Automatic determination of may/must set usage in data-flow analysis

Andrew Stone, Michelle Strout, Shweta Behere

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings - 8th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2008
Pages153-162
Number of pages10
DOIs
StatePublished - 2008
Externally publishedYes
Event8th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2008 - Beijing, China
Duration: Sep 28 2008Sep 29 2008

Publication series

NameProceedings - 8th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2008

Conference

Conference8th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2008
Country/TerritoryChina
CityBeijing
Period9/28/089/29/08

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software

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