Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/55495
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMatinee Kiewkanyaen_US
dc.contributor.authorSuttipong Suraken_US
dc.date.accessioned2018-09-05T02:57:13Z-
dc.date.available2018-09-05T02:57:13Z-
dc.date.issued2016-11-18en_US
dc.identifier.other2-s2.0-85006857342en_US
dc.identifier.other10.1109/JCSSE.2016.7748880en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85006857342&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/55495-
dc.description.abstract© 2016 IEEE. Software size is one of the most important internal attributes of software product. The information obtained from estimating software size will be useful for planning about effort, cost and activities schedule of later phases. This paper proposes an approach for constructing C++ software size estimation model using a statistical technique called Multiple linear regression analysis. The proposed model is constructed from structural complexity metrics that can be measured from class diagram. The paper also presents an automated tool for measuring these metrics, and in effect, estimating the C++ software size.en_US
dc.subjectComputer Scienceen_US
dc.titleConstructing C++ software size estimation model from class diagramen_US
dc.typeConference Proceedingen_US
article.title.sourcetitle2016 13th International Joint Conference on Computer Science and Software Engineering, JCSSE 2016en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.