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dc.contributor.authorvan Koten, Chikakoen_NZ
dc.contributor.authorGray, Andrewen_NZ
dc.date.available2011-04-07T03:05:35Z
dc.date.copyright2005-03en_NZ
dc.identifier.citationvan Koten, C., & Gray, A. (2005). An application of Bayesian network for predicting object-oriented software maintainability (Information Science Discussion Papers Series No. 2005/02). University of Otago. Retrieved from http://hdl.handle.net/10523/919en
dc.identifier.urihttp://hdl.handle.net/10523/919
dc.descriptionPreprint submitted to Elsevier Scienceen_NZ
dc.description.abstractAs the number of object-oriented software systems increases, it becomes more important for organizations to maintain those systems effectively. However, currently only a small number of maintainability prediction models are available for object-oriented systems. This paper presents a Bayesian network maintainability prediction model for an object-oriented software system. The model is constructed using object-oriented metric data in Li and Henry’s datasets, which were collected from two different object-oriented systems. Prediction accuracy of the model is evaluated and compared with commonly used regression-based models. The results suggest that the Bayesian network model can predict maintainability more accurately than the regression-based models for one system, and almost as accurately as the best regression-based model for the other system.en_NZ
dc.format.mimetypeapplication/pdf
dc.publisherUniversity of Otagoen_NZ
dc.relation.ispartofseriesInformation Science Discussion Papers Seriesen_NZ
dc.subjectobject-oriented systemsen_NZ
dc.subjectmaintainabilityen_NZ
dc.subjectBayesian network, regression treeen_NZ
dc.subjectregressionen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleAn application of Bayesian network for predicting object-oriented software maintainabilityen_NZ
dc.typeDiscussion Paperen_NZ
dc.description.versionUnpublisheden_NZ
otago.bitstream.pages21en_NZ
otago.date.accession2005-12-02en_NZ
otago.schoolInformation Scienceen_NZ
otago.openaccessOpen
otago.place.publicationDunedin, New Zealanden_NZ
dc.identifier.eprints16en_NZ
otago.school.eprintsSoftware Metrics Research Laboratoryen_NZ
otago.school.eprintsInformation Scienceen_NZ
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