49 citations · 279 across the 48 of their papers we have counts for
5 papers · 1 filter
LLM-Explorer: Towards Efficient and Affordable LLM-based Exploration for Mobile Apps
Shanhui Zhao, Hao Wen, Wenjie Du +5
Large language models (LLMs) have opened new opportunities for automated mobile app exploration, an important and challenging problem that used to suffer from the difficulty of gen…
DroidBot-GPT: GPT-powered UI Automation for Android
Hao Wen, Hongming Wang, Jiaxuan Liu +1
This paper introduces DroidBot-GPT, a tool that utilizes GPT-like large language models (LLMs) to automate the interactions with Android mobile applications. Given a natural langua…
WhyGen: Explaining ML-powered Code Generation by Referring to Training Examples
Weixiang Yan, Yuanchun Li
Deep learning has demonstrated great abilities in various code generation tasks. However, despite the great convenience for some developers, many are concerned that the code genera…
Dynamic Slicing for Deep Neural Networks
Ziqi Zhang, Yuanchun Li, Yao Guo +2
Program slicing has been widely applied in a variety of software engineering tasks. However, existing program slicing techniques only deal with traditional programs that are constr…
Humanoid: A Deep Learning-based Approach to Automated Black-box Android App Testing
Yuanchun Li, Ziyue Yang, Yao Guo +1
Automated input generators are widely used for large-scale dynamic analysis of mobile apps. Such input generators must constantly choose which UI element to interact with and how t…