In Object-Oriented Software Framework Improving Maintenance Exercises Through K-Means Clustering Approach

The k-means strategy is a generally utilized clustering procedure that tries to minimize the average squared distance between focuseson a similar group. Despite the fact that it offers no exactness ensures,its effortlessness, as well as speed, are extremely engaging. Open source products/projects focusing on the same or comparable applications are basic these days.Software maintenance is very overexerted and time-consuming process.It utilizes lots of imperative benefits during software development process.Consequently, to design object-based software framework, it is essential to recognize maintainability on the top priority of software development. To discover maintainable classes various machine learning techniques are applied. In this paper, K-Means clustering method is utilized at the design level to identify the maintainable classes, and the descriptive analysis has demonstrated in terms of performance metric as confusion matrix.