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ISQI CT-GenAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Managing Risks of Generative AI in Software Testing | 25% | - Data privacy, security, and compliance concerns - Hallucinations, bias, inaccuracy, and consistency risks - Validation, verification, and mitigation strategies |
| LLM-Powered Test Infrastructure | 10% | - RAG, fine-tuning, and model adaptation - AI agents and integration with test tools - Architecture and deployment considerations |
| Prompt Engineering for Effective Software Testing | 35% | - Principles and structure of effective prompts - Iterative refinement and evaluation of prompts - Prompt patterns for test design, data generation, automation |
| Deploying and Integrating GenAI in Test Organisations | 15% | - Roles, skills, and team readiness - Strategy, governance, and adoption roadmap - Measuring value and continuous improvement |
| Introduction to Generative AI for Software Testing | 15% | - Core concepts: Generative AI, LLMs, foundation models - Use cases across the testing lifecycle - Capabilities and limitations relevant to testing |
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
Question 1
Which statement BEST differentiates an LLM-powered test infrastructure from a traditional chatbot system used in testing?
A. It focuses primarily on visual dashboards and user navigation features
B. It produces scripted conversational responses similar to traditional bots
C. It provides fixed responses from predefined rule sets and scripts
D. It dynamically generates test insights using contextual information
Question 2
Which concept refers to breaking text into smaller units for processing by LLMs?
A. Tokenization
B. Embeddings
C. Transformer
D. Context Window
Question 3
Which statement about fine-tuning for test tasks is INCORRECT?
A. It enhances relevance to organizational terminology and formats
B. It replaces the model's general knowledge entirely and prevents overfitting
C. It can be applied to smaller SLMs to improve task performance with lower compute
D. It adapts a pre-trained model to a domain using task-specific data
Question 4
Which statement about data privacy risks in GenAI-assisted testing is INCORRECT?
A. Some GenAI tools may store/process data without explicit consent
B. Strict GDPR compliance eliminates all privacy risk
C. GenAI outputs can accidentally reveal sensitive information present in inputs
D. Using GenAI without regulatory compliance can lead to legal exposure
Question 5
What distinguishes an LLM-powered agent from a basic AI chatbot in test processes?
A. Use of a conversational tone and improved response personalization
B. Reliance on predefined templates to generate short, factual answers
C. Ability to trigger automated actions beyond conversation
D. Ability to respond to prompts without explicit user instructions
Solutions:
| Question 1 Answer: D | Question 2 Answer: A | Question 3 Answer: B | Question 4 Answer: B | Question 5 Answer: C |
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