How would you describe your current testing processes? Are they manual, automated or a combination of both? Over the past few years, more and more organizations have added test automation to the mix, and it’s easy to see why. Adil Mohammed, Founder and CEO of Virtuoso, shares seven key benefits of AI-powered test automation.
Manual testing can take hours and complicate ongoing development unless you have access to unlimited resources. Accuracy is also an issue – testers are only human and can easily miss small changes. Software testing is prone to error in organizations that rely solely on manual testing and often presents a bottleneck.
The limits of test automation
Many companies are now combining automation with manual testing to speed up the process. Teams can complete test cycles faster by automating repeated test cases, leaving the manual limited to defining the case, reviewing the results, and performing a final QA overview. ). However, test automation is never a case of “set and forget”. Each test environment must be set up manually, requiring significant resources upfront. Then, if the tests encounter dynamic or unusual data, issues may arise that require human resolution. The speed benefits of automation can therefore be negated by the time required to investigate and resolve any issues that arise.
Testing user interfaces (UIs) using a coded automation approach presents other challenges. For example, the test may not detect a button that has changed color or overlapping UI elements. Although automation has greatly improved the process, coded testing still relies on complex setup, consistent maintenance, and a team of human testers to check and fix. There is also a limit to the number of tests that can be run, with this number decreasing even further when the tests need to run across multiple browsers.
Learn more: Why You Should Exercise Caution When Using AI in Code Development
Go beyond traditional test automation
As technology develops, we see more and more ways that testing processes can accelerate business growth. For example, by combining robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), and natural language programming (NLP), companies can perform higher quality testing more quickly and with fewer resources. I have collected some of the concrete benefits of these new developments below.
Key Benefits of Cloud-Based, AI-Based Intelligent Test Automation
1. No-Code Testing Means Anyone Can Script
Recent developments have made no-code testing a real reality rather than a marketing promise that hasn’t delivered. For example, at Virtuoso, we combine AI with NLP to enable in-progress tests written in plain English, much like a manual test script. Our approach is unlike anything else on the market, and it is perhaps more accurate to call it Natural Language Scripting because it takes commands from a tester written in plain English and translates them into real code. The advantage of no-code testing is that it gives everyone on your team the power to generate tests, making the whole process more user-friendly and accessible. For example, NLP allows simple commands such as “click ‘add to bag'” to be translated by RPA, so the test software understands exactly what it needs to do.
2. Test faster, ship faster
No-code AI testing is significantly faster than manual testing or traditional automated solutions because testers save time by generating code. This allows companies to increase their ability to run tests and deploy faster. No-code tests can also run in parallel and across multiple browsers and devices, making them easy to scale. No-code testing technology can therefore accelerate time to market, which is essential in today’s competitive market.
3. Reduce costs
No-code software helps businesses reduce costs. Instead of hiring large teams to monitor and maintain automated tests, a small number of in-house specialists can easily set up smart tests to run. Additionally, cloud-based software is much more cost effective than on-premise software due to a lack of maintenance costs since the software owners perform the maintenance, not the users.
4. Improve accuracy
Manual testing is always prone to human error, and traditional test automation breaks down when it encounters dynamic data. Using an AI-based approach, you can easily test that the colors, sizes, and shapes of your elements are correct and in the right place. We call this visual regression testing, which dramatically increases the accuracy of your testing. It also works for functional testing – by using ML, testing understands how all the different elements are supposed to work and reduces test creation time. These features can save your teams hours of checking and fixing while simultaneously improving the accuracy and quality of your tests.
5. Test continuously
AI-driven testing fits into continuous integration/continuous delivery (CI/CD) and the software development lifecycle (SDLC). Organizations can define tests to not only run intelligently, but continuously. You can define conditions for your tests, for example, to trigger an action if a certain result occurs. And you can run multiple tests in parallel as often as needed to ensure your website is always bug-free and of the highest quality.
6. Perform (almost) zero maintenance
You unlock the power of self-healing testing by implementing AI-powered test automation. The technology considers all element IDs, so if a data point changes, then it has a pattern to compare and can correct itself. Basically, the test knows the difference between data that is supposed to change and a broken test.
7. Improve API testing
AI can also support end-to-end testing by recognizing relationships and patterns between the front-end interface and the back-end. Virtuoso’s functional API testing ensures that the two parts of a website are communicating properly, with AI flagging if any threads cross while exchanging information.
AI-powered automation delivers competitive advantage
At a time when rising inflation, soaring business costs and a tight labor market are putting unprecedented pressure on businesses, AI-powered test automation offers a golden opportunity to ship faster and improve quality. By increasing their test and development potential, companies can deploy faster and be first to market. This is a particular advantage for companies with fewer resources that cannot or do not want to hire large testing teams. With AI-powered automation, any organization can unlock unparalleled business value and secure competitive advantage.
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