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IEEE Transactions on Software Engineering
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CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Visualizing interactions in program executions
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Conference Companion on Human Factors in Computing Systems
PASTE '01 Proceedings of the 2001 ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering
ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
The Field Programming Environment: A Friendly Integrated Environment for Learning and Development
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Proceedings of the 2003 ACM symposium on Software visualization
Proceedings of the 2003 ACM symposium on Software visualization
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HCC '02 Proceedings of the IEEE 2002 Symposia on Human Centric Computing Languages and Environments (HCC'02)
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SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
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SoftVis '05 Proceedings of the 2005 ACM symposium on Software visualization
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IWPC '05 Proceedings of the 13th International Workshop on Program Comprehension
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WODA '08 Proceedings of the 2008 international workshop on dynamic analysis: held in conjunction with the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2008)
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Proceedings of the 4th ACM symposium on Software visualization
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Proceedings of the 9th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering
Software and Systems Modeling (SoSyM)
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RV'11 Proceedings of the Second international conference on Runtime verification
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A practical system that uses visualization for understanding the execution of complex programs must offer the user views of the execution that are specific to the program being understood and the particular problem at hand without significantly slowing down or perturbing the system being examined. This paper describes a visualization data model and its implementation that accomplishes this. The model starts with program events that can be instrumented efficiently and with little overhead. It uses extended finite state automata to model program behaviors in terms of events. It builds time-varying data structures based on these automata. The data structures are then made available to various visualizations through a set of mappings that let the user dynamically control the visualization. The model and its implementation have been demonstrated on a range of specific understanding problems with a variety of different visualizations.