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ISQI CT-GenAI Exam Syllabus Topics:

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

2. Which consideration BEST aligns LLM choice with organizational goals in a GenAI testing strategy?

A) Select broad-coverage models offering diverse functionalities for various test scenarios
B) Select open-source models prioritizing creativity over compliance or performance consistency
C) Select LLMs aligned to measurable test outcomes, compatible with current infrastructure
D) Select models with maximum vendor visibility and strong online presence to ensure reliability

3. A tester uploads crafted images that steer the LLM into validating non-existent acceptance criteria. Which attack vector is this?

A) Request manipulation
B) Data poisoning
C) Data exfiltration
D) Malicious code generation

4. 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

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

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

Solutions: