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Building A Software Cost Estimation Model Based On Categorical Data

Published: 04 April 2001 Publication History
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  • Abstract

    This paper explores the possibility of generating a multi-organisational software cost estimation model by analysing the software cost data collected by the International Software Benchmarking Standards Group. This database contains data about recently developed projects characterised mostly by attributes of categorical nature such as the project business area, organisation type, application domain and usage of certain tools or methods. The generation of the model is based on a statistical technique which has been proposed as alternative to the standard regression approach, namely the categorical regression or regression with optimal scaling. This technique starts with the quantification of the qualitative attributes (expressed either on nominal or ordinal scale), that appear frequently within such data, and proceeds by using the obtained scores as independent variables of a regression model. The generated model is validated by measuring certain indicators of accuracy.

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    • (2020)Identifying Software Cost Attributes of Software Project Management in Global Software DevelopmentProceedings of the 13th International Conference on Intelligent Systems: Theories and Applications10.1145/3419604.3419780(1-5)Online publication date: 23-Sep-2020
    • (2016)Multi-objective software effort estimationProceedings of the 38th International Conference on Software Engineering10.1145/2884781.2884830(619-630)Online publication date: 14-May-2016
    • (2016)Software cost estimation based on modified K-Modes clustering AlgorithmNatural Computing: an international journal10.1007/s11047-015-9492-715:3(415-422)Online publication date: 1-Sep-2016
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    cover image Guide Proceedings
    METRICS '01: Proceedings of the 7th International Symposium on Software Metrics
    April 2001
    ISBN:0769510434

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    IEEE Computer Society

    United States

    Publication History

    Published: 04 April 2001

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    • (2020)Identifying Software Cost Attributes of Software Project Management in Global Software DevelopmentProceedings of the 13th International Conference on Intelligent Systems: Theories and Applications10.1145/3419604.3419780(1-5)Online publication date: 23-Sep-2020
    • (2016)Multi-objective software effort estimationProceedings of the 38th International Conference on Software Engineering10.1145/2884781.2884830(619-630)Online publication date: 14-May-2016
    • (2016)Software cost estimation based on modified K-Modes clustering AlgorithmNatural Computing: an international journal10.1007/s11047-015-9492-715:3(415-422)Online publication date: 1-Sep-2016
    • (2014)How to build a good practice software project portfolio?Companion Proceedings of the 36th International Conference on Software Engineering10.1145/2591062.2591187(64-73)Online publication date: 31-May-2014
    • (2013)A novel fuzzy based approach for effort estimation in software developmentACM SIGSOFT Software Engineering Notes10.1145/2507288.250731338:5(1-6)Online publication date: 26-Aug-2013
    • (2010)Adaptive ridge regression system for software cost estimating on multi-collinear datasetsJournal of Systems and Software10.1016/j.jss.2010.07.03283:11(2332-2343)Online publication date: 1-Nov-2010
    • (2009)The relationship between software development team size and software development costCommunications of the ACM10.1145/1435417.143544952:1(141-144)Online publication date: 1-Jan-2009
    • (2009)A study of the non-linear adjustment for analogy based software cost estimationEmpirical Software Engineering10.1007/s10664-008-9104-614:6(603-643)Online publication date: 1-Dec-2009
    • (2008)Analogy Based Cost Estimation Configuration with RulesProceedings of the 2008 conference on Knowledge-Based Software Engineering: Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering10.5555/1566274.1566322(317-326)Online publication date: 29-Jun-2008
    • (2008)Functional size measurement revisitedACM Transactions on Software Engineering and Methodology10.1145/1363102.136310617:3(1-36)Online publication date: 27-Jun-2008
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