The Möbius Framework and Its Implementation
IEEE Transactions on Software Engineering
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
A synthetic traffic model for Quake3
Proceedings of the 2004 ACM SIGCHI International Conference on Advances in computer entertainment technology
Trace based analysis of process interaction models
WSC '05 Proceedings of the 37th conference on Winter simulation
Traviando - Debugging Simulation Traces with Message Sequence Charts
QEST '06 Proceedings of the 3rd international conference on the Quantitative Evaluation of Systems
An integrated framework for enabling effective data collection and statistical analysis with ns-2
WNS2 '06 Proceeding from the 2006 workshop on ns-2: the IP network simulator
A trace-based visual inspection technique to detect errors in simulation models
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Identifying hierarchical structure in sequences: a linear-time algorithm
Journal of Artificial Intelligence Research
Recovering model invariants from simulation traces with Petri net analysis techniques
Winter Simulation Conference
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Most discrete event simulation frameworks are able to output simulation runs as a trace. The Network Simulator 2 (NS2) is a prominent example that does so to decouple generation of dynamic behavior from its evaluation. If a modeler is interested in the specific details and confronted with lengthy traces from simulation runs, support is needed to identify relevant pieces of information. In this paper, we present a new phrase-based browser that has its roots in information retrieval, language acquisition and text compression which is refined to work with trace data derived from simulation models. The browser is a new navigation feature of Traviando, a trace visualizer and analyzer for simulation traces. The browsing technique allows a modeler to investigate particular patterns seen in a trace, that may be of interest due to their frequent or rare occurrence. We demonstrate how this approach applies to traces generated with NS2.