Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
Programmers find it difficult to gauge the code complexity of an application, which makes the concept difficult to understand. The McCabe metric and Halstead`s software science are two common code complexity measures. The McCabe metric determines code complexity based on the number of control paths created by the code. While this information supplies only a portion of the complex picture, it provides an easy-to-compute, high-level measure of a program`s complexity. The McCabe metric is often used for testing. Halstead bases his approach on the mathematical relationships among the number of variables, the complexity of the code and the type of programming language statements. In this study, the 2 software complexity measures are applied to Merge sort algorithm. The intention is to study what kind of new information about the algorithm the complexity measures are able to give and to study which software complexity measures are the most useful ones in algorithm comparison. The results explicitly show that Merge sort has the least Halstead’s Volume, Program Difficulty and Program Effort when programmed in Assembly language and has the least cyclomatic number when programmed in Visual BASIC.
How to cite this article:
S.O. Olabiyisi and O.A. Bello . An Exploratory Study of Software Complexity Measures of Merge Sort Algorithm.
DOI: https://doi.org/10.36478/jeasci.2008.368.372
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2008.368.372