STAREAST 2025 - Industry Insights

What if Generative AI could do more than generate code—what if it could understand your application, adapt to change, and continuously optimize your tests? In this session, we unveil a transformative Gen AI solution that is purpose-built for test automation. It brings autonomous test discovery, intelligent modular design, context-aware maintenance, and predictive insights into quality risks. More than just a tool, it becomes an extension of your team—embedding best practices, scaling effortlessly, and evolving alongside your application.

This session explores how Quality Assurance (QA) has evolved from a final checkpoint into a critical, strategic function embedded throughout the software development lifecycle. Hülya Kayacı from Quality Professionals highlights QA’s role in ensuring software reliability, supporting fast-paced development, and protecting revenue. Topics include the impact of SaaS, the integration of QA in DevOps, the economics of proactive testing, and the evolving role of AI and automation in quality practices.

There is no question that Generative AI models can improve the productivity of almost every role within the software development process. However, while a lot of attention has focused on generating software using tools such as GitHub Copilot, Amazon CodeWhisperer, Tabnine, and more, these tools can assist software testers in their job too. Join Coveros CEO Jeffery Payne to explore how Generative AI solutions help software testers generate and supplement tests, create automated test scripts, and even suggest improvements to what you’ve already created.

AI isn’t just a buzzword – it’s transforming the way we build, test, and secure applications. Join this session to understand the vision for the future, and how that’s driving the innovation of today and tomorrow. By leveraging AI properly, you can cut down the total cost of ownership of your testing efforts through preventing scripts from breaking due to locator changes, making scripts easier to create and maintain, and increasing coverage of your tests.

In an era where AI-driven agents are making waves across industries, the conversation often centers around machines replacing humans. But in software quality assurance, the real transformation lies in collaboration, not replacement.
In this talk, we’ll explore how AI testing agents can elevate and empower QA professionals—not eliminate them. We'll walk through how these agents assist in test discovery, authoring, and execution, while being guided, validated, and fine-tuned by human expertise.

Most quality engineering focuses on finding existing bugs, but what if we could predict where bugs will appear before writing code? This talk introduces a framework for using generative AI to analyze code changes, requirements, and historical bug patterns to forecast potential quality issues. Discover how to build a predictive quality model that helps teams prioritize testing efforts and implement preventative measures before problems emerge.
 

Everyone’s talking about using GenAI to optimize testing, but what happens when your app is GenAI-powered.  This session explores how to test applications that generate dynamic, unpredictable outputs, where traditional approaches start to fall short.

Generative AI and agentic AI are revolutionizing end-to-end testing by automating complex tasks, enhancing accuracy, and reducing time-to-market. Generative AI creates realistic test scenarios, data and scripts, ensuring comprehensive coverage and increased quality. Agentic AI, with its decision-making capabilities, dynamically adapts testing strategies based on real-time analysis, optimizing resource allocation and improving test efficiency. Together, they enable continuous testing and integration, facilitating agile development along with rapid feedback.