利用价值流提高流敏感点分析的性能

Lian Li, C. Cifuentes, Nathan Keynes
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引用次数: 83

摘要

指向分析是一种基本的静态分析技术,它计算指针可能指向的内存对象集。许多不同的应用程序,如与安全相关的程序分析、错误检查和多线程程序分析,都需要精确的指向信息才能有效。近年来的研究工作主要集中在通过流动灵敏度提高点对分析的精度上,并取得了很大进展。然而,即使有了最近的进展,流敏感点分析仍然比流不敏感点分析要慢得多。本文提出了一种简化价值流图中一般图可达性问题的流敏感点分析的新方法。值流图总结了指针变量之间的依赖关系,包括通过指针解引用实现的内存依赖关系。然后可以将每个指针变量的要设置的点计算为可以在图中到达它的内存对象集。我们开发了一种算法,通过检查内存对象的指向集(即指向对象的指针集)来有效地构建值流图。内存对象的指向信息对于诸如转义分析和信息流分析等应用程序非常有用。我们的方法直观,易于实施,效率很高。该实现大约有2000行代码,比现有的流敏感点分析更有效。运行时可与最先进的流不敏感点分析相媲美。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Boosting the performance of flow-sensitive points-to analysis using value flow
Points-to analysis is a fundamental static analysis technique which computes the set of memory objects that a pointer may point to. Many different applications, such as security-related program analyses, bug checking, and analyses of multi-threaded programs, require precise points-to information to be effective. Recent work has focused on improving the precision of points-to analysis through flow-sensitivity and great progress has been made. However, even with all recent progress, flow-sensitive points-to analysis can still be much slower than a flow-insensitive analysis. In this paper, we propose a novel method that simplifies flow-sensitive points-to analysis to a general graph reachability problem in a value flow graph. The value flow graph summarizes dependencies between pointer variables, including those memory dependencies via pointer dereferences. The points-to set for each pointer variable can then be computed as the set of memory objects that can reach it in the graph. We develop an algorithm to build the value flow graph efficiently by examining the pointed-to-by set of a memory object, i.e., the set of pointers that point to an object. The pointed-to-by information of memory objects is very useful for applications such as escape analysis, and information flow analysis. Our approach is intuitive, easy to implement and very efficient. The implementation is around 2000 lines of code and it is more efficient than existing flow-sensitive points-to analyses. The runtime is comparable with the state-of-the-art flow-insensitive points-to analysis.
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