5.1 Describe AI's Role Across the Software Development Lifecycle (requirements, Prototyping, Implementation, Testing, Deployment) AI-TECHNICAL-PRACTITIONER Practice Questions (Page 5)

Questions 21–24

1. 21application · medium

   A company is about to release a major update to its application. The QA team has generated a large number of test cases, but the test execution time is too long to run all of them before the release deadline. Which AI-driven testing strategy would best help them meet the deadline without sacrificing quality?

   • ADeploy the update and rely on AI-based monitoring to catch issues in production.
   • BUse AI to prioritize and execute the most critical test cases first, based on risk analysis.
   • CRun all test cases in parallel using a cloud-based test farm.
   • DReduce the number of test cases by randomly selecting a subset to run.
   Reveal Solution Discussion Select an answer first
2. 22application · medium

   A company wants to reduce the risk of failed deployments by using AI to analyze past deployment data and predict the likelihood of success for a new release. Which AI deployment practice best aligns with this goal?

   • AUse AI to write release notes and documentation for the deployment.
   • BUse AI to monitor the application after deployment and alert on anomalies.
   • CUse AI to analyze historical deployment metrics and identify patterns that correlate with failures.
   • DUse AI to automatically generate deployment scripts for the new release.
   Reveal Solution Discussion Select an answer first
4. 23foundation · easy

   Which AI capability helps minimize downtime during a deployment by deciding when to revert a change?

   • ARollback optimization
   • BAutomated code generation
   • CNatural language processing
   • DPredictive failure analysis
   Reveal Solution Discussion Select an answer first
5. 24application · medium

   A software company wants to implement AI across the SDLC to improve collaboration between development, QA, and operations teams. Which AI integration would most directly enhance collaboration?

   • AUse AI to automate test execution for QA only.
   • BUse AI to generate and share a common set of insights, such as risk assessments and quality metrics, across all phases.
   • CUse AI to automate code generation for developers only.
   • DUse AI to automate deployment for operations only.
   Reveal Solution Discussion Select an answer first