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In a 1977 review of permutation-generating algorithms, Robert Sedgewick concluded that it was at that time the most effective algorithm for generating permutations by computer. [2] The sequence of permutations of n objects generated by Heap's algorithm is the beginning of the sequence of permutations of n+1 objects.
Robert Sedgewick (born December 20, 1946) is an American computer scientist. He is the founding chair and the William O. Baker Professor in Computer Science at Princeton University [ 1 ] and was a member of the board of directors of Adobe Systems (1990–2016). [ 2 ]
Multi-key quicksort, also known as three-way radix quicksort, [1] is an algorithm for sorting strings.This hybrid of quicksort and radix sort was originally suggested by P. Shackleton, as reported in one of C.A.R. Hoare's seminal papers on quicksort; [2]: 14 its modern incarnation was developed by Jon Bentley and Robert Sedgewick in the mid-1990s. [3]
The main part of the book is organized into three parts. The first part, covering three chapters and roughly the first quarter of the book, concerns the symbolic method in combinatorics, in which classes of combinatorial objects are associated with formulas that describe their structures, and then those formulas are reinterpreted to produce the generating functions or exponential generating ...
A pairing heap is a type of heap data structure with relatively simple implementation and excellent practical amortized performance, introduced by Michael Fredman, Robert Sedgewick, Daniel Sleator, and Robert Tarjan in 1986. [1] Pairing heaps are heap-ordered multiway tree structures, and can be considered simplified Fibonacci heaps.
The algorithms make exactly the same comparisons, but in a different order. An often desirable property of a sorting algorithm is stability – that is the order of elements that compare equal is not changed, allowing controlling order of multikey tables (e.g. directory or folder listings) in a natural way.
All of the red-black tree algorithms that have been proposed are characterized by a worst-case search time bounded by a small constant multiple of log N in a tree of N keys, and the behavior observed in practice is typically that same multiple faster than the worst-case bound, close to the optimal log N nodes examined that would be observed in a perfectly balanced tree.
The heapsort algorithm can be divided into two phases: heap construction, and heap extraction. The heap is an implicit data structure which takes no space beyond the array of objects to be sorted; the array is interpreted as a complete binary tree where each array element is a node and each node's parent and child links are defined by simple arithmetic on the array indexes.