一句话：为 Go 提出字段敏感并结合指向分析的逃逸分析框架 MEA2，显著减少堆分配且编译开销低于 1%。
逃逸分析通过识别对象与指针的动态生命周期，使非逃逸变量可分配在栈上，从而减少堆分配、缓解 GC 压力。Go 作为垃圾回收语言，其编译器采用快速但保守的逃逸分析：字段不敏感，且省略指向集（points-to set）计算，导致更多变量被分配到堆上。实证统计表明，字段访问与间接内存访问在真实 Go 程序中普遍存在，为逃逸分析提升性能提供了空间。本文提出 MEA2，一个构建在基于 LLVM 的 Go 编译器 GoLLVM 之上的逃逸分析框架，将字段敏感性与指向分析相结合，并设计了一种新颖的泛型函数摘要表示，以支持快速的跨过程分析。作者在 12 个广泛使用的开源项目中用 MEA2 执行栈分配进行评测。结果显示，与 Go 的逃逸分析相比，MEA2 平均减少 7.9% 的堆分配点（最高 25.7%），平均减少 11.6% 的动态内存分配量（最高 35.5%），同时逃逸分析的时间开销保持在编译过程的 1% 以内。
Escape analysis plays a crucial role in garbage-collected languages as it enables the allocation of non-escaping variables on the stack by identifying the dynamic lifetimes of objects and pointers. This helps in reducing heap allocations and alleviating garbage collection pressure. However, Go, as a garbage-collected language, employs a fast yet conservative escape analysis, which is field-insensitive and omits point-to-set calculation to expedite compilation. This results in more variables being allocated on the heap. Empirical statistics reveal that field access and indirect memory access are prevalent in real-world Go programs, suggesting potential opportunities for escape analysis to enhance program performance. In this paper, we propose MEA 2 , an escape analysis framework atop GoLLVM (an LLVM-based Go compiler), which combines field sensitivity and points-to analysis. Moreover, a novel generic function summary representation is designed to facilitate fast inter-procedural analysis. We evaluated it by using MEA 2 to perform stack allocation in 12 wildly-use open-source projects. The results show that, compared to Go’s escape analysis, MEA 2 can reduce heap allocation sites by 7.9 % on average (up to 25.7 % ) while reducing the dynamic memory allocation size by 11.6 % on average (up to 35.5 % ). All this is achieved while keeping the time overhead of escape analysis within 1 % of the compilation process.
@article{DingL0TC24,
title = {MEA2: A Lightweight Field-Sensitive Escape Analysis with Points-to Calculation for Golang},
author = {Boyao Ding and Qingwei Li and Yu Zhang and Fugen Tang and Jinbao Chen},
journal = {Proceedings of the ACM on Programming Languages},
volume = {8},
number = {OOPSLA2},
year = {2024},
doi = {10.1145/3689759}
}