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Software testing has evolved a lot since the time when the waterfall model was used. All the work was done in a sequential manner and only after the development phase was complete the testers used to test the product. Testers used to find bugs but a lot of time and energy was wasted in the process to rebuild and code again.

Now companies are using an Agile model where the main goal is to find the bugs in continuous development, fix them quickly and release the app faster. There is a need to improve the automated testing process to complement the manual testing. More emphasis has been given to CI, CD, and DevOps to make the software development effective.

There has been a considerable change in the functioning of testing tools and test automation frameworks. The most important change is the introduction of AI in a test automation strategy.

According to G2Crowd, AI-powered bots are expected to cut business cost by $8 billion by 2022. Testing bots are already empowering automation testing and will play a major role in reducing the time and effort spent in mobile app testing.

Let’s have a look at how AI is breaking new ground for test automation.

1. Running automated tests that matter

It’s not a good strategy to run your entire test suite due to a very small change in your app that you couldn’t trace. You are probably already generating a lot of data from your test runs if you are doing continuous integration. But it will take a lot of time to go through the data and search for common patterns. So you need to know if you make a small change in code then what is the minimum number of test you need to run to figure out if the change is needed or not.

2. Reducing maintenance and eliminating flaky test

We can run several automated tests on a daily basis to ensure the functionalities of the app are still stable. Although, if we find out that half of this test failed. In that case, we would need to spend a lot of time to troubleshoot the failures and investigate the cause. Then there is a need to find ways to fix the failures and then work on the changes.

software maintainance

Using AI we can avoid issues and start detecting issues in the test before they even occur. So instead of reacting to it, we can proactively fix tests. AI can figure out which tests are stable or flaky based on the number of test runs and it can tell us what test needs to be modified to ensure test runs are stable. AI can also handle test running on different resolutions and can optimize the wait time used in the test to wait for the page to load.

3. Dependencies on other modules

Writing a test for systems having dependencies on other modules is also a challenge. AI can help us to mock responses from a database or server. The AI can start recording server responses once we have written the test and have run them for a period of time. So the next time we run the test it will access the stored responses and will continue to run without any obstacles. This will speed up the process as the delay in response is eliminated and the server or physical database is no more needed.

4. Learning from production data

Real user data can be used to create an automated test and with the help of AI, we can observe and learn how the customer is using our product. We can identify common actions such as search option, using filters, login/logout, etc and compile them into reusable components. These components can be used for our test as well. Therefore, we have an actual test written by AI based on the real data along with the reusable components.

5. Easy execution of tests and speeding up the release

In automation testing, the time and effort it takes to write and execute a test is a major challenge due to the complexity of the test automation tools, app, and programing language used. To mitigate these problems AI-based tools are being used. The use of dynamic locators and reusable components has made it possible to write and execute a test in hours which earlier used to take a week.

Conclusion

The DevOps theory says test early, test often, but this puts a lot of responsibility on the testing team. Also, it’s not feasible for testing teams to spend time to do exploratory testing manually for each new release. AI-based tools can perform codeless automation testing which will save us time and resources and give the testers some space to breathe.

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Do you know why Google has selected Gradle as the build system for Android Studio? Many Android developers work in a heterogeneous environment with different technology stacks. Gradle solves some of the hardest problems faced by the developers like how to automate the testing of apps and how to manage dependencies and variations that allow professional developers to develop variations of their app with one click. This is why pCloudy came up with a new update where you can now run Espresso with Gradle on pCloudy devices. Let’s get a brief introduction about Espresso and Gradle before we learn how to run Espresso with Gradle on pCloudy devices.
 
Espresso is a testing framework for Android which automatically synchronizes your test actions with the UI of your app. It also let the test wait until all the background activities have finished.
 
Gradle is an open source advanced build tool that allows seamless execution of tasks. It uses domain specific language and it is based on Groovy and Kotlin. It is a plugin based system so if you want to automate the task of building some package from sources then you can write the complete plugging in Java and share it with the world.
 
Gradle allows efficient and repeatable use of espresso and Test Orchestrator which allows automated yet fine-tuned control of the way you run your test. You can decide which specific test suites to be run to distribute the test cases across different devices. It is preferred by developers as it allows deep unit and functional testing rigs.
 

Power up your DevOps with Espresso and Gradle on pCloudy

You would be running Espresso on your machine using Android Studio and Gradle. However, the test would be running on pCloudy device. There is a pCloudy Espresso script that is provided by us and you need to put that espresso script in the workspace of the project. Along with the Gradle script, you will also get a config file. The gradle script will read input parameters from this config file.
 
Then you run Gradle to invoke the script which will upload your Application APK, test APK and other APK files to pCloudy. It would acquire a device to run your test on, it would execute those tests it will report back the status of what is happening into the Android Studio. After the test cases are run you can see the detailed reports and after that gradle script will release the device for other users to use.
 
There is a one-time setup that you need to do to place the gradle script in the workspace and you need to fill in the configuration file. So when you run the gradle script it will complete all the task for you and generate the report.
 

Steps to run Espresso with Gradle on pcloudy

 
1. Download the espresso starter pack from here and Unzip it
2. You will find three files,
a. pCloudy_Espresso.jar
b. Config.properties
c. build.gradle.SAMPLE
(This is a sample build.gradle that shows how to change your build.gradle to add the pCloudy Espresso jar.)
3. Copy the contents of the file build.gradle.Sample to the build.gradle file of your Android Application to register the new Gradle task and update as appropriate (see the image below)
 
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4. Place the config.properties file in your android workspace in the same directory as your build.gradle file.
 
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5. Update the config.properties file as guided in the comments in the file.

6. In your Android workspace run the command by typing the name of the gradle task as below.
 
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7. Once the test execution is complete you will get a URL of the test execution report. Some fields in the report are empty right now. We will fix them in subsequent phases.
 
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The use of gradle has made it easier to run Espresso test on pCloudy devices. We can just use the configuration file and easily run the test scripts on pCloudy devices. This will save time and effort as it further simplifies the app testing process in pCloudy.
 
You can watch our webinar for more information.

 
Related Articles:

  • How to Run Espresso Test on Remote Devices
  • Appium vs Espresso: The Most Popular Automation Testing Framework in 2019
  • Run Espresso on pCloudy using pCoudy Utility
  • Automated Testing Using Espresso
  • Espresso with pCloudy.com