Large Language Model vs. Stack Overflow in Addressing Android Permission Related Challenges

The Android permission system regulates access to sensitive mobile device resources such as camera and location. To access these resources, third-party developers need to request permissions. However, the Android permission system is complex and fast-evolving, presenting developers with numerous challenges surrounding compatibility issues, misuse of permissions, and vulnerabilities related to permissions. Our study aims to explore whether Large Language Models (LLMs) can serve as a reliable tool to assist developers in using Android permissions correctly and securely, thereby reducing the risks of misuse and security vulnerabilities in apps. In our study, we analyzed 1,008 Stack Overflow questions related to Android permissions and their accepted answers. In parallel, we generate answers to these questions using a popular LLM tool, ChatGPT. We focused on how well the ChatGPT’s responses align with the accepted answers on Stack Overflow. Our findings show that above 50% of ChatGPT’s answers align with Stack Overflow’s accepted answers. ChatGPT offers better-aligned responses for challenges related to Documentation and Conceptual Understanding, while it provides less aligned answers for Debugging-related issues. In addition, we found that ChatGPT provides more consistent answers for 73.27% questions. Our study demonstrates the potential for using LLMs such as ChatGPT as a supporting tool to help developers navigate Android permission-related problems.CCS CONCEPTS• Security and privacy → Software and application security; • Computing methodologies → Artificial intelligence.