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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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Various shape analysis algorithms have been introduced but their relation in terms of precision often remains unclear as different analyses use different representations of analysis results. The aim of our work is to extract alias sets from shape analysis results to compute a relative precision factor that expresses for a given program how much more precise one analysis is than the other. We present a significant improvement over an existing algorithm based on 3-valued logic to compute alias sets from shape graphs. Instead of looking only at the final nodes in pointer access paths, our common tail algorithm takes sequences of selectors into account. The common tail algorithm is strictly more precise than the existing algorithm by Reps, Sagiv, and Wilhelm, for our benchmarks we can reduce the number of conservative results by a factor of up to 5 in the best case while incurring an additional analysis overhead that is below 10% even in the worst case of our benchmarks. We selected two well-known graph-based shape analyses that use different representations of analysis results to demonstrate the usefulness of our approach. The shape analysis proposed by Nielson, Nielson & Hankin (NNH) and the analysis by Sagiv, Reps & Wilhelm (SRW) were implemented for a subset of C++ in the SATIrE program analysis framework. We are thus able to determine that NNH is more precise than SRW by a factor of 1.62 on average for our set of benchmarks.
机译:已经介绍了各种形状分析算法,但是由于不同的分析使用不同的分析结果表示形式,因此它们在精度方面的关系通常仍然不清楚。我们工作的目的是从形状分析结果中提取别名集,以计算相对精度因子,该因子表示给定程序对一种分析的精确度比另一种分析的精确度。我们提出了对现有的基于三值逻辑的算法的重大改进,该算法可从形状图计算别名集。我们的通用尾部算法不仅考虑指针访问路径中的最后节点,还考虑了选择器序列。普通尾部算法比Reps,Sagiv和Wilhelm的现有算法严格更精确,对于我们的基准测试,在最佳情况下,我们可以将保守结果的数量减少多达5倍,同时会产生额外的分析开销即使在基准测试的最坏情况下也低于10%。我们选择了两个著名的基于图形的形状分析,它们使用不同表示形式的分析结果来证明我们方法的有用性。 Nielson,Nielson&Hankin(NNH)提出的形状分析以及Sagiv,Reps&Wilhelm(SRW)进行的分析是在SATIrE程序分析框架中对C ++的子集进行的。因此,对于我们的一组基准,我们可以确定NNH比SRW精确1.62倍。

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