Surprise Bug Report Prediction Utilizing Optimized Integration with Imbalanced Learning Strategy
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Yang Qu | Shikai Guo | Chen Guo | Rong Chen | Hui Li | Guofeng Gao | Rong Chen | Yang Qu | Shikai Guo | Hui Li | Guofeng Gao | Chen Guo
[1] Wu Deng,et al. An Improved Ant Colony Optimization Algorithm Based on Hybrid Strategies for Scheduling Problem , 2019, IEEE Access.
[2] Premkumar T. Devanbu,et al. How, and why, process metrics are better , 2013, 2013 35th International Conference on Software Engineering (ICSE).
[3] Michele Lanza,et al. An extensive comparison of bug prediction approaches , 2010, 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010).
[4] Xinli Yang,et al. High-Impact Bug Report Identification with Imbalanced Learning Strategies , 2017, Journal of Computer Science and Technology.
[5] David Lo,et al. DRONE: Predicting Priority of Reported Bugs by Multi-factor Analysis , 2013, ICSM.
[6] Serge Demeyer,et al. Predicting Reassignments of Bug Reports - An Exploratory Investigation , 2013, 2013 17th European Conference on Software Maintenance and Reengineering.
[7] David Lo,et al. Information Retrieval Based Nearest Neighbor Classification for Fine-Grained Bug Severity Prediction , 2012, 2012 19th Working Conference on Reverse Engineering.
[8] Akito Monden,et al. The Effects of Over and Under Sampling on Fault-prone Module Detection , 2007, ESEM 2007.
[9] Kenneth Magel,et al. Efficient Bug Triaging Using Text Mining , 2013, J. Softw..
[10] Thomas Zimmermann,et al. Quality of bug reports in Eclipse , 2007, eclipse '07.
[11] Liang Feng,et al. Practical Duplicate Bug Reports Detection in a Large Web-Based Development Community , 2013, APWeb.
[12] Jian Ma,et al. Sentiment classification: The contribution of ensemble learning , 2014, Decis. Support Syst..
[13] Tao Xie,et al. Cooperative Software Testing and Analysis: Advances and Challenges , 2014, Journal of Computer Science and Technology.
[14] Gail C. Murphy,et al. Who should fix this bug? , 2006, ICSE.
[15] Neeraj Bhargava,et al. Decision Tree Analysis on J48 Algorithm for Data Mining , 2013 .
[16] Audris Mockus,et al. High-impact defects: a study of breakage and surprise defects , 2011, ESEC/FSE '11.
[17] Lior Rokach,et al. Ensemble-based classifiers , 2010, Artificial Intelligence Review.
[18] Nitesh V. Chawla,et al. SMOTE: Synthetic Minority Over-sampling Technique , 2002, J. Artif. Intell. Res..
[19] Ge Guo,et al. Quantized Sliding Mode Control of Unmanned Marine Vehicles: Various Thruster Faults Tolerated With a Unified Model , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.
[20] Rong Chen,et al. Identify Severity Bug Report with Distribution Imbalance by CR-SMOTE and ELM , 2019, Int. J. Softw. Eng. Knowl. Eng..
[21] Rong Chen,et al. Identification of High Priority Bug Reports via Integration Method , 2018 .
[22] Elliot Soloway,et al. Where the bugs are , 1985, CHI '85.
[23] Asha Gowda Karegowda,et al. Cascading k-means with Ensemble Learning: Enhanced Categorization of Diabetic Data , 2012, J. Intell. Syst..
[24] Song Wang,et al. Local-based active classification of test report to assist crowdsourced testing , 2016, 2016 31st IEEE/ACM International Conference on Automated Software Engineering (ASE).
[25] Xin Yao,et al. Using Class Imbalance Learning for Software Defect Prediction , 2013, IEEE Transactions on Reliability.
[26] David Lo,et al. Improved Duplicate Bug Report Identification , 2012, 2012 16th European Conference on Software Maintenance and Reengineering.
[27] Ashish Sureka,et al. Detecting Duplicate Bug Report Using Character N-Gram-Based Features , 2010, 2010 Asia Pacific Software Engineering Conference.
[28] Song Wang,et al. Towards Effectively Test Report Classification to Assist Crowdsourced Testing , 2016, ESEM.
[29] Sotiris B. Kotsiantis,et al. Combining Bagging, Boosting and Dagging for Classification Problems , 2007, KES.
[30] Zarinah Mohd Kasirun,et al. Why so complicated? Simple term filtering and weighting for location-based bug report assignment recommendation , 2013, 2013 10th Working Conference on Mining Software Repositories (MSR).
[31] Bart Goethals,et al. Predicting the severity of a reported bug , 2010, 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010).
[32] Cheng G. Weng,et al. A New Evaluation Measure for Imbalanced Datasets , 2008, AusDM.
[33] Xinli Yang,et al. Automated Identification of High Impact Bug Reports Leveraging Imbalanced Learning Strategies , 2016, 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC).
[34] Ming Wen,et al. An empirical study of bug report field reassignment , 2014, 2014 Software Evolution Week - IEEE Conference on Software Maintenance, Reengineering, and Reverse Engineering (CSMR-WCRE).
[35] Onaiza Maqbool,et al. Bug Prioritization to Facilitate Bug Report Triage , 2012, Journal of Computer Science and Technology.
[36] Hajimu Iida,et al. Understanding Key Features of High-Impact Bug Reports , 2017, 2017 8th International Workshop on Empirical Software Engineering in Practice (IWESEP).
[37] Seetha Hari,et al. Learning From Imbalanced Data , 2019, Advances in Computer and Electrical Engineering.
[38] Audris Mockus,et al. A large-scale empirical study of just-in-time quality assurance , 2013, IEEE Transactions on Software Engineering.
[39] Fang Wu,et al. Predicting Defect Priority Based on Neural Networks , 2010, ADMA.
[40] Petra Perner,et al. Data Mining - Concepts and Techniques , 2002, Künstliche Intell..
[41] Kangshun Li,et al. Identifying key classes in object-oriented software using generalized k-core decomposition , 2018, Future Gener. Comput. Syst..
[42] Eleni Stroulia,et al. A contextual approach towards more accurate duplicate bug report detection and ranking , 2013, Empirical Software Engineering.
[43] Wu Deng,et al. A novel collaborative optimization algorithm in solving complex optimization problems , 2016, Soft Computing.
[44] Bin Zhang,et al. Timely daily activity recognition from headmost sensor events. , 2019, ISA transactions.
[45] Gail E. Kaiser,et al. BUGMINER: Software Reliability Analysis Via Data Mining of Bug Reports , 2011, SEKE.
[46] Francisco Herrera,et al. An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics , 2013, Inf. Sci..
[47] Ken-ichi Matsumoto,et al. Classifying Bug Reports to Bugs and Other Requests Using Topic Modeling , 2013, 2013 20th Asia-Pacific Software Engineering Conference (APSEC).
[48] Andreas Zeller,et al. It's not a bug, it's a feature: How misclassification impacts bug prediction , 2013, 2013 35th International Conference on Software Engineering (ICSE).
[49] Siau-Cheng Khoo,et al. Towards more accurate retrieval of duplicate bug reports , 2011, 2011 26th IEEE/ACM International Conference on Automated Software Engineering (ASE 2011).
[50] Ken-ichi Matsumoto,et al. A Dataset of High Impact Bugs: Manually-Classified Issue Reports , 2015, 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories.
[51] Taghi M. Khoshgoftaar,et al. Balancing Misclassification Rates in Classification-Tree Models of Software Quality , 2004, Empirical Software Engineering.
[52] Tim Menzies,et al. Automated severity assessment of software defect reports , 2008, 2008 IEEE International Conference on Software Maintenance.
[53] Rong Chen,et al. Fusion of Multi-RSMOTE With Fuzzy Integral to Classify Bug Reports With an Imbalanced Distribution , 2019, IEEE Transactions on Fuzzy Systems.
[54] Sinno Jialin Pan,et al. Transfer defect learning , 2013, 2013 35th International Conference on Software Engineering (ICSE).
[55] Rong Chen,et al. Ensemble Data Reduction Techniques and Multi-RSMOTE via Fuzzy Integral for Bug Report Classification , 2018, IEEE Access.
[56] Xinli Yang,et al. Deep Learning for Just-in-Time Defect Prediction , 2015, 2015 IEEE International Conference on Software Quality, Reliability and Security.
[57] Rong Chen,et al. The Influence Ranking for Testers in Bug Tracking Systems , 2019, Int. J. Softw. Eng. Knowl. Eng..
[58] Hui Li,et al. Fault-tolerant Compensation Control Based on Sliding Mode Technique of Unmanned Marine Vehicles Subject to Unknown Persistent Ocean Disturbances , 2020, International Journal of Control, Automation and Systems.
[59] Bo Li,et al. Study on an improved adaptive PSO algorithm for solving multi-objective gate assignment , 2017, Applied Soft Computing.
[60] Serge Demeyer,et al. Comparing Mining Algorithms for Predicting the Severity of a Reported Bug , 2011, 2011 15th European Conference on Software Maintenance and Reengineering.
[61] Xi Yang,et al. Evolutionary extreme learning machine with sparse cost matrix for imbalanced learning. , 2019, ISA transactions.
[62] Carl K. Chang,et al. ElementRank: Ranking Java Software Classes and Packages using a Multilayer Complex Network-Based Approach , 2019 .
[63] David Lo,et al. Accurate developer recommendation for bug resolution , 2013, 2013 20th Working Conference on Reverse Engineering (WCRE).
[64] Julie Beth Lovins,et al. Development of a stemming algorithm , 1968, Mech. Transl. Comput. Linguistics.