Exploiting hardware performance counters with flow and context sensitive profiling
Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
Extracting usability information from user interface events
ACM Computing Surveys (CSUR)
ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
Visualizing the Execution of Java Programs
Revised Lectures on Software Visualization, International Seminar
JIVE: visualizing Java in action demonstration description
Proceedings of the 25th International Conference on Software Engineering
The information mural: a technique for displaying and navigating large information spaces
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
The Tau Parallel Performance System
International Journal of High Performance Computing Applications
Proceedings of the 2006 AVI workshop on BEyond time and errors: novel evaluation methods for information visualization
Exploiting the Analogy Between Traces and Signal Processing
ICSM '06 Proceedings of the 22nd IEEE International Conference on Software Maintenance
Streamsight: a visualization tool for large-scale streaming applications
Proceedings of the 4th ACM symposium on Software visualization
Execution trace analysis through massive sequence and circular bundle views
Journal of Systems and Software
Discovering actionable patterns in event data
IBM Systems Journal
Visual and algorithmic tooling for system trace analysis: a case study
ACM SIGOPS Operating Systems Review
| Hi-index | 0.00 |
Information in event traces from software systems can help developers with performance analysis, debuggingand troubleshooting. However, the volume of data contained in these traces can make such tasks a challenge. In this paper we propose a new tool, Zinsight, to visualize event traces from complex systems. Our contribution is a novel combination of visualizations and pattern extraction techniques, enabling user exploration, analysis and understanding of traces containing millions of events. Three complimentary views help the user answer different questions. First, the Event Flow view shows the trace in its entirety or in detail. The user sees visual patterns representing phases of processing and the relative order of events. Second, the Event Statistics view quantifies events, and presents distributions and averages enabling the user to identify outlier behavior. Third, the Sequence Context view extracts patterns of interest from the trace and represents them along with frequency and performance data in succinct execution flow diagrams. The user can navigate from patterns to their constituent instance sequences and even back to individual events in the other views. Questions can be answered and hypotheses tested using the most natural view for the task.