Towards Optimized K Means Clustering using Nature-inspired Algorithms for Software Bug Prediction
In today’s software development environment, the necessity for providing quality software products has undoubtedly remained the largest difficulty. As a result, early software bug prediction in the development phase is critical for lowering maintenance costs and improving overall software performance. Clustering is a well-known unsupervised method for data classification and finding related patterns hidden in datasets.
