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Comparing Effort Prediction Models for Web Design and Authoring Using Boxplots
Gold Coast, Queensland, Australia January 29-February 02
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ACSC.2001.906632Australasian Computer Science Confere ...
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Emilia Mendes, The University of Auckland
Nile Mosley, Auckland University of technology
Software practitioners recognise the importance of realistic estimates of effort to the successful management of software projects, the Web being no exception. Having realistic estimates at an early stage in a project's life cycle allow project managers and developement organisations to manage resources effectively. Prediction is a necessary part of an effective process, be it authoring, design, testing, or Web development as a whole. The first part of this paper describes a case study evaluation (CSE) where we measured characteristics of Web applications and the effort involved in designing and authoring those applications. The second half presents two prediction models generated using statistical techniques, namely linear regression and stepwise multiple regression. The prediction power of the models employed is then compared using boxplots of the residuals. Results suggest that stepwise regression gives better predictions than linear regression.
Citation:
Emilia Mendes, Nile Mosley, "Comparing Effort Prediction Models for Web Design and Authoring Using Boxplots," acsc, pp.125, Australasian Computer Science Conference (ACSC '01), 2001
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