Browsing by Author "Sotonwa K. A."

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    A Comparative Analysis of Complexity of C++ and Python Programming Languages Using Multi- Paradigm Complexity Metric (MCM)
    (International Journal of Science and Research (IJSR), 2018-10-26) Balogun M. O.; Sotonwa K. A.
    Software complexity metrics have used to quantifydifferent types of software properties such as cost, effort, time, maintainability, understanding and reliability. The existing metrics considered limited factors that affect software complexity, but do not consider the characteristics that affect complexity of multi-paradigm languages. In this work, a Multi-paradigm Complexity Metric (MCM) for measuring software complexity was developed for multi-paradigm codes. Multi-paradigm languages that were considered in thiswork are C++ and Python, these two languages combine the features of procedural and object oriented paradigms, therefore this research began with investigation of factors that affect the complexity of procedural code and object oriented code, so that the developed metric could be used not only for procedural code, but also either object oriented codes or in more general for multi-paradigm codes. The developed metric was then applied on sample programs written in most popular programming languages such as Python and C++, and the result of the developed metric was further evaluated with other existing complexity metrics like effective line of code (eLOC), cyclomatic complexity metric and Halstead complexity measures. The study showed that the developed complexity metric have significant comparison with the existing complexity metrics and can be used to rank numerous programs and difficulties of various modules.
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    Code Quality Metric of Searching Algorithms for Multi-Paradigm Languages
    (International Journal of Scientific Research and Management (IJSRM), 2019-05-20) Sotonwa K. A.; Balogun M. O.; Olusi Titilayo
    This study investigated the comprehensibility of a software code from a developer‟s point of view and proposed new metric accordingly. The factors that affect the complexity of procedural, object-oriented, and multi-paradigm codes were analyzed for this purpose. Addition to the investigated factors, various metrics and several aspects were combined in the proposed metric. The proposed metric were empirically validated in different paradigms.