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Computation of alias sets from shape graphs for comparison of shape analysis precision

机译:从形状图计算别名集以比较形状分析精度

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摘要

Various shape analyses have been introduced, but their precision often cannot be compared because they use different representations of analysis results. The aim of the authors work was to compare the precision of two well-known graph-based shape analyses, those presented by Sagiv, Reps and Wilhem (SRW); and by Nielson, Nielson and Hankin (NNH). Rather than comparing the shape graphs directly, their comparison uses alias information extracted from the graphs: for every pair (e1, e2) of pointer expressions in a programme, and for every programme point pt the authors determine the aliasing between e1 and e2. In their experiments, they use a new algorithm for extracting this alias information called the 'common tails' algorithm that is strictly more precise than the technique introduced by Reps, Sagiv and Wilhem (RSW). They present two interesting results: (i) they show that using their common tails algorithm, they are able to reduce the number of conservative results (strict may-aliases) by a factor of up to 5 (compared with the original RSW algorithm) while incurring an overhead of no more than 10% of analysis run-time. (ii) They show that NNH is more precise than SRW by a factor of 1.62 on average for their set of benchmarks.
机译:已经介绍了各种形状分析,但是由于使用了不同的分析结果表示形式,因此经常无法比较它们的精度。作者的工作目的是比较Sagiv,Reps和Wilhem(SRW)提出的两种基于图形的著名形状分析的精度;以及尼尔森,尼尔森和汉金(NNH)。它们的比较不是直接比较形状图,而是使用从图中提取的别名信息:对于程序中的每对指针表达式(e 1 ,e 2 ),以及对于每个程序点pt,作者确定e 1 和e 2 之间的别名。在他们的实验中,他们使用一种称为“常见尾巴”算法的新算法来提取此别名信息,该算法比Reps,Sagiv和Wilhem(RSW)引入的技术更加精确。他们提出了两个有趣的结果:(i)他们证明了使用共同的尾巴算法,他们能够将保守结果的数量(严格的可能混淆)减少多达5倍(与原始RSW算法相比),而产生的开销不超过分析运行时的10%。 (ii)他们表明,对于他们的一组基准,NHN比SRW的精确度平均高1.62倍。

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  • 来源
    《Software, IET》 |2014年第3期|120-133|共14页
  • 作者

    Pavlu V.; Schordan M.; Krall A.;

  • 作者单位

    Institute of Computer Languages, Vienna University of Technology, Vienna, Austria|c|;

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  • 正文语种 eng
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