Automatic Determination of May/Must Set Usage in Data-Flow Analysis

A. Stone, M. Strout, Shweta Behere
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引用次数: 3

Abstract

Data-flow analysis is a common technique to gather program information for use in transformations such as register allocation, dead-code elimination, common subexpression elimination, scheduling, and others. Tools for generating data-flow analysis implementations remove the need for implementers to explicitly write code that iterates over statements in a program, but still require them to implement details regarding the effects of aliasing, side effects, arrays, and user-defined structures. This paper presents the DFAGen Tool, which generates implementations for locally separable (e.g. bit-vector) data-flow analyses that are pointer, side-effect, and aggregate cognizant from an analysis specification that assumes only scalars. Analysis specifications are typically seven lines long and similar to those in standard compiler textbooks. The main contribution of this work is the automatic determination of may and must set usage within automatically generated data-flow analysis implementations.
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自动确定可能/必须设置使用数据流分析
数据流分析是一种收集程序信息的常用技术,用于转换,如寄存器分配、死代码消除、公共子表达式消除、调度等。用于生成数据流分析实现的工具消除了实现者显式编写迭代程序中语句的代码的需要,但仍然要求他们实现有关混叠、副作用、数组和用户定义结构的影响的细节。本文介绍了DFAGen工具,它生成局部可分离(例如位向量)数据流分析的实现,这些数据流分析是指针,副作用和聚合认知,来自仅假设标量的分析规范。分析规范通常有七行,类似于标准编译器教科书中的规范。这项工作的主要贡献是在自动生成的数据流分析实现中自动确定可能和必须设置的使用。
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