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dc.contributor.authorMukunga, Catherine W.
dc.contributor.authorNdia, John G.
dc.contributor.authorWambugu, Geoffrey M.
dc.date.accessioned2023-09-26T14:52:21Z
dc.date.available2023-09-26T14:52:21Z
dc.date.issued2023-05
dc.identifier.citationInternational Journal of Software Engineering & Applications (IJSEA), Vol.14, No.3, May 2023en_US
dc.identifier.urihttps://aircconline.com/abstract/ijsea/v14n3/14323ijsea02.html
dc.identifier.urihttp://hdl.handle.net/123456789/6403
dc.description.abstractSoftware project management includes a substantial area for estimating software maintenance effort. Estimation of software maintenance effort improves the overall performance and efficiency of software. The Constructive Cost Model (COCOMO) and other effort estimation models are mentioned in literature but are inappropriate for Python programming language. This research aimed to modify the Constructive Cost Model (COCOMO II) by considering a range of Python maintenance effort influencing factors to get estimations and incorporated size and complexity metrics to estimate maintenance effort. A within-subjects experimental design was adopted and an experiment questionnaire was administered to forty subjects aiming to rate the maintainability of twenty Python programs. Data collected from the experiment questionnaire was analyzed using descriptive statistics. Metric values were collected using a developed metric tool. The subject ratings on software maintainability were correlated with the developed model’s maintenance effort, a strong correlation of 0.610 was reported meaning that the model is valid.en_US
dc.language.isoenen_US
dc.subjectSoftware Maintenance, Software Maintenance effort, Software Maintenance estimation model, Python Software, Complexity metrics and size metricsen_US
dc.titleA Metrics-Based Model for Estimating the Maintenance Effort of Python Softwareen_US
dc.typeArticleen_US


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