Region-Based selective flow-sensitive pointer analysis

被引：22

作者：

Ye, Sen ^{[1
]}

Sui, Yulei ^{[1
]}

Xue, Jingling ^{[1
]}

机构：

[1] Programming Languages and Compilers Group, School of Computer Science and Engineering, UNSW, Kensington

来源：

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 2014年 / 8723卷

关键词：

Static analysis;

D O I：

10.1007/978-3-319-10936-7_20

中图分类号：

学科分类号：

摘要：

We introduce a new region-based SELective Flow-Sensitive (Selfs) approach to inter-procedural pointer analysis for C that operates on the regions partitioned from a program. Flow-sensitivity is maintained between the regions but not inside, making traditional flow-insensitive and flow-sensitive as well as recent sparse flow-sensitive analyses all special instances of our Selfs framework. By separating region partitioning as an independent concern from the rest of the pointer analysis, Selfs facilitates the development of flow-sensitive variations with desired efficiency and precision tradeoffs by reusing existing pointer resolution algorithms. We also introduce a new unification-based approach for region partitioning to demonstrate the generality and flexibility of our Selfs framework, as evaluated using SPEC2000/2006 benchmarks in LLVM. © Springer International Publishing Switzerland 2014.

引用

页码：319 / 336

页数：17

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