2 citations · 8 across the 16 of their papers we have counts for
16 papers · 1 filter
Detecting Vulnerability-Inducing Commits via Multi-Stage Reasoning with LLM-Based Agents
Liyou Chen, Hailong Sun, Xiang Gao +1
Detecting vulnerability-inducing commits (VICs) at submission time is critical for improving the security and reliability of software systems. However, this task is highly challeng…
Vulnerability Identification by Harnessing Inter-connected Multi-Source Information
Liyou Chen, Hailong Sun, Xiang Gao +3
The utilization of third-party open-source libraries is widespread in modern software development. Due to the dependency relationships, vulnerabilities within open-source libraries…
Generalizing Test Cases for Comprehensive Test Scenario Coverage
Binhang Qi, Yun Lin, Xinyi Weng +4
Test cases are essential for software development and maintenance. In practice, developers derive multiple test cases from an implicit pattern based on their understanding of requi…
MASFuzzer: Fuzz Driver Generation and Adaptive Scheduling via Multidimensional API Sequences
Xingyu Liu, Zengqin Huang, Xiang Gao +1
Fuzz testing of software libraries relies on fuzz drivers to invoke library APIs. Traditionally, these drivers are written manually by developers - a process that is time-consuming…
InfCode-C++: Intent-Guided Semantic Retrieval and AST-Structured Search for C++ Issue Resolution
Qingao Dong, Mengfei Wang, Hengzhi Zhang +7
Large language model (LLM) agents have recently shown strong performance on repository-level issue resolution, but existing systems are almost exclusively designed for Python and r…
InfCode: Adversarial Iterative Refinement of Tests and Patches for Reliable Software Issue Resolution
KeFan Li, Mengfei Wang, Hengzhi Zhang +7
Large language models have advanced software engineering automation, yet resolving real-world software issues remains difficult because it requires repository-level reasoning, accu…
Code2Bench: Scaling Source and Rigor for Dynamic Benchmark Construction
Zhe Zhang, Runlin Liu, Aishan Liu +3
The evaluation of code-generating Large Language Models (LLMs) is fundamentally constrained by two intertwined challenges: a reliance on static, easily contaminated problem sources…
Generating Project-Specific Test Cases with Requirement Validation Intention
Binhang Qi, Yun Lin, Xinyi Weng +5
Test cases are valuable assets for maintaining software quality. State-of-the-art automated test generation techniques typically focus on maximizing program branch coverage or tran…
Context-Enhanced Vulnerability Detection Based on Large Language Model
Yixin Yang, Bowen Xu, Xiang Gao +1
Vulnerability detection is a critical aspect of software security. Accurate detection is essential to prevent potential security breaches and protect software systems from maliciou…
Agent That Debugs: Dynamic State-Guided Vulnerability Repair
Zhengyao Liu, Yunlong Ma, Jingxuan Xu +4
In recent years, more vulnerabilities have been discovered every day, while manual vulnerability repair requires specialized knowledge and is time-consuming. As a result, many dete…
Type-aware LLM-based Regression Test Generation for Python Programs
Runlin Liu, Zhe Zhang, Yunge Hu +3
Automated regression test generation has been extensively explored, yet generating high-quality tests for Python programs remains particularly challenging. Because of the Python's…
LLM-based Unit Test Generation via Property Retrieval
Zhe Zhang, Xingyu Liu, Yuanzhang Lin +3
Automated unit test generation has been widely studied, with Large Language Models (LLMs) recently showing significant potential. Moreover, in the context of unit test generation,…
Scalable Defect Detection via Traversal on Code Graph
Zhengyao Liu, Xitong Zhong, Xingjing Deng +3
Detecting defects and vulnerabilities in the early stage has long been a challenge in software engineering. Static analysis, a technique that inspects code without execution, has e…
Investigating White-Box Attacks for On-Device Models
Mingyi Zhou, Xiang Gao, Jing Wu +3
Numerous mobile apps have leveraged deep learning capabilities. However, on-device models are vulnerable to attacks as they can be easily extracted from their corresponding mobile…
Software Engineering for OpenHarmony: A Research Roadmap
Li Li, Xiang Gao, Hailong Sun +12
Mobile software engineering has been a hot research topic for decades. Our fellow researchers have proposed various approaches (with over 7,000 publications for Android alone) in t…
Reusing Convolutional Neural Network Models through Modularization and Composition
Binhang Qi, Hailong Sun, Hongyu Zhang +1
With the widespread success of deep learning technologies, many trained deep neural network (DNN) models are now publicly available. However, directly reusing the public DNN models…