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Less Is More: Unlocking Semi-Supervised Deep Learning for Vulnerability Detection
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Does Active Learning Work? A Review of the Research
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VulGraB : Graph ‐embedding‐based code vulnerability detection with bi‐directional gated graph neural network
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Wilcoxon-Signed-Rank Test
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Cross-company defect prediction via semi-supervised clustering-based data filtering and MSTrA-based transfer learning
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Sample-based software defect prediction with active and semi-supervised learning
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Label propagation based semi-supervised learning for software defect prediction
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APIReal: an API recognition and linking approach for online developer forums
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Revisiting supervised and unsupervised models for effort-aware just-in-time defect prediction
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Revisiting the VCCFinder approach for the identification of vulnerability-contributing commits
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DebtFree: minimizing labeling cost in self-admitted technical debt identification using semi-supervised learning
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SSPCatcher: Learning to catch security patches
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Semi-Supervised Learning Based Tag Recommendation for Docker Repositories
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A review of uncertainty quantification in deep learning: Techniques, applications and challenges
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Software defect number prediction: Unsupervised vs supervised methods
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Effort-Aware semi-Supervised just-in-Time defect prediction
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COSTE: Complexity-based OverSampling TEchnique to alleviate the class imbalance problem in software defect prediction
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Malware classification for the cloud via semi-supervised transfer learning
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ASSBert: Active and semi-supervised bert for smart contract vulnerability detection
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The rise of software vulnerability: Taxonomy of software vulnerabilities detection and machine learning approaches
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LDFR: Learning deep feature representation for software defect prediction
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GRACE: Empowering LLM-based software vulnerability detection with graph structure and in-context learning
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Semi-supervised two-phase familial analysis of Android malware with normalized graph embedding
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Combining global and minutia deep features for partial high-resolution fingerprint matching
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Near linear time algorithm to detect community structures in large-scale networks
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Software Vulnerability Analysis and Discovery Using Deep Learning Techniques: A Survey
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When Less is Enough: Positive and Unlabeled Learning Model for Vulnerability Detection
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Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
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Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
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Automated Vulnerability Detection in Source Code Using Deep Representation Learning
inferredcites →https://doi.org/10.1109/icse48619.2023.00022openalex-snapshot
Data Quality for Software Vulnerability Datasets
inferredcites →https://doi.org/10.1109/icse48619.2023.00148openalex-snapshot
Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attention
inferredcites →https://doi.org/10.1109/icse48619.2023.00191openalex-snapshot
Vulnerability Detection with Graph Simplification and Enhanced Graph Representation Learning
inferredcites →https://doi.org/10.1109/icse48619.2023.00192openalex-snapshot
Does data sampling improve deep learning-based vulnerability detection? Yeas! and Nays!
inferredcites →https://doi.org/10.1109/icse48619.2023.00211openalex-snapshot
VULGEN: Realistic Vulnerability Generation Via Pattern Mining and Deep Learning
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Software Vulnerability Detection Using Deep Neural Networks: A Survey
inferredcites →https://doi.org/10.1109/mc.2012.345openalex-snapshot
Juliet 1.1 C/C++ and Java Test Suite
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Learning Graph Embedding With Adversarial Training Methods
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Web Application Vulnerability Prediction Using Hybrid Program Analysis and Machine Learning
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UltraVCS: Ultra-Fine-Grained Variable-Based Code Slicing for Automated Vulnerability Detection
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A Semisupervised Approach for Industrial Anomaly Detection via Self-Adaptive Clustering
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Tri-training: exploiting unlabeled data using three classifiers
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A Survey on Deep Semi-Supervised Learning
inferredcites →https://doi.org/10.1109/tnnls.2021.3133262openalex-snapshot
Graph-Based Class-Imbalance Learning With Label Enhancement
inferredcites →https://doi.org/10.1109/tnnls.2022.3152527openalex-snapshot
Learning From Noisy Labels With Deep Neural Networks: A Survey
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.2019.2949275openalex-snapshot
Improving Vulnerability Inspection Efficiency Using Active Learning
inferredcites →https://doi.org/10.1109/tse.2020.2986415openalex-snapshot
Better Data Labelling With EMBLEM (and how that Impacts Defect Prediction)
inferredcites →https://doi.org/10.1109/tse.2020.3031401openalex-snapshot
Identifying Self-Admitted Technical Debts With Jitterbug: A Two-Step Approach
inferredcites →https://doi.org/10.1109/tse.2021.3087402openalex-snapshot
Deep Learning Based Vulnerability Detection: Are We There Yet?
inferredcites →https://doi.org/10.1109/tse.2021.3135465openalex-snapshot
Making the most of small Software Engineering datasets with modern machine learning
inferredcites →https://doi.org/10.1109/tse.2023.3285910openalex-snapshot
CPVD: Cross Project Vulnerability Detection Based on Graph Attention Network and Domain Adaptation
inferredcites →https://doi.org/10.1109/tse.2023.3286586openalex-snapshot
Vulnerability Detection by Learning From Syntax-Based Execution Paths of Code
inferredcites →https://doi.org/10.1109/tse.2023.3340267openalex-snapshot
Meta-Path Based Attentional Graph Learning Model for Vulnerability Detection
inferredcites →https://doi.org/10.1109/tse.2024.3381235openalex-snapshot
MASTER: Multi-Source Transfer Weighted Ensemble Learning for Multiple Sources Cross-Project Defect Prediction
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Improve Computer-Aided Diagnosis With Machine Learning Techniques Using Undiagnosed Samples
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Cliff´s Delta Calculator: A non-parametric effect size program for two groups of observations
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Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering
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Software defect prediction using semi-supervised learning with dimension reduction
inferredcites →https://doi.org/10.1145/2365324openalex-snapshot
Proceedings of the 8th International Conference on Predictive Models in Software Engineering
inferredcites →https://doi.org/10.1145/279943openalex-snapshot
Proceedings of the eleventh annual conference on Computational learning theory
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Proceedings of the 38th International Conference on Software Engineering Companion
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Log clustering based problem identification for online service systems
inferredcites →https://doi.org/10.1145/2931037openalex-snapshot
Proceedings of the 25th International Symposium on Software Testing and Analysis
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Practitioners' expectations on automated fault localization
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Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security
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Proceedings of the 17th International Conference on Mining Software Repositories
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A C/C++ Code Vulnerability Dataset with Code Changes and CVE Summaries
inferredcites →https://doi.org/10.1145/3468264openalex-snapshot
Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
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Vulnerability detection with fine-grained interpretations
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Proceedings of the 44th International Conference on Software Engineering
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LiDetector : License Incompatibility Detection for Open Source Software
inferredcites →https://doi.org/10.1145/3522674openalex-snapshot
Code Structure–Guided Transformer for Source Code Summarization
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Proceedings of the 19th International Conference on Mining Software Repositories
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Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis
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Path-sensitive code embedding via contrastive learning for software vulnerability detection
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On the Significance of Category Prediction for Code-Comment Synchronization
inferredcites →https://doi.org/10.1145/3540250openalex-snapshot
Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
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Semi-supervised pre-processing for learning-based traceability framework on real-world software projects
inferredcites →https://doi.org/10.1145/3540250.3549165openalex-snapshot
The best of both worlds: integrating semantic features with expert features for defect prediction and localization
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I Know What You Are Searching for: Code Snippet Recommendation from Stack Overflow Posts
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Learning to Detect Memory-related Vulnerabilities
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HGVul: A Code Vulnerability Detection Method Based on Heterogeneous Source-Level Intermediate Representation
inferredcites →https://doi.org/10.1214/009053606000000425openalex-snapshot
On the Benjamini–Hochberg method
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Deep Neural Networks for Learning Graph Representations
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.139openalex-snapshot
CodeBERT: A Pre-Trained Model for Programming and Natural Languages
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VulSniper: Focus Your Attention to Shoot Fine-Grained Vulnerabilities
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Debiased Self-Training for Semi-Supervised Learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Learning to detect hardcoded secrets
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BMGANet: A deep learning model for source code vulnerability detection by integrating token-level and function-level features
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On the value of imbalance loss functions in enhancing deep learning-based vulnerability detection
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CIV: Leveraging causal subgraphs of vulnerability for noise reduction in vulnerability detection
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VulATMHD: Joint adaptive triplet mining and hybrid distillation for type-aware vulnerability classification
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Detecting duplicate vulnerability records across databases
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Investigating Evolutionary Characteristics of Deep Learning Framework Bugs in the Large Language Model Era
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Completion of Phrase-Based Concepts in Vulnerability Descriptions Through 1-Hop Relationship
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IFMA-VD: Boosting Vulnerability Detection with Inter-function Multilateral Association Insights
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Nistjson: Open-Source Tool for Json Processing and Software Vulnerabilities Analysis Based on Nist Nvd
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Continual Semi-Supervised Malware Detection
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