DeepInfer: Deep Type Inference from Smart Contract Bytecode

Zhao, Kunsong; Li, Zihao; Li, Jianfeng; Ye, He; Luo, Xiapu; Chen, Ting

doi:10.1145/3611643.3616343

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Enginee 2023

DOI: 10.1145/3611643.3616343

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DeepInfer: Deep Type Inference from Smart Contract Bytecode

Kunsong Zhao,

Zihao Li,

Jianfeng Li

et al.

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Cited by 6 publications

References 44 publications

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Demystifying DeFi MEV Activities in Flashbots Bundle

Li,

et al. 2023

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security

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Demystifying DeFi MEV Activities in Flashbots Bundle

Li,

et al. 2023

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security

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Are We There Yet? Unraveling the State-of-the-Art Smart Contract Fuzzers

Wu,

Li,

Yan

et al. 2024

Proceedings of the IEEE/ACM 46th International Conference on Software Engineering

Self Cite

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Given the growing importance of smart contracts in various applications, ensuring their security and reliability is critical. Fuzzing, an effective vulnerability detection technique, has recently been widely applied to smart contracts. Despite numerous studies, a systematic investigation of smart contract fuzzing techniques remains lacking. In this paper, we fill this gap by: 1) providing a comprehensive review of current research in contract fuzzing, and 2) conducting an in-depth empirical study to evaluate state-of-the-art contract fuzzers' usability. To guarantee a fair evaluation, we employ a carefully-labeled benchmark and introduce a set of pragmatic performance metrics, evaluating fuzzers from five complementary perspectives. Based on our findings, we provide direction for the future research and development of contract fuzzers.

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Following the “Thread”: Toward Finding Manipulatable Bottlenecks in Blockchain Clients

Wu,

Li,

Zhou

et al. 2024

Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis

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DeepInfer: Deep Type Inference from Smart Contract Bytecode

Cited by 6 publications

References 44 publications

Demystifying DeFi MEV Activities in Flashbots Bundle

Demystifying DeFi MEV Activities in Flashbots Bundle

Are We There Yet? Unraveling the State-of-the-Art Smart Contract Fuzzers

Following the “Thread”: Toward Finding Manipulatable Bottlenecks in Blockchain Clients

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