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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 - Architecture and deployment considerations - AI agents and integration with test tools |
| Introduction to Generative AI for Software Testing | 15% | - Core concepts: Generative AI, LLMs, foundation models - Capabilities and limitations relevant to testing - Use cases across the testing lifecycle |
| Deploying and Integrating GenAI in Test Organisations | 15% | - Strategy, governance, and adoption roadmap - Measuring value and continuous improvement - Roles, skills, and team readiness |
| Prompt Engineering for Effective Software Testing | 35% | - Prompt patterns for test design, data generation, automation - Iterative refinement and evaluation of prompts - Principles and structure of effective prompts |
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
1. Which concept refers to breaking text into smaller units for processing by LLMs?
A) Tokenization
B) Transformer
C) Context Window
D) Embeddings
2. What defines a prompt pattern in the context of structured GenAI capability building?
A) Treating prompts as access credentials or compliance records rather than functional templates
B) Using ad hoc prompts without reference to previously proven structures or examples
C) Applying a reusable and structured template that guides GenAI models toward consistent outputs
D) Maintaining static documentation repositories without real-time prompt standardization processes
3. You are tasked with applying structured prompting to perform impact analysis on recent code changes. Which of the following improvements would BEST align the prompt with structured prompt engineering best practices for comprehensive impact analysis?
A) Include references to version control systems like Git in the constraints.
B) Include mapping code changes to affected modules, identifying test cases, prioritizing by risk level and change complexity
C) Specify that the role is a test architect specializing in CI/CD pipelines.
D) Add a step to review the change log for syntax errors before analysis.
4. Which option BEST differentiates the three prompting techniques?
A) Few-shot = examples; Chaining = multi-step prompts; Meta = model helps draft/refine prompts
B) Chaining = give examples; Few-shot = break tasks; Meta = manual edits only
C) Few-shot = no examples; Chaining = single prompt; Meta = disable iteration
D) Meta = step decomposition; Chaining = zero-shot only; Few-shot = manual optimization
5. An attacker sends extremely long prompts to overflow context so the model leaks snippets from its training data. Which attack vector is this?
A) Data poisoning
B) Malicious code generation
C) Data exfiltration
D) Request manipulation
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: C |
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