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Vision Transformer Inspired Automated Vulnerability Repair
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-47426-3_54openalex-snapshot
Dual-Component Deep Domain Adaptation: A New Approach for Cross Project Software Vulnerability Detection
inferredcites →https://doi.org/10.1007/978-3-030-58452-8_13openalex-snapshot
End-to-End Object Detection with Transformers
inferredcites →https://doi.org/10.1007/s10664-023-10346-3openalex-snapshot
AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities
inferredcites →https://doi.org/10.1016/j.infsof.2023.107336openalex-snapshot
Syntax-aware on-the-fly code completion
inferredcites →https://doi.org/10.1109/ase51524.2021.9678763openalex-snapshot
PyExplainer: Explaining the Predictions of Just-In-Time Defect Models
inferredcites →https://doi.org/10.1109/cns48642.2020.9162237openalex-snapshot
A Machine Learning Approach to Classify Security Patches into Vulnerability Types
inferredcites →https://doi.org/10.1109/dsaa53316.2021.9564227openalex-snapshot
V2W-BERT: A Framework for Effective Hierarchical Multiclass Classification of Software Vulnerabilities
inferredcites →https://doi.org/10.1109/icse43902.2021.00107openalex-snapshot
CURE: Code-Aware Neural Machine Translation for Automatic Program Repair
inferredcites →https://doi.org/10.1109/ijcnn.2019.8851923openalex-snapshot
Deep Domain Adaptation for Vulnerable Code Function Identification
inferredcites →https://doi.org/10.1109/ijcnn52387.2021.9533907openalex-snapshot
Information-theoretic Source Code Vulnerability Highlighting
inferredcites →https://doi.org/10.1109/msr52588.2021.00049openalex-snapshot
JITLine: A Simpler, Better, Faster, Finer-grained Just-In-Time Defect Prediction
inferredcites →https://doi.org/10.1109/msr52588.2021.00063openalex-snapshot
Applying CodeBERT for Automated Program Repair of Java Simple Bugs
inferredcites →https://doi.org/10.1109/saner53432.2022.00114openalex-snapshot
VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatements
inferredcites →https://doi.org/10.1109/saner53432.2022.00121openalex-snapshot
Where Should I Look at? Recommending Lines that Reviewers Should Pay Attention To
inferredcites →https://doi.org/10.1109/saner56733.2023.00036openalex-snapshot
D-ACT: Towards Diff-Aware Code Transformation for Code Review Under a Time-Wise Evaluation
inferredcites →https://doi.org/10.1109/sp46215.2023.10179420openalex-snapshot
Examining Zero-Shot Vulnerability Repair with Large Language Models
inferredcites →https://doi.org/10.1109/tse.2019.2940179openalex-snapshot
SEQUENCER: Sequence-to-Sequence Learning for End-to-End Program Repair
inferredcites →https://doi.org/10.1109/tse.2022.3144348openalex-snapshot
DeepLineDP: Towards a Deep Learning Approach for Line-Level Defect Prediction
inferredcites →https://doi.org/10.1109/tse.2022.3147265openalex-snapshot
Neural Transfer Learning for Repairing Security Vulnerabilities in C Code
inferredcites →https://doi.org/10.1109/tse.2022.3158252openalex-snapshot
GPT2SP: A Transformer-Based Agile Story Point Estimation Approach
inferredcites →https://doi.org/10.1109/tse.2023.3305244openalex-snapshot
VulExplainer: A Transformer-Based Hierarchical Distillation for Explaining Vulnerability Types
inferredcites →https://doi.org/10.1145/3379597.3387501openalex-snapshot
A C/C++ Code Vulnerability Dataset with Code Changes and CVE Summaries
inferredcites →https://doi.org/10.1145/3395363.3397369openalex-snapshot
CoCoNuT: combining context-aware neural translation models using ensemble for program repair
inferredcites →https://doi.org/10.1145/3468264.3468597openalex-snapshot
Vulnerability detection with fine-grained interpretations
inferredcites →https://doi.org/10.1145/3475960.3475985openalex-snapshot
CVEfixes: automated collection of vulnerabilities and their fixes from open-source software
inferredcites →https://doi.org/10.1145/3540250.3549098openalex-snapshot
VulRepair: a T5-based automated software vulnerability repair
inferredcites →https://doi.org/10.1145/3540250.3549119openalex-snapshot
CommentFinder: a simpler, faster, more accurate code review comments recommendation
inferredcites →https://doi.org/10.1145/3678167openalex-snapshot
Automatically Recommend Code Updates: Are We There Yet?
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.139openalex-snapshot
CodeBERT: A Pre-Trained Model for Programming and Natural Languages
inferredcites →https://doi.org/10.3115/1610075openalex-snapshot
Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing - EMNLP '06
inferredcites →https://doi.org/10.48550/arxiv.1310.4546openalex-snapshot
Distributed Representations of Words and Phrases and their Compositionality
inferredcites →https://doi.org/10.48550/arxiv.1910.10683openalex-snapshot
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
inferredcites →https://doi.org/10.48550/arxiv.2209.10406openalex-snapshot
Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle
inferredcites →https://doi.org/10.48550/arxiv.2209.10414openalex-snapshot
Statement-Level Vulnerability Detection: Learning Vulnerability Patterns Through Information Theory and Contrastive Learning
inferredcites →https://doi.org/10.48550/arxiv.2302.10352openalex-snapshot
A3Test: Assertion-Augmented Automated Test Case Generation
inferredcites →https://doi.org/10.48550/arxiv.2306.06109openalex-snapshot
Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-032-23347-9_1openalex-snapshot
Security Built-In, not Bolted-On: A Structured Taxonomy for Early Secure Software Development
inferred← citeshttps://doi.org/10.1007/s10515-025-00553-1openalex-snapshot
BRMDS: an LLM-based multi-dimensional summary generation approach for bug reports
inferred← citeshttps://doi.org/10.1007/s10664-026-10803-9openalex-snapshot
An exploratory study on fine-tuning large language models for secure code generation
inferred← citeshttps://doi.org/10.1007/s11432-025-4670-0openalex-snapshot
A survey on large language models for software engineering
inferred← citeshttps://doi.org/10.1016/j.future.2024.107671openalex-snapshot
LineJLocRepair: A line-level method for Automated Vulnerability Repair based on joint training
inferred← citeshttps://doi.org/10.1016/j.ijin.2025.11.005openalex-snapshot
Enhancing blockchain network security: A targetable machine learning model for effective vulnerability repair
inferred← citeshttps://doi.org/10.1016/j.jss.2025.112528openalex-snapshot
Enhancing vulnerability repair through the extraction and matching of repair patterns
inferred← citeshttps://doi.org/10.1016/j.jss.2025.112544openalex-snapshot
Learning never stops: Improving software vulnerability type identification via incremental learning
inferred← citeshttps://doi.org/10.1016/j.jss.2026.113015openalex-snapshot
Unveiling the power of code pre-trained models in automated program repair: A systematic review
inferred← citeshttps://doi.org/10.1016/j.neunet.2024.107067openalex-snapshot
Promises and perils of using Transformer-based models for SE research
inferred← citeshttps://doi.org/10.1109/acsac63791.2024.00086openalex-snapshot
R+R: Security Vulnerability Dataset Quality Is Critical
inferred← citeshttps://doi.org/10.1109/dsd67783.2025.00087openalex-snapshot
LLM4CVE: Enabling Iterative Automated Vulnerability Repair with Large Language Models
inferred← citeshttps://doi.org/10.1109/icicke65317.2025.11136289openalex-snapshot
AI-Driven Open Source Component Security Analysis and Intelligent Vulnerability Prediction Model
inferred← citeshttps://doi.org/10.1109/iscait64916.2025.11010430openalex-snapshot
A Mask Optimization Method for Automated Vulnerability Repair
inferred← citeshttps://doi.org/10.1109/saner67736.2026.00038openalex-snapshot
VULTERMINATOR: Bringing Back Template-Based Automated Repair for Fixing Java Vulnerabilities
inferred← citeshttps://doi.org/10.1109/tse.2026.3688237openalex-snapshot
Does AI Code Review Lead to Code Changes? A Case Study of GitHub Actions
inferred← citeshttps://doi.org/10.1142/s0218194025500731openalex-snapshot
PCRepair: A Context-Aware Template-Based Approach for Automated Program Repair
inferred← citeshttps://doi.org/10.1145/3641540openalex-snapshot
On the Reliability and Explainability of Language Models for Program Generation
inferred← citeshttps://doi.org/10.1145/3664602openalex-snapshot
Deep Domain Adaptation With Max-Margin Principle for Cross-Project Imbalanced Software Vulnerability Detection
inferred← citeshttps://doi.org/10.1145/3678167openalex-snapshot
Automatically Recommend Code Updates: Are We There Yet?
inferred← citeshttps://doi.org/10.1145/3691620.3695508openalex-snapshot
iSMELL: Assembling LLMs with Expert Toolsets for Code Smell Detection and Refactoring
inferred← citeshttps://doi.org/10.1145/3707457openalex-snapshot
A Catalog of Data Smells for Coding Tasks
inferred← citeshttps://doi.org/10.1145/3708522openalex-snapshot
Large Language Model for Vulnerability Detection and Repair: Literature Review and the Road Ahead
inferred← citeshttps://doi.org/10.1145/3708821.3736208openalex-snapshot
SAFE: A Novel Approach For Software Vulnerability Detection from Enhancing The Capability of Large Language Models
inferred← citeshttps://doi.org/10.1145/3712190openalex-snapshot
AI for DevSecOps: A Landscape and Future Opportunities
inferred← citeshttps://doi.org/10.1145/3744916.3787781openalex-snapshot
Software Vulnerability Management in the Era of Artificial Intelligence: An Industry Perspective
inferred← citeshttps://doi.org/10.1145/3762183openalex-snapshot
Leveraging Reviewer Experience in Code Review Comment Generation
inferred← citeshttps://doi.org/10.1145/3765752openalex-snapshot
On-the-Fly Generation-Quality Enhancement of Deep Code Models via Model Collaboration
inferred← citeshttps://doi.org/10.1145/3771930openalex-snapshot
On the Evaluation of Large Language Models in Multilingual Vulnerability Repair
inferred← citeshttps://doi.org/10.1145/3786582.3786847openalex-snapshot
Not All Input Helps: What Information Should We Feed to LLMs for Vulnerability Repair?
inferred← citeshttps://doi.org/10.1145/3796512openalex-snapshot
Fix Pattern-Aware Vulnerability Patch Generation via In-Context Learning
inferred← citeshttps://doi.org/10.1145/3820756.3844916openalex-snapshot
Minimizing Vulnerability Prevalence in Maven Dependencies via Answer Set Programming
inferred← citeshttps://doi.org/10.1145/3832193openalex-snapshot
Just Old Wine in a New Bottle: Improving Vulnerability Repair Robustness to Combat Homologous but Heterogeneous Vulnerabilities
inferred← citeshttps://doi.org/10.1145/3832783.3834364openalex-snapshot
Are Reasoning Traces Faithful in LLM-Based Code Vulnerability Detection?
inferred← citeshttps://doi.org/10.1186/s42400-025-00518-7openalex-snapshot
Source code vulnerability detection based on deep learning: a review
inferred← citeshttps://doi.org/10.2139/ssrn.5382161openalex-snapshot
A Targetable Machine Learning Model for Effective Vulnerability Repair in Smart Contracts
inferred← citeshttps://doi.org/10.23919/date69613.2026.11539456openalex-snapshot
Enhance Language Model-based Repair for Memory-related Vulnerabilities via Knowledge-and Semantic-guided Analysis
inferred← citeshttps://doi.org/10.32388/bt8oczopenalex-snapshot
R+R: Security Vulnerability Dataset Quality Is Critical
inferred← citeshttps://doi.org/10.3389/fcomp.2025.1655469openalex-snapshot
A dual perspective review on large language models and code verification
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Generative Artificial Intelligence in Supply Chain: Review, Trends, and Future Directions
inferred← citeshttps://doi.org/10.4018/979-8-2600-0512-5.ch002openalex-snapshot
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