LiveDroid: identifying and preserving mobile app state in volatile runtime environments
Umar Farooq, Zhijia Zhao, Manu Sridharan, Iulian Neamtiu
Abstract
Mobile operating systems, especially Android, expose apps to a volatile runtime environment. The app state that reflects past user interaction and system environment updates (e.g., battery status changes) can be destroyed implicitly, in response to runtime configuration changes (e.g., screen rotations) or memory pressure. Developers are therefore responsible for identifying app state affected by volatility and preserving it across app lifecycles. When handled inappropriately, the app may lose state or end up in an inconsistent state after a runtime configuration change or when users return to the app. To free developers from this tedious and error-prone task, we propose a systematic solution, LiveDroid, which precisely identifies the necessary part of the app state that needs to be preserved across app lifecycles, and automatically saves and restores it. LiveDroid consists of: (i) a static analyzer that reasons about app source code and resource files to pinpoint the program variables and GUI properties that represent the necessary app state, and (ii) a runtime system that manages the state saving and recovering. We implemented LiveDroid as a plugin in Android Studio and a patching tool for APKs. Our evaluation shows that LiveDroid can be successfully applied to 966 Android apps. A focused study with 36 Android apps shows that LiveDroid identifies app state much more precisely than an existing solution that includes all mutable program variables but ignores GUI properties. As a result, on average, LiveDroid is able to reduce the costs of state saving and restoring by 16.6X (1.7X - 141.1X) and 9.5X (1.1X - 43.8X), respectively. Furthermore, compared with the manual state handling performed by developers, our analysis reveals a set of 46 issues due to incomplete state saving/restoring, all of which can be successfully eliminated by LiveDroid.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers4
- An Empirical Study of Functional Bugs in Android AppsYiheng Xiong, Mengqian Xu, Ting Su, Jingling Sun et al.ISSTA 2023 · 40 citations
- Detecting and fixing data loss issues in Android appsWunan Guo, Zhen Dong, Liwei Shen, Wei Tian et al.ISSTA 2022 · 17 citations
- The ART of Sharing Points-to Analysis: Reusing Points-to Analysis Results Safely and EfficientlyShashin Halalingaiah, Vijay Sundaresan, Daryl Maier, V. Krishna NandivadaOOPSLA 2024 · 2 citations
- jwmalloc: A Verified Memory Allocator for Mobile DevicesJiawei Wang, Ming Fu, Ruixian Wang, Chao Xu et al.OSDI 2026
Builds on1
Related papers
- DDLDroid: Efficiently Detecting Data Loss Issues in Android AppsYuhao Zhou, Wei SongISSTA 2023 · 1 citation
- Transparent Runtime Change Handling for Android AppsZizhan Chen, Zili ShaoASPLOS 2023 · 1 citation
- PermDroid: automatically testing permission-related behaviour of Android applicationsShuaihao Yang, Zigang Zeng, Wei SongISSTA 2022 · 10 citations
- Data loss detector: automatically revealing data loss bugs in Android appsOliviero Riganelli, Simone Paolo Mottadelli, Claudio Rota, Daniela Micucci et al.ISSTA 2020 · 28 citations
- Detecting resource utilization bugs induced by variant lifecycles in AndroidYifei Lu, Minxue Pan, Yu Pei, Xuandong LiISSTA 2022 · 1 citation
