Empirical Evaluation of Mimic Software Project Data Sets for Software Effort Estimation

Author:

GAN Maohua1,YÜCEL Zeynep1,MONDEN Akito1,SASAKI Kentaro1

Affiliation:

1. Okayama University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Reference18 articles.

1. [1] T. Menzies, R. Krishna, and D. Pryor, “The seacraft repository of empirical software engineering data,” https://zenodo.org/communities/seacraft, 2017.

2. [2] J. Desharnais, “Analyse statistique de la productivitie des projects informatique a partie de la technique des point des function,” Masters Thesis University of Montreal, 1989.

3. [3] C.F. Kemerer, “An empirical validation of software cost estimation models,” Communications of the ACM, vol.30, no.5, pp.416-429, May 1987. 10.1145/22899.22906

4. [4] A.J. Albrecht and J.E. Gaffney, “Software function, source lines of code, and development effort prediction: a software science validation,” IEEE Trans. Softw. Eng., vol.SE-9, no.6, pp.639-648, 1983. 10.1109/tse.1983.235271

5. [5] B.W. Boehm, Software Engineering Economics, Prentice Hall PTR, Upper Saddle River, NJ, USA, 1981.

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1. Research Trends in Software Development Effort Estimation;2023 10th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI);2023-09-20

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