16 citations · 34 across the 16 of their papers we have counts for
16 papers
AgentExecutor: Partial Code Execution via Agentic Context Generation
Junkai Chen, Chengran Yang, Xing Hu +3
Executing code snippets is essential for dynamic program analysis, but it remains challenging to execute an arbitrary code snippet due to issues like missing context and incomplete…
Open the Oyster: Empirical Evaluation and Improvement of Code Reasoning Confidence in LLMs
Shufan Wang, Xing Hu, Junkai Chen +2
With the widespread application of large language models (LLMs) in the field of code intelligence, increasing attention has been paid to the reliability and controllability of thei…
Assessing and Advancing Benchmarks for Evaluating Large Language Models in Software Engineering Tasks
Xing Hu, Feifei Niu, Junkai Chen +5
Large language models (LLMs) are gaining increasing popularity in software engineering (SE) due to their unprecedented performance across various applications. These models are inc…
Automating Comment Generation for Smart Contract from Bytecode
Jianhang Xiang, Zhipeng Gao, Lingfeng Bao +3
Recently, smart contracts have played a vital role in automatic financial and business transactions. To help end users without programming background to better understand the logic…
Understanding Practitioners' Expectations on Clear Code Review Comments
Junkai Chen, Zhenhao Li, Qiheng Mao +3
The code review comment (CRC) is pivotal in the process of modern code review. It provides reviewers with the opportunity to identify potential bugs, offer constructive feedback, a…
Automated Unit Test Refactoring
Yi Gao, Xing Hu, Xiaohu Yang +1
Test smells arise from poor design practices and insufficient domain knowledge, which can lower the quality of test code and make it harder to maintain and update. Manually refacto…
GUIMigrator: Semantics-Preserving Transpilation from Android XML to Compose and SwiftUI
Yi Gao, Xing Hu, Xin Xia +1
Constructing user interfaces (UIs) is one of the most resource-intensive tasks in mobile development, often consuming more than half of overall effort. Although declarative framewo…
CATCODER: Repository-Level Code Generation with Relevant Code and Type Context
Zhiyuan Pan, Xing Hu, Xin Xia +1
Large language models (LLMs) have demonstrated remarkable capabilities in code generation tasks. However, repository-level code generation presents unique challenges, particularly…
Easy over Hard: A Simple Baseline for Test Failures Causes Prediction
Zhipeng Gao, Zhipeng Xue, Xing Hu +2
The test failure causes analysis is critical since it determines the subsequent way of handling different types of bugs, which is the prerequisite to get the bugs properly analyzed…
Automating Zero-Shot Patch Porting for Hard Forks
Shengyi Pan, You Wang, Zhongxin Liu +3
Forking is a typical way of code reuse, which provides a simple way for developers to create a variant software (denoted as hard fork) by copying and modifying an existing codebase…
Reasoning Runtime Behavior of a Program with LLM: How Far Are We?
Junkai Chen, Zhiyuan Pan, Xing Hu +3
Large language models for code (i.e., code LLMs) have shown strong code understanding and generation capabilities. To evaluate the capabilities of code LLMs in various aspects, man…
Pre-training by Predicting Program Dependencies for Vulnerability Analysis Tasks
Zhongxin Liu, Zhijie Tang, Junwei Zhang +2
Vulnerability analysis is crucial for software security. This work focuses on using pre-training techniques to enhance the understanding of vulnerable code and boost vulnerability…
PPT4J: Patch Presence Test for Java Binaries
Zhiyuan Pan, Xing Hu, Xin Xia +3
The number of vulnerabilities reported in open source software has increased substantially in recent years. Security patches provide the necessary measures to protect software from…
PS: Precise Patch Presence Test based on Semantic Symbolic Signature
Qi Zhan, Xing Hu, Zhiyang Li +3
During software development, vulnerabilities have posed a significant threat to users. Patches are the most effective way to combat vulnerabilities. In a large-scale software syste…
Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models
Shuzheng Gao, Wenxin Mao, Cuiyun Gao +4
Pre-trained code models have recently achieved substantial improvements in many code intelligence tasks. These models are first pre-trained on large-scale unlabeled datasets in a t…
Exploiting Library Vulnerability via Migration Based Automating Test Generation
Zirui Chen, Xing Hu, Xin Xia +4
In software development, developers extensively utilize third-party libraries to avoid implementing existing functionalities. When a new third-party library vulnerability is disclo…