A compost-site scale house wants reject/accept to be identical every time the same truck weight and moisture reading arrive. Their vision sorter, given the same hopper photo twice, can emit slightly different grade labels. How should a tester classify those behaviors?
Select an answer to reveal the explanation.
Short Explanation
Same truck weight in, same accept/reject out: that scale house is conventional and deterministic. The vision sorter can slap a different grade on the same hopper photo, which is the probabilistic, not-always-repeatable behavior testers plan oracles around. Identical outputs do not prove a neural network.
Full Explanation
Conventional programmed behavior is expected to be deterministic for the same input. AI-based classifiers are typically probabilistic and may not repeat the same label. Treating both as deterministic, both as models, or reversing the labels misses the contrast testers use when planning oracles and repeatability checks.