A systematic review of machine learning techniques for software fault prediction
暂无分享,去创建一个
[1] Anas N. Al-Rabadi,et al. A comparison of modified reconstructability analysis and Ashenhurst‐Curtis decomposition of Boolean functions , 2004 .
[2] Maurice H. Halstead,et al. Elements of software science (Operating and programming systems series) , 1977 .
[3] Maurice H. Halstead,et al. Elements of software science , 1977 .
[4] Chris F. Kemerer,et al. A Metrics Suite for Object Oriented Design , 2015, IEEE Trans. Software Eng..
[5] A. J. Paul,et al. Modelling the investment casting process: a novel approach for view factor calculations and defect prediction , 1995 .
[6] Susan A. Sherer,et al. Software fault prediction , 1995, J. Syst. Softw..
[7] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[8] Stephen G. MacDonell,et al. A comparison of techniques for developing predictive models of software metrics , 1997, Inf. Softw. Technol..
[9] Edward B. Allen,et al. GP-based software quality prediction , 1998 .
[10] Ming Zhao,et al. A comparison between software design and code metrics for the prediction of software fault content , 1998, Inf. Softw. Technol..
[11] Ekkehard Baisch,et al. Comparison of conventional approaches and soft-computing approaches for software quality prediction , 1999 .
[12] Mei-Hwa Chen,et al. An empirical study on object-oriented metrics , 1999, Proceedings Sixth International Software Metrics Symposium (Cat. No.PR00403).
[13] Shinji Kusumoto,et al. Prediction of fault-proneness at early phase in object-oriented development , 1999, Proceedings 2nd IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC'99) (Cat. No.99-61702).
[14] Taghi M. Khoshgoftaar,et al. An application of fuzzy clustering to software quality prediction , 2000, Proceedings 3rd IEEE Symposium on Application-Specific Systems and Software Engineering Technology.
[15] Ian Witten,et al. Data Mining , 2000 .
[16] Mark A. Hall,et al. Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning , 1999, ICML.
[17] Lionel C. Briand,et al. Exploring the relationships between design measures and software quality in object-oriented systems , 2000, J. Syst. Softw..
[18] Giovanni Denaro,et al. An empirical evaluation of fault-proneness models , 2002, ICSE '02.
[19] W. Pedrycz,et al. Software quality prediction using median-adjusted class labels , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).
[20] Taghi M. Khoshgoftaar,et al. Tree-based software quality estimation models for fault prediction , 2002, Proceedings Eighth IEEE Symposium on Software Metrics.
[21] Bojan Cukic,et al. Predicting fault prone modules by the Dempster-Shafer belief networks , 2003, 18th IEEE International Conference on Automated Software Engineering, 2003. Proceedings..
[22] A. ADoefaa,et al. ? ? ? ? f ? ? ? ? ? , 2003 .
[23] Tim Menzies,et al. How good is your blind spot sampling policy , 2004, Eighth IEEE International Symposium on High Assurance Systems Engineering, 2004. Proceedings..
[24] Tong-Seng Quah,et al. Prediction of software development faults in PL/SQL files using neural network models , 2004, Inf. Softw. Technol..
[25] Taghi M. Khoshgoftaar,et al. Fault Prediction Modeling for Software Quality Estimation: Comparing Commonly Used Techniques , 2003, Empirical Software Engineering.
[26] Bojan Cukic,et al. Robust prediction of fault-proneness by random forests , 2004, 15th International Symposium on Software Reliability Engineering.
[27] K. Kaminsky,et al. Building a genetically engineerable evolvable program (GEEP) using breadth-based explicit knowledge for predicting software defects , 2004, IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04..
[28] Bo Yu,et al. Extract rules from software quality prediction model based on neural network , 2004, 16th IEEE International Conference on Tools with Artificial Intelligence.
[29] Gerardo Canfora,et al. Impact analysis by mining software and change request repositories , 2005, 11th IEEE International Software Metrics Symposium (METRICS'05).
[30] Tibor Gyimóthy,et al. Empirical validation of object-oriented metrics on open source software for fault prediction , 2005, IEEE Transactions on Software Engineering.
[31] Michael R. Lyu,et al. A novel method for early software quality prediction based on support vector machine , 2005, 16th IEEE International Symposium on Software Reliability Engineering (ISSRE'05).
[32] Jana Polgar,et al. Object-Oriented Software Metrics , 2005, Encyclopedia of Information Science and Technology.
[33] Venkata U. B. Challagulla,et al. Empirical assessment of machine learning based software defect prediction techniques , 2005, 10th IEEE International Workshop on Object-Oriented Real-Time Dependable Systems.
[34] Hongfang Liu,et al. Building effective defect-prediction models in practice , 2005, IEEE Software.
[35] Taghi M. Khoshgoftaar,et al. An empirical study of predicting software faults with case-based reasoning , 2006, Software Quality Journal.
[36] Peter Kokol,et al. Estimating Software Quality with Advanced Data Mining Techniques , 2006, 2006 International Conference on Software Engineering Advances (ICSEA'06).
[37] Abraham Bernstein,et al. Predicting defect densities in source code files with decision tree learners , 2006, MSR '06.
[38] Venkata U. B. Challagulla,et al. A Unified Framework for Defect Data Analysis Using the MBR Technique , 2006, 2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06).
[39] Yuming Zhou,et al. Empirical Analysis of Object-Oriented Design Metrics for Predicting High and Low Severity Faults , 2006, IEEE Transactions on Software Engineering.
[40] Martin Höst,et al. Sensitivity of Website Reliability to Usage Profile Changes , 2007, The 18th IEEE International Symposium on Software Reliability (ISSRE '07).
[41] Bojan Cukic,et al. A Statistical Framework for the Prediction of Fault-Proneness , 2007 .
[42] Atchara Mahaweerawat,et al. Adaptive Self-Organizing Map Clustering for Software Fault Prediction , 2007 .
[43] Yue Jiang,et al. Fault Prediction using Early Lifecycle Data , 2007, The 18th IEEE International Symposium on Software Reliability (ISSRE '07).
[44] Silvio Romero de Lemos Meira,et al. A Constructive RBF Neural Network for Estimating the Probability of Defects in Software Modules , 2007, 2007 International Joint Conference on Neural Networks.
[45] Raed Shatnawi,et al. An empirical study of the bad smells and class error probability in the post-release object-oriented system evolution , 2007, J. Syst. Softw..
[46] Ayse Basar Bener,et al. Software Defect Prediction: Heuristics for Weighted Naïve Bayes , 2007, ICSOFT.
[47] Lars Lundberg,et al. Statistical models vs. expert estimation for fault prediction in modified code - an industrial case study , 2007, J. Syst. Softw..
[48] A. Zeller,et al. Predicting Defects for Eclipse , 2007, Third International Workshop on Predictor Models in Software Engineering (PROMISE'07: ICSE Workshops 2007).
[49] Banu Diri,et al. An Artificial Immune System Approach for Fault Prediction in Object-Oriented Software , 2007, 2nd International Conference on Dependability of Computer Systems (DepCoS-RELCOMEX '07).
[50] Hong-Zhong Huang,et al. Early Software Quality Prediction Based on a Fuzzy Neural Network Model , 2007, Third International Conference on Natural Computation (ICNC 2007).
[51] A. Bener,et al. A Multivariate Analysis of Static Code Attributes for Defect Prediction , 2007, Seventh International Conference on Quality Software (QSIC 2007).
[52] Joanne Bechta Dugan,et al. Empirical Analysis of Software Fault Content and Fault Proneness Using Bayesian Methods , 2007, IEEE Transactions on Software Engineering.
[53] Tim Menzies,et al. Data Mining Static Code Attributes to Learn Defect Predictors , 2007, IEEE Transactions on Software Engineering.
[54] Xiuzhen Zhang,et al. Comments on "Data Mining Static Code Attributes to Learn Defect Predictors" , 2007, IEEE Trans. Software Eng..
[55] Lionel C. Briand,et al. Data Mining Techniques for Building Fault-proneness Models in Telecom Java Software , 2007, The 18th IEEE International Symposium on Software Reliability (ISSRE '07).
[56] Taghi M. Khoshgoftaar,et al. Software quality estimation with limited fault data: a semi-supervised learning perspective , 2007, Software Quality Journal.
[57] S. Kanmani,et al. Object-oriented software fault prediction using neural networks , 2007, Inf. Softw. Technol..
[58] Zhan Li,et al. A practical method for the software fault-prediction , 2007, 2007 IEEE International Conference on Information Reuse and Integration.
[59] Bart Baesens,et al. Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings , 2008, IEEE Transactions on Software Engineering.
[60] Ayse Basar Bener,et al. Software Defect Prediction Using Call Graph Based Ranking (CGBR) Framework , 2008, 2008 34th Euromicro Conference Software Engineering and Advanced Applications.
[61] M.J. Khan,et al. Software quality prediction techniques: A comparative analysis , 2008, 2008 4th International Conference on Emerging Technologies.
[62] Ioannis Stamelos,et al. Regression via Classification applied on software defect estimation , 2008, Expert Syst. Appl..
[63] Aurora Trinidad Ramirez Pozo,et al. Predicting Fault Proneness of Classes Trough a Multiobjective Particle Swarm Optimization Algorithm , 2008, 2008 20th IEEE International Conference on Tools with Artificial Intelligence.
[64] Witold Pedrycz,et al. A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction , 2008, 2008 ACM/IEEE 30th International Conference on Software Engineering.
[65] Burak Turhan,et al. Implications of ceiling effects in defect predictors , 2008, PROMISE '08.
[66] Yi Zhang,et al. Classifying Software Changes: Clean or Buggy? , 2008, IEEE Transactions on Software Engineering.
[67] Karim O. Elish,et al. Predicting defect-prone software modules using support vector machines , 2008, J. Syst. Softw..
[68] Yue Jiang,et al. Techniques for evaluating fault prediction models , 2008, Empirical Software Engineering.
[69] Iker Gondra,et al. Applying machine learning to software fault-proneness prediction , 2008, J. Syst. Softw..
[70] Bart Baesens,et al. Mining software repositories for comprehensible software fault prediction models , 2008, J. Syst. Softw..
[71] Ayse Basar Bener,et al. On the relative value of cross-company and within-company data for defect prediction , 2009, Empirical Software Engineering.
[72] Wasif Afzal,et al. A Comparative Evaluation of Using Genetic Programming for Predicting Fault Count Data , 2008, 2008 The Third International Conference on Software Engineering Advances.
[73] B. Paech,et al. Exploring the Relationship of a File's History and Its Fault-Proneness: An Empirical Study , 2008, Testing: Academic & Industrial Conference - Practice and Research Techniques (taic part 2008).
[74] Rudolf Ferenc,et al. Using the Conceptual Cohesion of Classes for Fault Prediction in Object-Oriented Systems , 2008, IEEE Transactions on Software Engineering.
[75] A. Kaur,et al. Application of Random Forest in Predicting Fault-Prone Classes , 2008, 2008 International Conference on Advanced Computer Theory and Engineering.
[76] Arvinder Kaur,et al. Empirical validation of object-oriented metrics for predicting fault proneness models , 2010, Software Quality Journal.
[77] Ayse Basar Bener,et al. Validation of network measures as indicators of defective modules in software systems , 2009, PROMISE '09.
[78] Arvinder Kaur,et al. Software Fault Proneness Prediction Using Support Vector Machines , 2009 .
[79] Yue Jiang,et al. Misclassification cost-sensitive fault prediction models , 2009, PROMISE '09.
[80] Arvinder Kaur,et al. Prediction of Software Quality Model Using Gene Expression Programming , 2009, PROFES.
[81] Elaine J. Weyuker,et al. Comparing the effectiveness of several modeling methods for fault prediction , 2010, Empirical Software Engineering.
[82] Arashdeep Kaur,et al. Early Software Fault Prediction Using Real Time Defect Data , 2009, 2009 Second International Conference on Machine Vision.
[83] Banu Diri,et al. Clustering and Metrics Thresholds Based Software Fault Prediction of Unlabeled Program Modules , 2009, 2009 Sixth International Conference on Information Technology: New Generations.
[84] K. K. Aggarwal,et al. Empirical analysis for investigating the effect of object-oriented metrics on fault proneness: a replicated case study , 2009, Softw. Process. Improv. Pract..
[85] Harald C. Gall,et al. Cross-project defect prediction: a large scale experiment on data vs. domain vs. process , 2009, ESEC/SIGSOFT FSE.
[86] Arvinder Kaur,et al. Empirical analysis for investigating the effect of object-oriented metrics on fault proneness: a replicated case study , 2009 .
[87] Ayse Basar Bener,et al. Analysis of Naive Bayes' assumptions on software fault data: An empirical study , 2009, Data Knowl. Eng..
[88] Banu Diri,et al. A systematic review of software fault prediction studies , 2009, Expert Syst. Appl..
[89] Wasif Afzal,et al. Search-Based Prediction of Fault Count Data , 2009, 2009 1st International Symposium on Search Based Software Engineering.
[90] Taghi M. Khoshgoftaar,et al. Feature Selection with Imbalanced Data for Software Defect Prediction , 2009, 2009 International Conference on Machine Learning and Applications.
[91] Pradeep Singh,et al. An Investigation of the Effect of Discretization on Defect Prediction Using Static Measures , 2009, 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies.
[92] Lovre Hribar,et al. Software component quality prediction using KNN and Fuzzy logic , 2010, The 33rd International Convention MIPRO.
[93] Taghi M. Khoshgoftaar,et al. Predicting Faults in High Assurance Software , 2010, 2010 IEEE 12th International Symposium on High Assurance Systems Engineering.
[94] Aurora Trinidad Ramirez Pozo,et al. A symbolic fault-prediction model based on multiobjective particle swarm optimization , 2010, J. Syst. Softw..
[95] Wasif Afzal,et al. Using Faults-Slip-Through Metric as a Predictor of Fault-Proneness , 2010, 2010 Asia Pacific Software Engineering Conference.
[96] Parvinder S. Sandhu,et al. A model for early prediction of faults in software systems , 2010, 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE).
[97] Andreas Zeller,et al. Change Bursts as Defect Predictors , 2010, 2010 IEEE 21st International Symposium on Software Reliability Engineering.
[98] Yuming Zhou,et al. On the ability of complexity metrics to predict fault-prone classes in object-oriented systems , 2010, J. Syst. Softw..
[99] Michele Lanza,et al. An extensive comparison of bug prediction approaches , 2010, 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010).
[100] Arvinder Kaur,et al. Prediction of Fault-Prone Software Modules using Statistical and Machine Learning Methods , 2010 .
[101] Parag C. Pendharkar,et al. Exhaustive and heuristic search approaches for learning a software defect prediction model , 2010, Eng. Appl. Artif. Intell..
[102] Lionel C. Briand,et al. A systematic and comprehensive investigation of methods to build and evaluate fault prediction models , 2010, J. Syst. Softw..
[103] Wasif Afzal,et al. Search-based Prediction of Fault-slip-through in Large Software Projects , 2010, 2nd International Symposium on Search Based Software Engineering.
[104] Arvinder Kaur,et al. Empirical validation of object-oriented metrics for predicting fault proneness at different severity levels using support vector machines , 2010, Int. J. Syst. Assur. Eng. Manag..
[105] Ayse Basar Bener,et al. An industrial case study of classifier ensembles for locating software defects , 2011, Software Quality Journal.
[106] Taghi M. Khoshgoftaar,et al. Evolutionary Optimization of Software Quality Modeling with Multiple Repositories , 2010, IEEE Transactions on Software Engineering.
[107] Yann-Gaël Guéhéneuc,et al. Design evolution metrics for defect prediction in object oriented systems , 2010, Empirical Software Engineering.
[108] Danielle Azar,et al. An ant colony optimization algorithm to improve software quality prediction models: Case of class stability , 2011, Inf. Softw. Technol..
[109] Qinbao Song,et al. A General Software Defect-Proneness Prediction Framework , 2011, IEEE Transactions on Software Engineering.
[110] Nan-Hsing Chiu,et al. Combining techniques for software quality classification: An integrated decision network approach , 2011, Expert Syst. Appl..
[111] Y. Singh,et al. On the Applicability of Machine Learning Techniques for Object Oriented Software Fault Prediction , 2011 .
[112] Wasif Afzal,et al. On the application of genetic programming for software engineering predictive modeling: A systematic review , 2011, Expert Syst. Appl..
[113] Zhi-Hua Zhou,et al. Sample-based software defect prediction with active and semi-supervised learning , 2012, Automated Software Engineering.
[114] Bhekisipho Twala,et al. Software faults prediction using multiple classifiers , 2011, 2011 3rd International Conference on Computer Research and Development.
[115] Bhavani M. Thuraisingham,et al. Classification and Novel Class Detection in Concept-Drifting Data Streams under Time Constraints , 2011, IEEE Transactions on Knowledge and Data Engineering.
[116] Bharavi Mishra,et al. Impact of attribute selection on defect proneness prediction in OO software , 2011, 2011 2nd International Conference on Computer and Communication Technology (ICCCT-2011).
[117] Michele Lanza,et al. Evaluating defect prediction approaches: a benchmark and an extensive comparison , 2011, Empirical Software Engineering.
[118] Banu Diri,et al. Practical development of an Eclipse-based software fault prediction tool using Naive Bayes algorithm , 2011, Expert Syst. Appl..
[119] Filomena Ferrucci,et al. A Genetic Algorithm to Configure Support Vector Machines for Predicting Fault-Prone Components , 2011, PROFES.
[120] Ye Yang,et al. An investigation on the feasibility of cross-project defect prediction , 2012, Automated Software Engineering.
[121] Cagatay Catal,et al. Software fault prediction: A literature review and current trends , 2011, Expert Syst. Appl..
[122] Scott Dick,et al. Evaluating Stratification Alternatives to Improve Software Defect Prediction , 2012, IEEE Transactions on Reliability.
[123] A. Gupta,et al. Investigating object-oriented design metrics to predict fault-proneness of software modules , 2012, 2012 CSI Sixth International Conference on Software Engineering (CONSEG).
[124] Guangchun Luo,et al. Transfer learning for cross-company software defect prediction , 2012, Inf. Softw. Technol..
[125] Ken-ichi Matsumoto,et al. Locating Source Code to Be Fixed Based on Initial Bug Reports - A Case Study on the Eclipse Project , 2012, 2012 Fourth International Workshop on Empirical Software Engineering in Practice.
[126] Lean Yu,et al. An evolutionary programming based asymmetric weighted least squares support vector machine ensemble learning methodology for software repository mining , 2012, Inf. Sci..
[127] Yong Hu,et al. Systematic literature review of machine learning based software development effort estimation models , 2012, Inf. Softw. Technol..
[128] P. Singh,et al. Empirical investigation of fault prediction capability of object oriented metrics of open source software , 2012, 2012 Ninth International Conference on Computer Science and Software Engineering (JCSSE).
[129] Ruchika Malhotra,et al. Fault Prediction Using Statistical and Machine Learning Methods for Improving Software Quality , 2012, J. Inf. Process. Syst..
[130] R. Geetha Ramani,et al. Predicting fault-prone software modules using feature selection and classification through data mining algorithms , 2012, 2012 IEEE International Conference on Computational Intelligence and Computing Research.
[131] Antonio García Cabot,et al. Performing systematic literature review in software engineering , 2012 .
[132] Jesús S. Aguilar-Ruiz,et al. Searching for rules to detect defective modules: A subgroup discovery approach , 2012, Inf. Sci..
[133] Vandana Bhattacherjee,et al. Software Fault Prediction Using Quad Tree-Based K-Means Clustering Algorithm , 2012, IEEE Transactions on Knowledge and Data Engineering.
[134] Olcay Taner Yildiz,et al. Software defect prediction using Bayesian networks , 2012, Empirical Software Engineering.
[135] Richard Torkar,et al. Software fault prediction metrics: A systematic literature review , 2013, Inf. Softw. Technol..
[136] Akito Monden,et al. Assessing the Cost Effectiveness of Fault Prediction in Acceptance Testing , 2013, IEEE Transactions on Software Engineering.
[137] Bart Baesens,et al. Toward Comprehensible Software Fault Prediction Models Using Bayesian Network Classifiers , 2013, IEEE Transactions on Software Engineering.
[138] James M. Hogan,et al. Predicting Fault-Prone Software Modules with Rank Sum Classification , 2013, 2013 22nd Australian Software Engineering Conference.
[139] Ning Chen,et al. Software process evaluation: a machine learning framework with application to defect management process , 2013, Empirical Software Engineering.
[140] อนิรุธ สืบสิงห์,et al. Data Mining Practical Machine Learning Tools and Techniques , 2014 .
[141] L. Carvajal,et al. IEEE Transactions on Software Engineering , 2016 .