2023Unpublished venueOpen access

Evaluating the Accuracy of Different Software Complexity Metrics in Predicting Software Performance.

H. G. S. Lakshan, D. I. De Silva, M. V. N. Godapitiya, S. P. B. A. Prathyanga, K. L. P. Chamikara, P. S. Wimalagunasekara

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Abstract

To determine the complexity of software systems, software complexity measures are commonly utilized. However, their accuracy in forecasting software performance has been widely disputed. Accuracy of multiple software complexity measures in forecasting software performance are intended to be examined in this research study, employing numerous performance variables such as execution time, memory utilization, and scalability. Cyclomatic Complexity, Lines of Code, Halstead Complexity measures, and maintainability index are the most used methods to measure the complexity of software system. In this research result indicates how that different complexity matrices are vary in giving different software performance. Also examine what are the limitations of this different complexity matrixes.

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To determine the complexity of software systems, software complexity measures are commonly utilized. However, their accuracy in forecasting software performance has been widely disputed. Accuracy of multiple software complexity measures in forecasting software performance are intended to be examined in this research study, employing numerous performance variables such as execution time, memory utilization, and scalability. Cyclomatic Complexity, Lines of Code, Halstead Complexity measures, and maintainability index are the most used methods to measure the complexity of software system. In this research result indicates how that different complexity matrices are vary in giving different software performance. Also examine what are the limitations of this different complexity matrixes.

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Available abstract

To determine the complexity of software systems, software complexity measures are commonly utilized. However, their accuracy in forecasting software performance has been widely disputed. Accuracy of multiple software complexity measures in forecasting software performance are intended to be examined in this research study, employing numerous performance variables such as execution time, memory utilization, and scalability. Cyclomatic Complexity, Lines of Code, Halstead Complexity measures, and maintainability index are the most used methods to measure the complexity of software system. In this research result indicates how that different complexity matrices are vary in giving different software performance. Also examine what are the limitations of this different complexity matrixes.

Key concepts: Cyclomatic complexity, Programming complexity, Computer science, Software metric, Maintainability, Software sizing, Software construction, Software

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