10 papers
TATG: Tracking-Aware Testing Objective for LLM-based Test Generation
Guancheng Wang, Qinghua Xu, Lionel C. Briand
Complex Java methods remain challenging for automated unit test generation because achieving high coverage and fault detection often requires satisfying branch-specific testing req…
BeSpec: Behavior-Level Specification Alignment for Code Generation
Qinghua Xu, Guancheng Wang, Boxi Yu +1
LLMs have made substantial progress on automated code generation from natural-language descriptions of desired behavior (intent). Most existing methods improve generated programs t…
Uncertainty-Guided Label Rebalancing for CPS Safety Monitoring
John Ayotunde, Qinghua Xu, Guancheng Wang +1
Safety monitoring is essential for Cyber-Physical Systems (CPSs). However, unsafe events are rare in real-world CPS operations, creating an extreme class imbalance that degrades sa…
A Cross-Modal Prompt Injection Attack against Large Vision-Language Models with Image-Only Perturbation
Hao Yang, Zhuo Ma, Yang Liu +3
Large vision-language models (LVLMs) have emerged as a powerful paradigm for multimodal intelligence, but their growing deployment also expands the attack surface of prompt injecti…
Characterizing the Failure Modes of LLMs in Resolving Real-World GitHub Issues
Yanjie Jiang, Yian Huang, Guancheng Wang +3
Large Language Models (LLMs) are increasingly deployed to resolve real-world GitHub issues. However, despite their potential, the specific failure modes of these models in complex…
Call-Chain-Aware LLM-Based Test Generation for Java Projects
Guancheng Wang, Qinghua Xu, Lionel C. Briand +2
Large language models (LLMs) have recently shown strong potential for generating project-level unit tests. However, existing state-of-the-art approaches primarily rely on execution…