Design and Development of Machine Learning Technique for Software Project Risk Assessment - A Review

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.