Voyeur: graphical views of parallel programs
PADD '88 Proceedings of the 1988 ACM SIGPLAN and SIGOPS workshop on Parallel and distributed debugging
Visualization of message passing parallel programs with the TOPSYS parallel programming environment
Journal of Parallel and Distributed Computing - Special issue on tools and methods for visualization of parallel systems and computations
A methodology for building application-specific visualizations of parallel programs
Journal of Parallel and Distributed Computing - Special issue on tools and methods for visualization of parallel systems and computations
Pad: an alternative approach to the computer interface
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Distributed algorithms visualisation for educational purposes
ITiCSE '99 Proceedings of the 4th annual SIGCSE/SIGCUE ITiCSE conference on Innovation and technology in computer science education
Jazz: an extensible zoomable user interface graphics toolkit in Java
UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Introduction to Algorithms
Creating an Accurate Portrayal of Concurrent Executions
IEEE Concurrency
IEEE Computer Graphics and Applications
Visualizing the Performance of Parallel Programs
IEEE Software
Algorithm Visualization For Distributed Environments
INFOVIS '98 Proceedings of the 1998 IEEE Symposium on Information Visualization
Growing squares: animated visualization of causal relations
Proceedings of the 2003 ACM symposium on Software visualization
Causality visualization using animated growing polygons
INFOVIS'03 Proceedings of the Ninth annual IEEE conference on Information visualization
Visualizing Causal Semantics Using Animations
IEEE Transactions on Visualization and Computer Graphics
Analyzing animated representations of complex causal semantics
Proceedings of the 6th Symposium on Applied Perception in Graphics and Visualization
EuroVis'08 Proceedings of the 10th Joint Eurographics / IEEE - VGTC conference on Visualization
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Causality visualization is an important tool for many scientific domains that involve complex interactions between multiple entities (examples include parallel and distributed systems in computer science). However, traditional visualization techniques such as Hasse diagrams are not well-suited to large system executions, and users often have difficulties answering even basic questions using them, or have to spend inordinate amounts of time to do so. In this paper, we present the Growing Squares and Growing Polygons methods, two sibling visualization techniques that were designed to solve this problem by providing efficient 2D causality visualization through the use of color, texture, and animation. Both techniques have abandoned the traditional linear timeline and instead map the time parameter to the size of geometrical primitives representing the processes; in the Growing Squares case, each process is a color-coded square that receives color influences from other process squares as messages reach it; in the Growing Polygons case, each process is instead an n-sided polygon consisting of triangular sectors showing color-coded influences from the other processes. We have performed user studies of both techniques, comparing them with Hasse diagrams, and they have been shown to be significantly more efficient than old techniques, both in terms of objective performance as well as the subjective opinion of the test subjects (the Growing Squares technique is, however, only significantly more efficient for small systems).