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Swarm Intelligence-Empowered Bug Prediction Strategy for Decision Support in Software Defect Prediction
Abstract
Swarm intelligence is inherent in many living things and is inspiring new ways of thinking among computer scientists. Scientists from all walks of life including software corporates are interested in it because of its ties to collective intelligence behaviour. Bugs are an expensive and quality killer in software development. The development of DP models was driven by the critical need to predict defects early on. Classifying modules as either defect-prone or non-defect-prone relies heavily on machine learning algorithms. Improving software quality relies on defect prediction. SI improves the accuracy and efficacy of bug predictions by modelling their actions after the social group behaviour of insect colonies. The objective of this chapter is to outline swarm intelligence-based bug prediction in order to assist software engineers and QA teams with increased accuracy.
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