An Empirical Study of Refactorings and Technical Debt in Machine Learning Systems

Machine Learning (ML), including Deep Learning (DL), systems, i.e., those with ML capabilities, are pervasive in today's data-driven society. Such systems are complex; they are comprised of ML models and many subsystems that support learning processes. As with other complex systems, ML systems...

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Veröffentlicht in:	Proceedings / International Conference on Software Engineering S. 238 - 250
Hauptverfasser:	Tang, Yiming, Khatchadourian, Raffi, Bagherzadeh, Mehdi, Singh, Rhia, Stewart, Ajani, Raja, Anita
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.05.2021
Schlagworte:	Best practices Complex systems Data mining Deep learning empirical studies machine learning systems Open source software refactoring Software engineering software evolution software repository mining technical debt
ISBN:	1665402962, 9781665402965
ISSN:	1558-1225
Online-Zugang:	Volltext
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