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New and improved search algorithms and precise analysis of their average-case complexity

机译:新的和改进的搜索算法以及对平均情况复杂度的精确分析

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摘要

In this paper, we consider the searching problem over ordered sequences. It is well known that Binary Search (BS) algorithm solves this problem with very efficient complexity, namely with the complexity theta(log(2)n). The developments of the BS algorithm, such as Ternary Search (TS) algorithm do not improve the efficiency. The rapid increase in the amount of data has made the search problem more important than in the past. And this made it important to reduce average number of comparisons in cases where the asymptotic improvement is not achieved. In this paper, we identify and analyze an implementation issue of BS. Depending on the location of the conditional operators, we classify two different implementations for BS which are widely used in the literature. We call these two implementations weak and correct implementations. We calculate precise number of comparisons in average case for both implementations. Moreover, we transform the TS algorithm into an improved ternary search (ITS) algorithm. We also propose a new Binary-Quaternary Search (BQS) algorithm by using a novel dividing strategy. We prove that an average number of comparisons for both presented algorithms ITS and BQS is less than for the case of correct implementation of the BS algorithm. We also provide the experimental results. (C) 2019 Elsevier B.V. All rights reserved.
机译:在本文中,我们考虑了有序序列上的搜索问题。众所周知,二进制搜索(BS)算法以非常有效的复杂度,即复杂度theta(log(2)n)解决了该问题。三元搜索(TS)算法等BS算法的发展并未提高效率。数据量的迅速增加使搜索问题比过去更加重要。因此,在没有实现渐近改善的情况下,减少平均比较数非常重要。在本文中,我们确定并分析了BS的实施问题。根据条件运算符的位置,我们将BS中的两种不同实现方式分类,这在文献中被广泛使用。我们称这两个实现为弱和正确的实现。我们计算两种情况下平均情况下的精确比较数。此外,我们将TS算法转换为改进的三元搜索(ITS)算法。我们还通过使用一种新颖的划分策略,提出了一种新的二元-四元搜索(BQS)算法。我们证明,所提出的算法ITS和BQS的平均比较次数少于正确执行BS算法的情况。我们还提供了实验结果。 (C)2019 Elsevier B.V.保留所有权利。

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