91 citations · 94 across the 7 of their papers we have counts for
8 papers
Bug Report Specification Refinement with Trajectory Guidance for Automated Program Repair
S M Farah Al Fahim, Md Nakhla Rafi, Md Ahasanuzzaman +5
Bug reports serve as task specifications for repository-level automated program repair (APR) agents, but they often describe only the observed failure and omit repair-relevant info…
LogSemFuse: Semantic Evidence Fusion for Explainable Log Anomaly Detection
Hassan Jabri, Zeyang Ma, Zhijie Wang +1
Log anomaly detection is critical for reliability monitoring and failure diagnosis in modern software systems. Existing model-based detectors provide useful anomaly signals, but th…
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…
Crash Report Enhancement with Large Language Models: An Empirical Study
S M Farah Al Fahim, Md Nakhla Rafi, Zeyang Ma +3
Crash reports are central to software maintenance, yet many lack the diagnostic detail developers need to debug efficiently. We examine whether large language models can enhance cr…
Discovery of Timeline and Crowd Reaction of Software Vulnerability Disclosures
Yi Wen Heng, Zeyang Ma, Haoxiang Zhang +3
Reusing third-party libraries increases productivity and saves time and costs for developers. However, the downside is the presence of vulnerabilities in those libraries, which can…
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…
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…
LLMParser: An Exploratory Study on Using Large Language Models for Log Parsing
Zeyang Ma, An Ran Chen, Dong Jae Kim +2
Logs are important in modern software development with runtime information. Log parsing is the first step in many log-based analyses, that involve extracting structured information…