3 papers
cs.SE2026
AnomalyGen: Enhancing Log-Based Anomaly Detection with Code-Guided Data Augmentation
Xinyu Li, Yintong Huo, Chenxi Mao +4
Log-based anomaly detection is fundamentally constrained by training data sparsity. Our empirical study reveals that public benchmark datasets cover less than 10% of source code lo…
cs.SE2025
AnomalyGen: An Automated Semantic Log Sequence Generation Framework with LLM for Anomaly Detection
Xinyu Li, Yingtong Huo, Chenxi Mao +4
The scarcity of high-quality public log datasets has become a critical bottleneck in advancing log-based anomaly detection techniques. Current datasets exhibit three fundamental li…
cs.SE2024
eWAPA: An eBPF-based WASI Performance Analysis Framework for WebAssembly Runtimes
Chenxi Mao, Yuxin Su, Shiwen Shan +1
WebAssembly (Wasm) is a low-level bytecode format that can run in modern browsers. With the development of standalone runtimes and the improvement of the WebAssembly System Interfa…