Pointer analysis is the fundamental technique for compiler optimization and program analysis. Flow sensitive pointer analysis provides high precision but hard to scale to large-size 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. The algorithm contains two main steps. It first transforms the value-flow graph of a program into a constraint graph, on which a strongly-connected component detection is performed to ensure precision. It then propagates increases and decreases in points-to set in an interleaving manner to support both code deletion and insertion within a single analysis pass. IncSFS is guaranteed to terminate and compute the least fixed point when point-to relation during the analysis is object-acyclic. Experimental results on six large-scale real-world projects show that IncSFS is both precise and efficient, achieving average speedups of 9.60 x over full flow-sensitive pointer analysis and of 5.84 x over the traditional reset-recompute incremental approach. Furthermore, IncSFS improves efficiency by 15.8% compared with state-of-the-art incremental pointer analysis algorithms that also propagate changes in points-to sets.

@inproceedings{paperbot12403,
  title = {IncSFS: Incremental Full-Sparse Flow-Sensitive Pointer Analysis for C/C++},
  author = {Kunlin Liu and Zhenbang Chen and Piyi Zu and Yide Du and Ji Wang},
  booktitle = {ASE},
  year = {2026},
  doi = {10.1145/3832783.3837496}
}