11 citations · 31 across the 21 of their papers we have counts for
22 papers
From General Agents to RCA Experts: A Self-Evolving Harness for Root Cause Analysis
Haiyu Huang, Jiewei Lyu, Zhihan Jiang +5
Automated root cause analysis (RCA) with large language models (LLMs) has drawn growing attention. Today, SREs typically automate RCA with LLMs in one of two ways: directly using a…
AutoSQL: Extracting SQL Templates from Imperative ORM Code in Large-Scale Repositories
Junsong Pu, Yichen Li, Zhuangbin Chen +2
Suboptimal SQL queries can significantly degrade the performance of cloud systems, motivating the extraction and auditing of SQL statements before deployment. However, Go ORM frame…
SmartRAG: Native Graph-Based RAG for Mobile Device
Zhihan Jiang, Meng Li, Shenghao Liu +6
Deploying large language models (LLMs) as personal assistants on mobile devices demands privacy, low latency, and offline availability, yet the computational cost of giant models c…
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +355
Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…
ErrorPrism: Reconstructing Error Propagation Paths in Cloud Service Systems
Junsong Pu, Yichen Li, Zhuangbin Chen +6
Reliability management in cloud service systems is challenging due to the cascading effect of failures. Error wrapping, a practice prevalent in modern microservice development, enr…
LogPilot: Intent-aware and Scalable Alert Diagnosis for Large-scale Online Service Systems
Zhihan Jiang, Jinyang Liu, Yichen Li +7
Effective alert diagnosis is essential for ensuring the reliability of large-scale online service systems. However, on-call engineers are often burdened with manually inspecting ma…
Trace Sampling 2.0: Code Knowledge Enhanced Span-level Sampling for Distributed Tracing
Yulun Wu, Guangba Yu, Zhihan Jiang +2
Distributed tracing is an essential diagnostic tool in microservice systems, but the sheer volume of traces places a significant burden on backend storage. A common approach to mit…
UniSage: A Unified and Post-Analysis-Aware Sampling for Microservices
Zhouruixing Zhu, Zhihan Jiang, Tianyi Yang +1
Traces and logs serve as the backbone of observability in microservice architectures, yet their sheer volume imposes prohibitive storage and computational burdens. To reduce overhe…
CCISolver: End-to-End Detection and Repair of Method-Level Code-Comment Inconsistency
Renyi Zhong, Yintong Huo, Wenwei Gu +6
Comments within code serve as a crucial foundation for software documentation, facilitating developers to communicate and understand the code effectively. However, code-comment inc…
Towards Mitigating API Hallucination in Code Generated by LLMs with Hierarchical Dependency Aware
Yujia Chen, Mingyu Chen, Cuiyun Gao +3
Application Programming Interfaces (APIs) are crucial in modern software development. Large Language Models (LLMs) assist in automated code generation but often struggle with API h…
LLMPrism: Black-box Performance Diagnosis for Production LLM Training Platforms
Zhihan Jiang, Rui Ren, Guangba Yu +8
Large Language Models (LLMs) have brought about revolutionary changes in diverse fields, rendering LLM training of utmost importance for modern enterprises. To meet this demand, mu…
Hierarchical Prediction-based Management for LMaaS Systems
Zhihan Jiang, Yujie Huang, Guangba Yu +3
Large Language Models (LLMs) have revolutionized numerous domains, driving the rise of Language-Model-as-a-Service (LMaaS) platforms that process millions of queries daily. These p…
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…
Go Static: Contextualized Logging Statement Generation
Yichen Li, Yintong Huo, Renyi Zhong +6
Logging practices have been extensively investigated to assist developers in writing appropriate logging statements for documenting software behaviors. Although numerous automatic…
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…
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…
Exploring the Effectiveness of LLMs in Automated Logging Generation: An Empirical Study
Yichen Li, Yintong Huo, Zhihan Jiang +5
Automated logging statement generation supports developers in documenting critical software runtime behavior. Given the great success in natural language generation and programming…