Publication: Design and Development of Machine Learning Technique for Software Project Risk Assessment - A Review
Date
2020
Authors
Mahdi M.N.
M.h M.Z.
Yusof A.
Cheng L.K.
Mohd Azmi M.S.
Ahmad A.R.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
Accurate assessment of software project risk is amongst the key activities in a software project. It directly impacts the time and cost of software projects. This paper presents a literature review of designing developing machine learning techniques for software project risk assessment. The results of the review have concluded prominent trends of machine learning approaches, size metrics, and study findings in the growth and advancement of machine learning in project management. Besides that, this research provides a deeper insight and an important framework for future work in the software project risk assessment. Furthermore, we demonstrated that the assessment of project risk using machine-learning is more efficient in reducing a project's fault. It also increases the probability for the software project's prediction and response, provides a further way to reduce the probability chances of failure effectively and to increase the software development performance ratio. � 2020 IEEE.
Description
Machine learning; Project management; Software design; Design and Development; Development performance; Literature reviews; Machine learning approaches; Machine learning techniques; Size metrics; Software project; Software project risks; Risk assessment