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ISQI CT-GenAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Managing Risks of Generative AI in Software Testing | 25% | - Data privacy, security, and compliance concerns - Validation, verification, and mitigation strategies - Hallucinations, bias, inaccuracy, and consistency risks |
| Topic 2: Introduction to Generative AI for Software Testing | 15% | - Use cases across the testing lifecycle - Capabilities and limitations relevant to testing - Core concepts: Generative AI, LLMs, foundation models |
| Topic 3: Prompt Engineering for Effective Software Testing | 35% | - Iterative refinement and evaluation of prompts - Prompt patterns for test design, data generation, automation - Principles and structure of effective prompts |
| Topic 4: Deploying and Integrating GenAI in Test Organisations | 15% | - Measuring value and continuous improvement - Strategy, governance, and adoption roadmap - Roles, skills, and team readiness |
| Topic 5: LLM-Powered Test Infrastructure | 10% | - AI agents and integration with test tools - Architecture and deployment considerations - RAG, fine-tuning, and model adaptation |
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
1. Which statement BEST contrasts interaction style and scope?
A) Chatbots enforce fixed workflows; LLM apps support free-form exploration beneficial for software testing
B) Chatbots enable conversational interactions; LLM apps provide capabilities for defined test tasks.
C) Both are identical aside from UI theme.
D) Chatbots require API integration; LLM apps do not.
2. What BEST protects sensitive test data at rest and in transit?
A) Rely on obfuscation instead of encryption
B) Disable TLS and rely on VPN only
C) Use public file shares with read-only links
D) Enforce role-based access controls
3. 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) Generate conditions -> prioritize by risk -> map to requirements to find gaps
B) Prioritize requirements -> generate conditions -> review defects
C) Generate prioritized conditions in one shot -> verify coverage
D) Detect requirement defects -> generate conditions -> prioritize
4. Which competency MOST helps testers steer LLMs to produce useful, on-policy testware?
A) Writing low-level device drivers
B) Configuring network routers
C) Mastering prompt engineering
D) Designing custom CPU instructions
5. 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
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: A | Question # 4 Answer: C | Question # 5 Answer: D |
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