27 citations · 42 across the 24 of their papers we have counts for
9 papers · 1 filter
Towards Automatically Pruning Logging Code with Coding Agents: How Far Are We?
He Yang Yuan, Haonan Zhang, Xin Wang +4
Logging code supports debugging, monitoring, and software maintenance, but excessive logging can add noise, impose runtime overhead, and obscure diagnostic information. While prior…
Do Tool Calls Execute as Intended? Measuring and Repairing Intent-Execution Correspondence in LLM Agents
Boyang Yang, Zhenhao Li, Ziyao Yang +4
Agents built on large language models (LLMs) build and run software through tool calls. A call reaches its program through several hops, and any hop can change the call without not…
TAILOR: Template-Preserving Augmentation for Long-Tailed Log Parsing
Sepideh Hodaeian, Zhenhao Li, An Ran Chen
Log parsing is essential for system log analysis because it supports tasks such as debugging, monitoring, and anomaly detection by transforming unstructured log messages into struc…
AgentExecutor: Partial Code Execution via Agentic Context Generation
Junkai Chen, Chengran Yang, Xing Hu +3
Executing code snippets is essential for dynamic program analysis, but it remains challenging to execute an arbitrary code snippet due to issues like missing context and incomplete…
SWE-NFI: Studying and Benchmarking Coding Agents for Non-Functional Improvements
Pengyu Xue, He Yang Yuan, Xin Wang +6
Although coding agents have achieved impressive performance on correctness-oriented benchmarks, their ability to make behavior-preserving non-functional improvements (NFIs) remains…
Towards Secure Logging: Characterizing and Benchmarking Logging Code Security Issues with LLMs
He Yang Yuan, Xin Wang, Kundi Yao +3
Logging code plays an important role in software systems by recording key events and behaviors, which are essential for debugging and monitoring. However, insecure logging practice…
How Adversarial Environments Mislead Agentic AI?
Zhonghao Zhan, Huichi Zhou, Zhenhao Li +3
Tool-integrated agents are deployed on the premise that external tools ground their outputs in reality. Yet this very reliance creates a critical attack surface. Current evaluation…
ReLog: Execution-Aware Logging with Runtime Feedback for LLM-Oriented Debugging
Xin Wang, Yang Feng, Xiaoqian Jiao +3
Logging statements are essential for software debugging and maintenance. However, existing approaches to automatic logging generation rely on static analysis and produce statements…
LLM4Perf: Large Language Models Are Effective Samplers for Multi-Objective Performance Modeling
Xin Wang, Zhenhao Li, Zishuo Ding
The performance of modern software systems is critically dependent on their complex configuration options. Building accurate performance models to navigate this vast space requires…