A theory of using history for equational systems with applications

  • Authors:

  • Rakesh M. Verma

  • Affiliations:

  • Univ. of Houston, Houston, TX

  • Venue:
  • Journal of the ACM (JACM)
  • Year:
  • 1995

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Abstract

Implementation of programming language interpreters, proving theorem of the form A=B, implementation of abstract data types, and program optimization are all problems that can be reduced to the problem of finding a normal form for an expression with respect to a finite set of equations. In 1980, Chew proposed an elegant congruence closure based simplifier (CCNS) for computing with regular systems, which stores the history of it computations in a compact data structure. In 1990, Verma and Ramakrishnan showed that it can also be used for noetherian systems with no overlaps.In this paper, we develop a general theory of using CCNS for computing normal forms and present several applications. Our results are more powerful and widely applicable than earlier work. We present an independent set of postulates and prove that CCNS can be used for any system that satisfies them. (This proof is based on the notion of strong closure). We then show that CCNS can be used for consistent convergent systems and for various kinds of priority rewrite systems. This is the first time that the applicability of CCNS has been shown for priority systems. Finally, we present a new and simpler translation scheme for converting convergent systems into effectively nonoverlapping convergent priority systems. Such a translation scheme has been proposed earlier, but we show that it is incorrect.Because CCNS requires some strong properties of the given system, our demonstration of its wide applicability is both difficult and surprising. The tension between demands imposed by CCNS and our efforts to satisfy them gives our work much general significance. Our results are partly achieved through the idea of effectively simulating “bad” systems by almost-equivalent “good” ones, partly through our theory that substantially weakens the demands, and partly through the design of a powerful and unifying reduction proof method.