Browsing by Author "ADIGUN, Maria Funmilayo"

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    Comparative Analysis of Certain Data Analytic Languages Using Code Based Metrics
    (Bells University of Technology, 2019-10-17) ADIGUN, Maria Funmilayo; Prof. M. O. Abass
    Software complexity metrics is developed and used by the various software organizations for evaluating and assuring software code quality, operation, and maintenance. Software metrics measure various types of software complexity like size metrics, control flow metrics and data flow metrics. These software complexities must be continuously calculated, followed, and controlled because high complexity may result in more errors and difficulties in maintenance, understandability, modification and testing effort. The revival of data science due to the presence of large amount of data has resulted in the need for a good programming language on which many data science applications can be developed. Hence the need to apply programming complexity metrics to existing data analytic languages so as to guide programmers in choosing tools for building data science applications. For application, binary search and quicksort algorithms are considered. The programs are written in three different data analytic languages: Python, R and Scala. Software complexity for each is found using LOC, McCabe and Halstead models. The results are compared and Scala is realized to be the most complex for all the metrics while Python and R programs are averagely at par.