CT-GenAI Practice Questions

A.  

iv —> iii —> i —> ii

B.  

iv —> i —> iii —> ii

C.  

iii —> iv —> i —> ii

D.  

i —> iv —> iii —> ii

A.  

A tester configuring the assistant

B.  

End user during normal chat use

C.  

CI server automatically without human input

D.  

Product owner in user stories only

A.  

Few-shot = no examples; Chaining = single prompt; Meta = disable iteration

B.  

Meta = step decomposition; Chaining = zero-shot only; Few-shot = manual optimization

C.  

Chaining = give examples; Few-shot = break tasks; Meta = manual edits only

D.  

Few-shot = examples; Chaining = multi-step prompts; Meta = model helps draft/refine prompts

A.  

Symbolic AI

B.  

Generative AI

C.  

Classical Machine Learning

D.  

Deep Learning

A.  

Discovery; initiation and usage definition; utilization and iteration

B.  

Prototype; pilot; decommission

C.  

Training; certification; outsourcing

D.  

Planning; execution; sign-off

A.  

The number of tokens processed directly determines the carbon intensity of each query

B.  

The location of the data center determines model bias and accuracy levels

C.  

The duration of user sessions primarily affects latency but not power efficiency

D.  

The type of cloud platform affects processing speed but not total energy draw

A.  

Reliance on predefined templates to generate short, factual answers

B.  

Ability to respond to prompts without explicit user instructions

C.  

Ability to trigger automated actions beyond conversation

D.  

Use of a conversational tone and improved response personalization

A.  

Automated compliance validation during AI tool deployment

B.  

Failure to update system documentation within the test process

C.  

Difficulty in aligning project milestones with business outcomes

D.  

Violation of established data handling and regulatory compliance standards

A.  

Role: Act as a test automation engineer with API testing experience. | Context: You are verifying user registration that enforces field and format validation. | Instruction: Generate pytest scripts using requests for both positive (valid) and negative (invalid email, weak password, missing fields) cases. | Input Data: POST /api/register with validation rules for email and password length. | Constraints: Include fixtures, clear assertions, a

B.  

Role: Act as a test automation engineer. | Context: You are creating tests for a registration endpoint. | Instruction: Generate Python test scripts using pytest covering both valid and invalid inputs. | Input Data: POST /api/register with email and password. | Constraints: Follow pytest structure. | Output Format: Provide scripts.

C.  

Role: Act as an automation tester. | Context: You are validating an API endpoint. | Instruction: Generate Python test scripts that send POST requests and validate responses. | Input Data: User credentials. | Constraints: Include basic scenarios with asserts. | Output Format: Provide organized scripts.

D.  

Role: Act as a software engineer. | Context: You are testing registration logic. | Instruction: Create Python scripts to verify endpoint behavior. | Input Data: POST /api/register with test users. | Constraints: Add checks for status codes. | Output Format: Deliver functional scripts.

A.  

Include references to version control systems like Git in the constraints.

B.  

Specify that the role is a test architect specializing in CI/CD pipelines.

C.  

Add a step to review the change log for syntax errors before analysis.

D.  

Include mapping code changes to affected modules, identifying test cases, prioritizing by risk level and change complexity