11 papers
Towards the Generalizability of Leveraging ChatGPT in APR via Self-enhancing: An Empirical Study
Qingyuan Li, Chuanyi Li, Yaopeng Yang +3
Automated Program Repair (APR) increasingly relies on Large Language Models (LLMs). ChatGPT-enhanced APR uses techniques such as self-correction and autonomous agents to improve re…
UNICS: Multilingual Code Search via Unified Pseudocode and Contrastive Transfer Learning
Ye Fan, Jidong Ge, Chuanyi Li +2
While pre-trained models have achieved remarkable success in code search, their multilingual capabilities remain a major hurdle, plagued by data imbalance, cross-lingual semantic i…
Chiseling Out Efficiency: Structured Skeleton Supervision for Efficient Code Generation
Yu Yu, Zhihong Sun, Jia Li +8
Large Language Models (LLMs) are capable of generating syntactically correct and functionally complete programs, greatly streamlining software development. However, recent studies…
FailureMem: A Failure-Aware Multimodal Framework for Autonomous Software Repair
Ruize Ma, Yilei Jiang, Shilin Zhang +7
Multimodal Automated Program Repair (MAPR) extends traditional program repair by requiring models to jointly reason over source code, textual issue descriptions, and visual artifac…
RepoRepair: Leveraging Code Documentation for Repository-Level Automated Program Repair
Zhongqiang Pan, Chuanyi Li, Wenkang Zhong +3
Automated program repair (APR) struggles to scale from isolated functions to full repositories, as it demands a global, task-aware understanding to locate necessary changes. Curren…
Ensembling Large Language Models for Code Vulnerability Detection: An Empirical Evaluation
Zhihong Sun, Jia Li, Yao Wan +7
Code vulnerability detection is crucial for ensuring the security and reliability of modern software systems. Recently, Large Language Models (LLMs) have shown promising capabiliti…
Empirical Study of Code Large Language Models for Binary Security Patch Detection
Qingyuan Li, Binchang Li, Cuiyun Gao +2
Security patch detection (SPD) is crucial for maintaining software security, as unpatched vulnerabilities can lead to severe security risks. In recent years, numerous learning-base…
Feature Request Analysis and Processing: Tasks, Techniques, and Trends
Feifei Niu, Chuanyi Li, Haosheng Zuo +2
Feature requests are proposed by users to request new features or enhancements of existing features of software products, which represent users' wishes and demands. Satisfying user…
Refactoring Bug-Inducing: Improving Defect Prediction with Code Change Tactics Analysis
Feifei Niu, Junqian Shao, Christoph Mayr-Dorn +5
Just-in-time defect prediction (JIT-DP) aims to predict the likelihood of code changes resulting in software defects at an early stage. Although code change metrics and semantic fe…
Enhancement Report Approval Prediction: A Comparative Study of Large Language Models
Haosheng Zuo, Feifei Niu, Chuanyi Li
Enhancement reports (ERs) serve as a critical communication channel between users and developers, capturing valuable suggestions for software improvement. However, manually process…
When Deep Learning Meets Information Retrieval-based Bug Localization: A Survey
Feifei Niu, Chuanyi Li, Kui Liu +2
Bug localization is a crucial aspect of software maintenance, running through the entire software lifecycle. Information retrieval-based bug localization (IRBL) identifies buggy co…