806 research outputs found
Towards rule-based visual programming of generic visual systems
This paper illustrates how the diagram programming language DiaPlan can be
used to program visual systems. DiaPlan is a visual rule-based language that is
founded on the computational model of graph transformation. The language
supports object-oriented programming since its graphs are hierarchically
structured. Typing allows the shape of these graphs to be specified recursively
in order to increase program security. Thanks to its genericity, DiaPlan allows
to implement systems that represent and manipulate data in arbitrary diagram
notations. The environment for the language exploits the diagram editor
generator DiaGen for providing genericity, and for implementing its user
interface and type checker.Comment: 15 pages, 16 figures contribution to the First International Workshop
on Rule-Based Programming (RULE'2000), September 19, 2000, Montreal, Canad
Tag-Cloud Drawing: Algorithms for Cloud Visualization
Tag clouds provide an aggregate of tag-usage statistics. They are typically
sent as in-line HTML to browsers. However, display mechanisms suited for
ordinary text are not ideal for tags, because font sizes may vary widely on a
line. As well, the typical layout does not account for relationships that may
be known between tags. This paper presents models and algorithms to improve the
display of tag clouds that consist of in-line HTML, as well as algorithms that
use nested tables to achieve a more general 2-dimensional layout in which tag
relationships are considered. The first algorithms leverage prior work in
typesetting and rectangle packing, whereas the second group of algorithms
leverage prior work in Electronic Design Automation. Experiments show our
algorithms can be efficiently implemented and perform well.Comment: To appear in proceedings of Tagging and Metadata for Social
Information Organization (WWW 2007
Designing the automatic transformation of visual languages
AbstractThe design process of complex systems requires a precise checking of the functional and dependability attributes of the target design. The growing complexity of systems necessitates the use of formal methods, as the exhaustiveness of checks performed by the traditional simulation and testing is insufficient.For this reason, the mathematical models of various formal verification tools are automatically derived from UML-diagrams of the model by mathematical transformations guaranteeing a complete consistency between the target design and the models of verification and validation tools.In the current paper, a general framework for an automated model transformation system is presented. The method starts from a uniform visual description and a formal proof concept of the particular transformations by integrating the powerful computational paradigm of graph transformation, planner algorithms of artificial intelligence, and various concepts of computer engineering
Proceedings of the ECCS 2005 satellite workshop: embracing complexity in design - Paris 17 November 2005
Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr). Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr)
String Diagrams for -calculi and Functional Computation
This tutorial gives an advanced introduction to string diagrams and graph
languages for higher-order computation. The subject matter develops in a
principled way, starting from the two dimensional syntax of key categorical
concepts such as functors, adjunctions, and strictification, and leading up to
Cartesian Closed Categories, the core mathematical model of the lambda calculus
and of functional programming languages. This methodology inverts the usual
approach of proceeding from syntax to a categorical interpretation, by
rationally reconstructing a syntax from the categorical model. The result is a
graph syntax -- more precisely, a hierarchical hypergraph syntax -- which in
many ways is shown to be an improvement over the conventional linear term
syntax. The rest of the tutorial focuses on applications of interest to
programming languages: operational semantics, general frameworks for type
inference, and complex whole-program transformations such as closure conversion
and automatic differentiation
An introduction to Graph Data Management
A graph database is a database where the data structures for the schema
and/or instances are modeled as a (labeled)(directed) graph or generalizations
of it, and where querying is expressed by graph-oriented operations and type
constructors. In this article we present the basic notions of graph databases,
give an historical overview of its main development, and study the main current
systems that implement them
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