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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Deploying and Integrating GenAI in Test Organisations | 15% | - Measuring value and continuous improvement - Roles, skills, and team readiness - Strategy, governance, and adoption roadmap |
| Topic 2: Managing Risks of Generative AI in Software Testing | 25% | - Hallucinations, bias, inaccuracy, and consistency risks - Data privacy, security, and compliance concerns - Validation, verification, and mitigation strategies |
| Topic 3: LLM-Powered Test Infrastructure | 10% | - AI agents and integration with test tools - Architecture and deployment considerations - RAG, fine-tuning, and model adaptation |
| Topic 4: Prompt Engineering for Effective Software Testing | 35% | - Iterative refinement and evaluation of prompts - Principles and structure of effective prompts - Prompt patterns for test design, data generation, automation |
| Topic 5: Introduction to Generative AI for Software Testing | 15% | - Capabilities and limitations relevant to testing - Use cases across the testing lifecycle - Core concepts: Generative AI, LLMs, foundation models |
1. An attacker sends extremely long prompts to overflow context so the model leaks snippets from its training data. Which attack vector is this?
A) Data poisoning
B) Data exfiltration
C) Request manipulation
D) Malicious code generation
2. You must use GenAI to perform test analysis on a payments module with finalized requirements: (1) generate test conditions, (2) prioritize by risk, (3) check coverage gaps. Which sequence best applies prompt chaining?
A) Prioritize requirements -> generate conditions -> review defects
B) Generate conditions -> prioritize by risk -> map to requirements to find gaps
C) Generate prioritized conditions in one shot -> verify coverage
D) Detect requirement defects -> generate conditions -> prioritize
3. What is a key data-related aspect when defining a GenAI strategy for testing?
A) Use only auto-generated synthetic data to avoid dependency on enterprise repositories
B) Aggregate data from all available organizational repositories without filtration
C) Neglect legacy data sources as they provide limited immediate relevance to testing tasks
D) Prioritize accurate and relevant input data secured through defined quality procedures
4. 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) Rely on obfuscation instead of encryption
D) Enforce role-based access controls
5. When an organization uses an AI chatbot for testing, what is the PRIMARY LLMOps concern?
A) Focusing primarily on user experience improvements and response formatting
B) Maximizing scalability by deploying larger cloud-based LLM clusters
C) Achieving faster responses by reducing model checkpoints and updates
D) Maintaining data privacy and minimizing security risks from external services
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B | Question # 3 Answer: D | Question # 4 Answer: D | Question # 5 Answer: D |
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