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dc.contributor.authorBatar, Mustafa
dc.contributor.authorBirant, Kökten
dc.date.accessioned2022-10-20T10:28:04Z
dc.date.available2022-10-20T10:28:04Z
dc.date.issued2021en_US
dc.identifier.urihttps://dergipark.org.tr/tr/pub/alku/issue/64708/985839
dc.identifier.urihttps://hdl.handle.net/20.500.12868/1945
dc.description.abstractUp to now, several criteria (software parameters) have been determined in order to measure and evaluate software development projects: Productivity, engagement, attention to quality, code base knowledge and management, adherence to coding guidelines and techniques, learning and skills, personal responsibility and etc. However, there isn’t any universally accepted criteria or a methodology to measure and evaluate software development projects. In this context, for preparing the background of the study, several researches have been studied about “Software Development Projects”, “Software Development Process” and “Software Development Measurement and Evaluation”. Also, with this literature study, the common criteria set about measurement and evaluation of software development projects has been created, generated and presented. In addition, some information has been got and taken from 105 software experts (software analyzers, software developers and managers) with 55 different software companies so as to evaluate the use of the common criteria in real work life, and to identify criteria which are not seen in researches before, but used in real work life. Accordingly, a measurement and evaluation criteria set (software parameters) about the software development projects has been created based on the data mining algorithm – “Association Rule Mining Apriori Algorithm” – with its 12 inferences. This set has also consisted of 10 software parameters with 6 dual relationships. With the light of these data, the designed and developed software parameters have had high validation with more than 75 percent accuracy rate. As a natural result of this, the study will have had a positive effect on software engineering by shedding light on its working domain – software development.en_US
dc.language.isoturen_US
dc.relation.isversionofhttps://doi.org/10.46740/alku.985839en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectSoftware engineeringen_US
dc.subjectSoftware developmenten_US
dc.subjectSoftware development projectsen_US
dc.subjectSoftware parametersen_US
dc.subjectData miningen_US
dc.subjectApriori algorithmen_US
dc.titleData Mining based Inferences about Software Parametersen_US
dc.typearticleen_US
dc.contributor.departmentALKÜen_US
dc.identifier.volume3en_US
dc.identifier.issue3en_US
dc.identifier.startpage9en_US
dc.identifier.endpage24en_US
dc.relation.journalALKÜ Fen Bilimleri Dergisien_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararası - Başka Kurum Yazarıen_US


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