Filling the Test Automation Gaps with AI – Lessons from the ISTQB Glossary Project
Traditional test automation has long been stuck on execution, but the demand for full-cycle automation is growing as CI/CD and DevOps accelerate. Can the combination of Generative AI and Model-Based Testing (MBT) finally automate the entire process, from the test basis to the final result? In this session, Matthias Hamburg presents a real-world case study on the ISTQB Glossary App. By integrating GenAI with MBT, the team successfully transformed natural language requirements into test models, generated high-level test cases, and mapped them to automated execution. Full program : https://testingsummit.com/program/ #Testautomation #CICD #Genai

▶︎
How Netflix Uses Java - 2026 Edition

▶︎
Improve your testing with TMMi .... and AI

▶︎
Why The Russian Accent Terrifies Everyone

▶︎
Generative AI in Software testing

▶︎
More tests are always better? How to use AI to identify tests that bring little value

▶︎
How I Use Aspirin to Unclog Arteries

▶︎
Software Testing Course – Playwright, E2E, and AI Agents

▶︎
Becoming a Good Software Tester in the Age of AI, DevOps, and beyond

▶︎
Andrej Karpathy: From Vibe Coding to Agentic Engineering w/ Stephanie Zhan

▶︎
Taking action to lead software testing

▶︎
CAN YOU PROVE YOU TESTED IT? Audit Readiness for Development & Testing Teams

▶︎
RAG Crash Course for Beginners

▶︎
Turing Award Winner: Disagreeing with Google, Postgres, Future Problems | Mike Stonebraker

▶︎
Demis Hassabis: Why AGI is Bigger than the Industrial Revolution & Where Are The Bottlenecks in AI

▶︎
Full Walkthrough: Workflow for AI Coding — Matt Pocock

▶︎
The Strange Math That Predicts (Almost) Anything

▶︎
Building the PERFECT Linux PC with Linus Torvalds

▶︎
Why AI WON'T Replace Software Engineering...

▶︎
Exploratory Learning Styles

▶︎
