Chandrasekaran, J.
, Lanus, E.
, cody, T.
, Freeman, L.
, Kacker, R.
, Raunak, M.
and Kuhn, D.
(2024),
Leveraging Combinatorial Coverage in the Machine Learning Product Lifecycle, Computer (IEEE Computer), [online], https://doi.org/10.1109/MC.2024.3366142, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936815
(Accessed October 3, 2025)
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Leveraging Combinatorial Coverage in the Machine Learning Product Lifecycle
Published
Author(s)
Jaganmohan Chandrasekaran, erin lanus, tyler cody, laura freeman, , ,
Abstract
The data-intensive nature of machine learning (ML)-enabled systems introduces unique challenges in test and evaluation. We present an overview of combinatorial coverage, exploring its applications across the ML-enabled system lifecycle and its potential to address key limitations in performing test and evaluation for ML-enabled systems.Citation
Computer (IEEE Computer)
Volume
57
Issue
7
Pub Type
Journals
Download Paper
Keywords
Machine Learning, Combinatorial Coverage, Combinatorial Testing, Test generation, Model Maintenance, Regression Testing
Citation
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Created June 27, 2024, Updated July 17, 2024