Characterizing Technical Debt and Antipatterns in AI-Based Systems: A Systematic Mapping Study
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IEEE
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http://xplorestaging.ieee.org/ielx7/9462944/9462954/09463054.pdf?arnumber=9463054
Cited by 22 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Technical debt in AI-enabled systems: On the prevalence, severity, impact, and management strategies for code and architecture;Journal of Systems and Software;2024-10
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3. The Nature of Technical Debt in the Development of Descriptive Models for MBSE;INCOSE International Symposium;2024-07
4. Analyzing the Evolution and Maintenance of ML Models on Hugging Face;Proceedings of the 21st International Conference on Mining Software Repositories;2024-04-15
5. Unmasking Data Secrets: An Empirical Investigation into Data Smells and Their Impact on Data Quality;Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI;2024-04-14
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