Bug Prioritization Using Average One Dependence Estimator  

作　　者：Kashif Saleem Rashid Naseem Khalil Khan Siraj Muhammad Ikram Syed Jaehyuk Choi 

机构地区：[1]Department of IT and Computer Science,Institute of Applied Sciences and Technology,PakAustriaFochhshule,Haripur,Pakistan [2]Faculty of Computer Sciences and Information Technology,Superior University,Lahore,54660,Pakistan [3]Department of Computer Science,Shaheed Benazir Bhutto University,Sheringal,Upper Dir,Khyber Pakhtunkhwa,Pakitan [4]School of Computing,Gachon University,1342,Seongnam-daero,Sujeong-gu,Seongnam-si,13120,Korea

出　　处：《Intelligent Automation & Soft Computing》2023年第6期3517-3533,共17页智能自动化与软计算（英文）

基　　金：This work was supported in part by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.NRF-2020R1A2C1013308).

摘　　要：Automation software need to be continuously updated by addressing software bugs contained in their repositories.However,bugs have different levels of importance;hence,it is essential to prioritize bug reports based on their sever-ity and importance.Manually managing the deluge of incoming bug reports faces time and resource constraints from the development team and delays the resolu-tion of critical bugs.Therefore,bug report prioritization is vital.This study pro-poses a new model for bug prioritization based on average one dependence estimator;it prioritizes bug reports based on severity,which is determined by the number of attributes.The more the number of attributes,the more the severity.The proposed model is evaluated using precision,recall,F1-Score,accuracy,G-Measure,and Matthew’s correlation coefficient.Results of the proposed model are compared with those of the support vector machine(SVM)and Naive Bayes(NB)models.Eclipse and Mozilla datasetswere used as the sources of bug reports.The proposed model improved the bug repository management and out-performed the SVM and NB models.Additionally,the proposed model used a weaker attribute independence supposition than the former models,thereby improving prediction accuracy with minimal computational cost.

关 键 词：Bug report triaging PRIORITIZATION support vector machine Naive Bayes 

分 类 号：TP311.5[自动化与计算机技术—计算机软件与理论]