Degree profile of m-ary search trees: A vehicle for data structure compression
classification
🧮 math.PR
keywords
analysiscompressiondatanodenodesnumberoutdegreeprofile
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We revisit the random $m$-ary search tree and study a finer profile of its node outdegrees with the purpose of exploring possibilities of data structure compression. The analysis is done via P\'olya urns. The analysis shows that the number of nodes of each individual node outdegree has a phase transition: Up to $m=26$, the number of nodes of outdegree $k$, for $k=0,1, \ldots, m$, is asymptotically normal; that behavior changes at $m = 27$. Based on the analysis, we propose a compact $m$-ary tree that offers significant space saving.
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