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A Cloud-Based Software Defect Prediction System Using Data and Decision-Level Machine Learning Fusion

https://doi.org/10.3390/math11030632
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-29044-2openalex-snapshot
Experimentation in Software Engineering
inferredcites →https://doi.org/10.1007/s11042-021-11488-6openalex-snapshot
Heterogeneous stacked ensemble classifier for software defect prediction
inferredcites →https://doi.org/10.1007/s11219-011-9132-0openalex-snapshot
Predicting high-risk program modules by selecting the right software measurements
inferredcites →https://doi.org/10.1007/s11227-021-04113-8openalex-snapshot
Software-defect prediction within and across projects based on improved self-organizing data mining
inferredcites →https://doi.org/10.1007/s11334-021-00399-2openalex-snapshot
Bootstrap aggregation ensemble learning-based reliable approach for software defect prediction by using characterized code feature
inferredcites →https://doi.org/10.1007/s42979-020-0119-4openalex-snapshot
Evaluation of Sampling-Based Ensembles of Classifiers on Imbalanced Data for Software Defect Prediction Problems
inferredcites →https://doi.org/10.1016/j.procs.2015.02.154openalex-snapshot
Design of Software Fault Prediction Model Using BR Technique
inferredcites →https://doi.org/10.1109/access.2017.2785445openalex-snapshot
A Framework for Software Defect Prediction and Metric Selection
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Prediction of Diabetes Empowered With Fused Machine Learning
inferredcites →https://doi.org/10.1109/ictcs.2017.39openalex-snapshot
Software Defect Prediction using Feature Selection and Random Forest Algorithm
inferredcites →https://doi.org/10.1109/tase.2019.2895801openalex-snapshot
Temporal Prediction of Multiapplication Consolidated Workloads in Distributed Clouds
inferredcites →https://doi.org/10.1109/tse.2010.90openalex-snapshot
A General Software Defect-Proneness Prediction Framework
inferredcites →https://doi.org/10.1109/tse.2013.11openalex-snapshot
Data Quality: Some Comments on the NASA Software Defect Datasets
inferredcites →https://doi.org/10.1155/2016/2401496openalex-snapshot
Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction
inferredcites →https://doi.org/10.32604/iasc.2022.020362openalex-snapshot
Machine Learning Empowered Software Defect Prediction System
inferredcites →https://doi.org/10.3390/app10051745openalex-snapshot
Software Defect Prediction Using Heterogeneous Ensemble Classification Based on Segmented Patterns
inferredcites →https://doi.org/10.3390/app9132764openalex-snapshot
Performance Analysis of Feature Selection Methods in Software Defect Prediction: A Search Method Approach
inferredcites →https://doi.org/10.3390/electronics10020179openalex-snapshot
Empirical Analysis of Rank Aggregation-Based Multi-Filter Feature Selection Methods in Software Defect Prediction
inferredcites →https://doi.org/10.3390/s22093504openalex-snapshot
Rainfall Prediction System Using Machine Learning Fusion for Smart Cities
inferredcites →https://doi.org/10.3390/sym13112166openalex-snapshot
Software Defect Prediction Using Wrapper Feature Selection Based on Dynamic Re-Ranking Strategy
inferredcites →https://doi.org/10.4018/ijkss.2020040102openalex-snapshot
Comparison of Machine Learning Techniques for Software Quality Prediction
inferredcites →https://doi.org/10.4236/jsea.2019.125007openalex-snapshot
Software Defect Prediction Using Supervised Machine Learning and Ensemble Techniques: A Comparative Study
inferredcites →https://doi.org/10.5120/ijca2018917185openalex-snapshot
Early Prediction of Software Defect using Ensemble Learning: A Comparative Study
inferredcites →https://doi.org/10.5815/ijitcs.2020.03.04openalex-snapshot
Prediction of Defect Prone Software Modules using MLP based Ensemble Techniques
inferredcites →https://doi.org/10.5815/ijmecs.2020.01.03openalex-snapshot
A Classification Framework for Software Defect Prediction Using Multi-filter Feature Selection Technique and MLP
inferredcites →https://doi.org/10.5815/ijmecs.2020.05.03openalex-snapshot
Software Defect Prediction Using Variant based Ensemble Learning and Feature Selection Techniques
inferredcites →https://doi.org/10.6025/jnt/2018/9/3/94-101openalex-snapshot
Software Fault-Prediction using Combination of Neural Network and Naive Bayes Algorithm

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Machine Learning and Deep Learning Techniques to Predict Software Defects: A Bibliometric Analysis, Systematic Review, Challenges and Future Works
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Improving Software Defect Prediction: Resolving Data Imbalance with Ensemble Learning
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Enhanced Software Bug Prediction Using Ensemble Learning and Genetic Algorithm-Based Feature Selection
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A Comprehensive Literature Review on Advancing Software Defect Prediction: Techniques, Datasets, and Future Directions
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Enhancing Software Defect Prediction with an Advanced Ensemble Approach
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Contrastive Multimodal Models for Zero-Shot Cross-Domain Vision-Language Retrieval
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Predicting Software Perfection Through Advanced Models to Uncover and Prevent Defects
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Securing the Internet of Things (IoT) Application: Best Practices and Challenges in IoT Software
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Topological Deep Learning for Recognizing Manufacturing Defects in High-Precision Semiconductor Fabrication Lines
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Simulation Annealing Based Bacterial Foraging Optimization with Support Vector Machine for Predicting Potential Defects in Software
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Predicting Software Defects with an Intelligent Ensemble-Based Engine
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An Ensemble Learning Method Based on Neighborhood Granularity Discrimination Index and Its Application in Software Defect Prediction
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Improving Software Performance Through Early Bug Detection Using Large-Scale Machine Learning Models
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Insights of effectivity analysis of learning-based approaches towards software defect prediction
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МУЛЬТИАСПЕКТНІСТЬ ТА CТРАТЕГІЧНЕ ПЛАНУВАННЯ ПРИ СТВОРЕНІ БАГАТОЦІЛЬОВИХ МОДЕЛЕЙ ОЦІНКИ ЯКОСТІ ПРОГРАМНИХ СИСТЕМ
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FEDRak: Federated Learning-Based Symmetric Code Statement Ranking Model for Software Fault Forecasting
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Entangling Quantum Adversarial Network with Football Optimization for Software Defect Prediction
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