Last year’s defect tickets feed a predictor that only assigns categories such as “install” or “pay.” A second tool drafts new cases from this sprint’s stories. How should a tester classify these two uses?
Select an answer to reveal the explanation.
Short Explanation
One tool stamps folders; the other writes new pages. Categorizing past defects is classical ML-style prediction. Drafting fresh cases from stories is generative AI. Same shop, different roles—do not merge the labels.
Full Explanation
The syllabus contrasts classical ML uses that categorize or predict problems with GenAI’s role creating new content. Assigning install or pay labels to historical tickets fits the classical pattern. Drafting new cases from current stories fits generative AI. Calling both GenAI, both classical ML, or swapping in deep learning and symbolic AI blurs the Chapter 1 distinction testers need for adjacent test-shop examples.