Automatic Autoprojection of Recursive Equations with Global Variables and Abstract Data Types

Automatic Autoprojection of Recursive Equations with Global Variables and Abstract Data Types (1990)

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by Anders Bondorf , Olivier Danvy

Venue:	Science of Computer Programming
Citations:	114 - 28 self

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Datum	Value	Source
TITLE	Automatic Autoprojection of Recursive Equations with Global Variables and Abstract Data Types	user correction - Legacy Corrections
AUTHOR NAME	Anders Bondorf	SVM HeaderParse 0.1
AUTHOR AFFIL	DIKU, Dept. of Computer Science; University of Copenhagen	SVM HeaderParse 0.2
AUTHOR ADDR	Universitetsparken 1; DK-2100 Copenhagen, Denmark	SVM HeaderParse 0.1
AUTHOR NAME	Olivier Danvy	SVM HeaderParse 0.1
AUTHOR AFFIL	Dept. of Computing and Information Sciences; Kansas State University	SVM HeaderParse 0.2
AUTHOR ADDR	Manhattan, Kansas 66506, USA	SVM HeaderParse 0.1
ABSTRACT	Self-applicable partial evaluation has been implemented for half a decade now, but many problems remain open. This paper addresses and solves the problems of automating call unfolding, having an open-ended set of operators, and processing global variables updated by side effects. The problems of computation duplication and termination of residual programs are addressed and solved: residual programs never duplicate computations of the source program; residual programs do not terminate more often than source programs. This paper describes the automatic autoprojector (self-applicable partial evaluator) Similix; it handles programs with user defined primitive abstract data type operators which may process global variables. Abstract data types make it possible to hide actual representations of data and prevent specializing operators over these representations. The formally sound treatment of global variables makes Similix fit well in an applicative order programming environment. We present a new method for automatic call unfolding which is simpler, faster, and sometimes more effective than existing methods: it requires neither recursion analysis of the source program, nor call graph analysis of the residual program. To avoid duplicating computations and preserve termination properties, we introduce an abstract interpretation of the source program, abstract occurrence counting analysis, which is performed during preprocessing. We express it formally and simplify it. Similix has been implemented and self-applied. It has been used for a number of experiments such as compiler generation from interpretive specifications and generation of efficient pattern matchers from naive pattern matching programs.	user correction - Legacy Corrections
YEAR	1990	user correction - Legacy Corrections
VENUE	Science of Computer Programming	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	151--195	INFERENCE
VOLUME	16	INFERENCE
CITATIONS	5 found	ParsCit 1.0