A food-coop membership GUI already has a keyword library (Login, JoinShare, PayDues). Which GenAI regression ask best fits implementing automated scripts?
Select an answer to reveal the explanation.
Short Explanation
Keywords are the coop’s shared toolbox—Login, JoinShare, PayDues. Few-shot or structured prompts that map those keywords onto cases draft keyword-driven regression scripts. A strategy essay without scripts leaves the toolbox unused.
Full Explanation
For a food-coop membership GUI that already has a keyword library (Login, JoinShare, PayDues), the best GenAI regression ask for implementing automated scripts is a few-shot or structured prompt that maps keywords to cases and drafts keyword-driven scripts. Civic cooperative membership testing stays maintainable when automation reuses the house keyword vocabulary instead of inventing brittle low-level calls. Asking only for a multi-year strategy roadmap fails because strategy prose does not implement keyword scripts for the current suite. Ignoring the keyword library to invent unrelated driver calls fails by maintainability concept and fragments civic automation standards across shared volunteer maintainers. Measuring neuron coverage of an LLM that drafted membership emails fails because model coverage is not keyword-driven GUI scripting for the coop application. Exam caveat: when a keyword library exists, GenAI should be steered to compose with those keywords rather than free-form drivers. Operational check: provide sample keyword mappings and cases, generate scripts, execute against the coop GUI in a test tenant, reject any step that bypasses the civic keyword library without documented exception, and commit only reviewed keyword-driven diffs.