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Compatibility Issue Detection for Android Apps Based on Path-Sensitive Semantic Analysis

Sen Yang, Sen Chen, Lingling Fan, Sihan Xu, Zhanwei Hui, Song Huang

2023Year
12Citations
4Top-tier citations

Abstract

Android API-related compatibility issues have be-come a severe problem and significant challenge for app devel-opers due to the well-known Android fragmentation issues. To address this problem, many effective approaches such as app-based and API lifetime-based methods have been proposed to identify incompatible API usages. However, due to the various implementations of API usages and different API invoking paths, there is still a significant weakness of existing approaches, i.e., introducing a massive number of false positives (FP) and false negatives (FN). To this end, in this paper, we propose PSDroid, an automated compatibility detection approach for Android apps, which aims to reduce FPs and FNs by overcoming several technical bottlenecks. Firstly, we make substantial efforts to carry out a preliminary study to summarize a set of novel API usages with diverse checking implementations. Secondly, we construct a refined API lifetime database by leveraging a semantic resolving analysis on all existing Android SDK frameworks. Based on the above two key phases, we design and implement a novel path-sensitive semantic approach to effectively and automatically detect incompatibility issues. To demonstrate the performance, we compared with five existing approaches (i.e., FicFinder, ACRYL, CIDER, IctAPIFinder, and CID) and the results show that PSDroid outperforms existing tools. We also conducted an in-depth root cause analysis to comprehensively explain the ability of PSDroid in reducing FPs and FNs. Finally, 18/30 reported issues have been confirmed and further fixed by app developers.

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