20 citations · 24 across the 6 of their papers we have counts for
6 papers · 1 filter
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-…
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…
MBFL-DKMR: Improving Mutation-based Fault Localization through Denoising-based Kill Matrix Refinement
Hengyuan Liu, Xia Song, Yong Liu +1
Software debugging is a critical and time-consuming aspect of software development, with fault localization being a fundamental step that significantly impacts debugging efficiency…
An Empirical Study on Challenges for LLM Application Developers
Xiang Chen, Chaoyang Gao, Chunyang Chen +2
In recent years, large language models (LLMs) have seen rapid advancements, significantly impacting various fields such as computer vision, natural language processing, and softwar…
ConDefects: A New Dataset to Address the Data Leakage Concern for LLM-based Fault Localization and Program Repair
Yonghao Wu, Zheng Li, Jie M. Zhang +1
With the growing interest on Large Language Models (LLMs) for fault localization and program repair, ensuring the integrity and generalizability of the LLM-based methods becomes pa…
Large Language Models in Fault Localisation
Yonghao Wu, Zheng Li, Jie M. Zhang +3
Large Language Models (LLMs) have shown promise in multiple software engineering tasks including code generation, program repair, code summarisation, and test generation. Fault loc…