We present a hybrid visualization technique for compound graphs (i.e. networks with a hierarchical clustering defined on the nodes) that combines the use of adjacency matrices, node-link and arc diagrams to show the graph, and also combines the use of nested inclusion and icicle diagrams to show the hierarchical clustering. The graph visualized with our technique may have edges that are weighted and/or directed. We first explore the design space of visualizations of compound graphs and present a taxonomy of hybrid visualization techniques. We then present our prototype, which allows clusters (i.e. subtrees) of nodes to be grouped into matrices or split apart using a radial menu. We also demonstrate how our prototype can be used in the software engineering domain, and compare it to the commercial matrix-based visualization tool Lattix using a qualitative user study.

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N-Modular Redundancy (NMR) and N-Version Programming (NVP) are two popular fault tolerance techniques in which hardware and software redundancy is exploited to mask faults. Redundant hardware is used to improve fault tolerance rather than throughput. We introduce a scheme for combined hardware-software fault tolerance derived from NMR and NVP that shows how redundancy can also be used to improve throughput by grouping the execution of several tasks. Our scheme uses a dynamic task allocation algorithm with an optimistic execution policy where the number of task executions is kept close to the minimum required to produce fault-jree results. For equivalent hardware and software resources,the proposed method is 50% to 100% more efJicient in terms of throughput and latency.

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