DEVOPSdigest

Perforce Software announced the launch of AI Validation, a new capability within its Perfecto continuous testing platform for web and mobile applications.

Perfecto's AI Validation changes the way organizations experience testing. Instead of creating multiple scripts and frameworks, which are cumbersome and do not scale on multiple platforms that require consistent digital experiences, AI Validation uses advanced artificial intelligence to validate applications visually and contextually and dynamically adapts to application changes without human intervention. Designed to address the increasing complexity of modern applications, this innovation empowers teams to deliver software faster while maintaining the highest levels of quality.

Perforce's AI uses natural language prompts and does not rely on objects or code, instead creating durable tests that work across platforms. This user-centric approach eliminates the need for specialized scripting knowledge, allowing anyone—regardless of skill set—to adopt and scale test automation quickly. By removing co-pilot complexity, Perforce moves towards autonomous testing, an AI-driven approach to testing that eliminates the need for human intervention.

"The success that our early adopters have already experienced with AI Validation is a huge validator to our approach with testing," said Stephen Feloney, Vice President, Product Management at Perforce. "Creating more frameworks and more code in co-pilot does not help testers do what they have always wanted: validate exactly what appears on the screen. This is what AI Validation provides them. Our early customers are already experiencing a reduction in their time by around 20%, but we anticipate this will be closer to 50% or more as we continue to innovate in this area."

Perfecto's AI Validation is tailored for enterprise teams navigating the complexities of multi-platform testing. Its seamless integration into CI/CD workflows enables continuous and scalable testing that evolves with the dynamic demands of agile and DevOps practices. By simplifying processes and enhancing adaptability, it empowers teams to maintain quality and speed across the development life cycles.

Whether validating a complex trending graph, bar chart, or a dynamic calendar view—across Android, iOS, and varied screen resolutions—AI Validation significantly improves quality, lowers maintenance, and reduces costs while fundamentally changing how testing is done.

KEY FEATURES OF AI VALIDATION:

- Dynamic Adaptability: Manually updating scripts or object locators whenever an application changes leads to frequent test failures and costly maintenance. Perfecto's AI Validation inherently avoids this issue by eliminating reliance on fragile locators and script updates—so there is no need for continuous adjustments when the UI evolves. This ensures uninterrupted testing and significantly lowers costs.

- Contextual Test Coverage: Unlike basic OCR-based solutions, Perfecto's AI-driven approach verifies the meaning behind dynamic elements—charts, dashboards, or graphics—to ensure user experiences reflect the intended content. This deep level of coverage ensures thorough visual validation across all application layers.

- Efficiency At Scale: Slow feedback loops and fragmented processes bog down agile and DevOps teams. AI Validation seamlessly integrates into CI/CD pipelines, accelerating releases and allowing teams to adapt quickly to any change in their development cycle with extensible SDKs.

- Anyone Can Test: Test creation and maintenance demands specialized scripting skills, limiting participation to a few technical experts. AI Validation's natural language prompts open testing to everyone on the team, expanding coverage while freeing specialists to tackle more complex challenges.

Over the coming months, Perforce will unveil a series of releases that promise to redefine industry standards and push the boundaries of continuous testing. Some of these capabilities will include autonomous testing, the simplification of test creation through low-code workflows and AI-guided suggestions, the ability to automatically adapt to real-time changes across platforms, AI-driven dashboards that pinpoint root causes for faster resolution, and the ability to continuously adapt to UI, data, or logic changes in real time, eliminating manual updates and ensuring your testing remains resilient and future-ready.