Test automation has evolved. From being script-based and then model-based, it is fast-becoming AI-based. AI-powered testing helps identify any change in function and the test updates itself to avoid failure during execution.
This nimbleness is a result of natural language processing (NLP) and machine learning, which enable scripts to learn and adapt.
What is self-healing Test automation?
Automation testing services provide higher testing efficiency, a competitive advantage to organizations, and other key benefits, but those are somewhat offset by Agile and DevOps, and the fast, frequent changes to test scripts which may cause Test automation to stop working.
Those drawbacks are overcome through self-healing Test automation.
It is a testing mechanism which detects object changes in the product and intuitively updates with new attributes to ensure test cases are functional.
Self-healing Test automation tools not only help reduce downtime and improve the speed of development but testing teams and QA services can also achieve greater efficiency by creating basic automation scripts for multiple applications.
Importance of self-healing
Self-healing is essential to build an efficient maintenance process for Test automation.
A well-planned, well-executed maintenance frees Testing teams of repetitive exercises and almost never-ending test script changes and provides the foundation for Test automation to perform to its full potential.
The mechanism helps reap the following benefits, too.
Fewer failed tests
Let’s say your Testing team decides to schedule the Test automation suite to run during the night to collect the results the next day, when you also plan to create new Test cases.
Next morning, you discover the automation Tests stopped working. You come to know that the user interface (UI) development team changed the ID of the textbox, the Test automation suite did not recognize it and hence the Test failed.
That the tests might fail is not much of a surprise to testers. At times, however, a change in an application’s UI could be the cause of a failed Test.
With self-healing Test automation, Tests are unlikely to fail because the AI in automation tools can heal the code by itself.
The smart recorder feature helps find a better path to detect the item which had its attribute updated by the UI development team, debugs the code itself and continues to run the code.
Prevent Test flakiness
A flaky Test makes it challenging for Testing teams to identify if or not their tests are stable.
“Nosuchelementexception” is one of several errors causing flakiness to the Test design, something which Testing teams don’t have much control of.
By ensuring the Test design is up to date with the application, Tests are less likely to fail during execution while execution flows more seamlessly too.
Save time and effort
Changes in the test code is relative to the changes made by the developer in the application.
For example, if a developer has changed the ID or Class attributes on a webpage, the corresponding changes must be made in the Test script, too. The sticking point is this: if changes in the application are aplenty, testers would need to make as many changes in the Test script and run them.
Self-healing mechanism saves Testing teams time and effort by detecting the change and updating the test cases for every change made in the user interface.
It not only saves time and effort for Agile and development teams, but significantly reduces cost, too.
How to approach self-healing
Self-healing mechanism benefits users, developers and testers alike, but it’s vital to understand the building blocks of the system.
Knowing the application inside-out is one of the core principles. Easy as it is to activate self-healing mechanism in an automation framework, plenty of time could be lost if the production problems in an application aren’t identified earlier.
To overcome this issue, automated alerts could be set up to identify the most common errors.
Prevention better than cure
That’s right! While it may be nice to automatically recover from error cases, preventing them beforehand is always the best option. It’s essential to identify the key problems and address their root causes.
So, is self-healing Test automation the next big thing in QA?
As a technology, it is one of the innovations that help meet the demands of digital testing as digital disruption forces organizations to innovate quickly and efficiently.
Self-healing Test automation is valuable in multiple ways, primary of which is it helps testers from having to continuously update Test cases as applications evolve.
Software testing is and will continue to evolve with artificial intelligence automating tasks that have traditionally required human cognition and involve self-learning.
However, smart testing technologies without AI’s assistance will continue to play a key role in software testing.
Advancements such as automated test portfolio optimization, self-adjusting risk assessment, automated defect diagnosis, smart environment provisioning and more are expected to be critical in QA in the next few years.