apply the advice.

One way of passing this flag to the aspect class is to use the generated BuildConfig class, which can be set in the build file (build.gradle) of the app.

android {
  buildTypes {
    debug {
      // Flags for Aspect testing
      buildConfigField 'boolean', 'aspectjEnabled', true
    }
  }
}

Then in the pointcut of the aspect file, include the flag as a conditional.

pointcut myPointcut(): if (BuildConfig.aspectjEnabled) && ... // the rest of the pointcut

Of course we can go further and set that flag from a gradle project property, rather than hardcoding it in build.gradle.

Now when the build is done, pass a project property to determine whether we want the aspect flag to be set or not.

-PaspectjEnabledProperty=true

I also have this extra bit to set the aspect flag to false if the project property was not specified (which is the default when we want to do a normal build without aspects).

ext.aspectjEnabledProperty = getAspectJEnabledFlag()

def getAspectJEnabledFlag() {
  if (project.hasProperty('aspectjEnabledProperty'))
    return project.property('aspectjEnabledProperty')
  else
    return false
}

Then in the build file for the app, the value of the aspect flag to be put into the BuildConfig class will be set dynamically.

android {
  buildTypes {
    debug {
      // Flags for Aspect testing
      buildConfigField 'boolean', 'aspectjEnabled', "${aspectjEnabledProperty}"
    }
  }
}

In sumary, this means that if the property ‘aspectjEnabledProperty’ is not passed to the build or is set to false, then the AspectJ weaving does not happen. Then when required, the property can be set for testing that particular bit of code.

Of course you are not restricted to one aspect flag, you can set as many flags as you like for the different tests you want to run.

-PexceptionTestProperty=true -PcrashTestProperty=false -PservicesTestProperty=true

Testing Multiple Types of Errors

In the configuration above, I’ve used a boolean value as the flag to enable/disable aspect weaving in the pointcut. Using a boolean flag is the simplest case, and probably the most common type that used.

However what about if you want to test multiple types of errors and error handling. For instance, if you want to test having the adviced method throw different types of exceptions. Another example is if you want to simulate different status codes as the response from a network call.

Then instead of using a boolean value as the flag, use an integer (or any other simple type) for example.

-PaspectjTestingProperty=1

Then in the build file:

ext.aspectTestingFlag = getAspectTestingFlag()

def getAspectTestingFlag() {
  if (project.hasProperty('aspectjTestingProperty'))
    return project.property('aspectjTestingProperty')
  else
    // default value if property not specified
    return 0
}

android {
  buildTypes {
    debug {
      // Flags for Aspect testing
      buildConfigField 'int', 'aspectTestingFlag', "${aspectjTestingProperty}"
    }
  }
}

Then in the aspect, you can use the integer flag both as a conditional in the pointcut and as an indicator run different code in the advice.

aspect TestAspect {

  pointcut myPointcut(): if (BuildConfig.aspectjTestingFlag != 0) && ... // the rest of the pointcut

  int around(): myPointcut() {
    switch (BuildConfig.aspectjTestingFlag) {
      case 1:
      // return a particular status code, or throw a particular exception type

      case 2:
      // return a different status code, or throw a different exception type

      case 3:
      // return yet another status code, or throw a third different exception type

      default:
      return proceed();
    }
  }
}

Caveats

Just a few things to be aware of:

  1. As already mentioned, since we can only have AspectJ compile time weaving for Android development, this means some additional build time for the AspectJ tasks.
  2. Unfortunately Android Studio doesn’t have IDE support for AspectJ, since it is based on the community edition of IntelliJ IDEA.
    While the Ultimate version of Intellij does support AspectJ, I prefer using Android Studio.

    Tip:
    Sometimes to get the pointcuts correct I will copy files with the aspect, the classes I want to advice and their lib dependencies into a dummy Eclipse project so that I can use the AspectJ Development Tools (AJDT) to fine tune the pointcut. This allows me to see if the pointcuts are being applied correctly to the joinpoints I want.

  3. Using a Gradle plugin to handle incorporating AspectJ into the build process does make things easier. However this sometimes means having to wait for the authors of the plugin to keep up to date with the latest versions of the android gradle plugin or gradle.

Checking for Artifactory in a Jenkins Pipeline

One of my projects uses the Artifactory as the repository manager. Unfortunately when doing a Jenkins pipeline build, I sometimes forget to ensure the Artifactory server is up first and find the job has failed after running for a while.

I’ve added some script to my Jenkinsfile that will check for the Artifactory server early on and fail fast if it is not running.

Artifactory Check

For my purposes I just try to ping the Artifactory server.
This can be done by sending a http request:
http://[Your Artifactory URL]/artifactory/api/system/ping
and if successful should return the string ‘OK’.

Jenkins Pipeline example

This particular example requires the HTTP Request plugin to be installed. I added a declarative stage in the pipeline before the actual build for the Artifactory check.

In this stage the HTTP request call from the plugin will be successful if the response status code is in the default range (100 to 399) and the response content includes the string ‘OK’. If the response does not fulfil these conditions, then the Jenkins job will fail quickly.

pipeline {
  agent any
  options {
    // Stop the build early in case of compile or test failures
    skipStagesAfterUnstable()
  }
  stages {
    stage('Build') {
      environment {
        // artifactory server url
        artifactoryUrl = 'http://[Your Artifactory URL]/artifactory'
     }

    // stage to check the Artifactory server is up, else will fail the job
    stage('Artifactory check') {
      steps {
        script {
          echo 'Pinging Artifactory'

          // for a successful ping, the response status code must be in default acceptable range (100:399)
          // and contain 'OK' in the content
          def pingResponse = httpRequest url: "${artifactoryUrl}/api/system/ping", validResponseContent: 'OK'

          echo "Ping response status code: ${pingResponse.status}"
          echo "Ping response: ${pingResponse.content}"
        }
      }
    }

    // continue with other stages for the job

Alternatively if you don’t want the Artifactory check to fail the job, just change the parameters to the HTTP request to allow all response status codes and any response content to pass. Then if the ping fails, you can just set a flag, send a notification, print some info, etc, instead and let the job continue.

stage('Artifactory check') {
  steps {
    script {

      // Allow all response codes returned from the Artifactory ping request so it doesn't fail,
      // normal allowable codes are 100:399.
      def pingResponse = httpRequest url: "${artifactoryUrl}${artifactoryPingPath}", validResponseCodes: '100:599'

      echo "Ping response status code: ${pingResponse.status}"
      echo "Ping response: ${pingResponse.content}"

      if (pingResponse.status == 200 && pingResponse.content == 'OK')
        // flag successful check
      else
        // flag ping failure
    }
  }
}

Gradle Dependencies for Java, use compile or implementation?

While I was explaining to a colleague about using Gradle for Java projects (he was moving away from Maven), we came across various code samples. Some of the examples were using the compile configuration for dependencies, while others were using implements and api.


dependencies {
compile 'commons-httpclient:commons-httpclient:3.1'
compile 'org.apache.commons:commons-lang3:3.5'
}


dependencies {
api 'commons-httpclient:commons-httpclient:3.1'
implementation 'org.apache.commons:commons-lang3:3.5'
}

This post was a summary based on the documentation and StackOverflow questions to explain to him which configurations to use.

New Dependency Configurations

Gradle 3.4 introduced the Java-library plugin, which included the then new configurations implementation and api (amongst others). These were meant to replace the compile configuration which was deprecated for this plugin. The idea was that the new configurations would help to prevent leaking of transitive dependencies for multi-module projects.

Please note that in this post I am just using the compile vs implementation/api configurations as an example. Other new replacement configurations were introduced as well, please read the documentation for further information.

Java

For a Java project using Gradle 3.4+, then it depends on whether you are build an application or a library.

For a library project or a library module in a multiple module project, it is recommended to use the Java-library plugin, so in build.gradle use this

apply plugin: 'java-library'

instead of

apply plugin: 'java'

Then you would use either implementation or api, depending on whether you want to expose the dependency to consumers of the library.

For a plain application project, you can stick with the java plugin and continue to use the compile configuration. Having said that, I have tried using the Java-library plugin for an app project and it seems to work fine.

Android

For an Android project, the new configurations came with the Android Gradle Plugin 3.0. So unless you are still using the 2.x version of Android Studio / Android Gradle plugin, the use of compile is deprecated. So you should use implementation, even for an app.

In fact, when I recently upgraded my Android Studio, it came up with the message:

Configuration ‘compile’ is obsolete and has been replaced with ‘implementation’.
It will be removed at the end of 2018

I think this also applies if you use Kotlin instead of Java.

Groovy

How about a project with Groovy as well as Java? This can be for a mixed Groovy / Java project, or for a Java project which needs Groovy for some support tools (such as Spock or Logback configuration).

In the past I have used the Groovy plugin instead of the Java plugin for mixed projects. The Groovy plugin extends the Java plugin and will handle the compilation for Java sources as well as Groovy sources.

apply plugin: 'groovy'

You can continue to do this for Java application modules, but the documentation states that the Groovy plugin has compatibility issues with the Java-library plugin so will need a work around for library modules.

Of course this short post is for newbies, and has only scratched the surface in terms of learning about all the new dependency configurations.

 

JRebel for a Gradle Spring Boot App

There is some documentation on how to add JRebel to a Spring Boot app that uses Gradle as the build tool. It is basic but works fine.

All you have to do is to add a few lines to build.gradle:

if (project.hasProperty('rebelAgent')) {
 bootRun.jvmArgs += rebelAgent
}

Then set the property in gradle.properties:

rebelAgent=-agentpath:[path/to/JRebel library]

However there are several ways to improve on this.

Make JRebel Optional

For instance, what if you don’t always want JRebel everytime you start the app with ‘bootRun’? JRebel plugins for IDE’s like Intellij IDEA are smart enough to give you the option of running your app with or without JRebel

There would be several ways of doing this, but one would be to add the JRebel startup configuration in an optional task.


task addRebelAgent << {
  if (project.hasProperty('rebelAgent')) {
    bootRun.jvmArgs += rebelAgent
  }
  else
    println 'rebelAgent property not found'
}

task rebelRun(dependsOn: ['addRebelAgent', 'bootRun'])

Now running ‘bootRun’ would start the app normally, and if you want JRebel then use the ‘rebelRun’ task instead. I have also added a debug message if the ‘rebelAgent’ property is not available.

Another way would be to pass an optional property to the ‘bootRun’ task to use as a flag whether to add JRebel or not.

if (project.hasProperty('rebelAgent') &&
    project.hasProperty('addJRebel')) {
 bootRun.jvmArgs += rebelAgent
}

Then to use JRebel you just need to add the extra property.

gradle bootRun -PaddJRebel=true

Finding the Rebel Base

Putting the path to the JRebel library to use as the agent in a properties file allows multiple developers to have their own version. However the path is still hard-coded, which is something that should be avoided if possible.

Another way to specify the path is to use a system environment variable to point to where JRebel is installed. JetBrains recommends using REBEL_BASE. Once set up, that allows you to use the environment variable in multiple ways, e.g. Gradle build files, command line, build scripts, etc.

Here is an example using the additional ‘addRebelAgent’ task that I specified earlier, that I use on my Windows 64 machine.


task addRebelAgent << {
  project.ext {
    rebelAgent = "-agentpath:${System.env.REBEL_BASE}${rebelLibPath}"
  }
  if (project.hasProperty('rebelAgent')) {
    bootRun.jvmArgs += rebelAgent
  }
  else
    println 'rebelAgent property not found'
}

task rebelRun(dependsOn: ['addRebelAgent', 'bootRun'])

And in gradle.properties I have specified the path to the agent library from the JRebel installation location.


rebelLibPath=\\lib\\jrebel64.dll

All I’ve done here is to build the path in the ‘rebelAgent’ property from the REBEL_BASE environment variable and another property specifying the internal path to the library.


rebelAgent = "-agentpath:${System.env.REBEL_BASE}${rebelLibPath}"

 

 

Pluggable Tools with Docker Data Containers

There are some apps that have a simple installation process. When using them with other applications in Docker, they may be able to be installed in their own data volume container and used in a pluggable way.

The kind of apps I’m talking about are some Java apps (and in fact, Java itself) which follow this installation process:

  1. Install the contents of the app into a single directory
  2. Set an environmental variable to point to the installation directory, e.g. XXX_HOME
  3. Add the executables of the app to the PATH environmental

 

That’s it.

An example of an app installation that follows this pattern is Gradle:

  1. Uncompress the Gradle files from an archive to a directory.
  2. Set the enviromental variable GRADLE_HOME to point to the gradle installation directory
  3. Add GRADLE_HOME/bin to the PATH

 

Docker

Using Gradle as an example, here is a Dockerfile that installs it in a data volume container:

# Install Gradle as a data volume container. 
#
# The app container that uses this container will need to set the Gradle environmental variables.
# - set GRADLE_HOME to the gradle installation directory
# - add the /bin directory under the gradle directory to the PATH

FROM mini/base

MAINTAINER David Wong

# setup location for installation
ENV INSTALL_LOCATION /opt

# install Gradle version required
ENV GRADLE_VERSION 2.2.1

WORKDIR ${INSTALL_LOCATION}
RUN curl -L -O http://services.gradle.org/distributions/gradle-${GRADLE_VERSION}-bin.zip && \
    unzip -qo gradle-${GRADLE_VERSION}-bin.zip && \
    rm -rf gradle-${GRADLE_VERSION}-bin.zip
    
# to make the container more portable, the installation directory name is changed from the default
# gradle-${GRADLE_VERSION} to just gradle, with the version number stored in a text file for reference
# e.g. instead of /opt/gradle-2.2.1, the directory will be /opt/gradle

RUN mv gradle-${GRADLE_VERSION} gradle && \
    echo ${GRADLE_VERSION} > gradle/version
    
VOLUME ${INSTALL_LOCATION}/gradle

# echo to make it easy to grep
CMD /bin/sh -c '/bin/echo Data container for Gradle'

(From github https://github.com/davidwong/docker/blob/master/gradle/Dockerfile)

Build the image and container from the Dockerfile. Here I’ve tagged the image with the version number of the Gradle installation, and named the container gradle-2.2.1.


docker build -t yourrepo/gradle:2.2.1 .

docker run -i -t --name gradle-2.2.1 yourrepo/gradle:2.2.1

A few things to note about this installation:

  • I have changed the directory name where Gradle is installed from the default, by removing the version number in order to make it generic.
  • no environmental variables have been set, that will be done later
  • you can use any minimal image as the basis for the container, it justs need curl or wget in order to download the Gradle archive file

Now we have the Gradle installation in a docker data volume that can be persisted and shared by other containers.

You can then repeat this process with difference versions of Gradle to create separate data containers for each version (of course giving the containers different names, e.g. gradle-2.2.1, gradle-1.9, etc).

Use Case

I originally got this idea when I was running my Jenkins CI docker container. Some of the Jenkins builds required Gradle 2.x while others were using Gradle 1.x.

So instead of building multiple Jenkins + Gradle images for the different versions of Gradle required, I can now just run the Jenkins container with the appropriate Gradle data container. This is done by using –volumes-from to get access to the Gradle installation directory and setting the require environmental variables.

To use the data container with Gradle 2.2.1 installed:

docker run -i -t --volumes-from gradle-2.2.1 -e GRADLE_HOME=/opt/gradle -e PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/opt/gradle/bin myjenkins</pre>

To use the one with Gradle 1.9:

docker run -i -t --volumes-from gradle-1.9 -e GRADLE_HOME=/opt/gradle -e PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/opt/gradle/bin myjenkins</pre>

Of course there are limitations to this technique since Docker data volume containers were designed to share persistant data rather than application installs. In particular they do not allow sharing of environmental variables.

However this work around that can be useful in some circumstances.

Backup a Docker Data Container with Fig

I have been using data volume containers to persist data in docker containers.  There are various reasons why this tends to be a better option than just using data volumes, but probably the most important is portability.

Of course now we have to backup the data in the data containers. This can be for archiving, or when the containers that use the data need to be upgraded or recreated. If your backup requirements are simple you can simply use the docker cp command or something like tar.

A Jenkins example

As a simple example, let’s run a Jenkins server in a docker container and use a data volume container to persist its data.

1. Pull or build a Jenkins image from the official repository.

http://jenkins-ci.org/content/official-jenkins-lts-docker-image

2. The Jenkins images uses the directory /var/jenkins_home as the volume to store it’s data, so we need a data volume container for that volume. Here is a sample of a Dockerfile to build the data container:

Build and tag the image from the Dockerfile.

docker build -t your_repository:jenkins-data .

You can now create the data container, giving it a name for convenience. Optionally we can run the docker ps command afterwards to check that the container has been created, it should be in a stopped state.

docker run -i -t --name jenkins-data your_repository:jenkins-data
docker ps -a

3. Run the Jenkins server with the data container attached and make some changes, e.g. create a job, etc. The Jenkins data volume should have your changes in it now.

docker run --name=jenkins-sample -p 8080:8080 --volumes-from=jenkins-data jenkins

4. For this example we will use tar to backup the data container, using this command to create a temporary container to access the data container.

docker run -rm --volumes-from jenkins-data -v $(pwd):/backup busybox tar cvf /backup/jenkins_backup.tar /var/jenkins_home

There should now be a file jenkins_backup.tar in the current directory. Of course for real usage, we would probably run this command from a script and make it generic to be able to backup any data volume container.

I do give a fig …

Something else I use for development with Docker is the orchestration tool Fig (this has saved me a lot of typing!). So here is an example of  doing the same backup on the Jenkins data container using Fig.

1. Create Fig YAML file, using the same information that we used in the backup command.

2. Run Fig, that’s it!

fig up

This is a simple example that has only scratched the surface of what can be done with Docker (and Fig). If the backup requirements for the data is more complex, then you could also consider creating a dedicated container just for doing backups, with all the required tools installed in it.

The great thing about Docker is that once everything has been setup, you can get applications such as Jenkins up and running very quickly.

Another Defection to Android Studio

Like many other developers out there, I have been using Eclipse as my main IDE for many years now. However for Android development I have decided to take the plunge and migrate to Android Studio (especially since it has finally been released).

Here is a blog post I found that closely echoes what I have long thought regarding the issues with Eclipse:

http://engineering.meetme.com/2014/02/a-tale-of-migrating-from-eclipse-to-android-studio/

Build, build, build

For me, another reason was that the Ant build files I was using to handle building different versions (free vs paid, dev vs release, etc) were getting too complicated to manage easily. So I can now change over to Gradle at the same time, since that’s what Android Studio uses by default.

Gradle has the concept of build variants to handle building different versions of an Android app.

The Recurring Eclipse Re-install

Here are some other problems that I personally have had with using Eclipse.

  • Plugins, well not the plugins themselves, but having too many plugins. I’ve found that having lots of plugins in one Eclipse installation can cause Eclipse to misbehave , especially after several updates. There are several ways I use to get around this:
    • Keep separate Eclipse installations for different types of development, e.g one for Java, one for Android, one for Cloud, etc. Therefore each installation will only have a few plugins relevant to the type of development. However this is not always convenient if a project does require multiple types of development.
    • Every so often, when Eclipse starts to play up, do a fresh re-install of Eclipse (along with the latest version of the plugins required).
  • Intermittent miscellaneous bugs, e.g. cut and paste stops working, builds not alway done automatically, etc. A lot of these issues are more of a nuisance rather than being a serious problem, but all the same it tends to kill your productivity (and isn’t that why we use IDE’s in the first place?).

No Pain, No …

Make no mistake, despite what the Android Studio documentation might try to tell you, migrating a non-trivial project will take some time and probably involve some pain. But worth the effort I think.