- Maintenance-Related Concerns for Post-deployed Ethereum Smar Contract Development: Issues, Techniques, and Future Challenges (EMSE 21).
- Automating User Notice Generation for Smart Contract Functions (ASE 21)
- Empirical Evaluation of Smart Contract Testing: What Is the Best Choice? (ISSTA 21)
- Bitcontracts: Supporting Smart Contracts in Legacy Blockchains (NDSS 21)
- A Novel Machine Learning-Based Analysis Model for Smart Contract Vulnerability (SCN 21)
- Peculiar: Smart Contract Vulnerability Detection Based on Crucial Data Flow Graph and Pre-training Techniques（ISSRE 21）
- Making smart contract development more secure and easier （FSE'21）
- Investigation on Vulnerabilities Location in Solidity Smart Contracts (BLOCKCHAIN 2021)
- SolDetector: Detect Defects Based on Knowledge Graph of Solidity Smart Contract (SEKE 2021)
- VSCL: Automating Vulnerability Detection in Smart Contracts with Deep Learning. (IEEE ICBC 2021)
- Landscape estimation of solidity version usage on Ethereum via version identification （International Journal of Intelligent Systems. 2021）
- Blockchain-enabled fraud discovery through abnormal smart contractdetection on Ethereum（FGCS'21）
- SMARTIAN: Enhancing Smart Contract Fuzzing with Static and Dynamic Analyses（ASE'21）
- DeeSCVHunter: A Deep Learning-Based Framework for Smart Contract Vulnerability Detection（IJCNN）
- Testing Smart Contracts: Which Technique Performs Best? （ESEM'21）
- Pluto: Exposing Vulnerabilities in Inter-Contract Scenarios（TSE'21）
- SMARTGIFT: Learning to Generate Practical Inputs for Testing Smart Contracts（ESEM'21）
- Why Do Smart Contracts Self-Destruct? Investigating the Selfdestruct Function on Ethereum（TOSEM‘21’）
- SigRec: Automatic Recovery of Function Signatures in Smart Contracts（TSE'21）
- Aroc: An Automatic Repair Framework for On-chain Smart Contracts（TSE'21）