most citedNavigating the Labyrinth: Path-Sensitive Unit Test Generation with Large Language Models

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SE20251 cited

Navigating the Labyrinth: Path-Sensitive Unit Test Generation with Large Language Models

Dianshu Liao, Xin Yin, Shidong Pan +3

Unit testing is essential for software quality assurance, yet writing and maintaining tests remains time-consuming and error-prone. To address this challenge, researchers have prop…

cs.CR2025

A First Look at Privacy Risks of Android Task-executable Voice Assistant Applications

Shidong Pan, Yikai Ge, Xiaoyu Sun

With the development of foundation AI technologies, task-executable voice assistants (VAs) have become more popular, enhancing user convenience and expanding device functionality.…

cs.CR2025

Towards Context-aware Mobile Privacy Notice: Implementation of A Deployable Contextual Privacy Policies Generator

Haochen Gong, Zhen Tao, Shidong Pan +2

Lengthy and legally phrased privacy policies impede users' understanding of how mobile applications collect and process personal data. Prior work proposed Contextual Privacy Polici…

cs.SE2025

Deployability-Centric Infrastructure-as-Code Generation: Fail, Learn, Refine, and Succeed through LLM-Empowered DevOps Simulation

Tianyi Zhang, Shidong Pan, Zejun Zhang +2

Infrastructure-as-Code (IaC) generation holds significant promise for automating cloud infrastructure provisioning. Recent advances in Large Language Models (LLMs) present a promis…

cs.CR2025

Privacy Bills of Materials: A Transparent Privacy Information Inventory for Collaborative Privacy Notice Generation in Mobile App Development

Zhen Tao, Shidong Pan, Zhenchang Xing +5

Privacy regulations mandate that developers must provide authentic and comprehensive privacy notices, e.g., privacy policies or labels, to inform users of their apps' privacy pract…