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The Pipeline for the Continuous Development of Artificial Intelligence Models -- Current State of Research and Practice
To ease the development process, continuous pipelines for AI have become an active research area where consolidated and in-depth analysis regarding the terminology, triggers, tasks, and challenges is required.
Data Smells: Categories, Causes and Consequences, and Detection of Suspicious Data in AI-based Systems
High data quality is fundamental for today's AI-based systems.
Probabilistic Software Modeling: A Data-driven Paradigm for Software Analysis
Software systems are complex, and behavioral comprehension with the increasing amount of AI components challenges traditional testing and maintenance strategies. The lack of tools and methodologies for behavioral software comprehension leaves developers to testing and debugging that work in the boundaries of known scenarios.
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