Open AccessCOMPARISON OF SOFTWARE COMPLEXITY OF SEARCH ALGORITHM USING CODE BASED COMPLEXITY METRICS
Author(s) -
Bello Muriana,
Ogba Paul Onuh
Publication year - 2021
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2021.v06i05.003
Subject(s) - computer science , python (programming language) , algorithm , programming complexity , software , software metric , software quality , search algorithm , theoretical computer science , programming language , software development , software construction
Measures of software complexity areessential part of software engineering. Complexitymetrics can be used to forecast key informationregarding the testability, reliability, andmanageability of software systems from study ofthe source code. This paper presents the results ofthree distinct software complexity metrics thatwere applied to two searching algorithms (Linearand Binary search algorithm). The goal is tocompare the complexity of linear andbinary search algorithms implemented in (Python,Java, and C++ languages) and measure the samplealgorithms using line of code, McCabe andHalstead metrics. The findings indicate that theprogram difficulty of Halstead metrics hasminimal value for both linear and binary searchwhen implemented in python. Analysis ofVariance (ANOVA) was adopted to determinewhether there is any statistically significantdifferences between the search algorithms whenimplemented in the three programming languagesand it was revealed that the three (3)programming languages do not vary considerablyfor both linear and binary search techniqueswhich implies that any of the (3) programminglanguages is suitable for coding linear and binarysearch algorithms.