65 citations · 192 across the 26 of their papers we have counts for
26 papers
VulKey: Automated Vulnerability Repair Guided by Domain-Specific Repair Patterns
Jia Li, Zhuangbin Chen, Yuxin Su +1
The increasing prevalence of software vulnerabilities highlights the need for effective Automatic Vulnerability Repair (AVR) tools. While LLM-based approaches are promising, they s…
ComBench: A Repo-level Real-world Benchmark for Compilation Error Repair
Jia Li, Zeyang Zhuang, Zhuangbin Chen +3
Compilation errors pose pervasive and critical challenges in software development, significantly hindering productivity. Therefore, Automated Compilation Error Repair (ACER) techni…
KPIRoot+: An Efficient Integrated Framework for Anomaly Detection and Root Cause Analysis in Large-Scale Cloud Systems
Wenwei Gu, Renyi Zhong, Guangba Yu +8
To ensure the reliability of cloud systems, their performance is monitored using KPIs (key performance indicators). When issues arise, root cause localization identifies KPIs respo…
COCA: Generative Root Cause Analysis for Distributed Systems with Code Knowledge
Yichen Li, Yulun Wu, Jinyang Liu +4
Runtime failures are commonplace in modern distributed systems. When such issues arise, users often turn to platforms such as Github or JIRA to report them and request assistance.…
L4: Diagnosing Large-scale LLM Training Failures via Automated Log Analysis
Zhihan Jiang, Junjie Huang, Zhuangbin Chen +6
As Large Language Models (LLMs) show their capabilities across various applications, training customized LLMs has become essential for modern enterprises. However, due to the compl…
Demystifying and Extracting Fault-indicating Information from Logs for Failure Diagnosis
Junjie Huang, Zhihan Jiang, Jinyang Liu +7
Logs are imperative in the maintenance of online service systems, which often encompass important information for effective failure mitigation. While existing anomaly detection met…
TraceMesh: Scalable and Streaming Sampling for Distributed Traces
Zhuangbin Chen, Zhihan Jiang, Yuxin Su +2
Distributed tracing serves as a fundamental element in the monitoring of cloud-based and datacenter systems. It provides visibility into the full lifecycle of a request or operatio…
LUNAR: Unsupervised LLM-based Log Parsing
Junjie Huang, Zhihan Jiang, Zhuangbin Chen +1
Log parsing serves as an essential prerequisite for various log analysis tasks. Recent advancements in this field have improved parsing accuracy by leveraging the semantics in logs…
FaultProfIT: Hierarchical Fault Profiling of Incident Tickets in Large-scale Cloud Systems
Junjie Huang, Jinyang Liu, Zhuangbin Chen +7
Postmortem analysis is essential in the management of incidents within cloud systems, which provides valuable insights to improve system's reliability and robustness. At CloudA, fa…
MTAD: Tools and Benchmarks for Multivariate Time Series Anomaly Detection
Jinyang Liu, Wenwei Gu, Zhuangbin Chen +3
Key Performance Indicators (KPIs) are essential time-series metrics for ensuring the reliability and stability of many software systems. They faithfully record runtime states to fa…
LILAC: Log Parsing using LLMs with Adaptive Parsing Cache
Zhihan Jiang, Jinyang Liu, Zhuangbin Chen +6
Log parsing transforms log messages into structured formats, serving as the prerequisite step for various log analysis tasks. Although a variety of log parsing approaches have been…
Practical Anomaly Detection over Multivariate Monitoring Metrics for Online Services
Jinyang Liu, Tianyi Yang, Zhuangbin Chen +4
As modern software systems continue to grow in terms of complexity and volume, anomaly detection on multivariate monitoring metrics, which profile systems' health status, becomes m…
Maat: Performance Metric Anomaly Anticipation for Cloud Services with Conditional Diffusion
Cheryl Lee, Tianyi Yang, Zhuangbin Chen +2
Ensuring the reliability and user satisfaction of cloud services necessitates prompt anomaly detection followed by diagnosis. Existing techniques for anomaly detection focus solely…
Prism: Revealing Hidden Functional Clusters from Massive Instances in Cloud Systems
Jinyang Liu, Zhihan Jiang, Jiazhen Gu +6
Ensuring the reliability of cloud systems is critical for both cloud vendors and customers. Cloud systems often rely on virtualization techniques to create instances of hardware re…
A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We?
Zhihan Jiang, Jinyang Liu, Junjie Huang +6
Log data have facilitated various tasks of software development and maintenance, such as testing, debugging and diagnosing. Due to the unstructured nature of logs, log parsing is t…
Identifying Performance Issues in Cloud Service Systems Based on Relational-Temporal Features
Wenwei Gu, Jinyang Liu, Zhuangbin Chen +7
Cloud systems are susceptible to performance issues, which may cause service-level agreement violations and financial losses. In current practice, crucial metrics are monitored per…
Log-based Anomaly Detection based on EVT Theory with feedback
Jinyang Liu, Junjie Huang, Yintong Huo +6
System logs play a critical role in maintaining the reliability of software systems. Fruitful studies have explored automatic log-based anomaly detection and achieved notable accur…
Incident-aware Duplicate Ticket Aggregation for Cloud Systems
Jinyang Liu, Shilin He, Zhuangbin Chen +10
In cloud systems, incidents are potential threats to customer satisfaction and business revenue. When customers are affected by incidents, they often request customer support servi…
Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attention
Cheryl Lee, Tianyi Yang, Zhuangbin Chen +3
Prompt and accurate detection of system anomalies is essential to ensure the reliability of software systems. Unlike manual efforts that exploit all available run-time information,…
Eadro: An End-to-End Troubleshooting Framework for Microservices on Multi-source Data
Cheryl Lee, Tianyi Yang, Zhuangbin Chen +2
The complexity and dynamism of microservices pose significant challenges to system reliability, and thereby, automated troubleshooting is crucial. Effective root cause localization…
Heterogeneous Anomaly Detection for Software Systems via Attentive Multi-modal Learning
Baitong Li, Tianyi Yang, Zhuangbin Chen +3
Prompt and accurate detection of system anomalies is essential to ensure the reliability of software systems. Unlike manual efforts that exploit all available run-time information,…
Adaptive Performance Anomaly Detection for Online Service Systems via Pattern Sketching
Zhuangbin Chen, Jinyang Liu, Yuxin Su +4
To ensure the performance of online service systems, their status is closely monitored with various software and system metrics. Performance anomalies represent the performance deg…
Graph-based Incident Aggregation for Large-Scale Online Service Systems
Zhuangbin Chen, Jinyang Liu, Yuxin Su +5
As online service systems continue to grow in terms of complexity and volume, how service incidents are managed will significantly impact company revenue and user trust. Due to the…
Experience Report: Deep Learning-based System Log Analysis for Anomaly Detection
Zhuangbin Chen, Jinyang Liu, Wenwei Gu +2
Logs have been an imperative resource to ensure the reliability and continuity of many software systems, especially large-scale distributed systems. They faithfully record runtime…