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Towards efficient partial evaluation in logic programming

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Abstract

Partial evaluation is a symbolic manipulation technique used to produce efficient algorithms when part of the input to the algorithm is known. Other applications of partial evaluators such as universal compilation and compiler generation are also known to be possible. A partial evaluator receives as input a program and partially known input to that program, and outputs a residual program which should run at least as efficient as the input program with restricted input.

In this paper we study the case where both the input and residual programs are logic programs, being the partial evaluator itself a logic program. Up to now, partial evaluators have failed to process large “non=toy” examples. Here we present extensions to partial evaluators whic will allow us to produce more efficient residual programs using less computing resources, during partial evaluation.

First, the introduced extensions allow the processing of large examples, which is not possible with the previous techniques. This is now possible since the extensions use less CPU time and memory consumption during the partial evaluation process. Second, the extended partial evaluator produces smaller residual programs, producing important CPU time optimizing effects. With the standard techniques, a partial evaluator will most probably act as a pessimizer, not as an optimizer. Examples are given.

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Authors and Affiliations

  1. Computer Science Department, Pontificia Universidad Católica de Chile, PO Box 306, Santiago 22, Chile

    David A. Fuller, Sacha A. Bocic & Leopoldo E. Berstossi

Authors
  1. David A. Fuller
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  2. Sacha A. Bocic
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  3. Leopoldo E. Berstossi
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Additional information

David A. Fuller, Ph.D.: He received the B.S. degree in Electrical Engineering from the Pontificia Universidad Católica de Chile in 1982, the M.S. degree in Computer Science from the University of California at Los Angeles in 1984, and the Ph.D. degree in Computer Science from Imperial College of Science and Technology in 1989. He worked as a research assistant at Imperial College in the HOPE project. Currently he is an Assistant Professor of Computer Science at the Pontificia Universidad Católica de Chile where he directs a Research Lab. on Computer Supported Cooperative Work. His research interests include symbolic computation and intelligent cooperative systems.

Sacha Bocic, M.S.: He received the B.S. and the M.S. degree in Computer Science from the Pontificia Universidad Católica de Chile in 1991 and 1992, resp. He is currently a Manager of the Core Technology Group at Oracle Chile. His current interests include symbolic computation, distributed data base systems and multimedia.

Leopoldo E. Bertossi, Dr.: He received a Doctor in Exact Sciences (Mathematics) degree from the Pontificia Universidad Católica de Chile in 1988. He received a DAAD Scholarship (University of Freiburg, Abteilung fuer mathematische Logic und Grundlagen der Mathematik, Germany), and has been visiting Assistant Professor at the Department of Computer Science, University of Toronto, and the Department of Electrical Engineering and Computer Science of the University of Wisconsin-Milwaukee. Since 1992 he is an Associate Professor at the Pontificia Universidad Católica de Chile. His current research interests are knowledge representation, deductive databases, logic programming and foundations of probability and statistics.

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Fuller, D.A., Bocic, S.A. & Berstossi, L.E. Towards efficient partial evaluation in logic programming. New Gener Comput 14, 237–259 (1996). https://doi.org/10.1007/BF03037500

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