159,724 research outputs found
Solving Constraints in Model Transformations
Constraint programming holds many promises for model driven software development (MDSD). Up to now, constraints have only started to appear in MDSD modeling languages, but have not been properly reflected in model transformation. This paper introduces constraint programming in model transformation, shows how constraint programming integrates with QVT Relations - as a pathway to wide spread use of our approach - and describes the corresponding model transformation engine. In particular, the paper will illustrate the use of constraint programming for the specification of attribute values in target models, and provide a qualitative evaluation of the benefit drawn from constraints integrated with QVT Relations
Linking Backlund and Monodromy Charges for Strings on AdS_5 x S^5
We find an explicit relation between the two known ways of generating an
infinite set of local conserved charges for the string sigma model on AdS_5 x
S^5: the Backlund and monodromy approaches. We start by constructing the
two-parameter family of Backlund transformations for the string with an
arbitrary world-sheet metric. We then show that only for a special value of one
of the parameters the solutions generated by this transformation are compatible
with the Virasoro constraints. By solving the Backlund equations in a
non-perturbative fashion, we finally show that the generating functional of the
Backlund conservation laws is equal to a certain sum of the quasi-momenta. The
positions of the quasi-momenta in the complex spectral plane are uniquely
determined by the real parameter of the Backlund transform.Comment: 25 pages, 1 figur
Transformations in the Scale of Behaviour and the Global Optimisation of Constraints in Adaptive Networks
The natural energy minimisation behaviour of a dynamical system can be interpreted as a simple optimisation process, finding a locally optimal resolution of problem constraints. In human problem solving, high-dimensional problems are often made much easier by inferring a low-dimensional model of the system in which search is more effective. But this is an approach that seems to require top-down domain knowledge; not one amenable to the spontaneous energy minimisation behaviour of a natural dynamical system. However, in this paper we investigate the ability of distributed dynamical systems to improve their constraint resolution ability over time by self-organisation. We use a ‘self-modelling’ Hopfield network with a novel type of associative connection to illustrate how slowly changing relationships between system components can result in a transformation into a new system which is a low-dimensional caricature of the original system. The energy minimisation behaviour of this new system is significantly more effective at globally resolving the original system constraints. This model uses only very simple, and fully-distributed positive feedback mechanisms that are relevant to other ‘active linking’ and adaptive networks. We discuss how this neural network model helps us to understand transformations and emergent collective behaviour in various non-neural adaptive networks such as social, genetic and ecological networks
Improving the Computational Efficiency in Symmetrical Numeric Constraint Satisfaction Problems
Models are used in science and engineering for experimentation,
analysis, diagnosis or design. In some cases, they can be considered
as numeric constraint satisfaction problems (NCSP). Many models
are symmetrical NCSP. The consideration of symmetries ensures that
NCSP-solver will find solutions if they exist on a smaller search space.
Our work proposes a strategy to perform it. We transform the symmetrical
NCSP into a newNCSP by means of addition of symmetry-breaking
constraints before the search begins. The specification of a library of possible
symmetries for numeric constraints allows an easy choice of these
new constraints. The summarized results of the studied cases show the
suitability of the symmetry-breaking constraints to improve the solving
process of certain types of symmetrical NCSP. Their possible speedup
facilitates the application of modelling and solving larger and more
realistic problems.Ministerio de Ciencia y Tecnología DIP2003-0666-02-
Evaluation of Kermeta for Solving Graph-based Problems
Kermeta is a meta-language for specifying the structure and behavior of graphs of interconnected objects called models. In this paper,\ud
we show that Kermeta is relatively suitable for solving three graph-based\ud
problems. First, Kermeta allows the specification of generic model\ud
transformations such as refactorings that we apply to different metamodels\ud
including Ecore, Java, and Uml. Second, we demonstrate the extensibility\ud
of Kermeta to the formal language Alloy using an inter-language model\ud
transformation. Kermeta uses Alloy to generate recommendations for\ud
completing partially specified models. Third, we show that the Kermeta\ud
compiler achieves better execution time and memory performance compared\ud
to similar graph-based approaches using a common case study. The\ud
three solutions proposed for those graph-based problems and their\ud
evaluation with Kermeta according to the criteria of genericity,\ud
extensibility, and performance are the main contribution of the paper.\ud
Another contribution is the comparison of these solutions with those\ud
proposed by other graph-based tools
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Transformation of propositional calculus statements into integer and mixed integer programs: An approach towards automatic reformulation
A systematic procedure for transforming a set of logical statements or logical conditions imposed on a model into an Integer Linear Progamming (ILP) formulation Mixed Integer Programming (MIP) formulation is presented. An ILP stated as a system of linear constraints involving integer variables and an objective function, provides a powerful representation of decision problems through a tightly interrelated closed system of choices. It supports direct representation of logical (Boolean or prepositional calculus) expressions. Binary variables (hereafter called logical variables) are first introduced and methods of logically connecting these to other variables are then presented. Simple constraints can be combined to construct logical relationships and the methods of formulating these are discussed. A reformulation procedure which uses the extended reverse polish representation of a compound logical form is then described. These reformulation procedures are illustrated by two examples. A scheme of implementation.ithin an LP modelling system is outlined
Transformation As Search
In model-driven engineering, model transformations are con- sidered a key element to generate and maintain consistency between re- lated models. Rule-based approaches have become a mature technology and are widely used in different application domains. However, in var- ious scenarios, these solutions still suffer from a number of limitations that stem from their injective and deterministic nature. This article pro- poses an original approach, based on non-deterministic constraint-based search engines, to define and execute bidirectional model transforma- tions and synchronizations from single specifications. Since these solely rely on basic existing modeling concepts, it does not require the intro- duction of a dedicated language. We first describe and formally define this model operation, called transformation as search, then describe a proof-of-concept implementation and discuss experiments on a reference use case in software engineering
Rewriting Constraint Models with Metamodels
An important challenge in constraint programming is to rewrite constraint
models into executable programs calculat- ing the solutions. This phase of
constraint processing may require translations between constraint programming
lan- guages, transformations of constraint representations, model
optimizations, and tuning of solving strategies. In this paper, we introduce a
pivot metamodel describing the common fea- tures of constraint models including
different kinds of con- straints, statements like conditionals and loops, and
other first-class elements like object classes and predicates. This metamodel
is general enough to cope with the constructions of many languages, from
object-oriented modeling languages to logic languages, but it is independent
from them. The rewriting operations manipulate metamodel instances apart from
languages. As a consequence, the rewriting operations apply whatever languages
are selected and they are able to manage model semantic information. A bridge
is created between the metamodel space and languages using parsing techniques.
Tools from the software engineering world can be useful to implement this
framework
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