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ISQI CT-GenAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Fundamentals of Generative AI | 20% | - Generative AI Concepts
|
| Risks and Testing Challenges for Generative AI | 30% | - Quality Risks Specific to Generative AI
|
| Testing Activities for Generative AI | 30% | - Requirements-Based Testing
|
| Tools for Testing Generative AI | 20% | - Testing Tools Overview
|
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
1. The model flags anomalies in logs and also proposes partitions for input validation tests. Which metrics BEST evaluate these two outcomes together?
A) Accuracy for anomaly detection and Precision for coverage of valid/invalid partitions
B) Precision for anomaly identification and recall for coverage of valid/invalid partitions
C) Time efficiency for anomaly detection and accuracy for coverage of valid/invalid partitions
D) Diversity for anomaly identification and precision for partitions
2. 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) Add a step to review the change log for syntax errors before analysis.
C) Specify that the role is a test architect specializing in CI/CD pipelines.
D) Include mapping code changes to affected modules, identifying test cases, prioritizing by risk level and change complexity
3. What BEST protects sensitive test data at rest and in transit?
A) Disable TLS and rely on VPN only
B) Use public file shares with read-only links
C) Enforce role-based access controls
D) Rely on obfuscation instead of encryption
4. 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 (Duplicate entry in original source)
C) i, ii, iii
D) i, iii, v
5. Which statement BEST contrasts interaction style and scope?
A) Chatbots enable conversational interactions; LLM apps provide capabilities for defined test tasks.
B) Chatbots require API integration; LLM apps do not.
C) Both are identical aside from UI theme.
D) Chatbots enforce fixed workflows; LLM apps support free-form exploration beneficial for software testing
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: A |

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Zachary -
Thanks for your good CT-GenAI material.