Fast Flow Analysis with Godel Hashes

Shuying Liang, Weibin Sun, M. Might
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引用次数: 12

Abstract

Flow analysis, such as control-flow, data-flow, and exception-flow analysis, usually depends on relational operations on flow sets. Unfortunately, set related operations, such as inclusion and equality, are usually very expensive. They can easily take more than 97% of the total analyzing time, even in a very simple analysis. We attack this performance bottleneck by proposing Godel hashes to enable fast and precise flow analysis. Godel hashes is an ultra compact, partial-order-preserving, fast and perfect hashing mechanism, inspired by the proofs of Godel's incompleteness theorems. Compared with array, tree, traditional hash, and bit vector-backed set implementations, we find Godel hashes to be tens or even hundreds of times faster for performance in the critical operations of inclusion and equality. We apply Godel hashes in real-world analysis for object-oriented programs. The instrumented analysis is tens of times faster than the one with original data structures on DaCapo benchmarks.
哥德尔哈希快速流分析
流分析,如控制流、数据流和异常流分析,通常依赖于流集上的关系操作。不幸的是,与集合相关的操作,如包含和相等,通常非常昂贵。即使在一个非常简单的分析中,它们也可以轻松地占用总分析时间的97%以上。我们通过提出哥德尔哈希来实现快速精确的流量分析,从而解决了这个性能瓶颈。哥德尔哈希是一种超紧凑、部分保序、快速、完美的哈希机制,其灵感来自哥德尔不完备定理的证明。与数组、树、传统哈希和位向量支持集实现相比,我们发现哥德尔哈希在包含和相等的关键操作上的性能要快几十倍甚至几百倍。我们将哥德尔哈希应用于面向对象程序的实际分析中。仪器化的分析比在DaCapo基准测试中使用原始数据结构的分析快几十倍。
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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