8 papers
Automated Logging Is Language-Sensitive: A Multilingual Benchmark and Empirical Study of LLMs
Renyi Zhong, Yichen Li, Yulun Wu +3
Logging statements are central to debugging, failure diagnosis, and production observability, yet writing them requires developers to decide where to place a logging statement, whi…
Why Does the LLM Stop Computing: An Empirical Study of User-Reported Failures in Open-Source LLMs
Guangba Yu, Zirui Wang, Yujie Huang +4
The democratization of open-source Large Language Models (LLMs) allows users to fine-tune and deploy models on local infrastructure but exposes them to a First Mile deployment land…
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…
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…
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…
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…