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• W2001215825 abstract "Word-Level Decision Diagrams (WLDDs), like *BMDs and K*BMDs, have recently been introduced as a data structure for verification. The size of WLDDs largely depends on the chosen variable ordering, i.e. the ordering in which variables are encountered, on the decompositions carried out in each node, and on the grouping of the outputs. In this paper we present a framework for dynamic minimization of WLDDs by changing the ordering and the decomposition type. We discuss the difficulties with previous techniques if applied to WLDDs and present a new approach that efficiently adapts both, variable ordering and decomposition type choice. Furthermore, we present a technique that is based on computing lower bounds to speed up dynamic minimization. Finally, for output grouping a first heuristic is presented that groups the outputs based on information extracted from the circuit topology. For all approaches experimental results are given that show the efficiency of the techniques proposed." @default.
• W2001215825 created "2016-06-24" @default.
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• W2001215825 date "2002-12-01" @default.
• W2001215825 modified "2023-09-26" @default.
• W2001215825 title "Minimization of Word-Level Decision Diagrams" @default.
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• W2001215825 doi "https://doi.org/10.1016/s0167-9260(02)00047-0" @default.
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