Numerical study of depth recursion in complexity measurement using Halstead measure

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dc.contributor.authorOkeyinka, Aderemi E.
dc.contributor.authorBamigbola, Olabode Matthias
dc.date.accessioned2019-05-03T10:33:35Z
dc.date.available2019-05-03T10:33:35Z
dc.date.issued2012
dc.descriptionInternational Journal of Applied Science and Technology 2(6), 106 - 111en_US
dc.description.abstractComplexity of algorithms has been studied analytically using the concept of Big O notation. One of the flaws of the study is that the complexities obtained for algorithms are in most cases the same; whereas in reality such algorithms might vary in terms of efficiency. The reason for the disparity is, of course, due to the definition of the Big O itself which mathematically is sound anyway. However, for pragmatic purposes, there is need for estimating actual complexities of each algorithm to be sure of which one is the best given more than one algorithms solving the same problem. In this study, recursion is considered and the complexities of recursive algorithms are estimated numerically using Halstead measure. Our findings show that recursive algorithms are more complex and hence less efficient than non-recursive algorithms.en_US
dc.identifier.citationOkeyinka and Bamigbola (2012b)en_US
dc.identifier.urihttp://hdl.handle.net/123456789/1822
dc.language.isoenen_US
dc.subjectNumerical studyen_US
dc.subjectComplexityen_US
dc.subjectRecursionen_US
dc.subjectAlgorithmsen_US
dc.subjectBig Oen_US
dc.titleNumerical study of depth recursion in complexity measurement using Halstead measureen_US
dc.typeArticleen_US

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