一句话：提出 Chime，按启动模式区分 Activity 实例，上下文敏感建模 Activity 转换，提升 Android 静态分析精度。
现有 Android 静态分析以上下文不敏感的方式建模 Activity 转换，无法区分同一 Activity 类在不同启动模式（launch mode）下的不同实例，从而降低了 Activity 回调相关指针分析的精度，并可能产生不可行的 Activity 转换路径。本文提出 Chime，一种感知启动模式的上下文敏感 Activity 转换分析：它依据 Activity 的启动模式对其不同实例分别建模，上下文敏感地刻画 Activity 之间的转换，并与对象敏感（object-sensitive）指针分析协同工作，从而更精确地跟踪 Activity 实例及其回调。摘要未报告具体的实验评估与量化结果。
Existing static analyses model activity transitions in Android apps context-insensitively, making it impossible to distinguish different activity launch modes, reducing the pointer analysis precision for an activity's callbacks, and potentially resulting in infeasible activity transition paths. In this paper, we introduce Chime, a launch-mode-aware context-sensitive activity transition analysis that models different instances of an activity class according to its launch mode and the transitions between activities context-sensitively, by working together with an object-sensitive pointer analysis.
DOI 原文 ·
@inproceedings{paperbot4433,
title = {Launch-mode-aware context-sensitive activity transition analysis},
author = {Yifei Zhang and Yulei Sui and Jingling Xue},
booktitle = {ICSE},
year = {2018},
doi = {10.1145/3180155.3180188}
}