Can Large Language Models Detect Real-World Android Software Compliance Violations?
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Haoyi, Ran, Huaijin, Tang, Xunzhu |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
GDPR-Bench-Android: A Benchmark for Evaluating Automated GDPR Compliance Detection in Android
by: Ran, Huaijin, et al.
Published: (2025)
by: Ran, Huaijin, et al.
Published: (2025)
Understanding and Detecting Platform-Specific Violations in Android Auto Apps
by: Fakorede, Moshood, et al.
Published: (2025)
by: Fakorede, Moshood, et al.
Published: (2025)
AgentDroid: A Multi-Agent Framework for Detecting Fraudulent Android Applications
by: Pan, Ruwei, et al.
Published: (2025)
by: Pan, Ruwei, et al.
Published: (2025)
Assessing Privacy Compliance of Android Third-Party SDKs
by: Meng, Mark Huasong, et al.
Published: (2024)
by: Meng, Mark Huasong, et al.
Published: (2024)
Towards Understanding Android APIs: Official Lists, Vendor Customizations, and Real-World Usage
by: Wang, Sinan, et al.
Published: (2026)
by: Wang, Sinan, et al.
Published: (2026)
MalLoc: Toward Fine-grained Android Malicious Payload Localization via LLMs
by: Sun, Tiezhu, et al.
Published: (2025)
by: Sun, Tiezhu, et al.
Published: (2025)
Can Language Models Go Beyond Coding? Assessing the Capability of Language Models to Build Real-World Systems
by: Zhao, Chenyu, et al.
Published: (2025)
by: Zhao, Chenyu, et al.
Published: (2025)
LLM-CompDroid: Repairing Configuration Compatibility Bugs in Android Apps with Pre-trained Large Language Models
by: Liu, Zhijie, et al.
Published: (2024)
by: Liu, Zhijie, et al.
Published: (2024)
Benchmarking Large Language Models for Multi-Language Software Vulnerability Detection
by: Zhang, Ting, et al.
Published: (2025)
by: Zhang, Ting, et al.
Published: (2025)
Boosting Open-Source LLMs for Program Repair via Reasoning Transfer and LLM-Guided Reinforcement Learning
by: Tang, Xunzhu, et al.
Published: (2025)
by: Tang, Xunzhu, et al.
Published: (2025)
Automated Update of Android Deprecated API Usages with Large Language Models
by: Mahmud, Tarek, et al.
Published: (2024)
by: Mahmud, Tarek, et al.
Published: (2024)
Can Large Language Models Assist the Comprehension of ROS2 Software Architectures?
by: Duits, Laura, et al.
Published: (2026)
by: Duits, Laura, et al.
Published: (2026)
Evaluating Large Language Models for Detecting Architectural Decision Violations
by: Su, Ruoyu, et al.
Published: (2026)
by: Su, Ruoyu, et al.
Published: (2026)
MT4DP: Data Poisoning Attack Detection for DL-based Code Search Models via Metamorphic Testing
by: Chen, Gong, et al.
Published: (2025)
by: Chen, Gong, et al.
Published: (2025)
Automated Test Transfer Across Android Apps Using Large Language Models
by: Beyzaei, Benyamin, et al.
Published: (2024)
by: Beyzaei, Benyamin, et al.
Published: (2024)
SWE-Perf: Can Language Models Optimize Code Performance on Real-World Repositories?
by: He, Xinyi, et al.
Published: (2025)
by: He, Xinyi, et al.
Published: (2025)
Rethinking Legal Compliance Automation: Opportunities with Large Language Models
by: Hassani, Shabnam, et al.
Published: (2024)
by: Hassani, Shabnam, et al.
Published: (2024)
APPATCH: Automated Adaptive Prompting Large Language Models for Real-World Software Vulnerability Patching
by: Nong, Yu, et al.
Published: (2024)
by: Nong, Yu, et al.
Published: (2024)
Prompting Is All You Need: Automated Android Bug Replay with Large Language Models
by: Feng, Sidong, et al.
Published: (2023)
by: Feng, Sidong, et al.
Published: (2023)
Position Paper: Programming Language Techniques for Bridging LLM Code Generation Semantic Gaps
by: Du, Yalong, et al.
Published: (2025)
by: Du, Yalong, et al.
Published: (2025)
Can Large Language Models Solve Path Constraints in Symbolic Execution?
by: Wang, Wenhan, et al.
Published: (2025)
by: Wang, Wenhan, et al.
Published: (2025)
Large Language Models for Software Testing Education: an Experience Report
by: Yang, Peng, et al.
Published: (2026)
by: Yang, Peng, et al.
Published: (2026)
IDE-Bench: Evaluating Large Language Models as IDE Agents on Real-World Software Engineering Tasks
by: Mateega, Spencer, et al.
Published: (2026)
by: Mateega, Spencer, et al.
Published: (2026)
Evaluating Large Language Models in detecting Secrets in Android Apps
by: Alecci, Marco, et al.
Published: (2025)
by: Alecci, Marco, et al.
Published: (2025)
A Survey on Large Language Models for Software Engineering
by: Zhang, Quanjun, et al.
Published: (2023)
by: Zhang, Quanjun, et al.
Published: (2023)
Evaluating Large Language Models for Time Series Anomaly Detection in Aerospace Software
by: Liu, Yang, et al.
Published: (2026)
by: Liu, Yang, et al.
Published: (2026)
Automated Testing of the GUI of a Real-Life Engineering Software using Large Language Models
by: Rosenbach, Tim, et al.
Published: (2025)
by: Rosenbach, Tim, et al.
Published: (2025)
Prioritizing Software Requirements Using Large Language Models
by: Sami, Malik Abdul, et al.
Published: (2024)
by: Sami, Malik Abdul, et al.
Published: (2024)
Describing Globally Distributed Software Architectures for Tax Compliance
by: Dorner, Michael, et al.
Published: (2023)
by: Dorner, Michael, et al.
Published: (2023)
Patch-CLIP: A Patch-Text Pre-Trained Model
by: Tang, Xunzhu, et al.
Published: (2023)
by: Tang, Xunzhu, et al.
Published: (2023)
Evaluating Code Reasoning Abilities of Large Language Models Under Real-World Settings
by: Liu, Changshu, et al.
Published: (2025)
by: Liu, Changshu, et al.
Published: (2025)
How Effective are Large Language Models in Generating Software Specifications?
by: Xie, Danning, et al.
Published: (2023)
by: Xie, Danning, et al.
Published: (2023)
A Large-Scale Empirical Study of AI-Generated Code in Real-World Repositories
by: Mao, Tianhao, et al.
Published: (2026)
by: Mao, Tianhao, et al.
Published: (2026)
A Benchmark for Language Models in Real-World System Building
by: Jin, Weilin, et al.
Published: (2026)
by: Jin, Weilin, et al.
Published: (2026)
A Pilot Study on Detecting Software Design Patterns with Large Language Models: An Empirical Evaluation
by: Chowdhury, Oishik, et al.
Published: (2026)
by: Chowdhury, Oishik, et al.
Published: (2026)
SAFE: Advancing Large Language Models in Leveraging Semantic and Syntactic Relationships for Software Vulnerability Detection
by: Nguyen, Van, et al.
Published: (2024)
by: Nguyen, Van, et al.
Published: (2024)
Large Language Model-Driven Code Compliance Checking in Building Information Modeling
by: Madireddy, Soumya, et al.
Published: (2025)
by: Madireddy, Soumya, et al.
Published: (2025)
Darkit: A User-Friendly Software Toolkit for Spiking Large Language Model
by: Du, Xin, et al.
Published: (2024)
by: Du, Xin, et al.
Published: (2024)
Comparative Analysis of the Code Generated by Popular Large Language Models (LLMs) for MISRA C++ Compliance
by: Umer, Malik Muhammad
Published: (2025)
by: Umer, Malik Muhammad
Published: (2025)
SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?
by: Ma, Jeffrey Jian, et al.
Published: (2025)
by: Ma, Jeffrey Jian, et al.
Published: (2025)
Similar Items
-
GDPR-Bench-Android: A Benchmark for Evaluating Automated GDPR Compliance Detection in Android
by: Ran, Huaijin, et al.
Published: (2025) -
Understanding and Detecting Platform-Specific Violations in Android Auto Apps
by: Fakorede, Moshood, et al.
Published: (2025) -
AgentDroid: A Multi-Agent Framework for Detecting Fraudulent Android Applications
by: Pan, Ruwei, et al.
Published: (2025) -
Assessing Privacy Compliance of Android Third-Party SDKs
by: Meng, Mark Huasong, et al.
Published: (2024) -
Towards Understanding Android APIs: Official Lists, Vendor Customizations, and Real-World Usage
by: Wang, Sinan, et al.
Published: (2026)