Exam Name: ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0
Certification Provider: ISQI
Corresponding Certification: AI Testing
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ISQI CT-GenAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Fundamentals of Generative AI | 20% | - AI Development Lifecycle
|
| Topic 2: Testing Activities for Generative AI | 30% | - Model and Output Evaluation
|
| Topic 3: Tools for Testing Generative AI | 20% | - Using Tools for Common Testing Activities
|
| Topic 4: Risks and Testing Challenges for Generative AI | 30% | - Testing Challenges for Generative AI
|
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
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. Applying a reusable and structured template that guides GenAI models toward consistent outputs
- C. Using ad hoc prompts without reference to previously proven structures or examples
- D. Maintaining static documentation repositories without real-time prompt standardization processes
Correct Answer: B 🗳️
Explanation: Only visible for PremiumVCEDump members. You can sign-up / login (it's free).
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. Add a step to review the change log for syntax errors before analysis.
- B. Include mapping code changes to affected modules, identifying test cases, prioritizing by risk level and change complexity
- C. Include references to version control systems like Git in the constraints.
- D. Specify that the role is a test architect specializing in CI/CD pipelines.
Correct Answer: B 🗳️
The model flags anomalies in logs and also proposes partitions for input validation tests. Which metrics BEST evaluate these two outcomes together?
- A. Precision for anomaly identification and recall for coverage of valid/invalid partitions
- B. Accuracy for anomaly detection and Precision for coverage of valid/invalid partitions
- C. Diversity for anomaly identification and precision for partitions
- D. Time efficiency for anomaly detection and accuracy for coverage of valid/invalid partitions
Correct Answer: A 🗳️
Explanation: Only visible for PremiumVCEDump members. You can sign-up / login (it's free).
Your team needs to generate 500 API test cases for a REST API with 50 endpoints. You have documented 10 exemplar test cases that follow your organization's standard format. You want the LLM to generate test cases following the pattern demonstrated in your examples. Which of the following prompting techniques is BEST suited to achieve your goal in this scenario?
- A. Zero-shot prompting
- B. Meta prompting
- C. Prompt chaining
- D. Few-shot prompting
Correct Answer: D 🗳️
Explanation: Only visible for PremiumVCEDump members. You can sign-up / login (it's free).
Which statement BEST contrasts interaction style and scope?
- A. Both are identical aside from UI theme.
- B. Chatbots enforce fixed workflows; LLM apps support free-form exploration beneficial for software testing
- C. Chatbots enable conversational interactions; LLM apps provide capabilities for defined test tasks.
- D. Chatbots require API integration; LLM apps do not.
Correct Answer: C 🗳️
Explanation: Only visible for PremiumVCEDump members. You can sign-up / login (it's free).
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