With AI-driven test automation, test scripts can be automatically updated as systems change, which is one of its most appealing features.
This is particularly true for businesses dealing with the ongoing burden of maintaining test automation scripts. To address this issue, many top test tool vendors claim to have AI-driven test automation solutions, but it’s important to know what’s true and what isn’t.
In mobile and web-based testing, AI-driven test automation can now learn an application and dynamically adapt the automated tests as the application changes. This is achieved by recognizing UI elements and controls based on visual cues through the use of machine learning (ML) and intelligent object detection.
For instance, the label name, position, or color of a control on the screen or the type of control (input, button, dropdown, table, etc.). This strategy uses technology that is comparable to Tesla’s self-driving cars, which can adjust to shifting road conditions.
Once you’ve determined the technology and framework used for your application under test, deciding on which test tool to use becomes problematic. Making mobile testing even more difficult is the plethora of tools that must be used, many of which do not provide you with everything you require.
In addition, there are different devices with different capabilities, operating systems, and features, making mobile app automation challenges.There is also a distinction to be made between web application automation and mobile app automation.
You have a lot more time between developing a web application, the tools that came about to automate that, and the time it takes to actually create those tools specifically for any difficulties or problems arising from the web-based application.
The flakiness of web-based applications still exists for mobile applications when it comes to the automation of mobile applications. However, the technical identifiers are erratic when you try to interact with that element.
In addition, compared to web application automation, the tooling for mobile application automation has not had the same amount of time to develop.
Mobile automation is still in its infancy regarding tools and frameworks that can help you maintain your scripts and deal with flakiness.
Table of Contents
What Can You Do Before You Start Mobile Testing?
- Knowledge of your application
- Know what you need.
- The application’s essential elements and how they work
- requires a framework
- Verify the operation of your tests.
- Run a test at a respectable pace
- Aim for device fragmentation native frameworks that only function on one platform but complete tests.
Is Codeless Mobile App Testing The Way Forward?
As you can see, mobile testing is still in its early stages, and numerous scripting problems can make your test unstable.
As a result, many frameworks are being developed to address problems like the Appium Xpath error.
Going codeless and utilizing machine learning could be the solution.For instance, if a locator is not advised or cannot be found at runtime, the ML code may search for another identifier.
Artificial intelligence has a significant role to play in this area.The latest technological development we’re witnessing is the commercialization of artificial intelligence.
Consequently, this explains why you see more AI-driven automation solutions without code or script. With some modern frameworks, you still need to manually combine a few test steps before using AI enhancements to make it all work, which can lead to more inconsistent results.
Because of this product, like testgrid, which is genuinely scriptless and based on machine learning algorithms, exemplifies true AI-driven automation.
Is AI Automation Everything?
Although recent advancements in AI-driven test automation appear promising, there is still a lot of hype, so a healthy dose of skepticism is necessary.
Tricentis claims that even though Vision AI has been “trained” on over 12 million examples and over 9 million controls, it will still make mistakes, especially in situations it has never encountered.
The vendor claims that the product learns from its errors in the same way a human would, but it is still unclear how this learning affects the caliber of software delivery.
These are the lack of understanding of the source of truth, which is typically found in test cases, scant documentation, or in the minds of product owners, stakeholders, developers, and end users.
Lack of end-user empathy, which enables human testers to emotionally react to difficult-to-understand flows, sluggish loading times, awkward layouts, etc., is another very serious inefficiency.
AI-built test scripts may also make mistakes that result in false positives or halt the execution of tests. False positives, script mistakes, and bloated test suites are still potential problems that require attention.
It makes sense that people are excited about this new technology and its potential, given that test and development teams are expected to maintain quality while operating within tight financial constraints.
As systems become more complex and release cycle times shorten, it is evident that AI-driven test automation will be essential to assisting organizations in maintaining quality while operating quickly.
AI-driven test automation’s use is likely to grow as the technology develops and its economic advantages become more apparent. Depending on your specific use cases, this technology can boost efficiency and speed; however, more development is still needed before these products can fully realize their potential.
It’s also crucial to remember that AI-driven test automation does not replace your test automation team; instead, it releases them from the burden of automating simple tasks and allows them to concentrate on more intricate end-to-end business processes and backend validation. However, it raises the intriguing question of using AI to test AI.
Conclusion
In conclusion, we must pay attention to mobile app testing as technology develops and offers more advantages.
A really powerful artificial intelligence engine is enhancing mobile app testing, another innovation in and of itself.
According to Shannon, this is constantly being improved with each new release to ensure that it has the highest level of confidence, failures, passes, and everything else so that we can let our users know they’re in good hands when using TestGrid.
To know more about TestGrid, click here.
