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How does AI self-healing test automation shape the future of test automation?

How does AI self-healing test automation shape the future of test automation

Digitalization has transformed the way most businesses function.  Business processes and workflows have moved away from manual controls. While digital integration has made businesses more efficient, it has also made software development a cornerstone of every successful business model. In a market where accelerated delivery of quality software  products is critical, test automation has proven to be a core driver, enabling software companies to develop and test exhaustively in a relatively short time. But what happens when, in an increasingly agile world, the pace of development quickly outruns the speed of script maintenance? With constant UI changes, most test scripts fail to perform as intended, forcing testers to focus on updating, debugging, fixing, and maintaining the scripts. This process can quickly become a roadblock and significantly slow down test automation efforts. Due to the constant test maintenance requirements, not only do companies need to allocate more time, money, and resources to testing and test automation, but they also start seeing considerably less ROI.

This is where self-healing test automation steps in. It automatically identifies object changes and updates the user accordingly, reducing the need for constant maintenance by a wide margin.

This blog will discuss self-healing test automation, its benefits, and how it works.

What is self-healing test automation?

Before we delve into self-healing automation scripts, let’s first understand how testing currently works. Conventional test automation tools use application models to define application components, objects, and their attributes. These static definitions are then used to identify and operate on components. Every time the application is, the components and their parameters also change. But conventional test scripts aren’t built to work with these changes. They only function with static definitions; any component modifications will break the scripts. This is referred to as the fragility of test scripts.

Whenever a fragile script breaks, an automation engineer must step in, identify the issue, and fix the script. The engineer needs to inspect the object to find new property values, update the script or object repository, and rerun the test. The entire process of manual object identification maintenance and troubleshooting can take up to 15 minutes per occurrence.

Fifteen minutes in itself doesn’t sound like a lot. But the numbers start adding up when project size, application maturity, and development stage are considered. On average, one application deployment per week can encounter about 35 object changes. At 15 minutes per occurrence, it takes nearly nine hours to perform script maintenance.

Self-healing is a mechanism that employs artificial intelligence, machine learning, and natural language processing to dynamically adapt the script to any changes made in the application UI.

How does self-healing test automation work?

The primary reason behind the breaking of scripts is changes in the objects. Objects are items in the UI of the AUT, such as buttons and text boxes. Each object has specific properties that help the scripts identify them. Only then can the script interact with the object and run the test. Trouble ensues when these properties change, and a static script fails to identify the object, thus breaks down.

Here’s where the AI-powered self-healing mechanism helps. It can detect objects even after their properties have been altered, effectively negating any need to change the script. Here’s how this happens.

Upon scanning for objects and detecting changes to object parameters, instead of failing, it automatically edits the internal script to fit the new object properties. The self-healing feature scrapes, evaluates, chooses, and edits the script as required within a fraction of a second. Moreover, self-healing test automation can also sense the user actions and capture them to be reviewed later by the tester.

It drastically reduces testing downtime, improves ROI, adds another layer of automation to reduce manual intervention even further, and fits perfectly into an agile and DevOps methodology.

What are the benefits of self-healing testing?

The implications of self-healing can be wide-ranging. Here’s how it can change conventional test automation and make it better.

  • Building simpler, more streamlined automation frameworks

While writing test scripts, conventionally, it’s not advised to use absolute XPaths or outer HTML to identify objects. These are considered fragile methods and tend to break easily. But with self-healing, XPaths can be used to build scripts. This can standardize and simplify the framework, making script writing easier.

You can also avoid writing extremely specific scripts that fail with every new change and instead write more generic ones that can work with thousands of applications.

As we explore self-healing test automation further, many more avenues of improvement will open up.

  • Better testing efficiency

As mentioned above, test script maintenance alone can take up to 9 hours per week – an entire working day for an automation engineer. Not only do you need to pay for the extra hours, but you also end up with an inflated testing cycle that takes much longer to finish than anticipated.

Self-healing eliminates much of this extra maintenance time by automating object identification and subsequent script changes.

  • Fewer failed and flaky tests

Fragile tests fail as soon as they encounter an unrecognizable object. Flaky test designs are unreliable and contribute to the instability of the test automation framework. With self-healing, testers can create a limited set of tests, run them, identify the stable ones easily, and continue to work with them. This leads to a more stable testing framework.

  • Increase test coverage

Test coverage is a key metric that helps you track the accuracy of your testing efforts and the quality of your resulting software. While test automation helps increase test coverage, self-healing can further boost that number by another 5% to 10%. It does this by eliminating redundant code and increasing testing efficiency.

Test automation requires the self-healing feature to help it keep up with a dynamic product development market and evolving consumer mindset. It’s important to choose self-healing test automation tools to accelerate the pace of delivery, realize testing ROI, and reduce the time and effort spent on script maintenance. Avo Assure is one such testing solution.

Avo Assure is a robust, no-code, heterogenous, platform-agnostic test automation solution. with an advanced capability known as the upgrade analyzer. Instead of manually analyzing the updated line of code, Avo Assure automatically identifies the code change on the go and tests just that, saving time, effort, and resources. It also offers CI/CD integration, in-sprint automation, and elastic execution grid to accelerate the testing process further. With its intuitive reporting and UI, along with comprehensive support for over 150 technologies, Avo Assure is the ideal solution for fast-paced software development companies.

Avo Assure helped CNA Insurance, the US’s seventh largest property and casualty insurer, adopt an agile development approach, reduce testing time, and save money. CNA condensed testing cycles by 50%-60% and expedited execution time from 250 test cases/day/application to 627 test cases/day/application.

To learn more about self-healing and how it can help you build better software products at a faster clip, book a demo with us today.

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