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DSSDPP: Data Selection and Sampling Based Domain Programming Predictor for Cross-Project Defect Prediction

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

inferredcites →https://doi.org/10.1002/smr.2172openalex-snapshot
An improved transfer adaptive boosting approach for mixed‐project defect prediction
inferredcites →https://doi.org/10.1007/978-3-319-26396-0_1openalex-snapshot
Improving Relevancy Filter Methods for Cross-Project Defect Prediction
inferredcites →https://doi.org/10.1007/978-3-540-75225-7_5openalex-snapshot
A Hilbert Space Embedding for Distributions
inferredcites →https://doi.org/10.1007/s10515-011-0090-3openalex-snapshot
An investigation on the feasibility of cross-project defect prediction
inferredcites →https://doi.org/10.1007/s10515-011-0092-1openalex-snapshot
Sample-based software defect prediction with active and semi-supervised learning
inferredcites →https://doi.org/10.1007/s10515-015-0179-1openalex-snapshot
Multiple kernel ensemble learning for software defect prediction
inferredcites →https://doi.org/10.1007/s10515-017-0220-7openalex-snapshot
Cost-sensitive transfer kernel canonical correlation analysis for heterogeneous defect prediction
inferredcites →https://doi.org/10.1007/s10515-019-00259-1openalex-snapshot
Heterogeneous defect prediction with two-stage ensemble learning
inferredcites →https://doi.org/10.1007/s10664-008-9103-7openalex-snapshot
On the relative value of cross-company and within-company data for defect prediction
inferredcites →https://doi.org/10.1007/s10664-011-9173-9openalex-snapshot
Evaluating defect prediction approaches: a benchmark and an extensive comparison
inferredcites →https://doi.org/10.1007/s10664-013-9292-6openalex-snapshot
Towards improving statistical modeling of software engineering data: think locally, act globally!
inferredcites →https://doi.org/10.1007/s10664-014-9346-4openalex-snapshot
Value-cognitive boosting with a support vector machine for cross-project defect prediction
inferredcites →https://doi.org/10.1007/s10664-015-9396-2openalex-snapshot
Towards building a universal defect prediction model with rank transformed predictors
inferredcites →https://doi.org/10.1007/s10664-016-9468-yopenalex-snapshot
Global vs. local models for cross-project defect prediction
inferredcites →https://doi.org/10.1007/s10664-018-9661-2openalex-snapshot
Revisiting supervised and unsupervised models for effort-aware just-in-time defect prediction
inferredcites →https://doi.org/10.1007/s11219-015-9287-1openalex-snapshot
A transfer cost-sensitive boosting approach for cross-project defect prediction
inferredcites →https://doi.org/10.1007/s11390-015-1575-5openalex-snapshot
A Hybrid Instance Selection Using Nearest-Neighbor for Cross-Project Defect Prediction
inferredcites →https://doi.org/10.1007/s11390-017-1785-0openalex-snapshot
A Cluster Based Feature Selection Method for Cross-Project Software Defect Prediction
inferredcites →https://doi.org/10.1007/s11390-019-1959-zopenalex-snapshot
Cross Project Defect Prediction via Balanced Distribution Adaptation Based Transfer Learning
inferredcites →https://doi.org/10.1007/s11704-017-6015-yopenalex-snapshot
Combined classifier for cross-project defect prediction: an extended empirical study
inferredcites →https://doi.org/10.1016/j.infsof.2011.09.007openalex-snapshot
Transfer learning for cross-company software defect prediction
inferredcites →https://doi.org/10.1016/j.infsof.2015.01.014openalex-snapshot
Negative samples reduction in cross-company software defects prediction
inferredcites →https://doi.org/10.1016/j.infsof.2017.06.004openalex-snapshot
A benchmark study on the effectiveness of search-based data selection and feature selection for cross project defect prediction
inferredcites →https://doi.org/10.1016/j.infsof.2018.04.001openalex-snapshot
Cross project defect prediction using class distribution estimation and oversampling
inferredcites →https://doi.org/10.1016/j.infsof.2018.10.004openalex-snapshot
Software defect prediction based on kernel PCA and weighted extreme learning machine
inferredcites →https://doi.org/10.1016/j.infsof.2018.11.005openalex-snapshot
A two-phase transfer learning model for cross-project defect prediction
inferredcites →https://doi.org/10.1049/iet-sen.2017.0148openalex-snapshot
Progress on approaches to software defect prediction
inferredcites →https://doi.org/10.1049/iet-sen.2018.5131openalex-snapshot
Joint distribution matching model for distribution–adaptation‐based cross‐project defect prediction
inferredcites →https://doi.org/10.1109/access.2017.2771460openalex-snapshot
Evaluating Data Filter on Cross-Project Defect Prediction: Comparison and Improvements
inferredcites →https://doi.org/10.1109/esem.2009.5316002openalex-snapshot
Towards logistic regression models for predicting fault-prone code across software projects
inferredcites →https://doi.org/10.1109/esem.2013.20openalex-snapshot
Learning from Open-Source Projects: An Empirical Study on Defect Prediction
inferredcites →https://doi.org/10.1109/esem.2017.49openalex-snapshot
Training Data Selection for Cross-Project Defection Prediction: Which Approach Is Better?
inferredcites →https://doi.org/10.1109/icme.2019.00211openalex-snapshot
Easy Transfer Learning By Exploiting Intra-Domain Structures
inferredcites →https://doi.org/10.1109/icse.2013.6606584openalex-snapshot
Transfer defect learning
inferredcites →https://doi.org/10.1109/icse.2015.91openalex-snapshot
Revisiting the Impact of Classification Techniques on the Performance of Defect Prediction Models
inferredcites →https://doi.org/10.1109/promise.2007.10openalex-snapshot
Predicting Defects for Eclipse
inferredcites →https://doi.org/10.1109/tr.2019.2895462openalex-snapshot
A Novel Class-Imbalance Learning Approach for Both Within-Project and Cross-Project Defect Prediction
inferredcites →https://doi.org/10.1109/tr.2021.3074660openalex-snapshot
Cross-Project Defect Prediction via Landmark Selection-Based Kernelized Discriminant Subspace Alignment
inferredcites →https://doi.org/10.1109/tse.2007.256941openalex-snapshot
Data Mining Static Code Attributes to Learn Defect Predictors
inferredcites →https://doi.org/10.1109/tse.2007.70771openalex-snapshot
On the Distribution of Software Faults
inferredcites →https://doi.org/10.1109/tse.2008.35openalex-snapshot
Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings
inferredcites →https://doi.org/10.1109/tse.2011.103openalex-snapshot
A Systematic Literature Review on Fault Prediction Performance in Software Engineering
inferredcites →https://doi.org/10.1109/tse.2012.83openalex-snapshot
Local versus Global Lessons for Defect Prediction and Effort Estimation
inferredcites →https://doi.org/10.1109/tse.2013.11openalex-snapshot
Data Quality: Some Comments on the NASA Software Defect Datasets
inferredcites →https://doi.org/10.1109/tse.2014.2322358openalex-snapshot
Researcher Bias: The Use of Machine Learning in Software Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2016.2543218openalex-snapshot
HYDRA: Massively Compositional Model for Cross-Project Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2016.2553030openalex-snapshot
Comments on “Researcher Bias: The Use of Machine Learning in Software Defect Prediction”
inferredcites →https://doi.org/10.1109/tse.2016.2584050openalex-snapshot
An Empirical Comparison of Model Validation Techniques for Defect Prediction Models
inferredcites →https://doi.org/10.1109/tse.2016.2597849openalex-snapshot
An Improved SDA Based Defect Prediction Framework for Both Within-Project and Cross-Project Class-Imbalance Problems
inferredcites →https://doi.org/10.1109/tse.2017.2724538openalex-snapshot
A Comparative Study to Benchmark Cross-Project Defect Prediction Approaches
inferredcites →https://doi.org/10.1109/tse.2017.2770124openalex-snapshot
A Systematic Literature Review and Meta-Analysis on Cross Project Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2017.2780222openalex-snapshot
On the Multiple Sources and Privacy Preservation Issues for Heterogeneous Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2018.2794977openalex-snapshot
The Impact of Automated Parameter Optimization on Defect Prediction Models
inferredcites →https://doi.org/10.1109/tse.2018.2821670openalex-snapshot
Bellwethers: A Baseline Method for Transfer Learning
inferredcites →https://doi.org/10.1109/tse.2018.2836442openalex-snapshot
A Comprehensive Investigation of the Role of Imbalanced Learning for Software Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2018.2876537openalex-snapshot
The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models
inferredcites →https://doi.org/10.1109/tse.2018.2877612openalex-snapshot
Deep Semantic Feature Learning for Software Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2018.2877678openalex-snapshot
Perceptions, Expectations, and Challenges in Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2019.2891758openalex-snapshot
The Impact of Correlated Metrics on the Interpretation of Defect Models
inferredcites →https://doi.org/10.1109/tse.2019.2939303openalex-snapshot
Kernel Spectral Embedding Transfer Ensemble for Heterogeneous Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2020.2968520openalex-snapshot
An Empirical Study on Heterogeneous Defect Prediction Approaches
inferredcites →https://doi.org/10.1109/tse.2020.3001739openalex-snapshot
Revisiting Supervised and Unsupervised Methods for Effort-Aware Cross-Project Defect Prediction
inferredcites →https://doi.org/10.1142/s0218001419590377openalex-snapshot
An Investigation of Imbalanced Ensemble Learning Methods for Cross-Project Defect Prediction
inferredcites →https://doi.org/10.1145/1368088.1368114openalex-snapshot
A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction
inferredcites →https://doi.org/10.1145/1370788.1370794openalex-snapshot
Adapting a fault prediction model to allow inter languagereuse
inferredcites →https://doi.org/10.1145/2025113.2025120openalex-snapshot
ReLink
inferredcites →https://doi.org/10.1145/2499393.2499395openalex-snapshot
Training data selection for cross-project defect prediction
inferredcites →https://doi.org/10.1145/2568225.2568320openalex-snapshot
Dictionary learning based software defect prediction
inferredcites →https://doi.org/10.1145/2597073.2597075openalex-snapshot
An empirical study of just-in-time defect prediction using cross-project models
inferredcites →https://doi.org/10.1145/2597073.2597078openalex-snapshot
Towards building a universal defect prediction model
inferredcites →https://doi.org/10.1145/2786805.2786814openalex-snapshot
Heterogeneous defect prediction
inferredcites →https://doi.org/10.1145/2884781.2884839openalex-snapshot
Cross-project defect prediction using a connectivity-based unsupervised classifier
inferredcites →https://doi.org/10.1145/3106237.3106257openalex-snapshot
Revisiting unsupervised learning for defect prediction
inferredcites →https://doi.org/10.1145/3183339openalex-snapshot
How Far We Have Progressed in the Journey? An Examination of Cross-Project Defect Prediction
inferredcites →https://doi.org/10.1145/3377811.3380360openalex-snapshot
Understanding the automated parameter optimization on transfer learning for cross-project defect prediction
inferredcites →https://doi.org/10.1145/3383219.3383232openalex-snapshot
Assessing software defection prediction performance
inferredcites →https://doi.org/10.1609/aaai.v30i1.10306openalex-snapshot
Return of Frustratingly Easy Domain Adaptation
inferredcites →https://doi.org/10.1613/jair.346openalex-snapshot
Improved Heterogeneous Distance Functions
inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot
SMOTE: Synthetic Minority Over-sampling Technique
inferredcites →https://doi.org/10.18293/seke2017-043openalex-snapshot
A Data Filtering Method Based on Agglomerative Clustering
inferredcites →https://doi.org/10.5167/uzh-25785openalex-snapshot
Cross-project defect prediction: a large scale experiment on data vs. domain vs. process
inferredcites →https://doi.org/10.7551/mitpress/7503.003.0069openalex-snapshot
A Kernel Method for the Two-Sample-Problem

What points at this work

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

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Daanae: A Novel Approach to Cross-Project Defect Prediction Based on Dynamic Adversarial Adaptation Network and Autoencoder
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Unveiling the impact of unchanged modules across versions on the evaluation of within‐project defect prediction models
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On the relative value of imbalanced learning for code smell detection
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Framework for Personalized Support in University Course Planning
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Cross-Project Software Defect Prediction Based on Feature Selection and Knowledge Distillation
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An Empirical Study on Multi-source Cross-Project Defect Prediction Using Machine Learning
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Cross-project defect prediction based on autoencoder with dynamic adversarial adaptation
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Software defect prediction: future directions and challenges
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An empirical study of data sampling techniques for just-in-time software defect prediction
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The impact of unsupervised feature selection techniques on the performance and interpretation of defect prediction models
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TLSS_ICFS: A novel two-stage cross-project defect prediction approach
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MCOT-KB: Multi-source cross-project defect prediction with optimal transport domain adaptation and KMMBagging
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Multimodal Path Semantics and Contrastive Domain Adaptation for Cross-Domain Defect Pattern Prediction
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Hybrid balancing method for software fault prediction leveraging stacked ensembles
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A neighborhood rough sets-based ensemble method, with application to software fault prediction
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D-RGCN: Software defect prediction based on dual directed dependency graph reconstruction
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Cross-project software defects prediction using fuzzy embedding and deep learning
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Both reliable and unreliable predictions matter: Domain adaptation for bearing fault diagnosis without source data
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A systematic review on AI based class imbalance handling in software defect prediction
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Towards a framework for reliable performance evaluation in defect prediction
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Has cross-project defect prediction truly progressed? A five-year field diagnosis challenging the state-of-the-art
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Explainability-guided augmentation for data-scarce CPDP via semantic anchors
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An empirical study of neural network based graph representations for software defect prediction
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A privacy-preserving federated meta-learning framework for cross-project defect prediction in software systems
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Current Trends in Class Imbalance Learning for Software Defect Prediction
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An empirical comparison of data transformation techniques for clustering-based unsupervised software defect prediction
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Feature-based Transfer Learning in Cross-Project Defect Prediction: A Systematic Review
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Enhancing Cross-Project Software Defect Prediction with Federated Meta-Learning
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CPLS: Optimizing the Assignment of LLM Queries
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MICVIF: an automatic unsupervised feature selection method for software defect prediction
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TWAO: Time-Weight-Aware Oversampling Method for Just-in-Time Software Defect Prediction
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Empowering LLM-based Software Defect Prediction with Chain-of-Thought and In-context Learning
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Smart Contract Vulnerability Detection via Mask Consistency With Dynamic Margin Adjustment
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CFG2AT: Control Flow Graph and Graph Attention Network-Based Software Defect Prediction
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Unsupervised Software Defect Prediction Through Multiview Clustering
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An Approach for Cross-Project Defect Prediction Using Composite Distribution Alignment and Domain-Adversarial Neural Networks
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MBL-CPDP: A Multi-Objective Bilevel Method for Cross-Project Defect Prediction
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BLAZE: Cross-Language and Cross-Project Bug Localization via Dynamic Chunking and Hard Example Learning
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Adaptive Spectral Clustering and Structural Alignment for Cross-Project Defect Prediction
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Feature Disentanglement-Based Heterogeneous Defect Prediction
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SSF-LCP: Stable SHAP Feature Selection with a Lightweight Classifier Pool for Cross-Project Software Defect Prediction
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Cross-Project Software Defect Prediction Based on Iosmote-Psbp
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CURE: Conditional Unaligned Representation Enhancement for Heterogeneous Software Defect Prediction
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An image dataset for analyzing tea picking behavior in tea plantations
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Empirical Analysis of Data Sampling-Based Decision Forest Classifiers for Software Defect Prediction
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