activity
20172026
most citedCode Search based on Context-aware Code Translation

56 citations · 235 across the 36 of their papers we have counts for

collaborators

41 papers

cs.CR2026

Security of Agent-Integrated Software: When Human Operations and Agent Actions Coexist

Ding Yang, Yuchen Ling, Shengcheng Yu +2

Agent-Integrated Software (AIS) embeds an intelligent agent in a conventional application, supporting both human operations and agent actions. Human operations let users make preci…

cs.SE2024

Redefining Crowdsourced Test Report Prioritization: An Innovative Approach with Large Language Model

Yuchen Ling, Shengcheng Yu, Chunrong Fang +3

Context: Crowdsourced testing has gained popularity in software testing, especially for mobile app testing, due to its ability to bring diversity and tackle fragmentation issues. H…

cs.SE2024★ 6 cited

TestART: Improving LLM-based Unit Testing via Co-evolution of Automated Generation and Repair Iteration

Siqi Gu, Quanjun Zhang, Kecheng Li +5

Unit testing is crucial for detecting bugs in individual program units but consumes time and effort. Recently, large language models (LLMs) have demonstrated remarkable capabilitie…

cs.SE2024★ 11 cited

Practical, Automated Scenario-based Mobile App Testing

Shengcheng Yu, Chunrong Fang, Mingzhe Du +3

The importance of mobile application (app) quality insurance is increasing with the rapid development of the mobile Internet. Automated test generation approaches, as a dominant di…

cs.CV2024

Towards General Robustness Verification of MaxPool-based Convolutional Neural Networks via Tightening Linear Approximation

Yuan Xiao, Shiqing Ma, Juan Zhai +3

The robustness of convolutional neural networks (CNNs) is vital to modern AI-driven systems. It can be quantified by formal verification by providing a certified lower bound, withi…

cs.SE2024★ 1 cited

Pre-trained Model-based Actionable Warning Identification: A Feasibility Study

Xiuting Ge, Chunrong Fang, Quanjun Zhang +8

Actionable Warning Identification (AWI) plays a pivotal role in improving the usability of static code analyzers. Currently, Machine Learning (ML)-based AWI approaches, which mainl…