Browsing by Author "Omidiora E. O."

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    A Complexity Metric for Multi-Paradigm Programming Languages
    (International Journal of Emerging Technology and Advanced Engineering, 2014-04-22) Olabiyisi S. O.; Omidiora E. O.; Balogun M. O.
    Software complexity metrics are used to measure variety of software properties such as cost, effort, time, maintenance, understanding and reliability. Most of the existing metrics considered limited factors that affect software complexity, but do not consider the characteristics 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 used in this work combine the features of procedural and object oriented paradigms, therefore this research began with investigation of factors that affect the complexity of procedural code, thereafter with a more modern approach, the research was further extended by adding object oriented features, so that the developed metric could be used not only for procedural code, but also either object oriented codes or in more general meaning for multi-paradigm codes. The developed metric was then applied on sample programs written in most popular programming languages such as Python, Java and C++, and 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 competitive programs and difficulties of various modules.