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20242026
most citedLogUpdater: Automated Detection and Repair of Specific Defects in Logging Statements

6 citations · 6 across the 6 of their papers we have counts for

collaborators

8 papers

cs.SE2026

From Noisy Telemetry to Actionable Warnings: GPU Failure Prediction in Industrial Clusters

Yongqian Sun, Run Zhu, Wenwei Gu +9

GPU clusters are critical infrastructure for AI services, but accurate and actionable GPU failure prediction remains a problem in production settings. We study ticket-linked teleme…

cs.SE2025

AutoLogger: A Multi-Agent Framework for the End-to-End Automated Logging

Renyi Zhong, Yintong Huo, Wenwei Gu +2

Software logging is critical for system observability, yet developers face a dual crisis of costly overlogging and risky underlogging. Existing automated logging tools often overlo…

cs.SE2025

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…

cs.SE2025

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…

cs.SE2025

Larger Is Not Always Better: Exploring Small Open-source Language Models in Logging Statement Generation

Renyi Zhong, Yichen Li, Guangba Yu +4

Developers use logging statements to create logs that document system behavior and aid in software maintenance. As such, high-quality logging is essential for effective maintenance…

cs.SE2025

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…

cs.CR2025

Towards Imperceptible Adversarial Attacks for Time Series Classification with Local Perturbations and Frequency Analysis

Wenwei Gu, Renyi Zhong, Jianping Zhang +1

Adversarial attacks in time series classification (TSC) models have recently gained attention due to their potential to compromise model robustness. Imperceptibility is crucial, as…

cs.SE2024★ 6 cited

LogUpdater: Automated Detection and Repair of Specific Defects in Logging Statements

Renyi Zhong, Yichen Li, Jinxi Kuang +3

Developers use logging statements to track software runtime behaviors and system status. Yet, unclear or misleading logs can hide true execution patterns and hinder software mainte…