Software reliability models based on machine learning techniques: A review

In order to create outstanding quality, reliable software, the software business has many problems. The reliability of software is important for the reliability of the system. The quality of the software is impressive. It compares with the reliability of hardware by reflecting the perfection of architecture and the reliability of hardware. This paper examines emerging literature focused on machine learning approaches of software reliability models. We can divide the reliability analysis of software into three components: modelling, measuring and improvement. Following the analysis of full applicable articles concerning defects that occur during the elimination of fault, we have proposed a method focusing on the most relevant software reliability parameters using machine learning methods.