A QA team has deployed an SLM for log analysis. After three months, they notice the model's accuracy on new log formats has declined. What is the most appropriate action?

Increase the model's temperature to improve creativity

Re-evaluate the model on a new benchmark dataset and fine-tune it if necessary

Ignore the decline because the model was initially accurate

A team needs a model to summarize test execution reports. The summaries will be read by managers who need concise, accurate information. The team has a limited budget and cannot afford a large GPU server. Which model characteristic is most important for this task?

Accuracy and domain specificity

A QA team wants to use a model to automatically classify bug reports by severity. The team has a large dataset of labeled bug reports and wants to fine-tune a model for this specific task. They have access to a cloud GPU service and a budget for training. Which model choice is most appropriate?

Fine-tune an SLM on the labeled dataset

Fine-tune an LLM on the labeled dataset

Certified Tester Testing with Generative AI

Domain 5Objective 3

Selecting LLMs/SLMs for Software Test Tasks CT-GENAI Practice Questions (Page 4)

Part of the Deploying and Integrating Generative AI in Test organizations domain, which makes up ~23% of our current practice bank. ISTQB does not publish an official question count, but from its 60-minute exam (~25–40 total, ~6–9 in this domain), expect 1–1 from this objective — we provide 30 practice questions to prepare you well beyond it. (estimate)

30questions here

6free pages

10concepts

Questions 16–20

16application · medium
A QA team has deployed an SLM for log analysis. After three months, they notice the model's accuracy on new log formats has declined. What is the most appropriate action?
Select an answer first
17application · medium
A team needs a model to summarize test execution reports. The summaries will be read by managers who need concise, accurate information. The team has a limited budget and cannot afford a large GPU server. Which model characteristic is most important for this task?
Select an answer first
18application · medium
A QA team wants to use a model to automatically classify bug reports by severity. The team has a large dataset of labeled bug reports and wants to fine-tune a model for this specific task. They have access to a cloud GPU service and a budget for training. Which model choice is most appropriate?
Select an answer first
19foundation · easy
A test team needs to deploy a model for analyzing sensitive test data. Which deployment consideration is most important to ensure compliance with data protection regulations?
Select an answer first
20foundation · easy
Which integration feature is most important for a language model to work seamlessly with an existing test automation framework?
Select an answer first

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Selecting LLMs/SLMs for Software Test Tasks CT-GENAI Practice Questions (Page 4)

Questions 16–20

A QA team has deployed an SLM for log analysis. After three months, they notice the model's accuracy on new log formats has declined. What is the most appropriate action?

A team needs a model to summarize test execution reports. The summaries will be read by managers who need concise, accurate information. The team has a limited budget and cannot afford a large GPU server. Which model characteristic is most important for this task?

A QA team wants to use a model to automatically classify bug reports by severity. The team has a large dataset of labeled bug reports and wants to fine-tune a model for this specific task. They have access to a cloud GPU service and a budget for training. Which model choice is most appropriate?

A test team needs to deploy a model for analyzing sensitive test data. Which deployment consideration is most important to ensure compliance with data protection regulations?

Which integration feature is most important for a language model to work seamlessly with an existing test automation framework?

Keep studying — Deploying and Integrating Generative AI in Test organizations