4 papers · 1 filter
Large Language Models for Fuzz Testing in Microservices: A Systematic Literature Review
Ying Song, Ke Ping, Yuqing Wang +1
Microservice systems (MSS) increasingly rely on heterogeneous APIs whose combinatorial input space and stateful dependencies challenge traditional fuzz testing. Meanwhile, Large La…
Towards LLM Accelerated Rapid Reviews for Software Tool Discovery -- Case for Log Anomaly Detection
Jesse Nyyssölä, Hamza Bin Mazhar, Alexander Bakhtin +6
In software engineering research, the primary outcome is frequently a tool. However, for practitioners and academics alike, it is hard to tell which tools are maintained and do the…
A Comparative Study of Semantic Log Representations for Software Log-based Anomaly Detection
Yuqing Wang, Ying Song, Xiaozhou Li +2
Recent deep learning (DL) methods for log anomaly detection increasingly rely on semantic log representation methods that convert the textual content of log events into vector embe…
AnoMod: A Dataset for Anomaly Detection and Root Cause Analysis in Microservice Systems
Ke Ping, Hamza Bin Mazhar, Yuqing Wang +2
Microservice systems (MSS) have become a predominant architectural style for cloud services. Yet the community still lacks high-quality, publicly available datasets for anomaly det…