A framework for causal testing using causal directed acyclic graphs.
Project description
Causal Testing Framework: A Causal Inference-Driven Software Testing Framework
Causal testing is a causal inference-driven framework for functional black-box testing. This framework utilises graphical causal inference (CI) techniques for the specification and functional testing of software from a black-box perspective. In this framework, we use causal directed acyclic graphs (DAGs) to express the anticipated cause-effect relationships amongst the inputs and outputs of the system-under-test and the supporting mathematical framework to design statistical procedures capable of making causal inferences. Each causal test case focuses on the causal effect of an intervention made to the system-under test. That is, a prescribed change to the input configuration of the system-under-test that is expected to cause a change to some output(s).
Installation
See the readthedocs site for installation instructions.
Documentation
Further information on causal inference, the code, usage and more can be found on the docs
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