Introduce to AI Is Transforming Automation Testing
Artificial intelligence has powered up many software tools – from software development IDEs, human resources management software, software automation testing tools, and more!
Thanks to AI, the test automation software tools are more competent “decision-makers” during test creation, test execution, test maintenance, and even in the reporting stages. Over time, they have reduced the time and effort required for testing.
This article will focus on the impact made by AI on software test automation tools. We’ve listed some popular tools below as well!
AI-powered features you can expect in advanced test automation tools
Self-healing artificial intelligence – automate with ease.
The self-healing AI feature powering up several advanced automation testing tools helps ease up the test automation developer’s maintenance effort.
In the background, the self-healing AI capability works by first identifying the product code changes, and it automatically updates the automation code change. This is all done without human intervention.
Developers find this particularly useful in applications that have new session IDs associated with the UI widgets. For example, this is so with SAP applications.
Example – TestProject, Parasoft
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No-code, or less-code automation testing platforms – a true ally of Agile, DevOps
AI powers up the scriptless and less-code test automation platforms as well. These platforms require less programming, or no programming, code to build test scripts.
Unlike the coding method, these scriptless tools offer no-code visual methods of building test automation – using features like drag and drop actions. Therefore, non-technical people have joined the test automation bandwagon.
If your project is working in the DevOps or Agile model, your team is already performing tasks such that high-quality products are delivered quickly to the customer. The good news is that these platforms are a great choice. It is easy and quick to develop scripts using them, amplifying the overall test development speed!
Because of these platforms, more and more people are joining the test automation world. One doesn’t need to learn any programming language to contribute to a test automation framework.
Example – WorkSoft, TestCraft
Automatic test creation – reduced reliance on manual test development and manual testing!
The tools with these features help generate test scripts automatically using the Spidering AI. It crawls the website or application during test creation and learns step-by-step the application flows to power up the automatic test generation process!
With such features in place, it will reduce the reliance on manual testing or manual testers required to develop manual test cases.
Example – ReTest
Test record and playback performed – automate smartly.
Using AI, several software test automation tools implement the test recorder feature.
Using this feature, and as the QA engineer manually performs the user actions associated with the UI as they would while manual testing (such as the clicks, selections, or inputs), the tool in the background records the steps.
The recorded test scripts are subsequently a part of the test automation test suite. Once the recording is completed, the test scripts can be played back to be utilized to test the application in an automated fashion.
Example – TestProject’s Smart WebRecorder and MobileRecorder.
Cross-Browser, cross-device, and cross-platform automation testing.
For many Web automation projects, test coverage is vital. They aim to focus on as many browsers as possible. Cross-browser, cross-device or cross-platform testing is a challenge if performed using manual testing considering the plethora of attributes to be covered.
With the Cloud platforms’ help, tools powered by AI enable simulators, emulators, real device setups, and QA projects to use these platforms to perform cross-browser, cross-platform tests with ease. It allows you to choose from a wide choice of browsers and platforms as well.
Geo-location automation tools
Several e-Commerce organizations require verification that their application works across various locations in the world with AI and Cloud support.
With this utility, the website can be virtually tested from any location you require to be tested. In the tool, you just need to mention the geographical area as the input, and it publishes the result accordingly.
Example – BrowserStack.
Automatic bug discovery
These tools understand the product code, framework, and user flows. As time goes by, it improves from what it learns. All of this is possible due to AI and ML.
Accordingly, it anticipates plausible bugs and makes suggestions. As per the results, the QA engineer can decide to open the defect or not.
It helps detect dead hyperlinks, invalid web pages, etc.
Example – ReTest
Automatic test prioritization
At its core, this utility works similarly to the automatic bug discovery feature. It helps prioritize the test cases, as per several factors including user flows, the business rules input by the business analysts, etc.
The automatic test report analysis
The tools with this feature ensure that their AI/ML algorithm helps analyze the test results without human intervention.
It works by crawling through the historical data, comprehending it, making comparisons, and providing the associated test report analysis feedback.
Example – ReportPortal.io
Visual regression tests
Tools that offer this feature ensure that pixel-based comparisons are performed. In-depth visual tests are also performed involving CSS attributes of the web page elements.
Example – ReCheck
Examples of smart AI-enabled test automation tools
TestProject automation tool
This AI-enabled tool is free to use! It is an end-to-end test automation tool offering smart AI features such as the Smart Test Recorder for mobile tests and web tests. The automatic step recorder records every move by the test automation developer and builds the test scripts.
The tool’s self-healing AI capabilities are robust too, due to which the maintenance phase is a breeze!
ReTest automation tool
The AI-powered tool helps generate tests automatically. The re-check web feature allows the detection of functional and visual differences without human intervention. The AI system can be custom-trained while providing minimal Selenium tests from which to learn. It also holds the automatic bug detection feature.
Launchable automation tool
This AI-enabled test tool uses AI and ML algorithms to execute tests without modifying the existing project pipeline. It generates a dynamic subset of test scripts to be completed, as per any production code changes. It also helps identify the right tests as per the code changes.
SauceLabs automation tool
This AI-powered continuous testing solution tool holds the Failure Analysis feature to identify a test case’s common reasons to fail. It thus simplifies the root cause analysis stage whenever defects occur by analyzing failure patterns.
The tool provides a Cloud-based testing platform for performing live and automated continuous tests for web-based and mobile-based applications.
Conclusion
We are lucky that advanced smart test automation tools at our disposal can help our test automation development efforts. They are not only trendy, but they also help build test scripts quickly and efficiently. Tools such as TestProject and Parasoft are a few of those that have robust AI implementations.
Leveraging tools that use AI has helped build profits for software development companies in a short time. Not to mention that the customer is happy too – thanks to the fact that they receive a well-tested and high-quality product.
