Software Quality Estimation Using Machine Learning: Case-Based Reasoning Technique
Software quality estimation is one of the most interesting research areas in the domain of software engineering for last few decades. Large numbers of techniques and models have already been worked out in the area of error estimation. The aim of software quality estimation is to identify error prone tasks as the cost can be minimized with advance knowledge about the errors and this early treatment of error will enhance the software quality. In this paper, the authors have explored a set of data in university setting. This paper advocates the use of Case-Based Reasoning (i.e., CBR) to make a software quality estimation system by the help of human experts.