Hybrid Evolutionary Model for Just in Time Software Bug Prediction Based on Machine Learning Algorithm

Abstract

Software bug prediction is a significant feature in software development phase and in maintenance. Various machine learning techniques have been proposed and implemented to improve quality of software defect prediction.Defective software modules have an enormous effect in software's quality that foremost for overruns of cost, whereas delayed timelines lead to much higher maintenance costs. In this paper we have introduced a novel hybrid evolutionary approach forbug prediction in software. The results demonstrate the efficiency of our method for Just-In-Time software bug predictions and can further be used as a baseline for software bug predicting.