16 research outputs found

    Time travelling animated program executions

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    Visualizations of program executions are often generated on the fly. This has many advantages relative to off-line generation of animated video files. Video files, however, trivially support flexible viewing via controls that include reverse and fast forward. Here we report on an implementation of time travel that combines the best of both techniques. In ToonTalk both the construction and execution of programs are animated. Time travel enables the user to move back in time and replay animated executions. The replay can be paused and the user can skip forward or further back in time. The implementation of time travel is based records of every input event and periodic snapshots of the state of the computation

    VisCFSM: Visual, Constraint-Based, Frequent Subgraph Mining

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    Abstract-Graphs long have been valued as a pictorial way of representing relationships between entities. Contemporary applications use graphs to model social networks, protein interactions, chemical structures, and a variety of other systems. In many cases, it is useful to detect patterns within graphs. For example, one could be interested in identifying frequently occurring subgraphs, which is known as the frequent subgraph mining problem. A complete solution to this problem can result in numerous subgraphs and can be time-consuming to compute. An approximate solution is faster, but is subject to static heuristics that are beyond the control of the user. Herein we present VisCFSM, a visual, constraint-based, frequent subgraph mining system which allows the user to dynamically specify a variety of constraints on the subgraphs to be found while the mining algorithm is running. The constraint specification interactions are performed through a visual user interface, thereby facilitating a form of visual algorithm steering. This approach can be integrated with any frequent subgraph mining algorithm. Most importantly, this approach has the potential for the user to better, and more quickly, find the information that is of most interest to him/her in a graph

    A delta-driven execution model for semantic computing

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