Pei, Dan

Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

Su, Y., Zhao, Y., Niu, C., Liu, R., Sun, W., & Pei, D. (2019) · Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Anomaly Detection Techniques and ApplicationsSoftware System Performance and Reliability

Cited by 1,804

LogAnomaly: Unsupervised Detection of Sequential and Quantitative Anomalies in Unstructured Logs

Meng, W., Liu, Y., Zhu, Y., Zhang, S., Pei, D., Liu, Y., Chen, Y., Zhang, R., Tao, S., Sun, P., et al. (2019) · Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence

Software System Performance and ReliabilityAnomaly Detection Techniques and Applications

Cited by 708

Multivariate Time Series Anomaly Detection and Interpretation using Hierarchical Inter-Metric and Temporal Embedding

Li, Z., Zhao, Y., Han, J., Su, Y., Jiao, R., Wen, X., & Pei, D. (2021) · Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining

Anomaly Detection Techniques and ApplicationsSoftware System Performance and Reliability

Cited by 464

Unsupervised Detection of Microservice Trace Anomalies through Service-Level Deep Bayesian Networks

Liu, P., Xu, H., Ouyang, Q., Jiao, R., Chen, Z., Zhang, S., Yang, J., Mo, L., Zeng, J., Xue, W., et al. (2020) · 2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE)

Software System Performance and ReliabilityAnomaly Detection Techniques and Applications

Cited by 252

Practical Root Cause Localization for Microservice Systems via Trace Analysis

Li, Z., Chen, J., Jiao, R., Zhao, N., Wang, Z., Zhang, S., Wu, Y., Jiang, L., Yan, L., Wang, Z., et al. (2021) · 2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS)

Software System Performance and ReliabilitySoftware Testing and Debugging Techniques

Cited by 159

Robust Failure Diagnosis of Microservice System Through Multimodal Data

Zhang, S., Jin, P., Lin, Z., Sun, Y., Zhang, B., Xia, S., Li, Z., Zhong, Z., Ma, M., Jin, W., et al. (2023) · IEEE Transactions on Services Computing

Software System Performance and ReliabilitySoftware Engineering Research

Cited by 118

An empirical investigation of practical log anomaly detection for online service systems

Zhao, N., Wang, H., Li, Z., Peng, X., Wang, G., Pan, Z., Wu, Y., Feng, Z., Wen, X., Zhang, W., et al. (2021) · Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering

Software System Performance and ReliabilityAnomaly Detection Techniques and Applications

Cited by 77

G-RCA: a generic root cause analysis platform for service quality management in large IP networks

Yan, H., Breslau, L., Ge, Z., Massey, D., Pei, D., & Yates, J. (2012) · IEEE/ACM Transactions on Networking

Mobile Agent-Based Network ManagementSoftware-Defined Networks and 5G

Cited by 72

Failure Diagnosis in Microservice Systems: A Comprehensive Survey and Analysis

Zhang, S., Xia, S., Fan, W., Shi, B., Xiong, X., Zhong, Z., Ma, M., Sun, Y., & Pei, D. (2026) · ACM Transactions on Software Engineering and Methodology

Software System Performance and ReliabilityDistributed systems and fault tolerance

Cited by 57

Continuous delivery of personalized assessment and feedback in agile software engineering projects

Bai, X., Li, M., Pei, D., Li, S., & Ye, D. (2018) · Proceedings of the 40th International Conference on Software Engineering: Software Engineering Education and Training

Software Engineering Techniques and PracticesProblem and Project Based Learning

Cited by 39

Flow-of-action: SOP-enhanced LLM-based multi-agent system for root cause analysis

Pei, C., Wang, Z., Liu, F., Li, Z., Liu, Y., He, X., Kang, R., Zhang, T., Chen, J., Li, J., et al. (2025) · Companion Proceedings of the ACM on Web Conference 2025

Software System Performance and ReliabilitySoftware Engineering Research

Cited by 33

MonitorAssistant: simplifying cloud service monitoring via large language models

Yu, Z., Ma, M., Zhang, C., Qin, S., Kang, Y., Bansal, C., Rajmohan, S., Dang, Y., Pei, C., Pei, D., et al. (2024) · Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering

Software System Performance and ReliabilityAnomaly Detection Techniques and Applications

Cited by 32

Chain-of-event: interpretable root cause analysis for microservices through automatically learning weighted event causal graph

Yao, Z., Pei, C., Chen, W., Wang, H., Su, L., Jiang, H., Xie, Z., Nie, X., & Pei, D. (2024) · Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering

Software System Performance and ReliabilitySoftware Engineering Research

Cited by 21

Efficient and Robust Trace Anomaly Detection for Large-Scale Microservice Systems

Zhang, S., Pan, Z., Liu, H., Jin, P., Sun, Y., Ouyang, Q., Wang, J., Jia, X., Zhang, Y., Yang, H., et al. (2023) · 2023 IEEE 34th International Symposium on Software Reliability Engineering (ISSRE)

Software System Performance and ReliabilityAnomaly Detection Techniques and Applications

Cited by 14

Constructing Large-Scale Real-World Benchmark Datasets for AIOps

Li, Z., Zhao, N., Zhang, S., Sun, Y., Chen, P., Wen, X., Ma, M., & Pei, D. (2022) · arXiv

Software System Performance and ReliabilityCloud Computing and Resource Management

Cited by 11

FlowXpert: Expertizing Troubleshooting Workflow Orchestration with Knowledge Base and Multi-Agent Coevolution

Shi, B., Luo, Y., Wang, J., Zhao, Y., Zhang, S., Hao, B., Zhao, C., Sun, Y., Zhang, Z., Sun, R., et al. (2025) · Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2

Software System Performance and ReliabilityCloud Computing and Resource Management

Cited by 7

A comprehensive benchmark and empirical study of trace anomaly detection

Sun, Y., Shao, M., Nie, X., Yang, K., Li, X., Hao, B., Zhang, S., Pei, C., He, D., Li, Y., et al. (2025) · IEEE Transactions on Services Computing

Software System Performance and ReliabilityAnomaly Detection Techniques and Applications

Cited by 1