Stephen G. Kobourov

A system for graph-based visualization of the evolution of software

We describe GEVOL, a system that visualizes the evolution of software using a novel graph drawing technique for visualization of large graphs with a temporal component. GEVOL extracts information about a Java program stored within a CVS version control system and displays it using a temporal graph visualizer. This information can be used by programmers to understand the evolution of a legacy program: Why is the program structured the way it is? Which programmers were responsible for which parts of the program during which time periods? Which parts of the program appear unstable over long periods of time and may need to be rewritten? This type of information will complement that produced by more static tools such as source code browsers, slicers, and static analyzers.

PILOT: an interactive tool for learning and grading

We describe a Web-based interactive system, called PILOT, for testing computer science concepts. The strengths of PILOT are its universal access and platform independence, its use as an algorithm visualization tool, its ability to test algorithmic concepts, its support for graph generation and layout, its automated grading mechanism, and its ability to award partial credit to proposed solutions.

Balanced aspect ratio trees: combining the advantages of k -d trees and octrees

Given a set S of n points on Rd, we show, for fixed d, how to construct in O(nlogn) time a data structure we call the balanced aspect ratio (BAR) tree. A BAR tree is a binary space partition tree on S that has O(logn) depth in which every region is convex and “fat” (that is, has a bounded aspect ratio). While previous hierarchical data structures such as k-d trees, quadtrees, octrees, fair-split trees, and balanced box decompositions can guarantee some of these properties, we know of no previous data structure that combines all of these properties simultaneously. The BAR tree data structure has numerous applications ranging from geometric searching problems in fixed dimensional space to the visualization of graphs and three-dimensional worlds.

GMap: Visualizing graphs and clusters as maps

Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through dimensionality reduction techniques. However, these traditional methods often do not capture well the underlying structural information, clustering, and neighborhoods. In this paper, we describe GMap, a practical algorithm for visualizing relational data with geographic-like maps. We illustrate the effectiveness of this approach with examples from several domains.

Self-plagiarism in computer science

We are all too aware of the ravages of misconduct in the academic community. Students submit assignments inherited from their friends, online papermills provide term papers on popular topics, and occasionally researchers are found falsifying data or publishing the work of others as their own.This article examines a lesser-known but potentially no less bothersome form of scientific misconduct, namely self-plagiarism. Self-plagiarism occurs when authors reuse portions of their previous writings in subsequent research papers. Occasionally, the derived paper is simply a retitled and reformatted version of the original one, but more frequently it is assembled from bits and pieces of previous work.

Simultaneous Graph Drawing: Layout Algorithms and Visualization Schemes

In this paper we consider the problem of drawing and displaying a series of related graphs, i.e., graphs that share all, or parts of the same vertex set. We designed and implemented three different algorithms for simultaneous graph drawing and three different visualization schemes. The algorithms are based on a modification of the force-directed algorithm that allows us to take into account vertex weights and edge weights in order to achieve mental map preservation while obtaining individually readable drawings. The implementation is in Java and the system can be downloaded at http://simg.cs.arizona.edu/.

The geometric thickness of low degree graphs

We prove that the geometric thickness of graphs whose maximum degree is no more than four is two. All of our algorithms run in O(n) time, where n is the number of vertices in the graph. In our proofs, we present an embedding algorithm for graphs with maximum degree three that uses an n x n grid and a more complex algorithm for embedding a graph with maximum degree four. We also show a variation using orthogonal edges for maximum degree four graphs that also uses an n x n grid. The results have implications in graph theory, graph drawing, and VLSI design.

Ranges of human mobility in Los Angeles and New York

The advent of ubiquitous, mobile, personal devices creates an unprecedented opportunity to improve our understanding of human movement. In this work, we study human mobility in Los Angeles and New York by analyzing anonymous records of approximate locations of cell phones belonging to residents of those cities. We examine two data sets gathered six months apart, each representing hundreds of thousands of people, containing hundreds of millions of location events, and spanning two months of activity. We present, compare, and validate the daily range of travel for people in these populations. Our findings include that human mobility changes with the seasons: both Angelenos and New Yorkers travel less in the winter, with New Yorkers showing a greater decrease in mobility during the cold months. We also show that text messaging activity does not by itself accurately characterize daily range, whereas voice calling alone suffices. Finally, we show that our methodology is accurate by comparing our results to ground truth obtained from volunteers.

Selected Open Problems in Graph Drawing

In this manuscript, we present several challenging and interesting open problems in graph drawing. The goal of the listing in this paper is to stimulate future research in graph drawing.

Tight bounds on maximal and maximum matchings

In this paper, we study lower bounds on the size of maximal and maximum matchings in 3-connected planar graphs and graphs with bounded maximum degree. For each class, we give a lower bound on the size of matchings, and show that the bound is tight for some graph within the class.