Introduction

Mobile application automation testing is seeing incredible advances in technology due to applications of artificial intelligence, machine learning, predictive analytics, etc. thanks to the Industry 4.0-ready Mobile automation testing tools. These powerful tools have enabled mobile QA engineers to build high-quality automation scripts. 

This article details how artificial intelligence can help in resolving mobile test automation challenges, and examples of tools that you can use.

3 Major Challenges Faced in Mobile Application Testing

Mobile QA engineers need to be aware of 3 Major specific mobile app test challenges, namely –

• A massive number of combinations in testing perspectives.

A high number of people are using mobiles in their daily lives, more than ever before. As per research conducted in 2020, there are 3.5 billion smartphone users worldwide.  They are accessed in different dimensions, namely –

• • Geographic locations 
  • Different types of devices, OSs, browsers, etc.

Hence, while designing tests, the mobile application QA engineers need to incorporate several test perspectives, involving a high number of combinations. This is a considerable challenge.

•  Rapidly changing mobile application code and the associated tests. 

Unlike non-mobile applications, In the case of mobile apps, users are closer to mobile app development, as –

• • Users request a high number of features – it is easy to request one!
  • Users open defects quickly, for example, by mentioning issues in the mobile app reviews.

Accordingly, tests need to be updated or added. Imagine the number of test cases the QA engineer needs to build frequently concerning new features being introduced often. Also, due to the frequent changes happening in the mobile app as per the features or defects being opened by users, the testers need to be always ready when such frequent changes come in. They need to be literally on their toes!

• High possibility of mobile app uninstall rate in case users are unsatisfied.

As per research, 56 percent of the users uninstall mobile apps within the first seven days of installing them. Hence, the mobile app developers must build robust code, and the QA engineer tests them efficiently such that any user has excellent experience with the app starting from the moment it gets installed, so that they are always satisfied with it, and hence never uninstall the app.

5 Major Applications of AI/ML that Help Tackle the Mobile App Related Test Challenges

In this new era, a lot of test automation tools have incorporated AI / ML features that help the QA engineers to tackle the challenges faced in the mobile test arena. 

The best way to solve these issues is that the QA team needs to look for tools that make these features available. Tools like TestProject, CuriositySoftware, BrowserStack, Geoscreenshot, etc. are some examples that utilize some/all of these powerful features.

 Some useful features to look for in the tool are –

• Self-Healing Artificial Intelligence  – Automatic Test Maintenance and Debugging

Mobile test apps see a lot of change requests and feature requests throughout its lifecycle. Also, due to the high number of users using the apps, and the ease with which they share information regarding issues they faced using forums, review centres, etc., many defects are being opened directly by users.

Imagine a scenario wherein there is a change in the application, and the developer needs to inform the test team about the change made so that they can accordingly make their changes in the test automation code. But, is it realistic for the developer and tester to be always in sync in a highly changing/updating app like in the case of the mobile app development scenarios? 

Well, the self-healing feature helps in such cases. This feature allows for resolving this concern. In case there has been a change in the code, and the developer forgets to inform the QA engineer about this change for them to update the associated test code, there is no worry. 

This feature helps automatically fix the respective automation code and then continues to run the test automation without any error. With no human intervention, automatic test maintenance and debugging take place due to this feature.

• Spidering Artificial Intelligence  – Automatic Test Cases Creation

The Mobile app sees rapid changes due to the high number of change requests coming in by users. QA engineers need to keep adding new scripts accordingly. 

This is where spidering AI comes to the rescue –  these tools that contain this feature write scripts automatically for you. Just as a real spider crawls, it crawls the mobile web application/website. It then collects data concerning the aspects that require testing, be it screenshots, recording load times, etc. Accordingly, it designs user workflows and associated test cases, therefore.

For example, tools that hold this feature use test modellers that suit the requirement of mobile apps which rapidly change. It automatically maintains test cases, the associated test data, and automated tests as the test models vary.

• Smart Test Recorder, Mobile Screen Recorder – Smart and Adaptive to Frequent Changes

The mobile apps see a high number of changes and need to be tested across a variety of platforms, devices, resolutions, etc.  With this, there is a necessity that the test recorder is smart to adapt to the changes, using features like the self-healing feature. Apart from this, it should be smart to detect the variety of mobile devices that the app would be accessed. 

The mobile screen mirroring feature is also very useful. You could mirror the mobile screen onto the desktop. You can also choose amongst the many combinations of mobile devices that you can test from. Accordingly, the smart test recorders can record several objects’ details in the script as though being tested from the mobile of your choice, virtually.

1. Visual AI Test Support in a Wide Range of Cross-Device Tests

We know that web applications are accessed from several browsers on mobile devices. Now, maintaining a physical lab with all these browsers with the combination of being accessed from different mobiles is not realistic. This is where the intelligent cloud-enabled test automation tools come to your rescue.

Tools like these enable cross-browser testing using visual artificial intelligence for cross-browser testing that is fast, secure, and stable. The parallel test is also possible in these tools. One can perform tests round the clock, on a  high number of browsers and devices, virtually. 

• Geolocation Tests – Virtually Test from Anywhere in the World!

Mobile apps are accessed from everywhere in the world. With this, there is a necessity that we test this option virtually as if accessed from all plausible locations. The way the text as per the associated language is displayed, the locations’ currencies, etc. need to be tested if being displayed correctly. This is when Geolocation testing comes into the picture – with the help of AI. The QA Engineer can choose amongst the many locations listed and perform the tests as if being tested from the location of their choice.

Conclusion

Thanks to AI /ML, the Mobile test automation field has seen a lot of mechanical work being minimized, and several mobile app specific challenges being resolved.  QA engineers can now deliver products with high speed, and resiliency to sync with the rapid mobile application changes within a continuous delivery pipeline using AI/ML-powered tools. All these tools are easy to use, as well. 

While relying on the AI/ML features, the mobile test automation developers and QA engineers can meanwhile use the saved time in utilising the power of human cognitive intelligence on project tasks that AI/ML has not yet ramped up to!