48,956 research outputs found
Conditions, constraints and contracts: on the use of annotations for policy modeling.
Organisational policies express constraints on generation and processing of resources. However, application domains rely on transformation processes, which are in principle orthogonal to policy specifications and domain rules and policies may evolve in a non-synchronised way. In previous papers, we have proposed annotations as a flexible way to model aspects of some policy, and showed how they could be used to impose constraints on domain configurations, how to derive application conditions on transformations, and how to annotate complex patterns. We extend the approach by: allowing domain model elements to be annotated with collections of elements, which can be collectively applied to individual resources or collections thereof; proposing an original construction to solve the problem of annotations remaining orphan , when annotated resources are consumed; introducing a notion of contract, by which a policy imposes additional pre-conditions and post-conditions on rules for deriving new resources. We discuss a concrete case study of linguistic resources, annotated with information on the licenses under which they can be used. The annotation framework allows forms of reasoning such as identifying conflicts among licenses, enforcing the presence of licenses, or ruling out some modifications of a licence configuration
Specification and implementation of mapping rule visualization and editing : MapVOWL and the RMLEditor
Visual tools are implemented to help users in defining how to generate Linked Data from raw data. This is possible thanks to mapping languages which enable detaching mapping rules from the implementation that executes them. However, no thorough research has been conducted so far on how to visualize such mapping rules, especially if they become large and require considering multiple heterogeneous raw data sources and transformed data values. In the past, we proposed the RMLEditor, a visual graph-based user interface, which allows users to easily create mapping rules for generating Linked Data from raw data. In this paper, we build on top of our existing work: we (i) specify a visual notation for graph visualizations used to represent mapping rules, (ii) introduce an approach for manipulating rules when large visualizations emerge, and (iii) propose an approach to uniformly visualize data fraction of raw data sources combined with an interactive interface for uniform data fraction transformations. We perform two additional comparative user studies. The first one compares the use of the visual notation to present mapping rules to the use of a mapping language directly, which reveals that the visual notation is preferred. The second one compares the use of the graph-based RMLEditor for creating mapping rules to the form-based RMLx Visual Editor, which reveals that graph-based visualizations are preferred to create mapping rules through the use of our proposed visual notation and uniform representation of heterogeneous data sources and data values. (C) 2018 Elsevier B.V. All rights reserved
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Behavioral synthesis from VHDL using structured modeling
This dissertation describes work in behavioral synthesis involving the development of a VHDL Synthesis System VSS which accepts a VHDL behavioral input specification and performs technology independent synthesis to generate a circuit netlist of generic components. The VHDL language is used for input and output descriptions. An intermediate representation which incorporates signal typing and component attributes simplifies compilation and facilitates design optimization.A Structured Modeling methodology has been developed to suggest standard VHDL modeling practices for synthesis. Structured modeling provides recommendations for the use of available VHDL description styles so that optimal designs will be synthesized.A design composed of generic components is synthesized from the input description through a process of Graph Compilation, Graph Criticism, and Design Compilation. Experiments were performed to demonstrate the effects of different modeling styles on the quality of the design produced by VSS. Several alternative VHDL models were examined for each benchmark, illustrating the improvements in design quality achieved when Structured Modeling guidelines were followed
Convergence between Categorical Representations of Reeb Space and Mapper
The Reeb space, which generalizes the notion of a Reeb graph, is one of the
few tools in topological data analysis and visualization suitable for the study
of multivariate scientific datasets. First introduced by Edelsbrunner et al.,
it compresses the components of the level sets of a multivariate mapping and
obtains a summary representation of their relationships. A related construction
called mapper, and a special case of the mapper construction called the Joint
Contour Net have been shown to be effective in visual analytics. Mapper and JCN
are intuitively regarded as discrete approximations of the Reeb space, however
without formal proofs or approximation guarantees. An open question has been
proposed by Dey et al. as to whether the mapper construction converges to the
Reeb space in the limit.
In this paper, we are interested in developing the theoretical understanding
of the relationship between the Reeb space and its discrete approximations to
support its use in practical data analysis. Using tools from category theory,
we formally prove the convergence between the Reeb space and mapper in terms of
an interleaving distance between their categorical representations. Given a
sequence of refined discretizations, we prove that these approximations
converge to the Reeb space in the interleaving distance; this also helps to
quantify the approximation quality of the discretization at a fixed resolution
Optimal Recombination in Genetic Algorithms
This paper surveys results on complexity of the optimal recombination problem
(ORP), which consists in finding the best possible offspring as a result of a
recombination operator in a genetic algorithm, given two parent solutions. We
consider efficient reductions of the ORPs, allowing to establish polynomial
solvability or NP-hardness of the ORPs, as well as direct proofs of hardness
results
Avoiding Unnecessary Information Loss: Correct and Efficient Model Synchronization Based on Triple Graph Grammars
Model synchronization, i.e., the task of restoring consistency between two
interrelated models after a model change, is a challenging task. Triple Graph
Grammars (TGGs) specify model consistency by means of rules that describe how
to create consistent pairs of models. These rules can be used to automatically
derive further rules, which describe how to propagate changes from one model to
the other or how to change one model in such a way that propagation is
guaranteed to be possible. Restricting model synchronization to these derived
rules, however, may lead to unnecessary deletion and recreation of model
elements during change propagation. This is inefficient and may cause
unnecessary information loss, i.e., when deleted elements contain information
that is not represented in the second model, this information cannot be
recovered easily. Short-cut rules have recently been developed to avoid
unnecessary information loss by reusing existing model elements. In this paper,
we show how to automatically derive (short-cut) repair rules from short-cut
rules to propagate changes such that information loss is avoided and model
synchronization is accelerated. The key ingredients of our rule-based model
synchronization process are these repair rules and an incremental pattern
matcher informing about suitable applications of them. We prove the termination
and the correctness of this synchronization process and discuss its
completeness. As a proof of concept, we have implemented this synchronization
process in eMoflon, a state-of-the-art model transformation tool with inherent
support of bidirectionality. Our evaluation shows that repair processes based
on (short-cut) repair rules have considerably decreased information loss and
improved performance compared to former model synchronization processes based
on TGGs.Comment: 33 pages, 20 figures, 3 table
Boolean decomposition for AIG optimization
Restructuring techniques for And-Inverter Graphs (AIG), such as rewriting and refactoring, are powerful, scalable and fast, achieving highly optimized AIGs after few iterations. However, these techniques are biased by the original AIG structure and limited by single output optimizations. This paper investigates AIG optimization for area, exploring how far Boolean methods can reduce AIG nodes through local optimization.Boolean division is applied for multi-output functions using two-literal divisors and Boolean decomposition is introduced as a method for AIG optimization. Multi-output blocks are extracted from the AIG and optimized, achieving a further AIG node reduction of 7.76% on average for ITC99 and MCNC benchmarks.Peer ReviewedPostprint (author's final draft
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