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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Risks and Testing Challenges for Generative AI | 30% | - Testing Challenges for Generative AI
|
| 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: Fundamentals of Generative AI | 20% | - AI Development Lifecycle
|
1. Which statement about data privacy risks in GenAI-assisted testing is INCORRECT?
A) Some GenAI tools may store/process data without explicit consent
B) Using GenAI without regulatory compliance can lead to legal exposure
C) GenAI outputs can accidentally reveal sensitive information present in inputs
D) Strict GDPR compliance eliminates all privacy risk
2. 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) Output format
D) Constraints
3. Which standard specifies requirements for managing AI systems within an organization, supporting consistent GenAI use in testing?
A) ISO/IEC 42001:2023
B) EU AI Act
C) ISO/IEC 23053:2022
D) NIST AI RMF 1.0
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) i, iii, v
B) i, ii, iii (Duplicate entry in original source)
C) ii, iii, iv
D) i, ii, iii
5. What is a key data-related aspect when defining a GenAI strategy for testing?
A) Neglect legacy data sources as they provide limited immediate relevance to testing tasks
B) Use only auto-generated synthetic data to avoid dependency on enterprise repositories
C) Prioritize accurate and relevant input data secured through defined quality procedures
D) Aggregate data from all available organizational repositories without filtration
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: D | Question # 5 Answer: C |
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