Legacy testing processes are too slow and siloed to keep up with modern software delivery cycles. This article reveals why forward-thinking organizations are redesigning their approach to testing. Read this article to gain practical insight into what's driving the shift and how the right approach can accelerate product launches while reducing risk. When you're ready, contact Metisc to discuss next steps.
What is the shift from Continuous Automation Testing to Autonomous Testing?
The software testing landscape is transitioning from Continuous Automation Testing (CAT) platforms, which have traditionally streamlined testing processes, to Autonomous Testing platforms. This shift is driven by the need to address challenges posed by AI-driven development and the rapid pace of software delivery. Autonomous Testing platforms leverage generative AI and advanced AI tools, known as tester TuringBots, to enhance productivity and adapt to the complexities of modern software applications.
What challenges do current testing platforms face?
Continuous Automation Testing platforms have struggled to move beyond 23-25% automation coverage, which limits their effectiveness in addressing the complexities of modern software development. As developers increasingly utilize generative AI tools to produce code rapidly, these platforms are not fully equipped to handle the unique challenges, such as hallucinated outputs and the need for specialized testing of AI applications.
What are the benefits of Autonomous Testing platforms?
Autonomous Testing platforms provide several benefits, including the ability to test faster and manage larger volumes of code and functional requirements. They are designed to be intelligent and adaptive, which allows organizations to maintain accuracy and efficiency in their testing processes. This transition is essential for keeping pace with the demands of faster delivery cycles and the increasing complexity of AI-driven applications.
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