FAB Framework

FAB Framework image
The FAB framework, also called the FAB method, is a prompting structure for using a large language model (LLM) in boundary analysis, where each boundary value is described by its Field, Advantage and Business value. It turns a generic list of minimum, maximum and invalid values into context-rich boundaries that are tied to product risk.

Why it matters: Asking an LLM for "boundary values for the login feature" tends to return the same tidy, generic list every time, with no reasons behind it. Boundaries are everywhere and no team can test them all. FAB filters the noise: the Advantage explains why a value is worth testing, and the Business value links it to real users, risks and goals, so testers can prioritise.

In practice: The three parts are:

  • Field: the variable or input under boundary analysis.
  • Advantage: why exploring its edges reveals something other values might miss.
  • Business value: why the test matters to users, risk and the business.

A typical prompt names the feature and product, asks for the most important boundaries using FAB in a table, and ends by inviting the model to ask a few questions about the context first. Those questions surface assumptions and constraints the tester might otherwise miss.

Examples:

  • Testing a driving licence application's date of birth field one day before and exactly on the minimum legal age.
  • An LLM asking whether learner and full licences have different age rules before proposing boundaries.
  • A junior tester using the Advantage column to learn why a value matters, not just what it is.

Common pitfalls:

  • Dropping the request for the model to ask questions, so it fills gaps with generic assumptions.
  • Accepting the business value statements without checking them against the real rules, such as the legal age in the target jurisdiction.

What does FAB stand for in testing? Field, Advantage and Business value. It structures LLM prompts so each boundary value comes with a reason.

Can the FAB framework be used without an LLM? Yes. The same three questions work as a checklist for any tester prioritising boundary values by hand.
Explore MoT
Test Forward 2027 ยท Software Quality in the age of AI image
Tue, 19 Jan 2027
Test Forward is one afternoon at Station F with the QA and engineering people closing that gap in their own teams.
Prompting for Testers image
Unleash the power of generative AI to boost your software testing and day-to-day tech tasks
Into The Motaverse image
Into the MoTaverse is a podcast by Ministry of Testing, hosted by Rosie Sherry, exploring the people, insights, and systems shaping quality in modern software teams.
Subscribe to our newsletter