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Research Article | Open Access |

Software Project Estimation with Machine Learning

Author 1: Noor Azura Zakaria Author 2: Amelia Ritahani Ismail Author 3: Afrujaan Yakath Ali Author 4: Nur Hidayah Mohd Khalid Author 5: Nadzurah Zainal Abidin
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 12, No. 6 · Published 2021 · Cited by 21

DOI: https://doi.org/10.14569/IJACSA.2021.0120685

Abstract

This project involves research about software effort estimation using machine learning algorithms. Software cost and effort estimation are crucial parts of software project development. It determines the budget, time and resources needed to develop a software project. One of the well-established software project estimation models is Constructive Cost Model (COCOMO) which was developed in the 1980s. Even though such a model is being used, COCOMO has some weaknesses and software developers still facing the problem of lack of accuracy of the effort and cost estimation. Inaccuracy in the estimated effort will affect the schedule and cost of the whole project as well. The objective of this research is to use several algorithms of machine learning to estimate the effort of software project development. The best machine learning model is chosen to compare with the COCOMO.

Keywords

How to Cite this Article

Zakaria, N. A., Ismail, A. R., Ali, A. Y., Khalid, N. H. M., & Abidin, N. Z. (2021). Software Project Estimation with Machine Learning. International Journal of Advanced Computer Science and Applications, 12(6). https://doi.org/10.14569/IJACSA.2021.0120685

Zakaria, Noor Azura, et al.. "Software Project Estimation with Machine Learning." International Journal of Advanced Computer Science and Applications, vol. 12, no. 6, 2021, https://doi.org/10.14569/IJACSA.2021.0120685.

@article{Zakaria2021,
  title     = {Software Project Estimation with Machine Learning},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {6},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Noor Azura Zakaria and Amelia Ritahani Ismail and Afrujaan Yakath Ali and Nur Hidayah Mohd Khalid and Nadzurah Zainal Abidin},
  doi       = {10.14569/IJACSA.2021.0120685},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120685}
}

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