Redefining what Software Testing is and how it is being used to ensure a customer centric approach test result is delivered to your customers in areas that are unknown

• Delegates will be able to understand the needs and essentials of Software Testing in their industry
• Software Testing not only just plays the role of testing a software but to provide a better all round quality assurance
• Outcome of software testing will not only test defects of a system, but to ensure a more customer centric approach when it comes to having the results presented

As Infrastructure as Code (IaC) continues to reshape the modern DevOps landscape, ensuring that our code is robust, maintainable, and secure becomes paramount. This session dives into the practical journey of testing IaC—from simple input validations in Terraform all the way to advanced integration testing with Terratest and the power of full programming language frameworks like AWS CDK, CDKTF, and CDK8s.

We’ll explore the evolution from pinning module versions to adopting trunk-based development, highlighting how this shift enables continuous evaluation of all dependent IaC modules. You’ll discover how to get started with TF Test for quick unit tests, then expand your testing strategy to end-to-end checks in real-world cloud environments via Terratest. Finally, we’ll demonstrate how leveraging a complete language framework (using the CDKs) can drive deeper test coverage and faster iteration cycles.

If you’re seeking to elevate your Terraform and IaC testing practices, this talk will give you a clear roadmap for achieving consistent quality, reliability, and velocity in your infrastructure.

• Understand the progression from basic Terraform validations to comprehensive testing strategies involving pinned versions, trunk-based development, and beyond.
• Learn how to apply best practices for validating module inputs, writing effective TF Tests, and ensuring continuous validation across your codebase.
• Discover how Terratest helps you run true end-to-end tests against real cloud deployments, reducing the risk of production issues and infrastructure drift.
• Explore how AWS CDK, CDKTF, and CDK8s enable deeper test coverage, rapid iteration, and integration with standard software testing frameworks, opening the door to more advanced CI/CD capabilities.
• Gain insight into setting up a scalable testing environment for your IaC, including tips on managing complexity, versioning strategies, and automated pipelines.

This session will discuss automation, test data management, test scripting, exploratory testing enhance testing with Large Language Model (LLM) Identify opportunities to improve test quality with AI Construct test automation with AI tools Ideas during exploratory testing using AI tools Leverage AI tools to aid the design process of new features Improve testability with AI tools Maximize output with prompt engineering

Leverage AI and LLMs and GenAI to improve your software and data testing efficiency Learn new tools and tricks for Testing

I have been working in software test & QA for more than 10 years, recently AI/ML is quite hot. There will be challenge and opportunity to transform SW Test & QA. I lead my team did some trial and experimental, there are successful stories and also some lesson learned. I want to use this opportunity to share what are the key challenges facing in this AI/ML/GenAI new era. What the approach and strategy can help you or your team navigate quickly in the new world. Following topics will be shared:

• Overview of AI & AI testing challenge
• Lesson learned of how navigating the AI in SW Test, and AI testing from both theory and practice point of view
• Next plans & looking forward cooperation with all stakeholders who are interesting in these areas
• Q&A

Quality isn’t just about finding bugs anymore—it’s a key factor in business success and development speed. Many teams face challenges like disconnected efforts, slow feedback, and lack of a clear strategy, leading to delays, higher costs, and inefficiencies.

This session will help you build a quality roadmap that brings business, operations, and development teams together. We’ll cover a simple 4-step framework—Strategic Planning, Prioritization, Execution, and Continuous Adaptation—to create a scalable and efficient quality process.

We’ll also explore how AI, automation, and real-time monitoring can strengthen quality assurance, making teams more efficient and resilient in today’s fast-moving digital world.

• The critical role of a quality roadmap in business success and development efficiency
• A structured 4-step framework to build and implement a quality roadmap
• Best practices for aligning quality goals with business and operational priorities
• Strategies to reduce costs and optimize workflows through automation and AI-based quality engineering
• Practical insights on measuring quality success using business, operational, and technical KPIs

Kiran Kumar is a results-driven IT professional with 18 years of expertise in Enterprise Architecture, DevOps, automation, and infrastructure management. TOGAF, CKD, AWS certified, specializing in OpenShift, Ansible, SRE, performance engineering, and migration. Skilled in automation, application reliability, and team management, ensuring high-quality deliverables.

Passionate Technologist specialization in High Performance computing
Interest: Parallel & concurrent programming, Java, Algorithmic electronic trading &
Real-time Trading System and FIX tech.
Contributing/Research in Financial Engineering and Financial Mathematical models (Stochastic/Brownian Equation/PDE).

Donghao Huang is VP of R&D at Mastercard Singapore, leading AI innovation in financial systems. With 25 patents and numerous research papers, he specializes in Generative AI and machine learning. Holding degrees from top universities, he pioneers secure, intelligent payment solutions while pursuing a Doctor of Engineering at SMU.