Performance Evaluation of Some Selected Sorting Algorithms by the Use of Halstead Complexity Metrics
Journal Title: Transactions on Machine Learning and Artificial Intelligence - Year 2017, Vol 5, Issue 2
Abstract
Complexity is developed to demonstrate feasible metrics for process obtaining objectives and quantifiable measurement, which may have numerous valuable applications in schedule and budget planning, cost estimation and optimal personnel task assignments a particular software. Also it aids the developer and practitioners in evaluating the software complexity due to its simplicity, which serves both as an analyzer and as a predicator in quantitative software engineering. In this research work, the Halstead complexity metrics were applied to three sorting algorithms and C�]Sharp programming language was used to implement them. The results shows the variant performances of sorting algorithms and the best algorithm that can perform better in a defined system of application.
Authors and Affiliations
A. O Afolabi
Keywords
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- DOI 10.14738/tmlai.52.2793
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