Machine Learning Testing: Survey, Landscapes and Horizons

This paper provides a comprehensive survey of techniques for testing machine learning systems; Machine Learning Testing (ML testing) research. It covers 144 papers on testing properties (e.g., correctness, robustness, and fairness), testing components (e.g., the data, learning program, and framework...

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Bibliographic Details

Published in:	IEEE transactions on software engineering Vol. 48; no. 1; pp. 1 - 36
Main Authors:	Zhang, Jie M., Harman, Mark, Ma, Lei, Liu, Yang
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.01.2022 IEEE Computer Society
Subjects:	Data models deep neural network Learning programs Machine learning Machine translation Robustness Software engineering Software testing Training data Trends Workflow
ISSN:	0098-5589, 1939-3520
Online Access:	Get full text
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