21 citations · 32 across the 11 of their papers we have counts for
12 papers
We Must Have Missed This Comment: Detecting and Repairing Stale Function References in Linux Kernel Comments
Kexin Sun, Yunbo Lyu, Xutong Ma +6
As the Linux kernel evolves, code comments may become outdated, as the functions they reference can be refactored or removed independently without corresponding updates to the comm…
Improving LLM-Based Go Code Review through Issue-List Generation and Context Augmentation
Kexin Sun, Yucong Guan, Jiaqi Sun +6
LLMs have shown strong potential for automating code review, yet their practical utility depends heavily on the design of generation and context strategies. In this paper, we inves…
AACR-Bench: Evaluating Automatic Code Review with Holistic Repository-Level Context
Lei Zhang, Yongda Yu, Minghui Yu +11
High-quality evaluation benchmarks are pivotal for deploying Large Language Models (LLMs) in Automated Code Review (ACR). However, existing benchmarks suffer from two critical limi…
Brevity is the Soul of Wit: Condensing Code Changes to Improve Commit Message Generation
Hongyu Kuang, Ning Zhang, Hui Gao +6
Commit messages are valuable resources for describing why code changes are committed to repositories in version control systems (e.g., Git). They effectively help developers unders…
Does AI Code Review Lead to Code Changes? A Case Study of GitHub Actions
Kexin Sun, Hongyu Kuang, Sebastian Baltes +6
AI-based code review tools automatically review and comment on pull requests to improve code quality. Despite their growing presence, little is known about their actual impact. We…
AUCAD: Automated Construction of Alignment Dataset from Log-Related Issues for Enhancing LLM-based Log Generation
Hao Zhang, Dongjun Yu, Lei Zhang +6
Log statements have become an integral part of modern software systems. Prior research efforts have focused on supporting the decisions of placing log statements, such as where/wha…
AVIATE: Exploiting Translation Variants of Artifacts to Improve IR-based Traceability Recovery in Bilingual Software Projects
Kexin Sun, Yiding Ren, Hongyu Kuang +5
Traceability plays a vital role in facilitating various software development activities by establishing the traces between different types of artifacts (e.g., issues and commits in…
TRIAD: Automated Traceability Recovery based on Biterm-enhanced Deduction of Transitive Links among Artifacts
Hui Gao, Hongyu Kuang, Wesley K. G. Assunção +5
Traceability allows stakeholders to extract and comprehend the trace links among software artifacts introduced across the software life cycle, to provide significant support for so…
Using Consensual Biterms from Text Structures of Requirements and Code to Improve IR-Based Traceability Recovery
Hui Gao, Hongyu Kuang, Kexin Sun +6
Traceability approves trace links among software artifacts based on whether two artifacts are related by system functionalities. The traces are valuable for software development, b…
Modeling Review History for Reviewer Recommendation:A Hypergraph Approach
Guoping Rong, Yifan Zhang, Lanxin Yang +3
Modern code review is a critical and indispensable practice in a pull-request development paradigm that prevails in Open Source Software (OSS) development. Finding a suitable revie…
Exploiting the Unique Expression for Improved Sentiment Analysis in Software Engineering Text
Kexin Sun, Hui Gao, Hongyu Kuang +4
Sentiment analysis on software engineering (SE) texts has been widely used in the SE research, such as evaluating app reviews or analyzing developers sentiments in commit messages.…
Macro action selection with deep reinforcement learning in StarCraft
Sijia Xu, Hongyu Kuang, Zhi Zhuang +3
StarCraft (SC) is one of the most popular and successful Real Time Strategy (RTS) games. In recent years, SC is also widely accepted as a challenging testbed for AI research becaus…