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Article

Software Project Management Using Machine Learning Technique—A Review

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Institute of Informatics and Computing in Energy, Universiti Tenaga Nasional, Kajang 43000, Malaysia
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College of Computing and Informatics (CCI), Universiti Tenaga Nasional, Kajang 43000, Malaysia
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Department of Computer Technology, Information Technology Collage, Imam Ja’afar Al-Sadiq University, Baghdad 10064, Iraq
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Uniten R&D Sdn Bhd, Universiti Tenaga Nasional, Kajang 43000, Malaysia
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Author to whom correspondence should be addressed.
Academic Editor: Vito Conforti
Appl. Sci. 2021, 11(11), 5183; https://doi.org/10.3390/app11115183
Received: 12 April 2021 / Revised: 29 April 2021 / Accepted: 5 May 2021 / Published: 2 June 2021
(This article belongs to the Special Issue Software Engineering: Computer Science and System)
Project management planning and assessment are of great significance in project performance activities. Without a realistic and logical plan, it isn’t easy to handle project management efficiently. This paper presents a wide-ranging comprehensive review of papers on the application of Machine Learning in software project management. Besides, this paper presents an extensive literature analysis of (1) machine learning, (2) software project management, and (3) techniques from three main libraries, Web Science, Science Directs, and IEEE Explore. One-hundred and eleven papers are divided into four categories in these three repositories. The first category contains research and survey papers on software project management. The second category includes papers that are based on machine-learning methods and strategies utilized on projects; the third category encompasses studies on the phases and tests that are the parameters used in machine-learning management and the final classes of the results from the study, contribution of studies in the production, and the promotion of machine-learning project prediction. Our contribution also offers a more comprehensive perspective and a context that would be important for potential work in project risk management. In conclusion, we have shown that project risk assessment by machine learning is more successful in minimizing the loss of the project, thereby increasing the likelihood of the project success, providing an alternative way to efficiently reduce the project failure probabilities, and increasing the output ratio for growth, and it also facilitates analysis on software fault prediction based on accuracy. View Full-Text
Keywords: machine learning technique; software project estimation; software estimation; software project management; project risk assessment machine learning technique; software project estimation; software estimation; software project management; project risk assessment
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MDPI and ACS Style

Mahdi, M.N.; Mohamed Zabil, M.H.; Ahmad, A.R.; Ismail, R.; Yusoff, Y.; Cheng, L.K.; Azmi, M.S.B.M.; Natiq, H.; Happala Naidu, H. Software Project Management Using Machine Learning Technique—A Review. Appl. Sci. 2021, 11, 5183. https://doi.org/10.3390/app11115183

AMA Style

Mahdi MN, Mohamed Zabil MH, Ahmad AR, Ismail R, Yusoff Y, Cheng LK, Azmi MSBM, Natiq H, Happala Naidu H. Software Project Management Using Machine Learning Technique—A Review. Applied Sciences. 2021; 11(11):5183. https://doi.org/10.3390/app11115183

Chicago/Turabian Style

Mahdi, Mohammed N., Mohd H. Mohamed Zabil, Abdul R. Ahmad, Roslan Ismail, Yunus Yusoff, Lim K. Cheng, Muhammad S.B.M. Azmi, Hayder Natiq, and Hushalini Happala Naidu. 2021. "Software Project Management Using Machine Learning Technique—A Review" Applied Sciences 11, no. 11: 5183. https://doi.org/10.3390/app11115183

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