Bugs in machine learning-based systems: a faultload benchmark

The rapid escalation of applying Machine Learning (ML) in various domains has led to paying more attention to the quality of ML components. There is then a growth of techniques and tools aiming at improving the quality of ML components and integrating them into the ML-based system safely. Although m...

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Bibliographic Details
Published in:	Empirical software engineering : an international journal Vol. 28; no. 3; p. 62
Main Authors:	Morovati, Mohammad Mehdi, Nikanjam, Amin, Khomh, Foutse, Jiang, Zhen Ming (Jack)
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.06.2023 Springer Nature B.V Springer Verlag
Subjects:	Benchmarks Compilers Computer Science Interpreters Machine learning Programming Languages Reliability engineering Reproducibility Software engineering Software Engineering/Programming and Operating Systems Software reliability Special Issue on Software Testing in the Machine Learning Era Software reliability engineering Software testing Benchmark Machine learning-based system Software bug
ISSN:	1382-3256, 1573-7616
Online Access:	Get full text
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