The Causal Testing Framework is composed of a causal inference-driven architecture designed for functional black-box testing. It leverages graphical causal inference (CI) techniques to specify and evaluate software behaviour from a black-box perspective. Within this framework, causal directed acyclic graphs (DAGs) are used to represent the expected cause–effect relationships between the inputs and outputs of the system under test, supported by mathematical foundations for designing statistical procedures that enable causal inference. Each causal test case targets the causal effect of a specific intervention on the system under test--that is, a deliberate modification to the input configuration expected to produce a corresponding change in one or more outputs.