Bug_Prioritization Framework for Bug Fixing using Meta-Heuristics Algorithm

B.Tech CSE Final Year Major Project

Completed By: Manan Chaudhary, Megha Jain, Kartikeya Consul

Jaypee Institute of Information and Technology

INTRODUCTION

The bug prioritization proposed framework assists in identifying the most severe bugs to programmers. It includes a feature weighting method that focuses on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to find relevant features for severity forecasting. This framework incorporates four stages to operate effectively and utilize performance indicators such as capability ranking, bug severities, and mean bug fixing time to rank programmers. The proposed model also employs classification algorithms such as KNN to predict various levels of bug intensity. Two experiments were conducted to evaluate the effectiveness of the proposed model, which involved predicting bug intensity levels using PSO-KNN and GA-KNN methods. Overall, the model is a promising framework that can enhance the bug triage process and improve the quality of bug fixing. The proposed model aims to refine a pre-trained framework iteratively using both latest data and sections of historical information. While the model has some issues related to memory, it is a feasible approach for improving the pre-trained framework.