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Feature Selection Using Artificial Immune Network: An Approach for Software Defect Prediction
2021
Intelligent Automation and Soft Computing
Software Defect Prediction (SDP) is a dynamic research field in the software industry. A quality software product results in customer satisfaction. However, the higher the number of user requirements, the more complex will be the software, with a correspondingly higher probability of failure. SDP is a challenging task requiring smart algorithms that can estimate the quality of a software component before it is handed over to the end-user. In this paper, we propose a hybrid approach to address
doi:10.32604/iasc.2021.018405
fatcat:pbbk4bcp7vcxjhpvj3eg6q27ee