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An empirical study of the Cobb-Douglas production function properties of software development effort

Authors:

Parag C. Pendharkar,

James A. Rodger,

Girish H. SubramanianAuthors Info & Claims

Information and Software Technology, Volume 50, Issue 12

Pages 1181 - 1188

https://doi.org/10.1016/j.infsof.2007.10.019

Published: 01 November 2008 Publication History

Abstract

In this paper we study whether software development effort exhibits Cobb-Douglas functional form with respect to team size and software size. We empirically test this relationship using real-world software engineering data set containing over 500 software projects. The results of our experiments indicate that the hypothesized Cobb-Douglas function form for software development effort with respect to team size and software size is true. We also find increasing returns to scale relationship between software size and team size with software development effort.

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Cited By

Pendharkar PRodger J(2021)Quantitative software project management with mixed dataJournal of Software: Evolution and Process10.1002/smr.234833:6Online publication date: 1-Jun-2021
https://dl.acm.org/doi/10.1002/smr.2348
De Andrés JLandajo MLorca P(2018)Using Nonlinear Quantile Regression for the Estimation of Software CostHybrid Artificial Intelligent Systems10.1007/978-3-319-92639-1_35(422-432)Online publication date: 20-Jun-2018
https://dl.acm.org/doi/10.1007/978-3-319-92639-1_35
Pendharkar P(2015)Ensemble based point and confidence interval forecasting in software engineeringExpert Systems with Applications: An International Journal10.1016/j.eswa.2015.08.00242:24(9441-9448)Online publication date: 30-Dec-2015
https://dl.acm.org/doi/10.1016/j.eswa.2015.08.002
Show More Cited By

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An empirical study of the Cobb-Douglas production function properties of software development effort

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Published In

cover image Information and Software Technology

Information and Software Technology Volume 50, Issue 12

November, 2008

125 pages

ISSN:0950-5849

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2007.

Publisher

Butterworth-Heinemann

United States

Publication History

Published: 01 November 2008

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Cited By

Pendharkar PRodger J(2021)Quantitative software project management with mixed dataJournal of Software: Evolution and Process10.1002/smr.234833:6Online publication date: 1-Jun-2021
https://dl.acm.org/doi/10.1002/smr.2348
De Andrés JLandajo MLorca P(2018)Using Nonlinear Quantile Regression for the Estimation of Software CostHybrid Artificial Intelligent Systems10.1007/978-3-319-92639-1_35(422-432)Online publication date: 20-Jun-2018
https://dl.acm.org/doi/10.1007/978-3-319-92639-1_35
Pendharkar P(2015)Ensemble based point and confidence interval forecasting in software engineeringExpert Systems with Applications: An International Journal10.1016/j.eswa.2015.08.00242:24(9441-9448)Online publication date: 30-Dec-2015
https://dl.acm.org/doi/10.1016/j.eswa.2015.08.002
Pai DSubramanian GPendharkar P(2015)Benchmarking software development productivity of CMMI level 5 projectsInformation Technology and Management10.1007/s10799-015-0234-416:3(235-251)Online publication date: 1-Sep-2015
https://dl.acm.org/doi/10.1007/s10799-015-0234-4
Pendharkar PRodger J(2012)A distributed problem-solving framework for probabilistic software effort estimationExpert Systems: The Journal of Knowledge Engineering10.1111/j.1468-0394.2011.00607.x29:5(492-505)Online publication date: 1-Nov-2012
https://dl.acm.org/doi/10.1111/j.1468-0394.2011.00607.x
Yiftachel PHadar IPeled DFarchi EGoldwasser D(2011)The study of resource allocation among software development phasesAdvances in Software Engineering10.1155/2011/5792922011(6-6)Online publication date: 1-Jan-2011
https://dl.acm.org/doi/10.1155/2011/579292
Fernández-Diego MMartínez-Gómez MTorralba-Martínez JMenzies TKoru G(2010)Sensitivity of results to different data quality meta-data criteria in the sample selection of projects from the ISBSG datasetProceedings of the 6th International Conference on Predictive Models in Software Engineering10.1145/1868328.1868348(1-9)Online publication date: 12-Sep-2010
https://dl.acm.org/doi/10.1145/1868328.1868348

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