Foster, M. orcid.org/0000-0001-8233-9873, Clark, A. orcid.org/0000-0002-6830-0566, Wild, C. orcid.org/0009-0009-1195-1497 et al. (6 more authors) (2025) The causal testing framework. Journal of Open Source Software, 10 (107). 7739. ISSN 2475-9066
Abstract
Scientific models possess several properties that make them notoriously difficult to test, including a complex input space, long execution times, and non-determinism, rendering existing testing techniques impractical. In fields such as epidemiology, where researchers seek answers to challenging causal questions, a statistical methodology known as Causal Inference (CI) (Hernán & Robins, 2020; Pearl, 2009) has addressed similar problems, enabling the inference of causal conclusions from noisy, biased, and sparse observational data instead of costly randomised trials. CI works by using domain knowledge to identify and mitigate for biases in the data, enabling them to answer causal questions that concern the effect of changing some feature on the observed outcome. The Causal Testing Framework (CTF) is a software testing framework that uses CI techniques to establish causal effects between software variables from pre-existing runtime data rather than having to collect bespoke, highly curated datasets especially for testing.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2025 The authors. Authors of papers retain copyright and release the work under a Creative Commons Attribution 4.0 International License (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/ |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/T030526/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Mar 2025 13:31 |
Last Modified: | 12 Mar 2025 14:41 |
Status: | Published |
Publisher: | The Open Journal |
Refereed: | Yes |
Identification Number: | 10.21105/joss.07739 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:224188 |