使用IFDS/IDE和Soot进行程序间数据流分析

E. Bodden
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引用次数: 128

摘要

Reps、Horwitz和Sagiv的IFDS和IDE框架是用于有限域上分布流函数的数据流问题的程序间分析的两个通用框架。许多数据流问题确实具有分布流函数,因此可以表示为IFDS或IDE问题,从像真实活变量这样的基本分析到像当前文献中的类型状态和安全信息流等问题的复杂分析。在这项工作中,我们描述了基于Soot的通用IFDS/IDE求解器的实现,并从用户的角度和实现方面将其与Watson库for Analysis (WALA)中的IFDS实现进行了对比。虽然WALA的实现主要面向内存效率,但我们目前更关注可扩展性和易用性,我们将效率作为次要目标。我们将进一步讨论IFDS/IDE实现的可能扩展,这些扩展可能有助于支持更广泛的分析。
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Inter-procedural data-flow analysis with IFDS/IDE and Soot
The IFDS and IDE frameworks by Reps, Horwitz and Sagiv are two general frameworks for the inter-procedural analysis of data-flow problems with distributive flow functions over finite domains. Many data-flow problems do have distributive flow functions and are thus expressible as IFDS or IDE problems, reaching from basic analyses like truly-live variables to complex analyses for problems from the current literature such as typestate and secure information-flow. In this work we describe our implementation of a generic IFDS/IDE solver on top of Soot and contrast it with an IFDS implementation in the Watson Libraries for Analysis (WALA), both from a user's perspective and in terms of the implementation. While WALA's implementation is geared much towards memory efficiency, ours is currently geared more towards extensibility and ease of use and we focus on efficiency as a secondary goal. We further discuss possible extensions to our IFDS/IDE implementation that may be useful to support a wider range of analyses.
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