Predicting the delay of issues with due dates in software projects
暂无分享,去创建一个
Aditya K. Ghose | Morakot Choetkiertikul | Truyen Tran | Khanh Hoa Dam | K. Dam | T. Tran | A. Ghose | Morakot Choetkiertikul
[1] Andreas Zeller,et al. How Long Will It Take to Fix This Bug? , 2007, Fourth International Workshop on Mining Software Repositories (MSR'07:ICSE Workshops 2007).
[2] Bianca Zadrozny,et al. Transforming classifier scores into accurate multiclass probability estimates , 2002, KDD.
[3] Thomas Zimmermann,et al. Optimized assignment of developers for fixing bugs an initial evaluation for eclipse projects , 2009, 2009 3rd International Symposium on Empirical Software Engineering and Measurement.
[4] Harald C. Gall,et al. Predicting the fix time of bugs , 2010, RSSE '10.
[5] Anh Duc Duong,et al. Addressing cold-start problem in recommendation systems , 2008, ICUIMC '08.
[6] Honglak Lee,et al. Efficient L1 Regularized Logistic Regression , 2006, AAAI.
[7] Wil M. P. van der Aalst,et al. A recommendation system for predicting risks across multiple business process instances , 2015, Decis. Support Syst..
[8] Philip J. Guo,et al. Characterizing and predicting which bugs get fixed: an empirical study of Microsoft Windows , 2010, 2010 ACM/IEEE 32nd International Conference on Software Engineering.
[9] Xu Ruzhi,et al. CMM-based software risk control optimization , 2003, Proceedings Fifth IEEE Workshop on Mobile Computing Systems and Applications.
[10] David Lo,et al. Dual analysis for recommending developers to resolve bugs , 2015, J. Softw. Evol. Process..
[11] Akito Monden,et al. Revisiting common bug prediction findings using effort-aware models , 2010, 2010 IEEE International Conference on Software Maintenance.
[12] Thomas Zimmermann,et al. Duplicate bug reports considered harmful … really? , 2008, 2008 IEEE International Conference on Software Maintenance.
[13] Aditya K. Ghose,et al. Characterization and Prediction of Issue-Related Risks in Software Projects , 2015, 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories.
[14] Gediminas Adomavicius,et al. A Naive Bayes machine learning approach to risk prediction using censored, time‐to‐event data , 2014, Statistics in medicine.
[15] David Lo,et al. Automated prediction of bug report priority using multi-factor analysis , 2014, Empirical Software Engineering.
[16] Bo Yu,et al. Combining Classifiers in Software Quality Prediction: A Neural Network Approach , 2005, ISNN.
[17] Ying Zou,et al. Studying the fix-time for bugs in large open source projects , 2011, Promise '11.
[18] Iulian Neamtiu,et al. Bug-fix time prediction models: can we do better? , 2011, MSR '11.
[19] Limin Wang,et al. Combining decision tree and Naive Bayes for classification , 2006, Knowl. Based Syst..
[20] Ruzhi Xu,et al. CMM-based software risk control optimization , 2003, IRI.
[21] Aditya K. Ghose,et al. Predicting Delays in Software Projects Using Networked Classification (T) , 2015, 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE).
[22] Tao Xie,et al. An approach to detecting duplicate bug reports using natural language and execution information , 2008, 2008 ACM/IEEE 30th International Conference on Software Engineering.
[23] Mark Keil,et al. Software project risks and their effect on outcomes , 2004, CACM.
[24] Lucas D. Panjer. Predicting Eclipse Bug Lifetimes , 2007, Fourth International Workshop on Mining Software Repositories (MSR'07:ICSE Workshops 2007).
[25] Donald E. Neumann. An Enhanced Neural Network Technique for Software Risk Analysis , 2002, IEEE Trans. Software Eng..
[26] J. Friedman. Stochastic gradient boosting , 2002 .
[27] LiuMei,et al. Software project risk analysis using Bayesian networks with causality constraints , 2013, DSS 2013.
[28] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[29] Thomas Zimmermann,et al. Automatic Identification of Bug-Introducing Changes , 2006, 21st IEEE/ACM International Conference on Automated Software Engineering (ASE'06).
[30] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[31] Bart Baesens,et al. Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings , 2008, IEEE Transactions on Software Engineering.
[32] Nicholas Jalbert,et al. Automated duplicate detection for bug tracking systems , 2008, 2008 IEEE International Conference on Dependable Systems and Networks With FTCS and DCC (DSN).
[33] David Lo,et al. Automatic, high accuracy prediction of reopened bugs , 2014, Automated Software Engineering.
[34] Aftab Iqbal,et al. Understanding Contributor to Developer Turnover Patterns in OSS Projects: A Case Study of Apache Projects , 2014 .
[35] David A. Cieslak,et al. Evaluating Probability Estimates from Decision Trees , 2006 .
[36] B. Boehm. Software risk management: principles and practices , 1991, IEEE Software.
[37] Bart Goethals,et al. Predicting the severity of a reported bug , 2010, 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010).
[38] Andrea Esuli,et al. Evaluation Measures for Ordinal Regression , 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.
[39] Ferdian Thung,et al. Automatic Defect Categorization , 2012, 2012 19th Working Conference on Reverse Engineering.
[40] Gianluigi Viscusi,et al. Pattern detection for conceptual schema recovery in data‐intensive systems , 2014, J. Softw. Evol. Process..
[41] David Lo,et al. Automatic Fine-Grained Issue Report Reclassification , 2014, 2014 19th International Conference on Engineering of Complex Computer Systems.
[42] Westley Weimer,et al. Modeling bug report quality , 2007, ASE '07.
[43] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[44] W. W. Muir,et al. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity , 1980 .
[45] Gail C. Murphy,et al. Automatic bug triage using text categorization , 2004, SEKE.
[46] Padraig Cunningham,et al. Exploring the Relationship between Membership Turnover and Productivity in Online Communities , 2014, ICWSM.
[47] Victoria J. Hodge,et al. A Survey of Outlier Detection Methodologies , 2004, Artificial Intelligence Review.
[48] Ron Kohavi,et al. Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid , 1996, KDD.
[49] Tim Menzies,et al. Automated severity assessment of software defect reports , 2008, 2008 IEEE International Conference on Software Maintenance.
[50] David Lo,et al. ELBlocker: Predicting blocking bugs with ensemble imbalance learning , 2015, Inf. Softw. Technol..
[51] Ken-ichi Matsumoto,et al. Studying re-opened bugs in open source software , 2012, Empirical Software Engineering.
[52] Harvey P. Siy,et al. Understanding the Effects of Developer Activities on Inspection Interval , 1997, Proceedings of the (19th) International Conference on Software Engineering.
[53] Gail C. Murphy,et al. Reducing the effort of bug report triage: Recommenders for development-oriented decisions , 2011, TSEM.
[54] Gail C. Murphy,et al. Who should fix this bug? , 2006, ICSE.
[55] Earl T. Barr,et al. Uncertainty, risk, and information value in software requirements and architecture , 2014, ICSE.
[56] Sven Apel,et al. Types and modularity for implicit invocation with implicit announcement , 2010, TSEM.
[57] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[58] Yong Hu,et al. Software Project Risk Management Modeling with Neural Network and Support Vector Machine Approaches , 2007, Third International Conference on Natural Computation (ICNC 2007).
[59] Ahmed E. Hassan,et al. Should I contribute to this discussion? , 2010, 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010).
[60] Philip J. Guo,et al. Characterizing and predicting which bugs get reopened , 2012, 2012 34th International Conference on Software Engineering (ICSE).
[61] Saharon Rosset,et al. Leakage in data mining: formulation, detection, and avoidance , 2011, TKDD.
[62] Per Runeson,et al. Detection of Duplicate Defect Reports Using Natural Language Processing , 2007, 29th International Conference on Software Engineering (ICSE'07).
[63] David A. Belsley,et al. Regression Analysis and its Application: A Data-Oriented Approach.@@@Applied Linear Regression.@@@Regression Diagnostics: Identifying Influential Data and Sources of Collinearity , 1981 .
[64] M. Kholief,et al. Bug fix-time prediction model using naïve Bayes classifier , 2012, 2012 22nd International Conference on Computer Theory and Applications (ICCTA).
[65] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[66] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[67] Moe Thandar Wynn,et al. Profiling Event Logs to Configure Risk Indicators for Process Delays , 2013, CAiSE.
[68] 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).
[69] Bijan Elahi. Software Risk Management , 2018 .
[70] Thomas Zimmermann,et al. What Makes a Good Bug Report? , 2008, IEEE Transactions on Software Engineering.
[71] Meiyappan Nagappan,et al. Characterizing and predicting blocking bugs in open source projects , 2018, J. Syst. Softw..
[72] David W. Hosmer,et al. Applied Logistic Regression , 1991 .
[73] Uirá Kulesza,et al. An Empirical Study of Delays in the Integration of Addressed Issues , 2014, 2014 IEEE International Conference on Software Maintenance and Evolution.
[74] Sun-Jen Huang,et al. An empirical analysis of risk components and performance on software projects , 2007, J. Syst. Softw..
[75] Jingsha He,et al. A recommendation system for a web portal , 2014, 2014 IEEE International Conference on Progress in Informatics and Computing.
[76] Jean-Michel Poggi,et al. Variable selection using random forests , 2010, Pattern Recognit. Lett..
[77] Dan Roth,et al. Understanding Probabilistic Classifiers , 2001, ECML.
[78] 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).