Workshops (Dag 1)

🏛️Spor 1 | 🎤Track 1

Kl.9.00 (Half-day) | In English

Test Planning Explained

By Predrag Skokovic from Quality House

Abstract:

The role of the Test Automation Engineer (TAE) is becoming increasingly important - it sounds simple like combining "technical development skills" with "testing and quality skills" - but the real effects are huge. Test Automation Engineers often build an important bridge between the business and the technical side.

Richard will explain how testers can grow into automation by learning coding skills - and how developers can strengthen their quality focus by adopting a testing mindset.

Often testers fear the transition into "technical" automation. With modern learning methods and AI-assisted tools, testers can learn, create, maintain, and analyze automation more efficiently.

When we look into the future, where intelligent agents take over specific tasks in the test automation lifecycle - such as test generation, optimization, and environment control - there is someone who will orchestrate this "team". And the TAE is ideally suited for this.

You will leave with a clear understanding of the current and future skills required in test automation.

Learning Objectives:

You will learn:

  • To understand the evolving role of the Test Automation Engineer

  • To overcome fear of code through practical entry points

  • To differentiate between classical automation and agent-based approaches

  • To define a personal upskilling roadmap towards becoming a TAE

  • To prepare for future collaboration with AI and autonomous testing tools

Session Outline:

  • Testing as an activity vs. testware as a product

  • Identifying business needs and expectations for testware

  • Considering users and designing testware accordingly

  • Implementing and maintaining testware as a product

  • Roadmap and current progress

Target Audience:

Advanced (hands-on experience with the topic)

🏛️Spor 1 | 🎤Track 1

Kl.13.30 (Half-day) | In English

Test Automation Strategies with Design Thinking

By Barış Sarıalioğlu from TesterYou

Abstract:

In an era where speed and quality define competitive advantage, test automation is no longer just a technical practice—it is a strategic capability. Yet, many automation initiatives fail to deliver sustainable value because they focus on tools and frameworks, overlooking the human, creative, and iterative dimensions of problem-solving.

This workshop explores how Design Thinking—with its emphasis on empathy, ideation, and experimentation—can be applied to create robust and adaptable test automation strategies. First we reframe automation challenges from the perspective of diverse stakeholders, ensuring that the solutions align with real user and business needs. Then, we move through ideation techniques to generate innovative approaches for architecture, maintainability, and integration across the delivery pipeline.

You will learn to prototype automation solutions quickly, validate them in realistic scenarios, and iterate based on feedback—transforming automation from a one-time implementation into a continuously evolving ecosystem.

You will gain practical tools and a mindset to build technically sound and future-ready automation strategies.

Learning Objectives:

You will learn:

  • Human-Centered Automation Planning – How to frame automation goals by understanding the real needs of users, testers, and business stakeholders.

  • Creative Problem-Solving Techniques – Using Design Thinking ideation methods to generate innovative automation approaches beyond traditional tool-driven thinking.

  • Rapid Prototyping of Automation Solutions – Applying quick, low-risk experiments to validate automation ideas before full-scale implementation.

  • Sustainable Maintainability Practices – Strategies for designing automation architectures that remain adaptable and cost-effective over time.

  • Iterative Improvement Mindset – How to continuously refine and evolve automation strategies using feedback loops and performance metrics

Session Outline:

  • Introduction & Context

  • Empathize: Understanding the Problem Space

  • Define & Ideate: Shaping the Strategy

  • Prototype & Test: From Idea to Reality

  • Wrap-Up & Key Takeaways

Target Audience:

Advanced (hands-on experience with the topic)

🏛️Spor 2 | 🎤Track 2 

Kl.9.00 (Full-day) | In English

Building an AI-Powered Testing Tools Platform

By Vivianne Guimarães and Tiago Gomes from Thoughtworks

Abstract:

Testing needs a good structure, because in that way we become more efficient, effective and, above all, transparent about the activities and their results. Creating a test plan ‘forces’ us to think carefully in advance about all the important details related to testing the software we’re working on, as well as to anticipate potential risks that may arise.

In this workshop we will discuss the following topics: software test models, test process in context, test planning vs test plan, test strategy and test approach, risks, and many more. Most importantly, we’ll exercise on a real-life example how to plan for test activities and to write it down in a test plan.

During the tutorial we will reference ISO 29119 - software testing standard, in order to guide our thoughts and actions, as any other relevant standard or framework would do.

Learning Objectives:

You will learn:

  • To distinguish between test planning and a test plan, understanding the unique value each brings in effective software testing.

  • To apply structured approaches to test planning, including selecting appropriate test models, defining strategies, and identifying risks.

  • To develop a practical, context-aware test plan, tailored to real-life project constraints, goals, and team dynamics.

  • To reference, incorporate, and adapt industry standards, such as ISO 29119, to guide planning decisions and ensure transparency and alignment.

Session Outline:

  • Part I - theory:

    - Introduction to workshop

    - Software testing models

    - Test process in context

    - Test planning process

    - Test plan

  • Part II - hands-on exercise through collaboration and discussion:

    - Exercise: Write a test plan for Sea Swimming Contest Software System

  • Part III - workshop closure

Target Audience:

Intermediate (basic understanding of the topic)

This workshop is suitable for those with a technical mindset. Please bring a computer with installation permissions to actively participate.

🏛️Spor 3 | 🎤Track 3 

Kl.9.00 (Full-day) | In English

AI Meets QA: A Full-Day Journey Through Testing, Tools, and Techniques

By Kari Kakkonen from Gofore

Abstract:

This workshop is a taste of the full ISTQB® AI Testing (CT-AI) 4-day course, with exciting AI and testing knowledge and exercises. The course is an introduction to the topic that lowers the threshold for learning more, perhaps taking a full course or self-studying for an ISTQB CT-AI exam.

Testers encounter the need to test systems that include AI elements more and more. Due to the nature of AI, all traditional test approaches and techniques do not work. Instead AI-specific techniques are needed.

We will cover AI and machine learning basics, AI-specific quality criteria, the testing done with teaching a machine learning model, and after teaching, test levels, approaches, and techniques for testing AI.

We will also cover how AI can help with testing. We will go through how you test AI-based systems and what the challenges are for self-learning systems. We will show how to you use AI to improve your testing.

Learning Objectives:

You will learn:

  • How to use AI-related quality characteristics for better testing

  • To use test techniques to deal with typical AI challenges

  • Situations in your everyday testing where they can utilize AI

Session Outline:

  • Introduction to AI – 60 minutes

    Exercise: Machine Learning with Teachable Machine 30 minutes

  • Quality Characteristics for AI Systems 60 minutes

    Exercise: Selecting Objectives and Acceptance Criteria 30 minutes

  • Testing AI-Based Systems 30 minutes

    Exercise: Explainability with ExpliClas 30

  • Techniques for the Testing of AI 30 minutes

    Exercise: Pairwise testing with Pairwiser 30 minutes

  • Techniques for the Testing of AI 30 minutes

    Exercise: Metamorphic testing 30 minutes

  • Techniques for the Testing of AI 30 minutes

    Exercise: Exploratory testing with TensorFlow 30 minutes

  • Using AI for Testing 30 minutes

    Exercise: GenAI testing 30 minutes

Target Audience:

Basic (no prior knowledge)