Which ONE of the following options describes a scenario of A/B testing the LEAST? SELECT ONE OPTION

A/B testing is a controlled experiment that compares two versions (A and B) of a single variable to determine which version performs better. The core idea is to test a change in a component (e.g., website design, ML model algorithm, offer text) while keeping other factors constant. Comparing the performance of a single ML system on two different input datasets does not fit this model. This is an evaluation of the system's robustness or performance across different data distributions, not a comparison between two versions of the system itself.

A. This is a classic A/B test, comparing two website versions (A and B) to measure user acceptance, a key performance indicator.
B. This is a typical A/B test in a recommendation system, where two different offers (A and B) are compared for effectiveness.
D. This is a form of A/B testing (often called a champion/challenger model) where two ML implementations (A and B) are compared on the same data.

1. ISTQB

"ISTQB Certified Tester AI Testing (CT-AI) Syllabus

" Version 1.0

2021. Section 3.3.3

"A/B Testing

" describes it as a method to compare two versions of a system under test.

2. Kohavi

R.

Tang

D.

& Xu

Y. (2020). Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. Cambridge University Press. Chapter 1

"Introduction and a Motivating Example

" defines A/B testing as comparing two variants

A and B.