6 papers
From Signals to Behaviors: Evidence-Based Android Malware Detection
Shiwen Song, Yiheng Xiong, Sen Chen +1
Android malware remains a persistent threat, and detecting it accurately is a long-standing open problem. Whether an app is malicious depends on what it actually does and the conte…
MIRAGE: Context-Aware Prompt Injection against Mobile GUI Agents via User-Generated Content
Ruoqi Guo, Yi Liu, Gelei Deng +7
Mobile graphical user interface (GUI) agents driven by vision-language models (VLMs) perceive the screen as rendered pixels and choose actions from what they see, so they cannot re…
From Exploration to Specification: LLM-Based Property Generation for Mobile App Testing
Yiheng Xiong, Shiwen Song, Bo Ma +2
Mobile apps often suffer from functional bugs that do not cause crashes but instead manifest as incorrect behaviors under specific user interactions. Such bugs are difficult to det…
Improving Random Testing via LLM-powered UI Tarpit Escaping for Mobile Apps
Mengqian Xu, Yiheng Xiong, Le Chang +3
Random GUI testing is a widely-used technique for testing mobile apps. However, its effectiveness is limited by the notorious issue -- UI exploration tarpits, where the exploration…
From Natural Language to Executable Properties for Property-based Testing of Mobile Apps
Yiheng Xiong, Ting Su, Jingling Sun +4
Property-based testing (PBT) is a popular software testing methodology and is effective in validating the functionality of mobile applications (apps for short). However, its adopti…
Enhancing Automated Program Repair via Faulty Token Localization and Quality-Aware Patch Refinement
Jiaolong Kong, Xiaofei Xie, Yiheng Xiong +2
Large language models (LLMs) have recently demonstrated strong potential for automated program repair (APR). However, existing LLM-based techniques primarily rely on coarse-grained…