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On the Embedding Phase of the Hopcroft and Tarjan Planarity Testing Algorithm
 ALGORITHMICA
, 1994
"... We give a detailed description of the embedding phase of the Hopcroft and Tarjan planarity testing algorithm. The embedding phase runs in linear time. An implementation based on this paper can be found in [MMN93]. ..."
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Cited by 35 (6 self)
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We give a detailed description of the embedding phase of the Hopcroft and Tarjan planarity testing algorithm. The embedding phase runs in linear time. An implementation based on this paper can be found in [MMN93].
The LEDA class real number
 MaxPlanck Institut Inform
, 1996
"... We describe the implementation of the LEDA [MN95, Nah95] data type real. Every integer is a real and reals are closed under the operations addition, subtraction, multiplication, division and squareroot. The main features of the data type real are ffl The userinterface is similar to that of the bu ..."
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Cited by 16 (5 self)
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We describe the implementation of the LEDA [MN95, Nah95] data type real. Every integer is a real and reals are closed under the operations addition, subtraction, multiplication, division and squareroot. The main features of the data type real are ffl The userinterface is similar to that of the builtin data type double.
GeoSheet: A Distributed Visualization Tool for Geometric Algorithms
 Int'l J. Computational Geometry & Applications
, 1994
"... GeoSheet (version 1.0) is an interactive visualization tool for visualizing geometric algorithms in distributed environments. It provides features such as interactive visualization of program states for debugging, highlevel graphical input/output manipulation facilities for geometric objects, reuse ..."
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Cited by 10 (3 self)
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GeoSheet (version 1.0) is an interactive visualization tool for visualizing geometric algorithms in distributed environments. It provides features such as interactive visualization of program states for debugging, highlevel graphical input/output manipulation facilities for geometric objects, reuse of existing data structures and algorithms implementation, and more importantly distributed executions on heterogeneous machines at different sites. To minimize development effort of the tool we make use of existing software packages available in public domain. Specifically we extend Xfig with a messagedriven interface and a socketbased interprocess communication (IPC) mechanism. This extendedXfig is the backbone of this version of the tool. Objectoriented programming methodology is used to construct the visualization interface. By deriving from traditional data type and algorithm libraries, our abstract GeoObject representation superclasses are easy to use, easy to construct, and hig...
Three Rules Suffice for Good Label Placement
 Algorithmica Special Issue on GIS
, 2000
"... The general labelplacement problem consists in labeling a set of features (points, lines, regions) given a set of candidates (rectangles, circles, ellipses, irregularly shaped labels) for each feature. The problem arises when annotating classical cartographical maps, diagrams, or graph drawings. Th ..."
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Cited by 10 (1 self)
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The general labelplacement problem consists in labeling a set of features (points, lines, regions) given a set of candidates (rectangles, circles, ellipses, irregularly shaped labels) for each feature. The problem arises when annotating classical cartographical maps, diagrams, or graph drawings. The size of a labeling is the number of features that receive pairwise nonintersecting candidates. Finding an optimal solution, i.e. a labeling of maximum size, is NPhard. We present an approach to attack the problem in its full generality. The key idea is to separate the geometric part from the combinatorial part of the problem. The latter is captured by the conflict graph of the candidates. We present a set of rules that simplify the conflict graph without reducing the size of an optimal solution. Combining the application of these rules with a simple heuristic yields nearoptimal solutions. We study competing algorithms and do a thorough empirical comparison on pointlabeling data. The new algorithm we suggest is fast, simple, and effective.
Graphical User Interface for Compiler Optimizations with SimpleSUIF
, 1996
"... OF THE THESIS Graphical User Interface for Compiler Optimizations with SimpleSUIF by Brian Keith Harvey Master of Science, Graduate Program in Computer Science University of California, Riverside, December, 1996 Professor Gary Tyson, Chairperson Very few tools exist which support the process ..."
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Cited by 9 (0 self)
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OF THE THESIS Graphical User Interface for Compiler Optimizations with SimpleSUIF by Brian Keith Harvey Master of Science, Graduate Program in Computer Science University of California, Riverside, December, 1996 Professor Gary Tyson, Chairperson Very few tools exist which support the process of studying back end optimizations. Currently, researchers examining different back end optimizations must rely on general debugging tools or design their own tools to help in the generation of optimizing functions. A tool designed to give information specifically tailored for optimization designers is necessary. Such a tool would allow researchers to view the results of a newly designed optimization or analyze how the intermediate code of a program changes depending on the order in which transformations are applied. More efficient development of optimization routines should be the result of using this tool. This thesis presents the Visual SimpleSUIF Compiler (VSSC) package, designed to a...
Towards WebBased Computing
, 1999
"... In a problem solving environment for geometric computing, a graphical user interface, or GUI, for visualization has become an essential component for geometric software development. In this paper we describe a visualization system, called GeoJAVA, which consists of a GUI and a geometric visualiza ..."
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Cited by 3 (1 self)
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In a problem solving environment for geometric computing, a graphical user interface, or GUI, for visualization has become an essential component for geometric software development. In this paper we describe a visualization system, called GeoJAVA, which consists of a GUI and a geometric visualization library that enables the user or algorithm designer to (1) execute and visualize an existing algorithm in the library or (2) develop new code over the Internet. The library consists of geometric code written in C/C++. The GUI is written using the Java programming language. Taking advantage of the socket classes and systemindependent application programming interfaces (API's) provided with the Java language, GeoJAVA oers a platform independent environment for distributed geometric computing that combines Java and C/C++. Users may remotely join a \channel" or discussion group in a location transparent manner to do collaborative research. The visualization of an algorithm, a C/C+...
The Prototyping Of Geomanager: A Geometric Algorithm Manipulation System
, 1995
"... Contents Acknowledgments ii 1 Introduction 1 1.1 Description of GeoMAMOS . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Description of GeoSheet and GeoIPC . . . . . . . . . . . . . . . . . . 2 1.3 Description of the Project . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3.1 Limitations of ..."
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Cited by 2 (2 self)
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Contents Acknowledgments ii 1 Introduction 1 1.1 Description of GeoMAMOS . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Description of GeoSheet and GeoIPC . . . . . . . . . . . . . . . . . . 2 1.3 Description of the Project . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3.1 Limitations of the original configuration . . . . . . . . . . . . 3 1.3.2 The solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3.3 Implementation approaches . . . . . . . . . . . . . . . . . . . 3 2 Project Requirements 5 2.1 Transparency to the user . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Hardcoded algorithms in GeoSheet . . . . . . . . . . . . . . . . . . . 5 2.3 System independence . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3 Project Implementation 7 3.1 Function pointers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2 GSArguments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.
Geometric Algorithm Visualization, Current Status and Future
 Applied Computational Geometry, Lin and Manocha (Eds
, 1996
"... . We give a survey of the current status of geometric algorithm visualization and offer some suggestions regarding geometric software library and future directions for visualization software. 1 Introduction Since its inception two decades ago computational geometry has become a very active research ..."
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. We give a survey of the current status of geometric algorithm visualization and offer some suggestions regarding geometric software library and future directions for visualization software. 1 Introduction Since its inception two decades ago computational geometry has become a very active research field within theoretical computer science. There are a good number of research publications collected in pub/geometry/geombib.tar.Z, available via anonymous ftp from ftp.cs.usask.ca. Several journals dedicated to computational geometry have been established. The reader is encouraged to visit the Web page on Geometry in Action by D. Eppstein at http://www.ics.uci.edu/ ~eppstein/geom.html and computational geometry page by J. Erickson at http:// www.cs.berkeley.edu/~jeffe/compgeom.html for more information. Only recently an informal assessment of the impact of the field on other science and engineering disciplines was conducted and the questions of its relevance to practice were raised among...
Implementation of a Linear ExpectedTime Algorithm for Finding Connected Components
"... We describe a robust and efficient implementation of the Karp and Tarzan [4] algorithm for finding the connected components of an undirected graph. The algorithm achieves to find the connected components of a graph G = (V,E) in O(V) expected time. The implementation of the algorithm (called GCOMPO ..."
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We describe a robust and efficient implementation of the Karp and Tarzan [4] algorithm for finding the connected components of an undirected graph. The algorithm achieves to find the connected components of a graph G = (V,E) in O(V) expected time. The implementation of the algorithm (called GCOMPONENTS) is based on the LEDA library of efficient data types and algorithms [5,6,7]. This is the first expectedtime algorithm for graph connectivity implemented in LEDA. Note that the best algorithm for finding the connected components in a graph requires time O(V+E) in the worst case. Such an algorithm called COMPONENTS, is implemented in LEDA. Contents 1. Introduction....................................................................................................................................1 2. The Algorithm................................................................................................................................2 3. The Implementation .......................