As an approach to optimization, this paper examines the decomposition of chain Datalog programs into P(left-)linear sequences of 1-rule programs. The notion of P (left-)linear, introduced here, encompasses numerous special (left-) linear forms and includes the traditional (left) linear as a subcase. The decompositions are first characterized in terms of properties of associated context-free languages. More specific characterizations are provided for three types of P (left-)linear decompositions with 1-rule components, and the corresponding decision problems considered. Finally, arbitrarily large, inherently nondecomposable, P-linear size-prime programs are exhibited
AbstractDatalog programs containing a unique rule and possibly some facts are known as single rule p...
Containment of monadic datalog programs over data trees (labelled trees with an equivalence relation...
The design of linear logic programming languages and theorem provers opens a number of new implement...
AbstractAs an approach to optimization, this paper examines the decomposition of chain Datalog progr...
AbstractIn an earlier paper one of the authors initiated an investigation into the composition of da...
AbstractWe consider logic programs without function symbols, called Datalog programs, and study thei...
Περιέχει το πλήρες κείμενοLinear Datalog programs are programs whose clauses have at most one intens...
AbstractWe explore the possibility of evaluating single-rule Datalog programs efficiently and with l...
AbstractLinear Datalog programs are programs whose clauses have at most one intensional atom in thei...
We present methods for optimizing chain Datalog programs by restructuring and postprocessing. The ru...
. We present a method for characterizing the least fixed-points of a certain class of Datalog progra...
Symmetric Datalog, a fragment of the logic programming language Datalog, is conjectured to capture a...
We identify a number of simple, syntactic properties of recursive subgoals in linear single-rule and...
We propose relational linear programming, a simple framework for combing linear programs (LPs) and l...
This paper describes a method for transforming any given set of Datalog rules into an e#cient specia...
AbstractDatalog programs containing a unique rule and possibly some facts are known as single rule p...
Containment of monadic datalog programs over data trees (labelled trees with an equivalence relation...
The design of linear logic programming languages and theorem provers opens a number of new implement...
AbstractAs an approach to optimization, this paper examines the decomposition of chain Datalog progr...
AbstractIn an earlier paper one of the authors initiated an investigation into the composition of da...
AbstractWe consider logic programs without function symbols, called Datalog programs, and study thei...
Περιέχει το πλήρες κείμενοLinear Datalog programs are programs whose clauses have at most one intens...
AbstractWe explore the possibility of evaluating single-rule Datalog programs efficiently and with l...
AbstractLinear Datalog programs are programs whose clauses have at most one intensional atom in thei...
We present methods for optimizing chain Datalog programs by restructuring and postprocessing. The ru...
. We present a method for characterizing the least fixed-points of a certain class of Datalog progra...
Symmetric Datalog, a fragment of the logic programming language Datalog, is conjectured to capture a...
We identify a number of simple, syntactic properties of recursive subgoals in linear single-rule and...
We propose relational linear programming, a simple framework for combing linear programs (LPs) and l...
This paper describes a method for transforming any given set of Datalog rules into an e#cient specia...
AbstractDatalog programs containing a unique rule and possibly some facts are known as single rule p...
Containment of monadic datalog programs over data trees (labelled trees with an equivalence relation...
The design of linear logic programming languages and theorem provers opens a number of new implement...