Static executes-before analysis for event driven programs

Rekha R. Pai, Abhishek Uppar, Akshatha Shenoy, Pranshul Kushwaha, D. D'Souza
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Abstract

The executes-before relation between tasks is fundamental in the analysis of Event Driven Programs with several downstream applications like race detection and identifying redundant synchronizations. We present a sound, efficient, and effective static analysis technique to compute executes-before pairs of tasks for a general class of event driven programs. The analysis is based on a small but comprehensive set of rules evaluated on a novel structure called the task post graph of a program. We show how to use the executes-before information to identify disjoint-blocks in event driven programs and further use them to improve the precision of data race detection for these programs. We have implemented our analysis in the Flowdroid framework in a tool called AndRacer and evaluated it on several Android apps, bringing out the scalability, recall, and improved precision of the analyses
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静态执行-在分析事件驱动程序之前
任务之间的“先执行后执行”关系是分析带有几个下游应用程序(如竞争检测和识别冗余同步)的事件驱动程序的基础。我们提出了一种可靠、高效和有效的静态分析技术,用于计算一类事件驱动程序的前置执行任务对。分析是基于一套小而全面的规则,在一种称为程序任务岗位图的新结构上进行评估。我们将展示如何使用execute -before信息来识别事件驱动程序中的不连接块,并进一步使用它们来提高这些程序的数据争用检测的精度。我们已经在Flowdroid框架中的一个名为AndRacer的工具中实现了我们的分析,并在几个Android应用程序上进行了评估,带来了可扩展性,召回率和提高的分析精度
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