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ISQI CT-GenAI Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Fundamentals of Generative AI	20%	- AI Terminology 1. Large Language Models (LLMs) 2. Machine Learning (ML) 3. Generative AI (GenAI) 4. Transformer architecture 5. Deep Learning 6. Tokens and prompts 7. Artificial Intelligence (AI) - AI Development Lifecycle 1. Evaluation 2. Deployment and monitoring 3. Data collection, preparation, and curation 4. Model training and fine-tuning - Generative AI Concepts 1. Alignment and guardrails 2. Training data and context windows 3. AI model behavior 4. Model types (Base, Instruction-tuned, RAG) 5. Emergent capabilities and limitations 6. Hallucinations
Topic 2: Risks and Testing Challenges for Generative AI	30%	- Quality Risks Specific to Generative AI 1. Inconsistent responses across runs 2. Offensive, harmful, or biased content 3. Dependency on external components 4. Incorrect or fabricated outputs (hallucinations) 5. Inappropriate output for the context 6. Input sensitivity (prompt brittleness) - Testing Challenges for Generative AI 1. Regulatory and compliance considerations 2. Complexity of the AI component 3. Test oracle problem 4. Ethical testing concerns 5. Non-deterministic output behavior 6. Subjectivity of quality assessment 7. Coverage challenges
Topic 3: Testing Activities for Generative AI	30%	- Model and Output Evaluation 1. Human evaluation methods 2. Checkpoint testing 3. Metamorphic testing 4. Automated evaluation methods 5. Output correctness and quality assessment - Requirements-Based Testing 1. Functional requirements for AI-based systems 2. Non-functional requirements for AI-based systems 3. AI-related quality requirements - Prompt-Based Testing 1. Test case design using prompts 2. Prompt engineering basics 3. Test data creation with GenAI - Traceability and Documentation 1. Test coverage of AI model components 2. Documentation requirements for AI testing
Topic 4: Tools for Testing Generative AI	20%	- Testing Tools Overview 1. Categories of GenAI testing tools 2. Selecting appropriate tools for specific testing needs - Using Tools for Common Testing Activities 1. Prompt testing tools 2. Security testing tools 3. Model evaluation tools 4. Simulation and monitoring tools

ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:

1. Which factor MOST influences the overall energy consumption of a Generative AI model used in software testing tasks?

A) The number of tokens processed directly determines the carbon intensity of each query
B) The type of cloud platform affects processing speed but not total energy draw
C) The duration of user sessions primarily affects latency but not power efficiency
D) The location of the data center determines model bias and accuracy levels

2. Which competency MOST helps testers steer LLMs to produce useful, on-policy testware?

A) Configuring network routers
B) Writing low-level device drivers
C) Mastering prompt engineering
D) Designing custom CPU instructions

3. Which of the following is NOT a valid form of LLM-driven test data generation?

A) Setting boundary values
B) Creating combinatorial data (e.g., pairwise)
C) Creating production database backups
D) Generating synthetic datasets

4. The model flags anomalies in logs and also proposes partitions for input validation tests. Which metrics BEST evaluate these two outcomes together?

A) Accuracy for anomaly detection and Precision for coverage of valid/invalid partitions
B) Time efficiency for anomaly detection and accuracy for coverage of valid/invalid partitions
C) Diversity for anomaly identification and precision for partitions
D) Precision for anomaly identification and recall for coverage of valid/invalid partitions

5. Your team needs to generate 500 API test cases for a REST API with 50 endpoints. You have documented 10 exemplar test cases that follow your organization's standard format. You want the LLM to generate test cases following the pattern demonstrated in your examples. Which of the following prompting techniques is BEST suited to achieve your goal in this scenario?

A) Prompt chaining
B) Meta prompting
C) Zero-shot prompting
D) Few-shot prompting

Solutions:

Question # 1
Answer: A

Question # 2
Answer: C

Question # 3
Answer: C

Question # 4
Answer: D

Question # 5
Answer: D