2 papers
cs.SE2025
Improving Code Understanding in Large Language Models through Concept-Aware Consistency Learning
Xiaoning Ren, Qiang Hu, Wei Ma +6
Large language models (LLMs) have recently shown impressive results on diverse code-related tasks, benefiting from large-scale training and instruction tuning. However, studies rev…
cs.SE2025
Scheduzz: Constraint-based Fuzz Driver Generation with Dual Scheduling
Yan Li, Wenzhang Yang, Yuekun Wang +4
Fuzzing a library requires experts to understand the library usage well and craft high-quality fuzz drivers, which is tricky and tedious. Therefore, many techniques have been propo…