09 Jun At the Cutting Edge: Trends in AI-driven QA testing
In a world where technology is advancing week by week, it’s crucial to stay on top of the latest trends in the quality assurance (QA) arena. Today, we’ll explore how artificial intelligence (AI) is transforming the QA landscape and its impact on the industry.
AI has established itself as a powerful tool in a variety of fields, and quality assurance is no exception. Thanks to the implementation of intelligent algorithms and machine learning, QA testing becomes more efficient, enabling early detection of problems and optimizing overall software quality.
Even before the recent explosion in use cases for artificial intelligence, Brown and Sharma (2020) in their article in “Software Quality Professional” , analyzed the growing importance of AI in the QA domain. The authors highlighted that this technology not only boosts testing efficiency, but also lowers costs and streamlines the development process. The article presents case studies where AI had already been successfully used in software quality assurance, addressing challenges such as identifying defects, improving test coverage and reducing the time and effort spent on manual testing.
On the other hand, a clear example of this technology used today is the case of test.ai. Founded by former Google and Microsoft engineers, it provides testing services for web applications . The technology used applies algorithms that are able to observe the interface and to understand everything that is displayed on the screen and evaluate the workflows of the application as a human would. However, because the bots can learn and understand the entire application at superhuman speed, they can perform tests on multiple environments or operating systems, different devices and screen sizes, all simultaneously and continuously. In addition, machine learning allows bots to become smarter with each iteration and discover aspects that humans may not have considered.
Given this reality, it is imperative that quality assurance professionals become familiar with the applications of AI in their field and be willing to adapt to new methodologies and technologies as they emerge. In this way, they will be able to stay ahead of the curve in an increasingly competitive and dynamic environment.
In this series of articles, we will continue to explore how the latest trends in QA are impacting the industry, with the goal of learning and adopting these advances for the benefit of our own careers and that of our companies. You are cordially invited to join this adventure in which we will discover together the future of quality assurance “At the cutting edge”.
Brown, N., & Sharma, P. (2020). The Growing Importance of Artificial Intelligence in Software
Quality Assurance. Software Quality Professional, 22(4), 31-43.
Sitio web de test.ai. https://test.ai/all-products