Path: csiph.com!weretis.net!feeder9.news.weretis.net!news.misty.com!news.iecc.com!.POSTED.news.iecc.com!nerds-end From: John R Levine Newsgroups: comp.compilers Subject: Paper: IncSFS: Incremental Full-Sparse Flow-Sensitive Pointer Analysis for C/C++ Date: Wed, 26 Aug 2026 12:59:34 -0400 Organization: Compilers Central Sender: johnl%iecc.com Approved: comp.compilers@iecc.com Message-ID: <26-08-010@comp.compilers> MIME-Version: 1.0 Content-Type: text/plain; charset="UTF-8" Injection-Info: gal.iecc.com; posting-host="news.iecc.com:2001:470:1f07:1126:0:676f:7373:6970"; logging-data="44247"; mail-complaints-to="abuse@iecc.com" Keywords: paper, analysis Posted-Date: 26 Aug 2026 13:01:53 EDT X-submission-address: compilers@iecc.com X-moderator-address: compilers-request@iecc.com X-FAQ-and-archives: http://compilers.iecc.com Xref: csiph.com comp.compilers:3747 Flow-sensitive pointer analysis is very effective but also very expensive. This paper proposes a way to make it a lot cheaper. Unlike a lot of recent papers, this one has nothing to do with LLMs. Abstract 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. https://arxiv.org/abs/2608.24391 Regards, John Levine, johnl@taugh.com, Taughannock Networks, Trumansburg NY Please consider the environment before reading this e-mail. https://jl.ly