9 papers · 1 filter
LLM4Log: A Systematic Review of Large Language Model-based Log Analysis
Zeyang Ma, Jinqiu Yang, Tse-Hsun Chen
Software systems generate massive, evolving, semi-structured logs that are central to reliability engineering and AIOps, yet difficult to analyze at scale under drift and limited l…
SBEST: Spectrum-Based Fault Localization Without Fault-Triggering Tests
Md Nakhla Rafi, Lorena Barreto Simedo Pacheco, An Ran Chen +3
Fault localization is a critical step in software maintenance. Yet, many existing techniques, such as Spectrum-Based Fault Localization (SBFL), rely heavily on the availability of…
A Multi-Agent Approach to Fault Localization via Graph-Based Retrieval and Reflexion
Md Nakhla Rafi, Dong Jae Kim, Tse-Hsun Chen +1
Identifying and resolving software faults remains a challenging and resource-intensive process. Traditional fault localization techniques, such as Spectrum-Based Fault Localization…
LibreLog: Accurate and Efficient Unsupervised Log Parsing Using Open-Source Large Language Models
Zeyang Ma, Dong Jae Kim, Tse-Hsun Chen
Log parsing is a critical step that transforms unstructured log data into structured formats, facilitating subsequent log-based analysis. Traditional syntax-based log parsers are e…
Studying and Benchmarking Large Language Models For Log Level Suggestion
Yi Wen Heng, Zeyang Ma, Zhenhao Li +3
Large Language Models (LLMs) have become a focal point of research across various domains, including software engineering, where their capabilities are increasingly leveraged. Rece…
Back to the Future! Studying Data Cleanness in Defects4J and its Impact on Fault Localization
Md Nakhla Rafi, An Ran Chen, Tse-Hsun Chen +1
For software testing research, Defects4J stands out as the primary benchmark dataset, offering a controlled environment to study real bugs from prominent open-source systems. Howev…