Artículos de revistas sobre el tema "Defect prediction model"
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Et.al, Christopher Paulraj. "An intelligent Model for Defect Prediction in Spot Welding". Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, n.º 3 (11 de abril de 2021): 3991–4002. http://dx.doi.org/10.17762/turcomat.v12i3.1689.
Texto completoMemon, Mashooque Ahmed, Mujeeb-ur-Rehman Maree Baloch, Muniba Memon y Syed Hyder Abbas Musavi. "A Regression Analysis Based Model for Defect Learning and Prediction in Software Development". July 2021 40, n.º 3 (1 de julio de 2021): 617–29. http://dx.doi.org/10.22581/muet1982.2103.15.
Texto completoYuan, Yuyu, Chenlong Li y Jincui Yang. "An Improved Confounding Effect Model for Software Defect Prediction". Applied Sciences 13, n.º 6 (8 de marzo de 2023): 3459. http://dx.doi.org/10.3390/app13063459.
Texto completoZhang, Wei, Zhen Yu Ma, Qing Ling Lu, Xiao Bing Nie y Juan Liu. "Research on Software Defect Prediction Method Based on Machine Learning". Applied Mechanics and Materials 687-691 (noviembre de 2014): 2182–85. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.2182.
Texto completoFalessi, Davide, Aalok Ahluwalia y Massimiliano DI Penta. "The Impact of Dormant Defects on Defect Prediction: A Study of 19 Apache Projects". ACM Transactions on Software Engineering and Methodology 31, n.º 1 (31 de enero de 2022): 1–26. http://dx.doi.org/10.1145/3467895.
Texto completoCHANG, CHING-PAO. "INTEGRATING ACTION-BASED DEFECT PREDICTION TO PROVIDE RECOMMENDATIONS FOR DEFECT ACTION CORRECTION". International Journal of Software Engineering and Knowledge Engineering 23, n.º 02 (marzo de 2013): 147–72. http://dx.doi.org/10.1142/s0218194013500022.
Texto completoNevendra, Meetesh y Pradeep Singh. "Cross-Project Defect Prediction with Metrics Selection and Balancing Approach". Applied Computer Systems 27, n.º 2 (1 de diciembre de 2022): 137–48. http://dx.doi.org/10.2478/acss-2022-0015.
Texto completoZhang, Jie, Gang Wang, Haobo Jiang, Fangzheng Zhao y Guilin Tian. "Research and Appalication of Software Defect Predictionn based on BP-Migration learning". MATEC Web of Conferences 232 (2018): 03017. http://dx.doi.org/10.1051/matecconf/201823203017.
Texto completoPeng, Xuemei. "Research on Software Defect Prediction and Analysis Based on Machine Learning". Journal of Physics: Conference Series 2173, n.º 1 (1 de enero de 2022): 012043. http://dx.doi.org/10.1088/1742-6596/2173/1/012043.
Texto completoHan, Wan Jiang, He Yang Jiang, Yi Sun y Tian Bo Lu. "Software Defect Distribution Prediction for BOSS System". Applied Mechanics and Materials 701-702 (diciembre de 2014): 67–70. http://dx.doi.org/10.4028/www.scientific.net/amm.701-702.67.
Texto completoCHANG, CHING-PAO y CHIH-PING CHU. "SOFTWARE DEFECT PREDICTION USING INTERTRANSACTION ASSOCIATION RULE MINING". International Journal of Software Engineering and Knowledge Engineering 19, n.º 06 (septiembre de 2009): 747–64. http://dx.doi.org/10.1142/s0218194009004428.
Texto completoLiu, Can, Sumaya Sanober, Abu Sarwar Zamani, L. Rama Parvathy, Rahul Neware y Abdul Wahab Rahmani. "Defect Prediction Technology in Software Engineering Based on Convolutional Neural Network". Security and Communication Networks 2022 (26 de abril de 2022): 1–8. http://dx.doi.org/10.1155/2022/5058461.
Texto completoLiu, Can, Sumaya Sanober, Abu Sarwar Zamani, L. Rama Parvathy, Rahul Neware y Abdul Wahab Rahmani. "Defect Prediction Technology in Software Engineering Based on Convolutional Neural Network". Security and Communication Networks 2022 (26 de abril de 2022): 1–8. http://dx.doi.org/10.1155/2022/5058461.
Texto completoShi, Sheng Li, Jin Shi y Rui Wang. "A Prediction Model Based on ISOMAP for Software Defects". Applied Mechanics and Materials 347-350 (agosto de 2013): 3278–82. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.3278.
Texto completoMalhotra, Ruchika y Shweta Meena. "Defect prediction model using transfer learning". Soft Computing 26, n.º 10 (22 de febrero de 2022): 4713–26. http://dx.doi.org/10.1007/s00500-022-06846-x.
Texto completoJorayeva, Manzura, Akhan Akbulut, Cagatay Catal y Alok Mishra. "Deep Learning-Based Defect Prediction for Mobile Applications". Sensors 22, n.º 13 (23 de junio de 2022): 4734. http://dx.doi.org/10.3390/s22134734.
Texto completoHan, Wan Jiang, Li Xin Jiang, Xiao Yan Zhang y Yi Sun. "A Software Defect Prediction Model during the Test Period". Applied Mechanics and Materials 475-476 (diciembre de 2013): 1186–89. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.1186.
Texto completoGoel, Lipika, Neha Nandal y Sonam Gupta. "An optimized approach for class imbalance problem in heterogeneous cross project defect prediction". F1000Research 11 (16 de septiembre de 2022): 1060. http://dx.doi.org/10.12688/f1000research.123616.1.
Texto completoZhang, Shenggang, Shujuan Jiang y Yue Yan. "A Software Defect Prediction Approach Based on BiGAN Anomaly Detection". Scientific Programming 2022 (13 de abril de 2022): 1–13. http://dx.doi.org/10.1155/2022/5024399.
Texto completoZhang, Hua Yin y Jian Long Ding. "Weighted Hybrid Defect Content and Effectiveness Model". Advanced Materials Research 846-847 (noviembre de 2013): 1762–67. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1762.
Texto completoCui, Mengtian, Songlin Long, Yue Jiang y Xu Na. "Research of Software Defect Prediction Model Based on Complex Network and Graph Neural Network". Entropy 24, n.º 10 (27 de septiembre de 2022): 1373. http://dx.doi.org/10.3390/e24101373.
Texto completoPan, Cong, Minyan Lu y Biao Xu. "An Empirical Study on Software Defect Prediction Using CodeBERT Model". Applied Sciences 11, n.º 11 (23 de mayo de 2021): 4793. http://dx.doi.org/10.3390/app11114793.
Texto completoVashisht, Rohit y Syed Afzal Murtaza Rizvi. "An Empirical Study of Heterogeneous Cross-Project Defect Prediction Using Various Statistical Techniques". International Journal of e-Collaboration 17, n.º 2 (abril de 2021): 55–71. http://dx.doi.org/10.4018/ijec.2021040104.
Texto completoZhao, Yu, Yi Zhu, Qiao Yu y Xiaoying Chen. "Cross-Project Defect Prediction Considering Multiple Data Distribution Simultaneously". Symmetry 14, n.º 2 (17 de febrero de 2022): 401. http://dx.doi.org/10.3390/sym14020401.
Texto completoMisirli, Ayse Tosun, Ayse Bener y Resat Kale. "AI-Based Software Defect Predictors: Applications and Benefits in a Case Study". AI Magazine 32, n.º 2 (5 de junio de 2011): 57. http://dx.doi.org/10.1609/aimag.v32i2.2348.
Texto completoTosun, Ayse, Ayse Bener y Resat Kale. "AI-Based Software Defect Predictors: Applications and Benefits in a Case Study". Proceedings of the AAAI Conference on Artificial Intelligence 24, n.º 2 (11 de julio de 2010): 1748–55. http://dx.doi.org/10.1609/aaai.v24i2.18807.
Texto completoAlmayyan, Waheeda. "Towards Predicting Software Defects with Clustering Techniques". International Journal of Artificial Intelligence & Applications 12, n.º 1 (31 de enero de 2021): 39–54. http://dx.doi.org/10.5121/ijaia.2021.12103.
Texto completoWang, Chongjiao, Changrong Yao, Bin Qiang, Siguang Zhao y Yadong Li. "A Machine Learning Framework for Predicting Bridge Defect Detection Cost". Infrastructures 6, n.º 11 (23 de octubre de 2021): 152. http://dx.doi.org/10.3390/infrastructures6110152.
Texto completoZheng, Xianda, Yuan-Fang Li, Huan Gao, Yuncheng Hua y Guilin Qi. "Towards Balanced Defect Prediction with Better Information Propagation". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 1 (18 de mayo de 2021): 759–67. http://dx.doi.org/10.1609/aaai.v35i1.16157.
Texto completoGrobler-Dębska, Katarzyna, Edyta Kucharska y Jerzy Baranowski. "Formal scheduling method for zero-defect manufacturing". International Journal of Advanced Manufacturing Technology 118, n.º 11-12 (22 de octubre de 2021): 4139–59. http://dx.doi.org/10.1007/s00170-021-08104-0.
Texto completoYi Zhu, Yi Zhu, Yu Zhao Yi Zhu, Qiao Yu Yu Zhao y Xiaoying Chen Qiao Yu. "Cross-Project Defect Prediction Method based on Feature Distribution Alignment and Neighborhood Instance Selection". 網際網路技術學刊 23, n.º 4 (julio de 2022): 761–69. http://dx.doi.org/10.53106/160792642022072304011.
Texto completoSchmidt, Immo, Lorenz Dingeldein, David Hünemohr, Henrik Simon y Max Weigert. "Application of Machine Learning Methods to Predict the Quality of Electric Circuit Boards of a Production Line". PHM Society European Conference 7, n.º 1 (29 de junio de 2022): 550–55. http://dx.doi.org/10.36001/phme.2022.v7i1.3372.
Texto completoVerna, Elisa, Gianfranco Genta, Maurizio Galetto y Fiorenzo Franceschini. "Defects-per-unit control chart for assembled products based on defect prediction models". International Journal of Advanced Manufacturing Technology 119, n.º 5-6 (31 de octubre de 2021): 2835–46. http://dx.doi.org/10.1007/s00170-021-08157-1.
Texto completoWang, Yan. "Efficient Prediction Method of Defect of Monitor Configuration Software". Journal of Advanced Computational Intelligence and Intelligent Informatics 23, n.º 2 (20 de marzo de 2019): 340–44. http://dx.doi.org/10.20965/jaciii.2019.p0340.
Texto completoKim, Jun y Ju Yeon Lee. "Development of a cost analysis-based defect-prediction system with a type error-weighted deep neural network algorithm". Journal of Computational Design and Engineering 9, n.º 2 (25 de febrero de 2022): 380–92. http://dx.doi.org/10.1093/jcde/qwac006.
Texto completoMalhotra, Ruchika y Juhi Jain. "Predicting defects in imbalanced data using resampling methods: an empirical investigation". PeerJ Computer Science 8 (29 de abril de 2022): e573. http://dx.doi.org/10.7717/peerj-cs.573.
Texto completoHolovský, Jakub, Michael Stuckelberger, Tomáš Finsterle, Brianna Conrad, Amalraj Peter Amalathas, Martin Müller y Franz-Josef Haug. "Towards Quantitative Interpretation of Fourier-Transform Photocurrent Spectroscopy on Thin-Film Solar Cells". Coatings 10, n.º 9 (25 de agosto de 2020): 820. http://dx.doi.org/10.3390/coatings10090820.
Texto completoTallian, T. E. "Simplified Contact Fatigue Life Prediction Model—Part II: New Model". Journal of Tribology 114, n.º 2 (1 de abril de 1992): 214–20. http://dx.doi.org/10.1115/1.2920876.
Texto completoOlaleye, T. O., O. T. Arogundade, Sanjay Misra, A. Abayomi-Alli y Utku Kose. "Predictive Analytics and Software Defect Severity: A Systematic Review and Future Directions". Scientific Programming 2023 (2 de febrero de 2023): 1–18. http://dx.doi.org/10.1155/2023/6221388.
Texto completoVijaya Kumar, Suria Devi, Saravanan Karuppanan y Mark Ovinis. "Artificial Neural Network-Based Failure Pressure Prediction of API 5L X80 Pipeline with Circumferentially Aligned Interacting Corrosion Defects Subjected to Combined Loadings". Materials 15, n.º 6 (18 de marzo de 2022): 2259. http://dx.doi.org/10.3390/ma15062259.
Texto completoSu, Qiang, Lei Liu y Shengjie Lai. "Measuring the assembly quality from the operator mistake view: a case study". Assembly Automation 29, n.º 4 (25 de septiembre de 2009): 332–40. http://dx.doi.org/10.1108/01445150910987745.
Texto completoKakkar, Misha, Sarika Jain, Abhay Bansal y P. S. Grover. "Nonlinear Geometric Framework for Software Defect Prediction". International Journal of Decision Support System Technology 12, n.º 3 (julio de 2020): 85–100. http://dx.doi.org/10.4018/ijdsst.2020070105.
Texto completoVashisht, Rohit y Syed Afzal Murtaza Rizvi. "Estimation of Target Defect Prediction Coverage in Heterogeneous Cross Software Projects". International Journal of Information System Modeling and Design 12, n.º 1 (enero de 2021): 73–93. http://dx.doi.org/10.4018/ijismd.2021010104.
Texto completo李勇, 李勇, Ming Wen Yong Li, Zhandong Liu Ming Wen y Haijun Zhang Zhandong Liu. "Using Cost-cognitive Bagging Ensemble to Improve Cross-project Defects Prediction". 網際網路技術學刊 23, n.º 4 (julio de 2022): 779–89. http://dx.doi.org/10.53106/160792642022072304013.
Texto completoSinaga, Benyamin Langgu, Sabrina Ahmad, Zuraida Abal Abas y Intan Ermahani A. Jalil. "A recommendation system of training data selection method for cross-project defect prediction". Indonesian Journal of Electrical Engineering and Computer Science 27, n.º 2 (1 de agosto de 2022): 990. http://dx.doi.org/10.11591/ijeecs.v27.i2.pp990-1006.
Texto completoChen, Chao y Xingyuan Zhang. "Research on laser ultrasonic surface defect identification based on a support vector machine". Science Progress 104, n.º 4 (octubre de 2021): 003685042110590. http://dx.doi.org/10.1177/00368504211059038.
Texto completoLiu, Wenjian, Baoping Wang y Wennan Wang. "Deep Learning Software Defect Prediction Methods for Cloud Environments Research". Scientific Programming 2021 (18 de noviembre de 2021): 1–11. http://dx.doi.org/10.1155/2021/2323100.
Texto completoLamba, Tripti, Kavita y A. K. Mishra. "Optimal Machine learning Model for Software Defect Prediction". International Journal of Intelligent Systems and Applications 11, n.º 2 (8 de febrero de 2019): 36–48. http://dx.doi.org/10.5815/ijisa.2019.02.05.
Texto completo., Shaik Nafeez Umar. "SOFTWARE TESTING DEFECT PREDICTION MODEL - A PRACTICAL APPROACH". International Journal of Research in Engineering and Technology 02, n.º 05 (25 de mayo de 2013): 741–45. http://dx.doi.org/10.15623/ijret.2013.0205001.
Texto completoShibo, Wang, Li Yong, Mi Wenbo y Liu Ying. "Software Defect Prediction Incremental Model using Ensemble Learning". International Journal of Performability Engineering 16, n.º 11 (2020): 1771. http://dx.doi.org/10.23940/ijpe.20.11.p9.17711780.
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