ISTQB CT-GenAI - Certified Tester Testing with Generative AI Exam
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Total 39 questions
Question #11 (Topic: Exam A)
What is the primary characteristic that distinguishes a system prompt from a user prompt in an interaction with an LLM?
A. A system prompt changes dynamically with each user input, while a user prompt remains constant throughout the conversation.
B. A system prompt contains specific questions or tasks from the user, while a user prompt defines the LLM's overall behavior.
C. A system prompt is always visible and editable by the chatbot user, unlike the user prompt.
D. A system prompt is usually set by the developer, while a user prompt is written by the end user.
Answer: D
Question #12 (Topic: Exam A)
You are a test analyst using Generative AI to support early test analysis activities for newly written user stories. Your objective is to ensure the stories are clear, testable, and ready for test case design.
Which of the following sequences BEST demonstrates how Generative AI can be applied to enhance test analysis through iterative review and refinement?
i. Initial Review: Ask the LLM to analyze the user stories and identify any ambiguities, gaps, or testability issues.
ii. Refinement Suggestions: Based on the identified issues, prompt the LLM to propose clearer or more testable rewordings.
iii. Testability Check: Submit the revised user stories to the LLM for a final assessment of their clarity, completeness, and readiness for test case generation.
iv. Risk-Based Prioritization: Use the LLM to assign risk levels to the conditions in the user stories and suggest testing priorities.
v. Direct Test Case Generation: Ask the LLM to produce full test cases based on the original user stories
Which of the following sequences BEST demonstrates how Generative AI can be applied to enhance test analysis through iterative review and refinement?
i. Initial Review: Ask the LLM to analyze the user stories and identify any ambiguities, gaps, or testability issues.
ii. Refinement Suggestions: Based on the identified issues, prompt the LLM to propose clearer or more testable rewordings.
iii. Testability Check: Submit the revised user stories to the LLM for a final assessment of their clarity, completeness, and readiness for test case generation.
iv. Risk-Based Prioritization: Use the LLM to assign risk levels to the conditions in the user stories and suggest testing priorities.
v. Direct Test Case Generation: Ask the LLM to produce full test cases based on the original user stories
A. i, ii, and iii
B. ii, iv, and v
C. iii, iv, and v
D. i, ii, and iv
Answer: A
Question #13 (Topic: Exam A)
Which of the following BEST reflects the shift in a tester's responsibility after the adoption of Generative AI in test activities within an organization?
A. Focusing on the manual creation of test documentation.
B. Maintaining test-specific prompt libraries and refining AI-generated output.
C. Delegating all test design activities to the AI.
D. Managing the overall organizational budget for AI tool procurement.
Answer: B
Question #14 (Topic: Exam A)
You are leading a team that uses Generative AI to enhance automated regression testing. You have identified that adapting test scripts to minor UI or API changes is a frequent challenge, leading to unnecessary failures and maintenance overhead. You want the LLM to proactively adjust test scripts to handle such modifications.
Which of the following improvements to a prompt would BEST enable the LLM to support self-healing and adaptive tests?
Which of the following improvements to a prompt would BEST enable the LLM to support self-healing and adaptive tests?
A. Add an instruction for the LLM to generate detailed test reports with success metrics and key insights.
B. Specify a constraint that the LLM should prioritize test execution based on module criticality and historical defect rates.
C. Expand the instruction to include analyzing code changes to identify high-risk areas for targeted regression testing.
D. Include a directive for the LLM to automatically analyze UI element changes and modify locators within test scripts to prevent failures.
Answer: D
Question #15 (Topic: Exam A)
You are a test manager, facing an unexpected rise in high-priority defects impacting your current sprint's test progress. To regain control and get the testing back on track, you plan to use a Generative AI model to re-evaluate the test execution schedule and optimize resource allocation. Your goal is to obtain not just a revised schedule, but also clear justifications and actionable strategies for test control.
Here is an initial draft of a prompt you've prepared for the AI:
Role: Act as a test manager.
Context: Analyze the current test progress and defect reports from the sprint.
Instruction: Propose adjustments to the test execution schedule.
Input Data: <<<Current test progress report (daily burn-down chart, test execution rates), recent defect log (severity, priority), original sprint test plan >>>.
Constraints: The revised schedule must aim to complete critical features on time.
Output Format: A table outlining proposed schedule changes for each test phase or feature, including new estimated completion dates.
Which of the following improvements would BEST enhance the LLM's ability to provide comprehensive and actionable insights for dynamic test control in this scenario?
i. Adjust the Role to "Act as an expert in Agile test management with strong risk mitigation skills" to guide the LLM's persona.
ii. Expand the Instruction to include identifying the root causes of the delays and proposing specific strategies for reallocating test resources, along with alternative approaches.
iii. Extend the Input Data to include historical test data from previous sprints to enable long-term trend analysis, not just current sprint data.
iv. Modify the Constraints to limit proposed schedule adjustments to a maximum of two days, regardless of the identified impact or necessary changes.
v. Reconfigure the Output Format to present raw, unprocessed metrics and dashboards.
Here is an initial draft of a prompt you've prepared for the AI:
Role: Act as a test manager.
Context: Analyze the current test progress and defect reports from the sprint.
Instruction: Propose adjustments to the test execution schedule.
Input Data: <<<Current test progress report (daily burn-down chart, test execution rates), recent defect log (severity, priority), original sprint test plan >>>.
Constraints: The revised schedule must aim to complete critical features on time.
Output Format: A table outlining proposed schedule changes for each test phase or feature, including new estimated completion dates.
Which of the following improvements would BEST enhance the LLM's ability to provide comprehensive and actionable insights for dynamic test control in this scenario?
i. Adjust the Role to "Act as an expert in Agile test management with strong risk mitigation skills" to guide the LLM's persona.
ii. Expand the Instruction to include identifying the root causes of the delays and proposing specific strategies for reallocating test resources, along with alternative approaches.
iii. Extend the Input Data to include historical test data from previous sprints to enable long-term trend analysis, not just current sprint data.
iv. Modify the Constraints to limit proposed schedule adjustments to a maximum of two days, regardless of the identified impact or necessary changes.
v. Reconfigure the Output Format to present raw, unprocessed metrics and dashboards.
A. i and iii
B. ii
C. ii and iv
D. i, iii, and v
Answer: B
