As shown in the diagram above, self-healing test automation works to handle these changes. During script execution, if one of the object properties used fails due to a change in the application under test, the automation framework will scrape the new application under test (DOM extractor) at runtime and try to find an alternate element for the execution to proceed.

The self-healing algorithm uses information stored in a database that maintains all of the historical object properties based on historical test runs. It then uses similarity scoring algorithms to evaluate how alike each property is between the old objects and the available objects on the page. Each property associated with that object is then given a confidence score and depending on the threshold defined by the automation engineer, the self-healing engine will decide to proceed with self-healing or not. At the end of test suite execution, the reports generated will also reflect this and inform the test engineers about the self-healed test cases.

If required, this self-healing model can further be augmented with technologies like natural language processing (NLP) and machine learning (ML) techniques to dynamically adapt testing to changes in an application’s user interface (UI) or environments.

What are the benefits of self-healing test automation?
There’s no denying the benefits that self-healing automation can offer. These techniques will change the overall approach to test automation. With reduced test flakiness, automation engineers can now spend their time on new script development instead of being bogged down by script maintenance.

Self-automation also reduces the number of failed tests that automation engineers have to deal with, therefore reducing the time and efforts on the part of the automation team to debug those failures. More importantly, there are fewer breaks in the constant cycle of continuous integration and testing due to application change.

With the added automation to self-heal tests, the “test lifecycle automation” is positioned to be one of the main disruptive innovations changing the way testing is performed in the coming decade.

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