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Generic sensitivity: customizing context-sensitive pointer analysis for generics

Haofeng Li, Jie Lu, Haining Meng, Liqing Cao, Yongheng Huang, Lian Li, Lin Gao

2022Year
6Citations
2Top-tier citations

Abstract

Generic programming has been extensively used in object-oriented programs such as Java. However, existing context-sensitive pointer analyses perform poorly in analyzing generics. This paper introduces generic sensitivity, a new context customization scheme targeting generics. We design our context customization scheme in such a way that generic instantiation sites, i.e., locations instantiating generic classes/methods with concrete types, are always preserved as key context elements. This is realized by augmenting contexts with a type variable lookup map, which is efficiently updated during the analysis in a context-sensitive manner.

We have implemented different variants of generic-sensitive analysis in Wala and experimental results show that the generic customization scheme can significantly improve performance and precision of context-sensitive pointer analyses. For instance, generic context customization significantly improves precision of 1-objectsensitive analysis, with an average speedup of 1.8×. In addition, generic context customization enables a 1-object-sensitive analysis to achieve overall better precision than a 2-object-sensitive analysis, with an averagely speed up of 12.6 × (62 × for chart).

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