20,398 research outputs found
Independence in CLP Languages
Studying independence of goals has proven very useful in the context of logic programming. In particular, it has provided a formal basis for powerful automatic parallelization tools, since independence ensures that two goals may be evaluated in parallel while preserving correctness and eciency. We extend the concept of independence to constraint logic programs (CLP) and
prove that it also ensures the correctness and eciency of the parallel evaluation of independent goals. Independence for CLP languages is more complex than for logic programming as search space preservation is necessary but no longer sucient for ensuring correctness and eciency. Two
additional issues arise. The rst is that the cost of constraint solving may depend upon the order constraints are encountered. The second is the need to handle dynamic scheduling. We clarify these issues by proposing various types of search independence and constraint solver independence, and show how they can be combined to allow dierent optimizations, from parallelism to intelligent
backtracking. Sucient conditions for independence which can be evaluated \a priori" at run-time are also proposed. Our study also yields new insights into independence in logic programming languages. In particular, we show that search space preservation is not only a sucient but also a necessary condition for ensuring correctness and eciency of parallel execution
Independence in constraint logic programs
Studying independence of literals, variables, and substitutions has proven very useful in the context of logic programming (LP). Here we study independence in the broader context of constraint logic programming (CLP). We show that a naive extrapolation of the LP definitions of independence to CLP is unsatisfactory (in fact, wrong) for two reasons. First, because interaction between variables through constraints is more complex than in the case of logic programming. Second, in order to ensure the efUciency of several optimizations not only must independence of the search space be considered, but also an orthogonal issue - "independence of constraint solving." We clarify these issues by proposing various types of search independence
and constraint solver independence, and show how they can be combined to allow different independence-related optimizations, from parallelism to intelligent backtracking. Sufficient conditions for independence which can be evaluated "a-priori" at run-time are also proposed. Our results suggest that independence, provided a suitable definition is chosen, is even more useful in CLP than in LP
Business Process Configuration According to Data Dependency Specification
Configuration techniques have been used in several fields, such as the design of business
process models. Sometimes these models depend on the data dependencies, being easier to describe
what has to be done instead of how. Configuration models enable to use a declarative representation
of business processes, deciding the most appropriate work-flow in each case. Unfortunately,
data dependencies among the activities and how they can affect the correct execution of the process,
has been overlooked in the declarative specifications and configurable systems found in the literature.
In order to find the best process configuration for optimizing the execution time of processes according
to data dependencies, we propose the use of Constraint Programming paradigm with the aim of
obtaining an adaptable imperative model in function of the data dependencies of the activities
described declarative.Ministerio de Ciencia y TecnologĂa TIN2015-63502-C3-2-RFondo Europeo de Desarrollo Regiona
Data optimizations for constraint automata
Constraint automata (CA) constitute a coordination model based on finite
automata on infinite words. Originally introduced for modeling of coordinators,
an interesting new application of CAs is implementing coordinators (i.e.,
compiling CAs into executable code). Such an approach guarantees
correctness-by-construction and can even yield code that outperforms
hand-crafted code. The extent to which these two potential advantages
materialize depends on the smartness of CA-compilers and the existence of
proofs of their correctness.
Every transition in a CA is labeled by a "data constraint" that specifies an
atomic data-flow between coordinated processes as a first-order formula. At
run-time, compiler-generated code must handle data constraints as efficiently
as possible. In this paper, we present, and prove the correctness of two
optimization techniques for CA-compilers related to handling of data
constraints: a reduction to eliminate redundant variables and a translation
from (declarative) data constraints to (imperative) data commands expressed in
a small sequential language. Through experiments, we show that these
optimization techniques can have a positive impact on performance of generated
executable code
Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design
The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface
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