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Smart Contract Code Repair Recommendation based on Reinforcement Learning and Multi-metric Optimization

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What this work says

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

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Metallaxis‐FL: mutation‐based fault localization

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Deep Reinforcement Learning: An Overview

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Pharaoh: A Beam Search Decoder for Phrase-Based Statistical Machine Translation Models

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iMashup: a mashup-based framework for service composition

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The dependence of Cohen's kappa on the prevalence does not matter

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A critical professional ethical analysis of Non-Fungible Tokens (NFTs)

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A review on the attention mechanism of deep learning

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A survey of robot learning from demonstration

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The Analysis of Panel Data Under a Markov Assumption

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Poly Network attack underlines growing DeFi risks

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Automated Generation of Test Cases for Smart Contract Security Analyzers

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Systematic Review of Security Vulnerabilities in Ethereum Blockchain Smart Contract

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Inferring Program Transformations From Singular Examples via Big Code

inferredcites →https://doi.org/10.1109/ase.2019.00136openalex-snapshot

MuSC: A Tool for Mutation Testing of Ethereum Smart Contract

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Software-Defined Infrastructure for Decentralized Data Lifecycle Governance: Principled Design and Open Challenges

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The DAO attack paradoxes in propositional logic

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BLOCKEYE: Hunting for DeFi Attacks on Blockchain

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A systematic study of automated program repair: Fixing 55 out of 105 bugs for $8 each

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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/icsme.2018.00037openalex-snapshot

A Closer Look at Real-World Patches

inferredcites →https://doi.org/10.1109/iwbose.2018.8327567openalex-snapshot

Smart contracts vulnerabilities: a call for blockchain software engineering?

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A Blockchain-Based Decentralized Federated Learning Framework with Committee Consensus

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Towards Generating Cost-Effective Test-Suite for Ethereum Smart Contract

inferredcites →https://doi.org/10.1109/saner48275.2020.9054825openalex-snapshot

SMARTSHIELD: Automatic Smart Contract Protection Made Easy

inferredcites →https://doi.org/10.1109/sp40001.2021.00057openalex-snapshot

SGUARD: Towards Fixing Vulnerable Smart Contracts Automatically

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A Location-Based Factorization Machine Model for Web Service QoS Prediction

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Web Service QoS Prediction via Collaborative Filtering: A Survey

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An Analysis and Survey of the Development of Mutation Testing

inferredcites →https://doi.org/10.1109/tse.2011.104openalex-snapshot

GenProg: A Generic Method for Automatic Software Repair

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Nopol: Automatic Repair of Conditional Statement Bugs in Java Programs

inferredcites →https://doi.org/10.1109/tse.2017.2755013openalex-snapshot

Automatic Software Repair: A Survey

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Predictive Mutation Testing

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Automatic Detection and Repair Recommendation of Directive Defects in Java API Documentation

inferredcites →https://doi.org/10.1109/tse.2019.2942301openalex-snapshot

Smart Contract Development: Challenges and Opportunities

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Checking Smart Contracts With Structural Code Embedding

inferredcites →https://doi.org/10.1109/tse.2020.2989002openalex-snapshot

Defining Smart Contract Defects on Ethereum

inferredcites →https://doi.org/10.1109/tse.2021.3123170openalex-snapshot

Aroc: An Automatic Repair Framework for On-Chain Smart Contracts

inferredcites →https://doi.org/10.1109/wetseb.2019.00008openalex-snapshot

Slither: A Static Analysis Framework for Smart Contracts

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Javalanche

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On the localness of software

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An analysis of patch plausibility and correctness for generate-and-validate patch generation systems

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On the "naturalness" of buggy code

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Making Smart Contracts Smarter

inferredcites →https://doi.org/10.1145/2993600.2993611openalex-snapshot

Formal Verification of Smart Contracts

inferredcites →https://doi.org/10.1145/3106237.3106309openalex-snapshot

S3: syntax- and semantic-guided repair synthesis via programming by examples

inferredcites →https://doi.org/10.1145/3180155.3180233openalex-snapshot

Context-aware patch generation for better automated program repair

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ReGuard

inferredcites →https://doi.org/10.1145/3213846.3213871openalex-snapshot

Shaping program repair space with existing patches and similar code

inferredcites →https://doi.org/10.1145/3238147.3238177openalex-snapshot

ContractFuzzer: fuzzing smart contracts for vulnerability detection

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Securify

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Practical program repair via bytecode mutation

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TBar: revisiting template-based automated program repair

inferredcites →https://doi.org/10.1145/3318162openalex-snapshot

Automated program repair

inferredcites →https://doi.org/10.1145/3319535.3363230openalex-snapshot

Learning to Fuzz from Symbolic Execution with Application to Smart Contracts

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Automated patch correctness assessment

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Getafix: learning to fix bugs automatically

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sFuzz

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An Improved Gas Efficient Library for Securing IoT Smart Contracts Against Arithmetic Vulnerabilities

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How effective are smart contract analysis tools? evaluating smart contract static analysis tools using bug injection

inferredcites →https://doi.org/10.1145/3402450openalex-snapshot

Smart Contract Repair

inferredcites →https://doi.org/10.1145/3468264.3468544openalex-snapshot

A syntax-guided edit decoder for neural program repair

inferredcites →https://doi.org/10.1145/3505247openalex-snapshot

Context-Aware Code Change Embedding for Better Patch Correctness Assessment

inferredcites →https://doi.org/10.1145/3510003.3510222openalex-snapshot

Neural program repair with execution-based backpropagation

inferredcites →https://doi.org/10.1145/3551349.3556926openalex-snapshot

SelfAPR: Self-supervised Program Repair with Test Execution Diagnostics

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The Complexity of Markov Decision Processes

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Attention-based encoder-decoder model for answer selection in question answering

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Security Analysis Methods on Ethereum Smart Contract Vulnerabilities: A Survey

inferredcites →https://doi.org/10.48550/arxiv.2108.10071openalex-snapshot

Elysium: Context-Aware Bytecode-Level Patching to Automatically Heal Vulnerable Smart Contracts

inferredcites →https://doi.org/10.60882/cispa.24612708openalex-snapshot

teEther: Gnawing at Ethereum to Automatically Exploit Smart Contracts

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Advances in Neural Information Processing Systems 14

What points at this work

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

inferred← citeshttps://doi.org/10.1016/j.bcra.2025.100402openalex-snapshot

How far should we go away from smart contract to smarter contractor? A systematic review

inferred← citeshttps://doi.org/10.1016/j.jss.2024.112107openalex-snapshot

ReenRepair: Automatic and semantic equivalent repair of reentrancy in smart contracts

inferred← citeshttps://doi.org/10.1109/ase63991.2025.00140openalex-snapshot

Leveraging Mixture-of-Experts Framework for Smart Contract Vulnerability Repair with Large Language Model

inferred← citeshttps://doi.org/10.1109/icassp55912.2026.11463459openalex-snapshot

FlowMemRep: Automated Workflow with Memory-Aware for Smart Contract Vulnerability Repair Using LLMs

inferred← citeshttps://doi.org/10.1109/icpads67057.2025.11323070openalex-snapshot

A Reinforcement Learning-Based Approach for Storage Assignment in Coded Blockchain

inferred← citeshttps://doi.org/10.1109/prdc67299.2025.00030openalex-snapshot

Automated Vulnerability Repair of Obfuscated and Non-Obfuscated Smart Contracts Using Large Language Models

inferred← citeshttps://doi.org/10.1109/tdsc.2025.3579124openalex-snapshot

Blockchain-Assisted Searchable Integrity Auditing for Large-Scale Similarity Data With Arbitration

inferred← citeshttps://doi.org/10.1109/tnse.2025.3583926openalex-snapshot

ContractScanner: Detecting and Localizing Vulnerabilities of Smart Contracts via Graph-Based Semantic Modeling of Source Code

inferred← citeshttps://doi.org/10.1109/tse.2025.3618123openalex-snapshot

Do Automated Fixes Truly Mitigate Smart Contract Exploits?

inferred← citeshttps://doi.org/10.1145/3691620.3695292openalex-snapshot

Oracle-Guided Vulnerability Diversity and Exploit Synthesis of Smart Contracts Using LLMs

inferred← citeshttps://doi.org/10.1145/3719004openalex-snapshot

Characterizing Smart Contract Evolution

inferred← citeshttps://doi.org/10.1145/3744709openalex-snapshot

Anomaly Detection Services for Blockchain Smart Contracts with Unknown Vulnerabilities

inferred← citeshttps://doi.org/10.1145/3768292.3770397openalex-snapshot

Curriculum-Guided Reinforcement Learning for Synthesizing Gas-Efficient Financial Derivatives Contracts

inferred← citeshttps://doi.org/10.1145/3769013openalex-snapshot

Blockchain Smart Contract Security: Threats and Mitigation Strategies in a Lifecycle Perspective

inferred← citeshttps://doi.org/10.1145/3843776.3844671openalex-snapshot

RAWL: Retrieval-Augmented Smart Contract Repair using Weisfeiler-Lehman-Based Retrieval

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/10.3390/e27030294openalex-snapshot

ESfix: An Embedded Program Repair Tool for Effective Removal of Concurrency Defects

inferred← citeshttps://doi.org/10.3390/electronics13193942openalex-snapshot

Automated Repair of Smart Contract Vulnerabilities: A Systematic Literature Review

inferred← citeshttps://doi.org/10.3390/fi17040183openalex-snapshot

Securing Decentralized Ecosystems: A Comprehensive Systematic Review of Blockchain Vulnerabilities, Attacks, and Countermeasures and Mitigation Strategies

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