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Constructing Dependable Data-Driven Software With Machine Learning
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DOI：10.1109/MS.2021.3067940.png)
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Abstract
En 中文
Many data-driven software systems present dependability challenges caused by the distribution and dynamicity of their application environments. We investigate machine learning-driven construction techniques combined with pattern-based architecture, showing that system dependability is linked to data and function quality.
Keywords:
Software development managemrny
Machine learning
Data integrity
Data models
Sensors
Training data
Software Construction
Machine Learning
Artificial Intelligence
Data Quality
Dependability
Architecture Pattern
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