5.1 Describe AI's Role Across the Software Development Lifecycle (requirements, Prototyping, Implementation, Testing, Deployment) AI-TECHNICAL-PRACTITIONER Practice Questions (Page 3)

Questions 11–15

1. 11application · easy

   A development team is prototyping a new feature. They have a rough idea of the user interface and want to quickly generate a working front-end code skeleton that they can refine. Which AI capability would be most useful for this task?

   • AAutomated release management to deploy the prototype automatically.
   • BAutomated code generation from a high-level description of the UI components.
   • CAutomated test case generation for the UI components.
   • DPredictive failure analysis to identify potential UI bugs.
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2. 12expert · hard

   A company is deploying a new version of its application. They have implemented AI-based predictive monitoring that can detect anomalies and trigger automated rollbacks. However, the monitoring system sometimes generates false positives, causing unnecessary rollbacks. How should the team address this trade-off between safety and stability?

   • AAdjust the AI model's sensitivity threshold to reduce false positives, accepting that some real issues may be missed.
   • BIncrease the sensitivity threshold to catch more issues, accepting more false positives.
   • CDisable automated rollback and rely on manual rollback procedures.
   • DUse AI to generate more test cases to reduce the need for rollback.
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4. 13application · medium

   A company deploys updates to its web application frequently. After a recent deployment, they noticed an increase in error rates and want to automatically roll back to the previous version if similar issues occur in the future. Which AI-driven deployment practice would best enable this?

   • AUse AI to write more unit tests before each deployment, but rely on manual monitoring after release.
   • BUse AI to monitor application metrics in real time and trigger an automated rollback when anomalies are detected.
   • CUse AI to schedule deployments during low-traffic periods to minimize impact.
   • DUse AI to generate release notes for each deployment, but keep manual rollback procedures.
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5. 14foundation · easy

   Which AI application is most directly associated with the implementation phase of the SDLC?

   • APredictive monitoring
   • BAutomated release management
   • CAutomated test case generation
   • DAutomated code generation
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6. 15foundation · easy

   How does AI improve collaboration across the entire software development lifecycle?

   • ABy eliminating the need for code reviews
   • BBy replacing all manual testing with automated tools
   • CBy automatically writing all documentation
   • DBy providing insights and automation that connect activities from requirements to deployment
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