) Inderpal Singh Mumick AT&T Bell Laboratories mumick@research.att.com Abstract Magic-sets transformation is typically applied to a program in two phases -- an adornment phase, and a magic-sets phase. A major drawback of the two-phase transformation is that join ordering, needed to do

A system of rules for transforming programs is described, with the programs in the form of recursion equations An initially very simple, lucid. and hopefully correct program IS transformed into a more efficient one by altering the recursion structure Illustrative examples of program transformations

this paper we will write database queries in datalog [Ull89]. Datalog is the language of horn clause logic rules, written as "if-then" rules. A datalog rule is required to be range-restricted: it must define a finite relation for the predicate in the head of the rule. In this paper we will concentrate on nonrecursive queries. Mumick [Mum91] shows that nonrecursive datalog programs can be expressed in SQL using views, and that SQL queries can be expressed in datalog extended with duplicates and grouping with aggregation. Thus, the algorithms developed in this paper can be mapped to relational database systems having SQL as their query language. We will use dependency graphs to represent the dependence between predicates in a datalog program.

case, substantially improving on previously defined approaches. Magic-Set-transformed disjunctive programs frequently contain redundant rules. We tackle this problem and propose a method for preventing the generation of such superfluous rules during the Magic-Set transformation. In addition, we provide

.e., from the input to some internal program points. We overcome this limitation with a technique used up to now for logic pro-grams only. It adds new magic blocks of code to P, whose functional be-haviours are the internal behaviours of P. We prove this transformation correct with an operational semantics

We describe the implementation of the magic-sets transformation in the Starburst extensible relational database system. To our knowledge this is the first implementation of the magic-sets transformation in a relational database system. The Starburst implementation has many novel features that make

program transformation based on the magic-sets, which generates models and analyzes negation-as-failure atoms dynamically. We also show experimental results which show remarkable speedup compared with the original procedure. 1 Introduction The stable model semantics [GL88] is now one of the standard

proposal, Stagewise Orthogonal Matching Pursuit (StOMP), successively transforms the signal into a negligible residual. Starting with initial residual r0 = y, at the s-th stage it forms the ‘matched filter ’ Φ T rs−1, identifies all coordinates with amplitudes exceeding a specially-chosen threshold, solves

transformation that adds new magic blocks of code to the program P, whose functional behaviours are the internal behaviours of P. We prove the transformation correct w.r.t. an operational semantics and define an equivalent denotational semantics, devised for abstract interpretation, whose denotations

Summary Three exponential iterative methods for one-dimensional one-phase Stefan problems based on the transformation of the moving boundary problem into a fixed one, the discretization of the time variable, and the piecewise linearization of the resulting two-point boundary-value problem at each