Use Travis to extract testing APKs for PSLab

Travis CI is a popular continuous integration tool built to test software and deployments done at GitHub repositories. They provide free plans to open source projects. PSLab Android is using Travis to ensure that all the pull requests made and the merges are build-bug frees. Travis can do this pretty well, but that is not all it can do. It’s a powerful tool and we can think of it as a virtual machine (with high specs) installed in a server for us to utilize efficiently.

There was a need in PSLab development that, if we want to test the functionalities of code at a branch. To fulfil this need, one has to download the branch to his local machine and use gradle to build a new apk. This is a tedious task, not to mention reviewers, even developers wouldn’t like to do this.

If the apk files were generated and in a branch, we can simply download them using a console command.

$ wget<repository>/<branch>/<file with extension>


With the help of Travis integration, we can create a simple script to generate these apks for us. This is done as follows;

Once the Travis build is complete for a triggering event such as a pull request, it will run it’s “after_success” block. We are going to execute a script at this point. Simply add the following code snippet.

  - 'if [ "$TRAVIS_PULL_REQUEST" == "false" ]; then bash <script-name>.sh; fi'


This will run the script you have mentioned using bash. Here we will have the following code snippets in the specified bash script.

First of all we have to define the branch we want to build. This can be done using a variable assignment.



Once the build is complete, there will be new folders in the virtual machine. One of them is the app folder. Inside this folder contains the build folder where all the apk files are generated. So the next step is to copy these apk files to a place of our preference. I am using a folder named apk to make it much sense.

cd apk
\cp -r ../app/build/outputs/apk/*/**.apk .
\cp -r ../app/build/outputs/apk/debug/output.json debug-output.json
\cp -r ../app/build/outputs/apk/release/output.json release-output.json
\cp -r ../ .


Usually, the build folder has following apk files

  • app-debug.apk
  • app-release-unsigned.apk
  • app-release.apk

Release apks are usually signed with a key and it would cause issues while installation. So we have to filter out the debug apk that we usually use for debugging and get it as the output apk. This involves simple file handling operations in Linux and a bit of git.

First of all, rename the apk file so that it will be different from other files.

# Rename apks with dev prefixes
mv app-debug.apk app-dev-debug.apk


Then add and commit them to a specific branch where we want the output from.

git add -A
git commit -am "Travis build pushed [development]"
git push origin apk --force --quiet> /dev/null


Once it is all done, you will have a branch created and updated with the apk files you have defined.


Figure 1: UI of pslab-android apk branch


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Setting up the Circle.CI config for SUSI Android

SUSI.AI Android app uses CircleCI to check for tests whenever a new PR is made. This is done to ensure that the app is consistent with the new changes and there is no problem adding that particular code change. CircleCI has now launched a v2 version of the .yml file and therefore to continue using CircleCI it is time to upgrade to v2 version of the script.

Circle.CI config version 1

Config file tells the CI on what commands to run to test the build, which will determine if the build is successful or failed like tests, lints etc and hooks commands to run if the tests pass, which environment to run the code in – python, java, android, etc.

Circle.CI published that 31, August 2018 is the last date upto when they will support the config version 1.0, therefore it Circle.CI was updated to version 2.0.

The version 2.0 has an updated syntax of the script and previous script was modified so that it could provide the configuration for the CI builds.

The updated script is shown below :

version: 2
  working_directory: ~/code
    – image: circleci/android:api-27-alpha
    JVM_OPTS: -Xmx3200m
    – checkout
    – restore_cache:
        key: jars-{{ checksum “build.gradle” }}-{{ checksum  “app/build.gradle” }}
    – run:
        name: Download Dependencies
        command: ./gradlew androidDependencies
    – save_cache:
          – ~/.gradle
        key: jars-{{ checksum “build.gradle” }}-{{ checksum  “app/build.gradle” }}
    – run:
        name: lint check
        command: ./gradlew lint
    – run:
        name: Run Tests
        command: ./gradlew build
    – run:
          bash exec/
          bash exec/
    – store_artifacts:
        path: app/build/reports
        destination: reports
    – store_artifacts:
        path: app/build/outputs
        destination: outputs
    – store_test_results:
        path: app/build/test-results

Few checks such as the connectedCheck, which were required for the UI testing, are not included in this script and instead an approach towards the increasing number of unit tests is followed. The reason being, implementing UI tests is a hard task for apps which have no constant designs and have constantly changing specifications. Since the architecture used is MVP, so on moving all logic to presenter components there won’t be a need of most UI tests at all. This problem with UI tests will further increase in future. Therefore, moving in the direction of increasing unit tests is better because they are both easy, small and quick to code and run and the degree of dependence on flaky UI tests also decreases.

If the view is implementing small sections of display logic, just verifying that the presenter calls those is enough to guarantee that the UI is going to work.

The command in the previous config such as

./gradlew connectedCheck

was removed and instead ./gradlew build was added to start the unit tests instead, also due to the updated gradle dependencies, changes were made to the apk uploading commands and also changes were performed in the file.

bash exec/
chmod +x exec/

In the above code, lines concerned with can be combined and the resultant command was written as :

bash exec/

The script was configured and the latest build tools were added to make the script work.


Continuous Integration – Martin Fowler:

Circle CI version 2.0 for android :

Circle CI configuration reference :


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Deployment terms in Open Event Frontend

In Open Event Frontend, once a pull request is opened, we see some tests running on for the specific pull request like ‘Codacy’, ‘Codecov’, ‘Travis’, etc. New contributors eventually get confused what the tests are about. So this blog would be a walkthrough to these terms that we use and what they mean about the PR.

Travis: Everytime you make a pull request, you will see this test running and in some time giving the output whether the test passed or failed. Travis is the continuous integration test that we are using to test that the changes that the pull request you proposed does not break any other things. Sometimes you will see the following message which indicates that your changes is breaking something else which is not intended.

Thus, by looking at the Travis logs, you can see where the changes proposed in the pull request are breaking things. Thus, you can go ahead and correct the code and push again to run the Travis build until it passes.

Codacy: Codacy is being used to check the code style, duplication, complexity and coverage, etc. When you create a pull request or update the pull request, this test runs which checks whether the code followed certain style guide or if there is duplication in code, etc. For instance let’s say if your code has a html page in which a tag has an attribute which is left undefined. Then codacy will be throwing error failing the tests. Thus you need to see the logs and go correct the bug in code. The following message shows that the codacy test has passed.


Codecov is a code coverage test which indicates how much of the code change that is proposed in the pull request is actually executed. Consider out of the 100 lines of code that you wrote, only 80 lines is being actually executed and rest is not, then the code coverage decreases. The following indicates the codecov report.

Thus, it can be seen that which files are affected by what percent.


The surge link is nothing but the deployment link of the changes in your pull request.

Thus, checking the link manually, we can test the behavior of the app in terms of UI/UX or the other features that the pull request adds.




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Continuous Integration and Automated Testing for Engelsystem

Every software development group tests its products, yet delivered software always has defects. Test engineers strive to catch them before the product is released but they always creep in and they often reappear, even with the best manual testing processes. Using automated testing is the best way to increase the effectiveness, efficiency and coverage of your software testing.

Manual software testing is performed by a human sitting in front of a computer carefully going through application screens, trying various usage and input combinations, comparing the results to the expected behavior and recording their observations. Manual tests are repeated often during development cycles for source code changes and other situations like multiple operating environments and hardware configurations.

Continuous integration (CI) has emerged as one of the most efficient ways to develop code. But testing has not always been a major part of the CI conversation.

In some respects, that’s not surprising. Traditionally, CI has been all about speeding up the coding, building, and release process. Instead of having each programmer write code separately, integrate it manually, and then wait until the next daily or weekly build to see if the changes broke anything, CI lets developers code and compile on a virtually continuous basis. It also means developers and admins can work together seamlessly since the programming and build processes are always in sync.

Continuous Integration (CI) is a development practice that requires developers to integrate code into a shared repository several times a day. Each check-in is then verified by an automated build, allowing teams to detect problems early.

By integrating regularly, you can detect errors quickly, and locate them more easily.

Solve problems quickly

Because you’re integrating so frequently, there is significantly less back-tracking to discover where things went wrong, so you can spend more time building features.

Continuous Integration is cheap. Not continuously integrating is costly. If you don’t follow a continuous approach, you’ll have longer periods between integrations. This makes it exponentially more difficult to find and fix problems. Such integration problems can easily knock a project off-schedule, or cause it to fail altogether.

Continuous Integration brings multiple benefits to your organization:

  • Say goodbye to long and tense integrations
  • Increase visibility which enables greater communication
  • Catch issues fast and nip them in the bud
  • Spend less time debugging and more time adding features
  • Proceed with the confidence you’re building on a solid foundation
  • Stop waiting to find out if your code’s going to work
  • Reduce integration problems allowing you to deliver software more rapidly

“Continuous Integration doesn’t get rid of bugs, but it does make them dramatically easier to find and remove.”

– Martin Fowler, Chief Scientist, ThoughtWorks

Continuous Integration is backed by several important principles and practices.

Practices in Continuous Integration:

  • Maintain a single source repository
  • Automate the build
  • Make your build self-testing
  • Every commit should build on an integration machine
  • Keep the build fast
  • Test in a clone of the production environment
  • Make it easy for anyone to get the latest executable
  • Everyone can see what’s happening
  • Automate deployment

How to do Continuous Integration:

  • Developers check out code into their private workspaces.
  • When done, commit the changes to the repository.
  • The CI server monitors the repository and checks out changes when they occur.
  • The CI server builds the system and runs unit and integration tests.
  • The CI server releases deployable artifacts for testing.
  • The CI server assigns a build label to the version of the code it just built.
  • The CI server informs the team of the successful build.
  • If the build or tests fail, the CI server alerts the team.
  • The team fixes the issue at the earliest opportunity.
  • Continue to continually integrate and test throughout the project.

The CI implemented in Engelsystem are as follows:

  • Travis-CITravis CI is a hosted, distributed continuous integration service used to build and test software projects hosted on GitHub. It is integrated using the .travis.yml file in the root folder.
    language: php
    - '5.4'
    - '5.5'
    - '5.6'
    - '7.0'
    script: cd test && phpunit
  • Nitpick-CI:Automatic comments on PSR-2 violations in one click, so your team can focus on better code review. It requires one click for integratting with the repository.
  • Circle-CI: CircleCI was founded in 2011 with the mission of giving every developer state-of-the-art automated testing and continuous integration tools. It is integrated using a circle.yml file in the root folder of the repository.
    version: 5.4.5
    branch: master
    owner: fossasia
    - ./
    - curl -s | php
    - php composer.phar install -n
    - sed -i 's/^;//' ~/.phpenv/versions/$(phpenv global)/etc/conf.d/xdebug.ini
    - php test/
    - bash <(curl -s
  • Codacy: Check code style, security, duplication, complexity and coverage on every change while tracking code quality throughout your sprints.

Development: Issues/Bugs:

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