Halstead’s Complexity Measure of a Merge sort and Modified Merge sort Algorithms

G. B. Balogun, Muhideen Abdulraheem, Peter Ogirima Sadiku, Olawale Debo Taofeek, Adebisi Adewale
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Abstract

Complexity measuring tools in computer science are deployed to measure and compare different characteristics of algorithms in order to find the best one in solving a particular problem or that suits a particular situation. In view of this, Halstead’s complexity metrics is deployed to compare the efficiency of two external sorting methods; the Merge sort and the Modified Merge sort algorithms. The methodology used in achieving this, lies in the extraction of operators and operands from the C_sharp (C#) implemented program of the two algorithms. Six Halstead metrics are evaluated using these operators and operands as parameters. The results shows that the Modified Merge sort algorithm is much more efficient than the conventional Merge sort as it has a lower Program Volume, lower Program difficulty and a lower Program Effort even though the advantage of a higher Intelligence content goes to the Merge sort algorithm.
合并排序算法和修正合并排序算法的哈尔斯特德复杂度测量法
计算机科学中的复杂性测量工具用于测量和比较算法的不同特性,以便找到解决特定问题或适合特定情况的最佳算法。有鉴于此,Halstead 的复杂度度量工具被用来比较两种外部排序方法的效率:合并排序算法和修正合并排序算法。实现这一目标所使用的方法是从这两种算法的 C_sharp (C#) 实现程序中提取运算符和操作数。使用这些运算符和操作数作为参数,对六个 Halstead 指标进行了评估。结果表明,修改后的合并排序算法比传统的合并排序算法更有效率,因为它的程序量更少、程序难度更低和程序耗费更少,尽管合并排序算法具有智能含量更高的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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