12 papers
Agent-Based Test Assertion Generation via Diverse Perspective Aggregation
Dong Wang, Qiaoyu Han, Lin Yang +3
Test assertions are critical elements of unit tests, serving as checkpoints to validate expected behavior and ensure software correctness. Numerous techniques have been proposed to…
Evaluating Fuzz Testing for Reinforcement Learning Agents
Zhibin Kang, Hanmo You, Dong Wang +2
Reinforcement Learning (RL) agents are increasingly deployed in safety-critical domains such as robotics, autonomous driving, and drone control, where unexpected behaviors may lead…
KernelDiag: Agent-Based Root Cause Diagnosis for Kernel Crashes
Weijing Wang, Zan Wang, Dong Wang +2
The Linux kernel is one of the most complex software systems, where automated fuzzing continuously exposes thousands of crashes, yet root-cause diagnosis remains a manual and time-…
Large Language Models for Multi-Lingual Equivalent Mutant Detection: An Extended Empirical Study
Honglin Shu, Zhao Tian, Dong Wang +5
Mutation testing is a powerful technique for ensuring software quality. However, the presence of equivalent mutants introduces unnecessary costs and biases, limiting its practical…
Characterizing and Mitigating False-Positive Bug Reports in the Linux Kernel
Jiashuo Tian, Dong Wang, Chen Yang +3
False-positive bug reports represent a significant yet underexplored challenge in the development and maintenance of the Linux kernel. They occur when correct system behavior is mi…
Evaluating Large Language Models for Multilingual Vulnerability Detection at Dual Granularities
Honglin Shu, Michael Fu, Junji Yu +4
Various deep learning-based approaches utilizing pre-trained language models (PLMs) have been proposed for automated vulnerability detection. With recent advancements in large lang…