DocumentCode :
3315462
Title :
Dependence analysis for recursive data
Author :
Liu, Yanhong A.
Author_Institution :
Dept. of Comput. Sci., Indiana Univ., Bloomington, IN, USA
fYear :
1998
fDate :
14-16 May 1998
Firstpage :
206
Lastpage :
215
Abstract :
The paper describes a general and powerful method for dependence analysis in the presence of recursive data constructions. The particular analysis presented is for identifying partially dead recursive data, but the general framework for representing and manipulating recursive substructures applies to all dependence analyses. The method uses projections based on general regular free grammars extended with notions of live and dead, and defines the analysis as mutually recursive grammar transformers. To guarantee that the analysis terminates, we use carefully designed approximations. We describe how to approximate argument projections with grammars that can be computed without iterating and how to approximate resulting projections with a widening operation. We design an approximation operation that combines two grammars to give the most precise deterministic result possible. All grammar operations used in the analysis have efficient algorithms. The overall analysis yields significantly more precise results than other known methods
Keywords :
grammars; optimising compilers; program verification; trees (mathematics); approximation operation; dependence analyses; dependence analysis; general regular free grammars; grammar operations; mutually recursive grammar transformers; partially dead recursive data; precise deterministic result; recursive data; recursive data constructions; recursive substructures; Algorithm design and analysis; Computer languages; Computer science; Data analysis; Functional programming; High level languages; Information analysis; Optimizing compilers; Program processors; Transformers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Languages, 1998. Proceedings. 1998 International Conference on
Conference_Location :
Chicago, IL
ISSN :
1074-8970
Print_ISBN :
0-8186-8454-2
Type :
conf
DOI :
10.1109/ICCL.1998.674171
Filename :
674171
Link To Document :
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