一句话：提出将动态堆快照与完整静态程序行为分析结合的轻量级分析，以提升全程序静态分析的可扩展性。
传统全程序静态分析（例如对堆建模的指向分析）在真实应用上常面临严重的可扩展性问题。论文提出一种“羽量级”（featherweight）分析：它不是放弃对程序行为的静态分析，而是引入堆的动态快照作为分析输入，从而缩小或简化堆建模的规模，同时保留对程序行为的完整静态分析。其核心思想是用动态堆快照缓解全程序静态分析中堆抽象带来的可扩展性瓶颈。摘要未给出具体实验数据、基准测试或精度与性能结果。
Traditional whole-program static analysis (e.g., a points-to analysis that models the heap) encounters scalability problems for realistic applications. We propose a ``featherweight'' analysis that combines a dynamic snapshot of the heap with otherwise full static analysis of program behavior.
DOI 原文 ·
@inproceedings{paperbot4821,
title = {Shooting from the heap: ultra-scalable static analysis with heap snapshots},
author = {Neville Grech and George Fourtounis and Adrian Francalanza and Yannis Smaragdakis},
booktitle = {ISSTA},
year = {2018},
doi = {10.1145/3213846.3213860}
}