research-article

The adjusted analogy-based software effort estimation based on similarity distances

Authors:

Nan-Hsing Chiu,

Sun-Jen HuangAuthors Info & Claims

Journal of Systems and Software, Volume 80, Issue 4

Pages 628 - 640

https://doi.org/10.1016/j.jss.2006.06.006

Published: 01 April 2007 Publication History

Abstract

Analogy-based estimation is a widely adopted problem solving method that has been evaluated and confirmed in software effort or cost estimation domains. The similarity measures between pairs of projects play a critical role in the analogy-based software effort estimation models. Such a model calculates a distance between the software project being estimated and each of the historical software projects, and then retrieves the most similar project for generating an effort estimate. Although there exist numerous analogy-based software effort estimation models in literature, little theoretical or experimental works have been reported on the method of deriving an effort estimate from the adjustment of the reused effort based on the similarity distance. The present paper investigates the effect on the improvement of estimation accuracy in analogy-based estimations when the genetic algorithm method is adopted to adjust reused effort based on the similarity distances between pairs of projects. The empirical results show that applying a suitable linear model to adjust the analogy-based estimations is a feasible approach to improving the accuracy of software effort estimates. It also demonstrates that the proposed model is comparable with those obtained when using other effort estimation methods.

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Cited By

Kumar KSrinivas K(2023)An accurate analogy based software effort estimation using hybrid optimization and machine learning techniquesMultimedia Tools and Applications10.1007/s11042-023-14522-x82:20(30463-30490)Online publication date: 23-Feb-2023
https://dl.acm.org/doi/10.1007/s11042-023-14522-x
Rijwani PJain S(2022)Software Effort Estimation Development From Neural Networks to Deep Learning ApproachesJournal of Cases on Information Technology10.4018/JCIT.29671524:4(1-16)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.4018/JCIT.296715
Agrawal AMenzies TMinku LWagner MYu Z(2020)Better software analytics via “DUO”: Data mining algorithms using/used-by optimizersEmpirical Software Engineering10.1007/s10664-020-09808-925:3(2099-2136)Online publication date: 22-Apr-2020
https://dl.acm.org/doi/10.1007/s10664-020-09808-9
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Index Terms

The adjusted analogy-based software effort estimation based on similarity distances
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. Project and people management
      2. Software management
2. Software and its engineering
  1. Software creation and management
    1. Designing software
      1. Software implementation planning
        Software design techniques
    2. Software development process management

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Elsevier Science Inc.

United States

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Published: 01 April 2007

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Cited By

Kumar KSrinivas K(2023)An accurate analogy based software effort estimation using hybrid optimization and machine learning techniquesMultimedia Tools and Applications10.1007/s11042-023-14522-x82:20(30463-30490)Online publication date: 23-Feb-2023
https://dl.acm.org/doi/10.1007/s11042-023-14522-x
Rijwani PJain S(2022)Software Effort Estimation Development From Neural Networks to Deep Learning ApproachesJournal of Cases on Information Technology10.4018/JCIT.29671524:4(1-16)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.4018/JCIT.296715
Agrawal AMenzies TMinku LWagner MYu Z(2020)Better software analytics via “DUO”: Data mining algorithms using/used-by optimizersEmpirical Software Engineering10.1007/s10664-020-09808-925:3(2099-2136)Online publication date: 22-Apr-2020
https://dl.acm.org/doi/10.1007/s10664-020-09808-9
Khazaiepoor MBardsiri AKeynia F(2019)A Dataset-Independent Model for Estimating Software Development Effort Using Soft Computing TechniquesApplied Computer Systems10.2478/acss-2019-001124:2(82-93)Online publication date: 1-Dec-2019
https://dl.acm.org/doi/10.2478/acss-2019-0011
Jie G(2018)Function Point Method Based on Hierarchical Convolutional Neural NetworkProceedings of the 2018 10th International Conference on Information Management and Engineering10.1145/3285957.3285979(1-4)Online publication date: 22-Sep-2018
https://dl.acm.org/doi/10.1145/3285957.3285979
(2018)Duplex output software effort estimation model with self-guided interpretationInformation and Software Technology10.1016/j.infsof.2017.09.01094:C(1-13)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1016/j.infsof.2017.09.010
Fernández-Diego MGonzález-Ladrón-De-Guevara F(2018)Application of mutual information-based sequential feature selection to ISBSG mixed dataSoftware Quality Journal10.1007/s11219-017-9391-526:4(1299-1325)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s11219-017-9391-5
Wu DLi JBao C(2018)Case-based reasoning with optimized weight derived by particle swarm optimization for software effort estimationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-017-2985-922:16(5299-5310)Online publication date: 1-Aug-2018
https://dl.acm.org/doi/10.1007/s00500-017-2985-9
Idri AAbnane IAbran A(2018)Support vector regression‐based imputation in analogy‐based software development effort estimationJournal of Software: Evolution and Process10.1002/smr.211430:12Online publication date: 12-Dec-2018
https://dl.acm.org/doi/10.1002/smr.2114
Gautam SSingh V(2018)The state‐of‐the‐art in software development effort estimationJournal of Software: Evolution and Process10.1002/smr.198330:12Online publication date: 12-Dec-2018
https://dl.acm.org/doi/10.1002/smr.1983
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