Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Leveraging Combinatorial Coverage in the Machine Learning Product Lifecycle

Published

Author(s)

Jaganmohan Chandrasekaran, erin lanus, tyler cody, laura freeman, Raghu N. Kacker, M S Raunak, D. Richard Kuhn

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

Keywords

Machine Learning, Combinatorial Coverage, Combinatorial Testing, Test generation, Model Maintenance, Regression Testing

Citation

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 December 8, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created June 27, 2024, Updated July 17, 2024