Taxonomy of Aging-related Bugs in Deep Learning Libraries

Author:

Liu Zhihao1,Zheng Yang2,Du Xiaoting3,Hu Zheng2,Ding Wenjie1,Miao Yanming4,Zheng Zheng1

Affiliation:

1. School of Automation Science and Electrical Engineering,Beihang University,Beijing,China

2. School of Computer Science (National Pilot Software Engineering School)Beijing University of Posts and Telecommunications,Beijing,China

3. Huawei,TTE lab,Shenzhen,China

4. Central Software Institute, Huawei,Shenzhen,China

Publisher

IEEE

Cited by 5 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. SGT: Aging-related bug prediction via semantic feature learning based on graph-transformer;Journal of Systems and Software;2024-11

2. LLM-BRC: A large language model-based bug report classification framework;Software Quality Journal;2024-05-24

3. Compatibility Issues in Deep Learning Systems: Problems and Opportunities;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

4. IFCM: An improved Fuzzy C-means clustering method to handle Class Overlap on Aging-related Software Bug Prediction;2023 IEEE 34th International Symposium on Software Reliability Engineering (ISSRE);2023-10-09

5. Cross-Project Aging-Related Bug Prediction Based on Feature Transfer and Class Imbalance Learning;2023 IEEE 34th International Symposium on Software Reliability Engineering Workshops (ISSREW);2023-10-09

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