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Shilin He
Shilin He
Microsoft Research
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
Experience report: system log analysis for anomaly detection
S He, J Zhu, P He, MR Lyu
ISSRE 2016, 207-218, 2016
5802016
Tools and benchmarks for automated log parsing.
J Zhu, S He, J Liu, P He, Q Xie, Z Zheng, MR Lyu
ICSE 2019, 2019
464*2019
An evaluation study on log parsing and its use in log mining
P He, J Zhu, S He, J Li, MR Lyu
DSN 2016, 654-661, 2016
2852016
Towards automated log parsing for large-scale log data analysis
P He, J Zhu, S He, J Li, MR Lyu
IEEE TDSC 15 (6), 931-944, 2017
2162017
Loghub: A large collection of system log datasets towards automated log analytics
S He, J Zhu, P He, MR Lyu
arXiv preprint arXiv:2008.06448, 2020
2102020
Identifying impactful service system problems via log analysis
S He, Q Lin, JG Lou, H Zhang, MR Lyu, D Zhang
ESEC/FSE 2018, 60-70, 2018
1662018
A Survey on Automated Log Analysis for Reliability Engineering
S He, P He, Z Chen, T Yang, Y Su, MR Lyu
ACM Computing Surveys (CSUR), 2021
1572021
Characterizing the natural language descriptions in software logging statements
P He, Z Chen, S He, MR Lyu
ASE 2018, 178-189, 2018
902018
Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression
J Liu, J Zhu, S He, P He, Z Zheng, MR Lyu
ASE 2019, 2019
612019
UniParser: A Unified Log Parser for Heterogeneous Log Data
Y Liu, X Zhang, S He, H Zhang, L Li, Y Kang, Y Xu, M Ma, Q Lin, Y Dang, ...
WWW 2022, 2022
462022
Towards Understanding Neural Machine Translation with Word Importance
S He, Z Tu, X Wang, L Wang, MR Lyu, S Shi
EMNLP 2019, 2019
372019
Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine Translation
Y Hao, S He, W Jiao, Z Tu, M Lyu, X Wang
NAACL 2021, 2020
262020
Onion: identifying incident-indicating logs for cloud systems
X Zhang, Y Xu, S Qin, S He, B Qiao, Z Li, H Zhang, X Li, Y Dang, Q Lin, ...
ESEC/FSE 2021, 1253-1263, 2021
232021
Data Rejuvenation: Exploiting Inactive Training Examples for Neural Machine Translation
W Jiao, X Wang, S He, I King, MR Lyu, Z Tu
EMNLP 2020, 2020
222020
Fighting the Fog of War: Automated Incident Detection for Cloud Systems
L Li, X Zhang, X Zhao, P Zhao, B Qiao, S He, P Lee, J Sun, F Gao, L Yang, ...
USENIX ATC 2021, 131-146, 2021
212021
SPINE: A Scalable Log Parser with Feedback Guidance
X Wang, X Zhang, L Li, S He, H Zhang, Y Liu, L Zheng, Y Kang, Q Lin, ...
ESEC/FSE 2022, 1198-1208, 2022
202022
An Empirical Investigation of Missing Data Handling in Cloud Node Failure Prediction
M Ma, Y Liu, Y Tong, H Li, P Zhao, Y Xu, H Zhang, S He, L Wang, Y Dang, ...
ESEC/FSE 2022, 1453-1464, 2022
132022
Did We Miss Something Important? Studying and Exploring Variable-Aware Log Abstraction
Z Li, C Luo, THP Chen, W Shang, S He, Q Lin, D Zhang
ICSE 2023, 0
12*
An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection
Y Li, X Zhang, S He, Z Chen, Y Kang, J Liu, L Li, Y Dang, F Gao, Z Xu, ...
ACM SIGOPS Operating Systems Review 56 (1), 1-7, 2022
112022
Imdiffusion: Imputed diffusion models for multivariate time series anomaly detection
Y Chen, C Zhang, M Ma, Y Liu, R Ding, B Li, S He, S Rajmohan, Q Lin, ...
arXiv preprint arXiv:2307.00754, 2023
102023
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