Ch 2.2 | Zero-Shot, One-Shot & Few-Shot Prompting for Testers | ISTQB CT-GenAI | بالعربي

Chapter 2.2 of the ISTQB Certified Tester – Generative AI (CT-GenAI) syllabus. The difference between a prompt that produces generic test cases and one that matches your organization's exact format often comes down to one thing: examples. This session covers the three In-Context Learning techniques the CT-GenAI syllabus requires you to understand and apply. What this session covers: In-Context Learning (ICL) — what it is and why it matters for testing tasks The Schulhoff 2024 research paper — the taxonomy behind the syllabus content Zero-Shot Prompting: → When to use it (simple, well-defined tasks) → Limitations for complex or format-specific outputs → Live demo: defect classification without examples One-Shot Prompting: → How a single example shifts model behavior → When one example is enough vs when you need more Few-Shot Prompting: → How multiple examples establish pattern consistency → Format control: forcing your organization's exact test case structure → Live demo: generating test cases that match a specific template Choosing between Zero/One/Few-Shot for different testing scenarios 🎯 Exam alignment: Covers CT-GenAI Syllabus Section 2.1.2 — In-Context Learning techniques. 📄 Prompt examples: https://shorturl.at/KzohS 🔗 Schulhoff research paper: https://shorturl.at/elUsT 📄 Presentation: https://shorturl.at/dqddR ⏱️ Timestamps: 00:00 Introduction 00:47 (Not on Exam) Schulhoff paper walkthrough 03:54 Core Prompt Techniques 04:11 Zero-Shot Prompting—definition and demo 05:19 Zero-Shot live demo: defect classification 08:00 One-Shot Prompting—adding a single example 08:47 One-Shot live demo 09:48 Few-Shot Prompting—multiple examples for consistency 10:40 Few-Shot live demo: format-specific test case generation 📚 Full ISTQB CT-GenAI playlist:    • ISTQB-GenAI بالعربي   #ISTQB #CTGenAI #FewShotPrompting #ZeroShot #PromptEngineering #InContextLearning #SoftwareTesting #QAEngineer #ISTQBExam