How Far Have We Come in Detecting Anomalies in Distributed Systems? An Empirical Study with a Statement-level Fault Injection Method

Author:

Yang Yong,Wu Yifan,Pattabiraman Karthik,Wang Long,Li Ying

Funder

Research and Development

Science and Engineering Research Council

Publisher

IEEE

Cited by 12 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. Process-Oriented GCC Failure Analysis based on Fault Injection;2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD);2024-05-08

2. Hilogx: noise-aware log-based anomaly detection with human feedback;The VLDB Journal;2024-03-28

3. Advanced Machine Learning for Runtime Data Generation;12th Latin-American Symposium on Dependable and Secure Computing;2023-10-16

4. FAQ: Mitigating the Impact of Faults in the Weight Memory of DNN Accelerators through Fault-Aware Quantization;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18

5. An Empirical Study on Change-induced Incidents of Online Service Systems;2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP);2023-05

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