IncSFS：面向C/C++的增量全稀疏流敏感指针分析
IncSFS: Incremental Full-Sparse Flow-Sensitive Pointer Analysis for C/C++
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中文总结 AI 辅助
本文针对软件持续迭代场景提出首个面向C/C++的增量全稀疏流敏感指针分析算法IncSFS，实验显示其精度高，效率较同类方法有显著提升。
中文摘要 AI 辅助
指针分析是编译器优化与程序分析的基础技术，流敏感指针分析精度高但难以扩展到大型项目。针对软件持续迭代的快速演化场景，本文提出面向C/C++程序的首个增量全稀疏流敏感指针分析算法IncSFS。IncSFS首先将值流图转换为约束图，通过强连通分量检测保障精度；随后以交错方式传播指向集的增减变化，支持单次分析过程中代码的删除与插入。当分析期间指向关系保持对象无环时，IncSFS可保证终止并计算最小不动点。在6个大型真实项目上的实验表明，IncSFS精度高且效率优异，相比全流敏感指针分析平均加速9.60倍，相比传统重置重计算方法平均加速5.84倍；相比传播指向集变化的最新增量指针分析算法，效率提升15.8%。
英文摘要
Pointer analysis is a fundamental technique for compiler optimization and program analysis. Flow-sensitive pointer analysis provides high precision but is difficult to scale to large projects. Tailored for rapid iteration scenarios where software evolves continuously, we introduce IncSFS, the first incremental full-sparse flow-sensitive pointer analysis algorithm for C/C++ programs. IncSFS first transforms the value-flow graph into a constraint graph and performs strongly connected component detection to ensure precision. It then propagates increases and decreases in points-to sets in an interleaved manner, supporting code deletion and insertion within a single analysis pass. IncSFS is guaranteed to terminate and compute the least fixed point when the points-to relation remains object-acyclic during analysis. Experiments on six large-scale real-world projects show that IncSFS is precise and efficient, achieving average speedups of 9.60x over full flow-sensitive pointer analysis and 5.84x over the traditional reset-recompute approach. It also improves efficiency by 15.8% over state-of-the-art incremental pointer analysis algorithms that propagate points-to-set changes.
