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ISQI CT-GenAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: 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 |
| Topic 2: Prompt Engineering for Effective Software Testing | 35% | - Principles and structure of effective prompts - Prompt patterns for test design, data generation, automation - Iterative refinement and evaluation of prompts |
| Topic 3: Deploying and Integrating GenAI in Test Organisations | 15% | - Measuring value and continuous improvement - Strategy, governance, and adoption roadmap - Roles, skills, and team readiness |
| Topic 4: Introduction to Generative AI for Software Testing | 15% | - Capabilities and limitations relevant to testing - Core concepts: Generative AI, LLMs, foundation models - Use cases across the testing lifecycle |
| Topic 5: LLM-Powered Test Infrastructure | 10% | - Architecture and deployment considerations - AI agents and integration with test tools - RAG, fine-tuning, and model adaptation |
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
1. A prompt section states: "Web checkout module v3.2; focus on coupon application; existing regression suite IDs T-112-T-150; recent defect ID BUG-431." Which component is this?
A) Input data
B) Instruction
C) Constraints
D) Output format
2. A team notices vague, inconsistent LLM outputs for the same story for two different prompts. Which technique BEST helps choose the stronger wording among two prompt versions using predefined metrics?
A) Iterative prompt modification
B) A/B testing of prompts
C) Integrating user feedback
D) Output analysis
3. Which statement BEST describes vision-language models (VLMs)?
A) VLMs process audio and video but not images.
B) VLMs are a subset of multimodal LLMs integrating visual and textual information.
C) VLMs are unrelated to multimodal LLMs and focus only on UI automation.
D) VLMs are a superset of multimodal LLMs.
4. How do tester responsibilities MOSTLY evolve when integrating GenAI into test processes?
A) Shifting from test execution toward reviewing, refining, and validating AI-generated testware
B) Moving from black-box exploratory testing toward exclusively performing code-based white-box checks
C) Replacing existing test coverage validation with automated summary reports generated by AI
D) Transitioning from manual execution to complete automation with no human oversight
5. In the context of software testing, which statements (i-v) about foundation, instruction-tuned, and reasoning LLMs are CORRECT?
i. Foundation LLMs are best suited for broad exploratory ideation when test requirements are underspecified.
ii. Instruction-tuned LLMs are strongest at adhering to fixed test case formats (e.g., Gherkin) from clear prompts.
iii. Reasoning LLMs are strongest at multi-step root-cause analysis across logs, defects, and requirements.
iv. Foundation LLMs are optimal for strict policy compliance and template conformance.
v. Instruction-tuned LLMs can follow stepwise reasoning without any additional training or prompting.
A) ii, iii, iv
B) i, ii, iii
C) i, iii, v
D) i, ii, iii (Duplicate entry in original source)
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: B | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: B |
