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Software defect prediction using cost-sensitive neural network
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Cost-sensitive boosting neural networks for software defect prediction
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Object-oriented software fault prediction using neural networks
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Training cost-sensitive neural networks with methods addressing the class imbalance problem
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A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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A Bagging Algorithm for Imprecise Classification in Cost-Sensitive Scenarios
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On the application of search-based techniques for software engineering predictive modeling: A systematic review and future directions
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Threats to validity in search‐based predictive modelling for software engineering
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Comparison of threshold identification techniques for object-oriented software metrics
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Retracted: Scientific programming using optimized machine learning techniques for software fault prediction to improve software quality
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A phase wise approach for fault identification
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A random forest classifier with cost-sensitive learning to extract urban landmarks from an imbalanced dataset
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An empirical investigation of forecasting methods for ambulance calls - a case study
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Weighted knn using grey relational analysis for cross-project defect prediction
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Improving The Effectiveness of Classification Using The Data Level Approach and Feature Selection Techniques in Online Shoppers Purchasing Intention Prediction
inferred← citeshttps://doi.org/10.1088/1755-1315/252/4/042096openalex-snapshot
Research and Application of BP Algorithm Based on Genetic Algorithm in System Performance Bottleneck Analysis
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Predicting defects in object-oriented software using cost-sensitive classification
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A hybrid approach for optimizing software defect prediction using a grey wolf optimization and multilayer perceptron
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Quality and reliability studies in software defect management: a literature review
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Evaluating Data Filter on Cross-Project Defect Prediction: Comparison and Improvements
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A Framework for Software Defect Prediction and Metric Selection
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A Fault Detection and Health Monitoring Scheme for Ship Propulsion Systems Using SVM Technique
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An Ensemble Oversampling Model for Class Imbalance Problem in Software Defect Prediction
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Experimental Validation of Inheritance Metrics’ Impact on Software Fault Prediction
inferred← citeshttps://doi.org/10.1109/access.2019.2940557openalex-snapshot
Convolutional Neural Networks-Based Locating Relevant Buggy Code Files for Bug Reports Affected by Data Imbalance
inferred← citeshttps://doi.org/10.1109/access.2020.2974527openalex-snapshot
Adversarial Learning for Cross-Project Semi-Supervised Defect Prediction
inferred← citeshttps://doi.org/10.1109/access.2020.2981869openalex-snapshot
An Adversarial Discriminative Convolutional Neural Network for Cross-Project Defect Prediction
inferred← citeshttps://doi.org/10.1109/access.2020.2984179openalex-snapshot
What Ruined Your Cake: Impacts of Code Modifications on Bug Distribution
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Efficacy of Inheritance Aspect in Software Fault Prediction—A Survey Paper
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Improving Software Defect Prediction by Aggregated Change Metrics
inferred← citeshttps://doi.org/10.1109/access.2022.3219589openalex-snapshot
Learning Stretch-Shrink Latent Representations With Autoencoder and K-Means for Software Defect Prediction
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Toward Reduction in False Positives Just-In-Time Software Defect Prediction Using Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/access.2024.3388489openalex-snapshot
LCNN: Lightweight CNN Architecture for Software Defect Feature Identification Using Explainable AI
inferred← citeshttps://doi.org/10.1109/access.2024.3517419openalex-snapshot
Comprehensive Bibliographic Survey and Forward-Looking Recommendations for Software Defect Prediction: Datasets, Validation Methodologies, Prediction Approaches, and Tools
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Investigating the Use of Deep Neural Networks for Software Defect Prediction
inferred← citeshttps://doi.org/10.1109/aikiie60097.2023.10390074openalex-snapshot
An Identification of Software Defect Using Cost Based Support Vector Machine and Robust Similarity Aware Clustering Model
inferred← citeshttps://doi.org/10.1109/aist55798.2022.10064852openalex-snapshot
OPABP-Optimizing Parameters, to Improve Accuracy in Bug Prediction using Machine Learning
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An Imbalanced Deep Learning Model for Bug Localization
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Performance Evaluation of Advanced Machine Learning Classifiers for Software Defect Prediction
inferred← citeshttps://doi.org/10.1109/ccdc49329.2020.9164226openalex-snapshot
Latent Posterior Based Generative Adversarial Network for Imbalance Classification
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A Comparison of Classification Algorithms for Software Defect Prediction
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Software Fault Proneness Prediction with Group Lasso Regression: On Factors that Affect Classification Performance
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Analyzing the Effectiveness of Machine Learning Algorithms for Determining Faulty Classes: A Comparative Analysis
inferred← citeshttps://doi.org/10.1109/docs55193.2022.9967755openalex-snapshot
Unbalanced data processing for software defect prediction
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An Empirical Study on The Impact of The Interaction between Feature Selection and Sampling in Defect Prediction
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An Empirical Study on Spectral Clustering-based Software Defect Detection
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Overview of Mining Software Repositories
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Software Defect Prediction by Logistic Regression with Gradient Descent Cost Computation
inferred← citeshttps://doi.org/10.1109/esem.2017.48openalex-snapshot
File-Level Defect Prediction: Unsupervised vs. Supervised Models
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Enhancing Software Quality Assurance through Machine Learning-Based Fault Prediction
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Common threats to software quality predictive modeling studies using search-based techniques
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Enhancing Software Defect Prediction: A Machine Learning Approaches
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Revolutionizing Software Defect Prediction Through Deep Learning
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Kernel-based Class-specific Broad Learning System for software defect prediction
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Towards a New Hybrid Synthetic Minority Oversampling Technique for Imbalanced Problem in Software Defect Prediction
inferred← citeshttps://doi.org/10.1109/iceccc65144.2025.11064181openalex-snapshot
A Novel Hybrid Approach to Enhance Software Quality by Using the Honey Badger Algorithm (HBA) and Support Vector Machine (SVM)
inferred← citeshttps://doi.org/10.1109/icitri62858.2024.10699214openalex-snapshot
Improving Software Defect Prediction Performance through Effective Forward Selection Method with Linear Regression for Handling Class Imbalance
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Software fault prediction based on one-class SVM
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An Ensemble Model for Software Defect Prediction
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A Hybrid Nonlinear Manifold Detection Approach for Software Defect Prediction
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Software defect prediction based on class-association rules
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Boosting Code-line-level Defect Prediction with Spectrum Information and Causality Analysis
inferred← citeshttps://doi.org/10.1109/ipdpsw.2019.00138openalex-snapshot
Neural Network Frameworks. Comparison on Public Transportation Prediction
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Misclassification Cost-Sensitive Software Defect Prediction
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A Brief Analysis of Soft Computing Techniques in Software Fault Prediction
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A software defect detection algorithm based on asymmetric classification evaluation
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Combining feature selection, feature learning and ensemble learning for software fault prediction
inferred← citeshttps://doi.org/10.1109/mesiicon55227.2022.10093237openalex-snapshot
Optimized Decision Tree-based Early Phase Software Dependability Analysis in Uncertain Environment
inferred← citeshttps://doi.org/10.1109/msr.2017.4openalex-snapshot
The Impact of Using Regression Models to Build Defect Classifiers
inferred← citeshttps://doi.org/10.1109/qrs54544.2021.00058openalex-snapshot
eCPDP: Early Cross-Project Defect Prediction
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On Supervised Class-Imbalanced Learning: An Updated Perspective and Some Key Challenges
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A Novel Class-Imbalance Learning Approach for Both Within-Project and Cross-Project Defect Prediction
inferred← citeshttps://doi.org/10.1109/tr.2020.2996261openalex-snapshot
WR-ELM: Weighted Regularization Extreme Learning Machine for Imbalance Learning in Software Fault Prediction
inferred← citeshttps://doi.org/10.1109/tr.2022.3158949openalex-snapshot
Generative Oversampling Methods for Handling Imbalanced Data in Software Fault Prediction
inferred← citeshttps://doi.org/10.1109/tr.2024.3356515openalex-snapshot
Software Defect Prediction Approach Based on a Diversity Ensemble Combined With Neural Network
inferred← citeshttps://doi.org/10.1109/tse.2024.3503723openalex-snapshot
Line-Level Defect Prediction by Capturing Code Contexts With Graph Convolutional Networks
inferred← citeshttps://doi.org/10.1111/exsy.12977openalex-snapshot
Eliminating the high false‐positive rate in defect prediction through BayesNet with adjustable weight
inferred← citeshttps://doi.org/10.11113/jt.v79.11874openalex-snapshot
TACKLING IMBALANCED CLASS IN SOFTWARE DEFECT PREDICTION USING TWO-STEP CLUSTER BASED RANDOM UNDERSAMPLING AND STACKING TECHNIQUE
inferred← citeshttps://doi.org/10.1142/s0218194017400046openalex-snapshot
Improving Cross-Company Defect Prediction with Data Filtering
inferred← citeshttps://doi.org/10.1142/s0218194018500237openalex-snapshot
An Empirical Study on Software Defect Prediction Using Over-Sampling by SMOTE
inferred← citeshttps://doi.org/10.1142/s0218539323500067openalex-snapshot
Analysis of Hybridized Techniques with Class Imbalance Learning for Predicting Software Maintainability
inferred← citeshttps://doi.org/10.1142/s0218539325500093openalex-snapshot
A Transfer Weighted Homogeneous Ensemble Method for Cross-Project Software Fault Prediction
inferred← citeshttps://doi.org/10.1145/2884781.2884839openalex-snapshot
Cross-project defect prediction using a connectivity-based unsupervised classifier
inferred← citeshttps://doi.org/10.1145/3343440openalex-snapshot
A Systematic Review on Imbalanced Data Challenges in Machine Learning
inferred← citeshttps://doi.org/10.1145/3524842.3527934openalex-snapshot
Methods for stabilizing models across large samples of projects (with case studies on predicting defect and project health)
inferred← citeshttps://doi.org/10.1145/3568562.3568587openalex-snapshot
Combining Deep Learning and Kernel PCA for Software Defect Prediction
inferred← citeshttps://doi.org/10.1145/3582572openalex-snapshot
Code-line-level Bugginess Identification: How Far have We Come, and How Far have We Yet to Go?
inferred← citeshttps://doi.org/10.1145/3584871.3584885openalex-snapshot
An Artificial Neural Network Model based on Binary Particle Swarm Optimization for enhancing the efficiency of Software Defect Prediction
inferred← citeshttps://doi.org/10.1145/3628797.3628963openalex-snapshot
On the Value of Code Embedding and Imbalanced Learning Approaches for Software Defect Prediction
inferred← citeshttps://doi.org/10.1145/3643991.3644928openalex-snapshot
An Empirical Study on Just-in-time Conformal Defect Prediction
inferred← citeshttps://doi.org/10.1155/2016/2401496openalex-snapshot
Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction
inferred← citeshttps://doi.org/10.1155/2016/7658207openalex-snapshot
Prediction of Defective Software Modules Using Class Imbalance Learning
inferred← citeshttps://doi.org/10.1155/2021/6662932openalex-snapshot
Impact of Parameter Tuning for Optimizing Deep Neural Network Models for Predicting Software Faults
inferred← citeshttps://doi.org/10.1155/2022/2117339openalex-snapshot
Software Defect Prediction Using Artificial Neural Networks: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1155/2022/2581832openalex-snapshot
Software Defect Prediction through Neural Network and Feature Selections
inferred← citeshttps://doi.org/10.1155/2022/5024399openalex-snapshot
A Software Defect Prediction Approach Based on BiGAN Anomaly Detection
inferred← citeshttps://doi.org/10.1155/int/6463038openalex-snapshot
Software Defect Prediction Based on Fuzzy Cost Broad Learning System
inferred← citeshttps://doi.org/10.1162/evco_a_00304openalex-snapshot
High-Dimensional Unbalanced Binary Classification by Genetic Programming with Multi-Criterion Fitness Evaluation and Selection
inferred← citeshttps://doi.org/10.1177/18724981241289228openalex-snapshot
A novel hybrid JAYA optimization algorithm and extreme learning machine classifier (JAYA-ELM) for software reliability prediction
inferred← citeshttps://doi.org/10.12700/aph.18.10.2021.10.9openalex-snapshot
Software Defect Prediction using Deep Learning
inferred← citeshttps://doi.org/10.1371/journal.pone.0307112openalex-snapshot
A trustworthy hybrid model for transparent software defect prediction: SPAM-XAI
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