Proceedings IEEE Symposia on Human-Centric Computing Languages and Environments (Cat. No.01TH8587)
DOI: 10.1109/hcc.2001.995274
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Moses-a tool suite for visual modeling of discrete-event systems

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Cited by 22 publications
(11 citation statements)
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“…In the academic community, active objects and actors [13], [14], port-based objects [15], hybrid I/O automata [16], Moses [17], Polis [18], Ptolemy [19], and Ptolemy II [2] all emphasize actor orientation.…”
Section: A Actor Orientationmentioning
confidence: 99%
“…In the academic community, active objects and actors [13], [14], port-based objects [15], hybrid I/O automata [16], Moses [17], Polis [18], Ptolemy [19], and Ptolemy II [2] all emphasize actor orientation.…”
Section: A Actor Orientationmentioning
confidence: 99%
“…With the support of an underlying framework, e.g. the Moses tool suite [10], the designer can edit, simulate and automatically analyse heterogeneous models. At the time of writing, the core part of the presented work in this article has been implemented in the Moses.…”
Section: Introductionmentioning
confidence: 99%
“…Their static semantics is specified by a set of first-order predicates over the abstract syntax of the graphs. The reason for choosing this approach is mainly due to the strong tool support from the Moses tool suite [10]. It is also because this approach is generic to graph-like visual languages and thus makes heterogeneous modelling possible [20].…”
Section: Introductionmentioning
confidence: 99%
“…This is because it involves fewer traversals through these task graphs in subsequent invocations of the analysis, thereby saving the overheads associated with these traversals due to the potentially complicated data structures. This observation stems from our attempt to integrate this schedulability analysis algorithm inside a tool-suite [Esser and Janneck 2001] where the task graphs were specified using a graphical user interface and were embedded inside other data structures that were a part of this tool-suite. In this implementation we observed 20× speedups using our algorithm for task graphs with less than 40 vertices.…”
Section: Experiments With Step (I)mentioning
confidence: 99%