240 citations · 248 across the 8 of their papers we have counts for
8 papers · 1 filter
Cleaning Logs for Downstream Tasks (Registered Report)
Zahra G. Yazdi, Van-Hoang Le, Nyyti Saarimäki +3
Background: Software systems generate logs during execution to record critical events and runtime information for troubleshooting and monitoring. However, in practice, logs often c…
Stronger, Cheaper and Demonstration-Free Log Parsing with LLMs
Yi Xiao, Van-Hoang Le, Hongyu Zhang
Log parsing, the process of converting raw log messages into structured formats, is an important initial step for automated analysis of logs of large-scale software systems. Tradit…
OptLLM: Optimal Assignment of Queries to Large Language Models
Yueyue Liu, Hongyu Zhang, Yuantian Miao +2
Large Language Models (LLMs) have garnered considerable attention owing to their remarkable capabilities, leading to an increasing number of companies offering LLMs as services. Di…
LogShrink: Effective Log Compression by Leveraging Commonality and Variability of Log Data
Xiaoyun Li, Hongyu Zhang, Van-Hoang Le +1
Log data is a crucial resource for recording system events and states during system execution. However, as systems grow in scale, log data generation has become increasingly explos…
Log Parsing: How Far Can ChatGPT Go?
Van-Hoang Le, Hongyu Zhang
Software logs play an essential role in ensuring the reliability and maintainability of large-scale software systems, as they are often the sole source of runtime information. Log…
Log Parsing with Prompt-based Few-shot Learning
Van-Hoang Le, Hongyu Zhang
Logs generated by large-scale software systems provide crucial information for engineers to understand the system status and diagnose problems of the systems. Log parsing, which co…
Log-based Anomaly Detection with Deep Learning: How Far Are We?
Van-Hoang Le, Hongyu Zhang
Software-intensive systems produce logs for troubleshooting purposes. Recently, many deep learning models have been proposed to automatically detect system anomalies based on log d…
Log-based Anomaly Detection Without Log Parsing
Van-Hoang Le, Hongyu Zhang
Software systems often record important runtime information in system logs for troubleshooting purposes. There have been many studies that use log data to construct machine learnin…