1987•SIAM Journal on ComputingRequires access

Binary Search on a Tape

T. C. Hu, Michelle L. Wachs

Open publisher page 9 citations

Abstract

Given n records stored alphabetically on a tape, any comparison search procedure can be characterized by a binary tree. The complete binary tree (binary search) uses the minimum number of comparisons but not the minimum number of movements. The linear binary tree (sequential search) uses the minimum number of movements but not the minimum number of comparisons. A tape-optimal tree is a tree which minimizes the total cost of comparisons and movements. The tape-optimal tree is a “hybrid” of the linear tree and the complete binary tree, and is characterized for arbitrary n.

About this research paper

What this paper is about

Given n records stored alphabetically on a tape, any comparison search procedure can be characterized by a binary tree. The complete binary tree (binary search) uses the minimum number of comparisons but not the minimum number of movements. The linear binary tree (sequential search) uses the minimum number of movements but not the minimum number of comparisons. A tape-optimal tree is a tree which minimizes the total cost of comparisons and movements. The tape-optimal tree is a “hybrid” of the linear tree and the complete binary tree, and is characterized for arbitrary n.

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OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Given n records stored alphabetically on a tape, any comparison search procedure can be characterized by a binary tree. The complete binary tree (binary search) uses the minimum number of comparisons but not the minimum number of movements. The linear binary tree (sequential search) uses the minimum number of movements but not the minimum number of comparisons. A tape-optimal tree is a tree which minimizes the total cost of comparisons and movements. The tape-optimal tree is a “hybrid” of the linear tree and the complete binary tree, and is characterized for arbitrary n.

Key concepts: Self-balancing binary search tree, Optimal binary search tree, Random binary tree, Interval tree, Ternary search tree, Binary tree, Binary search tree, K-ary tree

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