CT-GENAIPreview

Which of the following statements BEST describes the purpose of embeddings in Large Language Models (LLMs) when processing and generating content?

In the context of Large Language Models (LLMs), which of the following statements (i-v) regarding 'tokenization' and 'context window' are CORRECT? i) Tokenization is the process of breaking down textual input into smaller units called tokens. ii) The context window dictates the maximum number of tokens that an LLM can consider at any given time to maintain coherence. iii) Increasing the size of an LLM's context window generally leads to a reduction in computational complexity and processing time. iv) Tokenization primarily involves converting tokens into high-dimensional vectors to capture their semantic relationships. v) A larger context window allows an LLM to maintain coherence over longer passages, such as when analyzing large test logs.

In the context of LLMs, which statement BEST characterizes an instruction-tuned Large Language Model?

A test team is analyzing screenshots of a mobile application's GUI alongside textual defect reports to identify visual inconsistencies that are not captured by these reports.
Which type of Generative AI model is MOST suited to assist with this task?

Which TWO of the following capabilities are primary strengths of Large Language Models (LLMs) when applied to software testing tasks? (Choose two.)

A test team is looking to leverage Generative AI. They have two immediate needs:
Need 1. For rapid, ad-hoc exploration: A new tester needs to quickly understand requirements and generate simple, one-off test ideas interactively.
Need 2. For structured, repetitive automation: The team wants to integrate AI into their existing continuous integration (CI) pipeline to automatically generate comprehensive test data for daily regression runs.
Which of the following statements BEST describes how AI chatbots and LLM-powered testing applications would apply to these needs?

A tester is crafting a prompt for an LLM to generate test cases. One part of the prompt reads:
"The generated test cases must be provided in a CSV file format, with columns for Test ID, Description, Preconditions, Test Steps, and Expected Result."
In which component of the six-part prompt structure would this line MOST LIKELY appear?

A test engineer is learning about the six components of a structured prompt for Generative AI in software testing.
Which of the following statements INCORRECTLY describes one of these components?

A test lead needs an LLM to generate a comprehensive test plan summary, which requires iterative refinement and review. The task is complex and benefits from breaking it into smaller, verifiable steps, where the output of one step informs the next.
Which core prompting technique is BEST suited for this scenario?

What is the primary characteristic that distinguishes a system prompt from a user prompt in an interaction with an LLM?

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 BEST reflects the shift in a tester's responsibility after the adoption of Generative AI in test activities within an organization?

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?

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.

You are working on a test automation task that generates XML-based test conditions conforming to a strict schema. To reduce errors and maintain format consistency, you decide to use a Generative AI model.
Which of the following is the BEST way to prompt the model to ensure it produces valid XML output across multiple iterations?