A/B testing (also called bucket testing or split testing) is an experimental method for comparing two versions of a single variable by exposing a subject to variant A or variant B and measuring which produces a more effective response. Supporting it in software requires two mechanisms: a feature flag, a boolean (or otherwise typed) value that toggles which variant of a behavior is presented, and a set of key performance indicators (KPIs) with a reporting mechanism that records user actions as tracked events so the variants' outcomes can be compared. This practice belongs to the domain of user experience research and software engineering practice, and it intersects with data privacy regulation (e.g., the GDPR), since collecting behavioral data to evaluate variants requires user consent and mechanisms for data access and erasure.
A/B testing (also called bucket testing or split testing) is an experimental method for comparing two versions of a single variable by exposing a subject to variant A or variant B and measuring which…