Soot-based implementation of a demand-driven reaching definitions analysis

Longwen Lu, Cheng Zhang, Jianjun Zhao
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引用次数: 1

Abstract

As a classical data-flow analysis, reaching definitions analysis is the corner stone of various techniques, such as code optimization and program slicing. The built-in data-flow analysis framework in Soot has been implemented in the traditional iterative style. While being able to meet general requirements for implementation of data flow analyses, the framework may be less efficient for a certain type of analyses in which the complete data-flow solution is unnecessary. In this paper, we introduce our Soot-based implementation of an inter-procedural demand-driven reaching definitions analysis. For a demand for reaching definitions facts, the analysis only explores relevant program points and variables, saving a considerable amount of computation. Preliminary results show that the implementation can be much more efficient than its traditional counterpart in several scenarios. The Soot framework has greatly facilitated the implementation by providing abundant basic analysis results via well designed APIs.
基于烟灰的需求驱动到达定义分析的实现
作为一种经典的数据流分析,达到定义分析是代码优化和程序切片等各种技术的基础。烟尘中内置的数据流分析框架以传统的迭代方式实现。虽然能够满足数据流分析实现的一般需求,但对于不需要完整数据流解决方案的特定类型的分析,该框架可能效率较低。在本文中,我们介绍了基于烟灰的程序间需求驱动的到达定义分析的实现。为了达到定义事实的要求,分析只挖掘相关的程序点和变量,节省了大量的计算。初步结果表明,在一些场景中,该实现可以比传统的实现更有效。Soot框架通过精心设计的api提供丰富的基本分析结果,极大地促进了实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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