Agenda

In this talk, Sargis will address this challenge by guiding you through the creation and deployment of a Dockerized Selenium grid, enhanced with autoscaling and video recording features. Capable of efficiently executing several thousand tests in a limited period, this advanced setup optimizes speed and reliability for UI tests. This deep dive will cover the strategic implementation of a high-performance Selenium grid, leveraging cloud technology for dynamic resource allocation and nuanced insight into each test. The discussion will be grounded in a practical context, showcasing a real-world application of a robust UI test ecosystem with multiple nodes to operate tests in isolated environments. This approach not only enhances test accuracy by eliminating external interference but also offers a scalable and efficient methodology applicable to both existing and new UI test suites.

This talk will explore the key challenges of ensuring applications perform under real-world conditions, from managing large user loads to identifying system bottlenecks. You’ll discover how modern tools like LoadRunner Enterprise can help simulate complex traffic patterns, diagnose issues early, and integrate performance testing into continuous development cycles. With practical insights and best practices, this session will equip you to deliver scalable, resilient, and high-performing applications, ensuring your software meets the demands of today’s users.

Join us for a session with Almantas, where you'll learn how AI can be harnessed to write tests both faster and with higher quality. Almantas will share tips and tricks, complemented by live demos that showcase the practical applications of AI in testing.

In this talk, you will learn how to use:

- GitHub Copilot to guide TDD and generate code from well-constructed tests.

- GPT-4 to:

- Refactor existing tests to follow desired patterns.

- Generate Gherkin scenarios from user stories, refining them for maximum clarity.

- Generate test code from Gherkin scenarios, and then create source code that the test code will verify.

These tools address the growing demand for faster, cost-effective testing solutions without compromising quality. This presentation will explore the rise of low-code and no-code test automation solutions, highlighting their key advantages: reduced training time, AI-powered inspections, cloud-based accessibility, and seamless integration into existing workflows. I’ll share real-world examples of how adopting no-code tools has transformed test automation, providing faster development cycles and easier maintenance. While not a universal solution, no-code automation is a significant step forward in meeting client expectations for speed, efficiency, and cost savings in post-pandemic software development.

It's time for the next evolution: Autonomous Testing. In my talk, I will explore our current position in this journey and the promising future that lies ahead. Traditional testing methods struggle to keep pace with today's rapid development cycles and are challenging to scale. While we once believed test automation would be the ultimate solution, it hasn't fully lived up to expectations. Despite widespread adoption, testing remains slow and difficult to scale, with over 70% of automation activities still being handled manually, such as scripting and maintenance.

Is there a better way forward? Could Autonomous Testing be the answer? Emerging trends suggest so. According to Gartner, Autonomous Testing, now referred to as AI-Augmented Testing, is at the forefront of innovation in the Agile and DevOps Hype Cycle, with widespread adoption predicted in the next 2-5 years.

The market's expectations are high, with many viewing Autonomous Testing as the next major step in software testing evolution. Many test automation tools already feature AI-driven capabilities, albeit in their early stages. In my presentation, I will provide an overview of these AI-based features and discuss the direction in which vendors are moving with these solutions.

However, embracing Autonomous Testing isn’t just about selecting the right tools. It requires a shift in testing strategy. I will offer practical advice on how to develop and implement an autonomous testing strategy that integrates seamlessly with your current processes. I'll share insights on where Autonomous Testing excels, where it may not be suitable, how to combine it with traditional methods, and how to prepare for the future—based on our extensive research and real-world experience.

Key Takeaways
- A comprehensive overview of Autonomous Testing
- Understanding the current capabilities of testing bots (what they can and cannot do)
- Practical steps to introduce Autonomous Testing in your organization