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VulRepair: a T5-based automated software 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/10.1007/978-3-030-17465-1_22openalex-snapshot
PhASAR: An Inter-procedural Static Analysis Framework for C/C++
inferredcites →https://doi.org/10.1007/s10664-017-9541-1openalex-snapshot
Are vulnerabilities discovered and resolved like other defects?
inferredcites →https://doi.org/10.1016/j.jss.2020.110817openalex-snapshot
A critical review on the evaluation of automated program repair systems
inferredcites →https://doi.org/10.1109/icmla.2018.00120openalex-snapshot
Automated Vulnerability Detection in Source Code Using Deep Representation Learning
inferredcites →https://doi.org/10.1109/icse.2019.00021openalex-snapshot
On Learning Meaningful Code Changes Via Neural Machine Translation
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/ms.2021.3072088openalex-snapshot
Actionable Analytics: Stop Telling Me What It Is; Please Tell Me What To Do
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/msr52588.2021.00055openalex-snapshot
Practitioners’ Perceptions of the Goals and Visual Explanations of Defect Prediction Models
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/tifs.2020.3044773openalex-snapshot
Combining Graph-Based Learning With Automated Data Collection for Code Vulnerability Detection
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.2018.2794977openalex-snapshot
The Impact of Automated Parameter Optimization on Defect Prediction 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.2019.2949275openalex-snapshot
Improving Vulnerability Inspection Efficiency Using Active Learning
inferredcites →https://doi.org/10.1109/tse.2020.2982385openalex-snapshot
An Empirical Study of Model-Agnostic Techniques for Defect Prediction Models
inferredcites →https://doi.org/10.1109/tse.2020.3023177openalex-snapshot
Predicting Defective Lines Using a Model-Agnostic Technique
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.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.2022.3156637openalex-snapshot
SeqTrans: Automatic Vulnerability Fix Via Sequence to Sequence Learning
inferredcites →https://doi.org/10.1145/1250734.1250739openalex-snapshot
Sound and precise analysis of web applications for injection vulnerabilities
inferredcites →https://doi.org/10.1145/1368088.1368112openalex-snapshot
Static detection of cross-site scripting vulnerabilities
inferredcites →https://doi.org/10.1145/2884781.2884857openalex-snapshot
Automated parameter optimization of classification techniques for defect prediction models
inferredcites →https://doi.org/10.1145/3180155.3180178openalex-snapshot
Spatio-temporal context reduction
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/10.1145/3475960.3475985openalex-snapshot
CVEfixes: automated collection of vulnerabilities and their fixes from open-source software
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-demos.6openalex-snapshot
Transformers: State-of-the-Art Natural Language Processing
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/10.18653/v1/2021.emnlp-main.685openalex-snapshot
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
inferredcites →https://doi.org/10.18653/v1/n18-2074openalex-snapshot
Self-Attention with Relative Position Representations
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/10.5281/zenodo.7080270openalex-snapshot
VulRepair: A T5-Based Automated Software Vulnerability Repair
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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PAVR: A Pre-Training Approach with Self-attention for Vulnerability Repair
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Parameter-Efficient Multi-classification Software Defect Detection Method Based on Pre-trained LLMs
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LineJLocRepair: A line-level method for Automated Vulnerability Repair based on joint training
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Enhancing blockchain network security: A targetable machine learning model for effective vulnerability repair
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kAPR: A coverage-guided, context-aware agent for automated repair of Linux kernel bugs
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GRACE: Empowering LLM-based software vulnerability detection with graph structure and in-context learning
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Unveiling the power of code pre-trained models in automated program repair: A systematic review
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R+R: Security Vulnerability Dataset Quality Is Critical
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A Comparative Study to Evaluate the Performance of Selective Models in Software Vulnerability Detection
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Beyond Bypass: Measuring Vulnerability Regression in LLM-Generated Security Patches
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Can GPT-O1 Kill All Bugs? An Evaluation of GPT-Family LLMs on QuixBugs
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Learning to Locate and Describe Vulnerabilities
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A Survey of Learning-based Automated Program Repair
inferred← citeshttps://doi.org/10.1145/3632746openalex-snapshot
Vision Transformer Inspired Automated Vulnerability Repair
inferred← citeshttps://doi.org/10.1145/3641540openalex-snapshot
On the Reliability and Explainability of Language Models for Program Generation
inferred← citeshttps://doi.org/10.1145/3643776openalex-snapshot
Refactoring to Pythonic Idioms: A Hybrid Knowledge-Driven Approach Leveraging Large Language Models
inferred← citeshttps://doi.org/10.1145/3643788.3648013openalex-snapshot
BOSS: A dataset to train ML-based systems to repair programs with out-of-bounds write flaws
inferred← citeshttps://doi.org/10.1145/3643991.3644919openalex-snapshot
Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study
inferred← citeshttps://doi.org/10.1145/3650212.3652108openalex-snapshot
FortifyPatch: Towards Tamper-Resistant Live Patching in Linux-Based Hypervisor
inferred← citeshttps://doi.org/10.1145/3650212.3680328openalex-snapshot
CREF: An LLM-Based Conversational Software Repair Framework for Programming Tutors
inferred← citeshttps://doi.org/10.1145/3650212.3680381openalex-snapshot
One Size Does Not Fit All: Multi-granularity Patch Generation for Better Automated Program Repair
inferred← citeshttps://doi.org/10.1145/3650212.3680384openalex-snapshot
AutoCodeRover: Autonomous Program Improvement
inferred← citeshttps://doi.org/10.1145/3658644.3690278openalex-snapshot
Fuzz to the Future: Uncovering Occluded Future Vulnerabilities via Robust Fuzzing
inferred← citeshttps://doi.org/10.1145/3661167.3661200openalex-snapshot
How the Training Procedure Impacts the Performance of Deep Learning-based Vulnerability Patching
inferred← citeshttps://doi.org/10.1145/3661167.3661210openalex-snapshot
Code Summarization without Direct Access to Code - Towards Exploring Federated LLMs for Software Engineering
inferred← citeshttps://doi.org/10.1145/3661167.3661281openalex-snapshot
Software Vulnerability Prediction in Low-Resource Languages: An Empirical Study of CodeBERT and ChatGPT
inferred← citeshttps://doi.org/10.1145/3663529.3663800openalex-snapshot
VinJ: An Automated Tool for Large-Scale Software Vulnerability Data Generation
inferred← citeshttps://doi.org/10.1145/3663529.3663846openalex-snapshot
Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4
inferred← citeshttps://doi.org/10.1145/3663529.3663861openalex-snapshot
X-Lifecycle Learning for Cloud Incident Management using LLMs
inferred← citeshttps://doi.org/10.1145/3663533.3664036openalex-snapshot
MoreFixes: A Large-Scale Dataset of CVE Fix Commits Mined through Enhanced Repository Discovery
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/10.1145/3664646.3664770openalex-snapshot
A Case Study of LLM for Automated Vulnerability Repair: Assessing Impact of Reasoning and Patch Validation Feedback
inferred← citeshttps://doi.org/10.1145/3671016.3672506openalex-snapshot
T-RAP: A Template-guided Retrieval-Augmented Vulnerability Patch Generation Approach
inferred← citeshttps://doi.org/10.1145/3678167openalex-snapshot
Automatically Recommend Code Updates: Are We There Yet?
inferred← citeshttps://doi.org/10.1145/3686803openalex-snapshot
Generative AI for Self-Adaptive Systems: State of the Art and Research Roadmap
inferred← citeshttps://doi.org/10.1145/3689217.3690622openalex-snapshot
How to Efficiently Manage Critical Infrastructure Vulnerabilities? Toward Large Code-graph Models
inferred← citeshttps://doi.org/10.1145/3689933.3690831openalex-snapshot
PenHeal: A Two-Stage LLM Framework for Automated Pentesting and Optimal Remediation
inferred← citeshttps://doi.org/10.1145/3691620.3695491openalex-snapshot
Spotting Code Mutation for Predictive Mutation Testing
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/10.1145/3691620.3695555openalex-snapshot
VulAdvisor: Natural Language Suggestion Generation for Software Vulnerability Repair
inferred← citeshttps://doi.org/10.1145/3696450openalex-snapshot
Evolving Paradigms in Automated Program Repair: Taxonomy, Challenges, and Opportunities
inferred← citeshttps://doi.org/10.1145/3699598openalex-snapshot
Exploring Automated Assertion Generation via Large Language Models
inferred← citeshttps://doi.org/10.1145/3705300openalex-snapshot
Distinguishing LLM-Generated from Human-Written Code by Contrastive Learning
inferred← citeshttps://doi.org/10.1145/3705306openalex-snapshot
ROSE: An IDE-Based Interactive Repair Framework for Debugging
inferred← citeshttps://doi.org/10.1145/3705310openalex-snapshot
EffFix: Efficient and Effective Repair of Pointer Manipulating Programs
inferred← citeshttps://doi.org/10.1145/3707454openalex-snapshot
Vulnerability Repair via Concolic Execution and Code Mutations
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/10.1145/3708821.3736220openalex-snapshot
Eradicating the Unseen: Detecting, Exploiting, and Remediating a Path Traversal Vulnerability across GitHub
inferred← citeshttps://doi.org/10.1145/3712190openalex-snapshot
AI for DevSecOps: A Landscape and Future Opportunities
inferred← citeshttps://doi.org/10.1145/3714393.3726486openalex-snapshot
A Dataset for Evaluating LLMs Vulnerability Repair Performance in Android Applications: Data/Toolset paper
inferred← citeshttps://doi.org/10.1145/3721977openalex-snapshot
A Survey of Source Code Representations for Machine Learning-Based Cybersecurity Tasks
inferred← citeshttps://doi.org/10.1145/3728930openalex-snapshot
REACCEPT: Automated Co-evolution of Production and Test Code Based on Dynamic Validation and Large Language Models
inferred← citeshttps://doi.org/10.1145/3728977openalex-snapshot
Fixing Outside the Box: Uncovering Tactics for Open-Source Security Issue Management
inferred← citeshttps://doi.org/10.1145/3735129openalex-snapshot
MORepair : Teaching LLMs to Repair Code via Multi-Objective Fine-Tuning
inferred← citeshttps://doi.org/10.1145/3735638openalex-snapshot
HDLdebugger: Streamlining HDL debugging with Large Language Models
inferred← citeshttps://doi.org/10.1145/3742876openalex-snapshot
Proceedings of the 24th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences
inferred← citeshttps://doi.org/10.1145/3742876.3742881openalex-snapshot
Comparative Analysis of Pre-trained Code Language Models for Automated Program Repair via Code Infill Generation
inferred← citeshttps://doi.org/10.1145/3744916.3773167openalex-snapshot
Rethinking the Capability of Fine-Tuned Language Models for Automated Vulnerability Repair
inferred← citeshttps://doi.org/10.1145/3744916.3773176openalex-snapshot
Exploring and Improving Real-World Vulnerability Data Generation via Prompting Large Language Models
inferred← citeshttps://doi.org/10.1145/3744916.3773260openalex-snapshot
INTENTFIX: Automated Logic Vulnerability Repair via LLM-Driven Intent Modeling
inferred← citeshttps://doi.org/10.1145/3744916.3787831openalex-snapshot
An Empirical Study of Fine-Grained Entity Relationships for Tracing Natural Language and Code Vulnerability Artifacts
inferred← citeshttps://doi.org/10.1145/3748647openalex-snapshot
Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey
inferred← citeshttps://doi.org/10.1145/3762183openalex-snapshot
Leveraging Reviewer Experience in Code Review Comment Generation
inferred← citeshttps://doi.org/10.1145/3769676openalex-snapshot
Large Language Models for Cyber Security: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1145/3771930openalex-snapshot
On the Evaluation of Large Language Models in Multilingual Vulnerability Repair
inferred← citeshttps://doi.org/10.1145/3773991openalex-snapshot
PanicFI: An Infrastructure for Fixing Panic Bugs in Real-World Rust Programs
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/10.1145/3786583.3786880openalex-snapshot
Fixing Security Vulnerabilities with Agentic AI in OSS-Fuzz
inferred← citeshttps://doi.org/10.1145/3786583.3786887openalex-snapshot
Intelligent Triage: Interpretable Incident Triage Workflow using LLM Extracted Triage Reasoning
inferred← citeshttps://doi.org/10.1145/3793638.3793639openalex-snapshot
Leveraging Transformers to Discover Software Vulnerabilities based on Source Code Slices
inferred← citeshttps://doi.org/10.1145/3793654.3793751openalex-snapshot
HYDRA: A Hybrid Heuristic-Guided Deep Representation Architecture for Predicting Latent Zero-Day Vulnerabilities in Patched Functions
inferred← citeshttps://doi.org/10.1145/3796522openalex-snapshot
A Systematic Literature Review of Parameter-Efficient Fine-Tuning for Large Code Models
inferred← citeshttps://doi.org/10.1145/3797896openalex-snapshot
Separate Bombs from Firecrackers: Intention-guided Vulnerability Assessment via LLM
inferred← citeshttps://doi.org/10.1145/3805760.3814903openalex-snapshot
SOSecure: The Wisdom of the Crowd for Safer AI-Generated Code
inferred← citeshttps://doi.org/10.1145/3818617openalex-snapshot
SGAgent: Suggestion-Guided LLM-Based Multi-Agent Framework for Repository-Level Software Repair
inferred← citeshttps://doi.org/10.1145/3832096openalex-snapshot
E4R-Reviewer: Effective and Explainable Automated Code Review via End-to-End Reasoning-Guided Alignment
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/10.1145/3832783.3837493openalex-snapshot
CiL-Agent: Compiler-in-the-Loop LLM Agent for Memory-Safe C Program Repair
inferred← citeshttps://doi.org/10.1145/3843776.3844674openalex-snapshot
Test Cases Considered Harmful
inferred← citeshttps://doi.org/10.1186/s42400-026-00618-yopenalex-snapshot
Sccodebert: an automatic vulnerability detection and repair method for smart contracts
inferred← citeshttps://doi.org/10.13189/csit.2022.100401openalex-snapshot
Secure Change Management Process: On the Effectiveness of DevSecOps
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/10.2139/ssrn.5983290openalex-snapshot
Tensor-based Graph Reinforcement Learning for Vulnerability Repair Recommendation
inferred← citeshttps://doi.org/10.2139/ssrn.6365614openalex-snapshot
SHARE-RAG: A Structure-Aware and Hypothesis-Guided Retrieval-Augmented
inferred← citeshttps://doi.org/10.2139/ssrn.6876912openalex-snapshot
SCARA: A Semantics-Constrained Autonomous Remediation Agent for Opaque Industrial Software Vulnerabilities
inferred← citeshttps://doi.org/10.2139/ssrn.6908622openalex-snapshot
Premise Chain Guided Retrieval of Relevant Historical Fixes for Automated Vulnerability Repair
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/10.23919/date69613.2026.11539570openalex-snapshot
VeriRepair: Toward Reliable LLM-Based RTL Repair via CoT-Supervised Multi-Objective Fine-Tuning and Hybrid Retrieval
inferred← citeshttps://doi.org/10.32388/bt8oczopenalex-snapshot
R+R: Security Vulnerability Dataset Quality Is Critical
inferred← citeshttps://doi.org/10.32388/xpjyhoopenalex-snapshot
Agent Centric Operating System – A Comprehensive Review and Outlook for Operating System
inferred← citeshttps://doi.org/10.3389/fcomp.2025.1655469openalex-snapshot
A dual perspective review on large language models and code verification
inferred← citeshttps://doi.org/10.3389/fpubh.2025.1551374openalex-snapshot
Using EEG technology to enhance performance measurement in physical education
inferred← citeshttps://doi.org/10.3390/ai6090216openalex-snapshot
Large Language Models in Cybersecurity: A Survey of Applications, Vulnerabilities, and Defense Techniques
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