3 papers
cs.SE2025
Exploring the Potential and Limitations of Large Language Models for Novice Program Fault Localization
Hexiang Xu, Hengyuan Liu, Yonghao Wu +3
Novice programmers often face challenges in fault localization due to their limited experience and understanding of programming syntax and logic. Traditional methods like Spectrum-…
cs.SE2025
FLIMs: Fault Localization Interference Mutants, Definition, Recognition and Mitigation
Hengyuan Liu, Zheng Li, Donghua Wang +3
Mutation-based Fault Localization (MBFL) has been widely explored for automated software debugging, leveraging artificial mutants to identify faulty code entities. However, MBFL fa…
cs.SE2025
LLMs are Bug Replicators: An Empirical Study on LLMs' Capability in Completing Bug-prone Code
Liwei Guo, Sixiang Ye, Zeyu Sun +6
Large Language Models (LLMs) have demonstrated remarkable performance in code completion. However, the training data used to develop these models often contain a significant amount…