{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:30:13Z","timestamp":1792787413756,"version":"4.5.0"},"publisher-location":"New York, NY, USA","reference-count":72,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T00:00:00Z","timestamp":1665360000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Nature Science Foundation of China","award":["62002034),"],"award-info":[{"award-number":["62002034),"]}]},{"name":"National Key Research and Development Project of China","award":["2020YFB1711900"],"award-info":[{"award-number":["2020YFB1711900"]}]},{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing","doi-asserted-by":"publisher","award":["cstc2021jcyj-msxmX0538"],"award-info":[{"award-number":["cstc2021jcyj-msxmX0538"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Major Key Project of PCL"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,10]]},"DOI":"10.1145\/3551349.3560428","type":"proceedings-article","created":{"date-parts":[[2023,1,5]],"date-time":"2023-01-05T20:43:54Z","timestamp":1672951434000},"page":"1-13","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":66,"title":["Reentrancy Vulnerability Detection and Localization: A Deep Learning Based Two-phase Approach"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4504-6806","authenticated-orcid":false,"given":"Zhuo","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Big Data &amp; Software, Chongqing University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Lei","sequence":"additional","affiliation":[{"name":"School of Big Data &amp; Software, Chongqing University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Big Data &amp; Software, Chongqing University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Computer, National University of Defense Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiachi","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Sun Yat-sen University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shangwen","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer, National University of Defense Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoguang","family":"Mao","sequence":"additional","affiliation":[{"name":"College of Computer, National University of Defense Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,1,5]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"The Bonferonni and \u0160id\u00e1k Corrections for Multiple Comparisons. Encyclopedia of measurement and statistics 3","author":"Abdi Herv\u00e9","year":"2007","unstructured":"Herv\u00e9 Abdi. 2007. The Bonferonni and \u0160id\u00e1k Corrections for Multiple Comparisons. Encyclopedia of measurement and statistics 3 (2007), 103\u2013107."},{"key":"e_1_3_2_1_2_1","unstructured":"Miltiadis Allamanis Marc Brockschmidt and Mahmoud Khademi. 2017. Learning to represent programs with graphs. arXiv preprint arXiv:1711.00740(2017)."},{"key":"e_1_3_2_1_3_1","volume-title":"Proceedings of the International Conference on Learning Representations.","author":"Alon Uri","year":"2018","unstructured":"Uri Alon, Shaked Brody, Omer Levy, and Eran Yahav. 2018. code2seq: Generating Sequences from Structured Representations of Code. In Proceedings of the International Conference on Learning Representations."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2993600.2993611"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3375624"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"B. Boehmke and B. Greenwell. 2019. Interpretable Machine Learning. Hands-On Machine Learning with R.","DOI":"10.1201\/9780367816377"},{"key":"e_1_3_2_1_7_1","first-page":"520","article-title":"[Defining the Ethereum Virtual Machine for Interactive Theorem Provers. 10.1007\/978-3-319-70278-0","volume":"33","author":"Brenner M.","year":"2017","unstructured":"M. Brenner, K. Rohloff, J. Bonneau, A. Miller, Pya Ryan, V. Teague, A. Bracciali, M. Sala, F. Pintore, and M. Jakobsson. 2017. [Defining the Ethereum Virtual Machine for Interactive Theorem Provers. 10.1007\/978-3-319-70278-0, Chapter 33 (2017), 520\u2013535.","journal-title":"Chapter"},{"key":"e_1_3_2_1_8_1","unstructured":"Luca Buratti Saurabh Pujar Mihaela Bornea Scott McCarley Yunhui Zheng Gaetano Rossiello Alessandro Morari Jim Laredo Veronika Thost Yufan Zhuang 2020. Exploring software naturalness through neural language models. arXiv preprint arXiv:2006.12641(2020)."},{"key":"e_1_3_2_1_9_1","unstructured":"Vitalik Buterin 2013. Ethereum white paper. GitHub repository 1(2013) 22\u201323."},{"key":"e_1_3_2_1_10_1","volume-title":"Introduction to modern statistical. Mechanics","author":"Chandler David","year":"1987","unstructured":"David Chandler. 1987. Introduction to modern statistical. Mechanics. Oxford University Press, Oxford, UK 5 (1987)."},{"key":"e_1_3_2_1_11_1","volume-title":"Computer Graphics Forum, Vol.\u00a039","author":"Chatzimparmpas Angelos","unstructured":"Angelos Chatzimparmpas, Rafael\u00a0Messias Martins, Ilir Jusufi, Kostiantyn Kucher, Fabrice Rossi, and Andreas Kerren. 2020. The state of the art in enhancing trust in machine learning models with the use of visualizations. In Computer Graphics Forum, Vol.\u00a039. Wiley Online Library, 713\u2013756."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2020.2989002"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/SOSE.2018.00036"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Gregory\u00a0W. Corder and Dale\u00a0I. Foreman. 2010. Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach. Vol.\u00a078. International Statistical Review. 451\u2013452 pages.","DOI":"10.1111\/j.1751-5823.2010.00122_6.x"},{"key":"e_1_3_2_1_15_1","volume-title":"Introducing Ethereum and solidity. Vol.\u00a0318","author":"Dannen Chris","unstructured":"Chris Dannen. 2017. Introducing Ethereum and solidity. Vol.\u00a0318. Springer."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/QSIC.2010.80"},{"key":"e_1_3_2_1_17_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805(2018).","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805(2018)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/SERA.2019.8886793"},{"key":"e_1_3_2_1_19_1","unstructured":"Finale Doshi-Velez and Been Kim. 2017. Towards a rigorous science of interpretable machine learning. arXiv preprint arXiv:1702.08608(2017)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Finale Doshi-Velez Mason Kortz Ryan Budish Chris Bavitz Sam Gershman David O\u2019Brien Kate Scott Stuart Schieber James Waldo David Weinberger 2017. Accountability of AI under the law: The role of explanation. arXiv preprint arXiv:1711.01134(2017).","DOI":"10.2139\/ssrn.3064761"},{"key":"e_1_3_2_1_21_1","unstructured":"M. Du N. Liu and X. Hu. 2018. Techniques for Interpretable Machine Learning. (2018)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3359786"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/WETSEB.2019.00008"},{"key":"e_1_3_2_1_24_1","volume-title":"Codebert: A pre-trained model for programming and natural languages. arXiv preprint arXiv:2002.08155(2020).","author":"Feng Zhangyin","year":"2020","unstructured":"Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, 2020. Codebert: A pre-trained model for programming and natural languages. arXiv preprint arXiv:2002.08155(2020)."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3324884.3415298"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSME.2019.00067"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-89722-6_10"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSME.2018.00066"},{"key":"e_1_3_2_1_29_1","volume-title":"Graphcodebert: Pre-training code representations with data flow. arXiv preprint arXiv:2009.08366(2020).","author":"Guo Daya","year":"2020","unstructured":"Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang, Shujie Liu, Long Zhou, Nan Duan, Alexey Svyatkovskiy, Shengyu Fu, 2020. Graphcodebert: Pre-training code representations with data flow. arXiv preprint arXiv:2009.08366(2020)."},{"key":"e_1_3_2_1_30_1","volume-title":"International conference on learning representations.","author":"Hellendoorn J","year":"2019","unstructured":"Vincent\u00a0J Hellendoorn, Charles Sutton, Rishabh Singh, Petros Maniatis, and David Bieber. 2019. Global relational models of source code. In International conference on learning representations."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/CSF.2018.00022"},{"key":"e_1_3_2_1_32_1","unstructured":"Joran Honig. 2022. tree-sitter-solidity. https:\/\/github.com\/JoranHonig\/tree-sitter-solidity."},{"key":"e_1_3_2_1_33_1","unstructured":"Hamel Husain Ho-Hsiang Wu Tiferet Gazit Miltiadis Allamanis and Marc Brockschmidt. 2019. Codesearchnet challenge: Evaluating the state of semantic code search. arXiv preprint arXiv:1909.09436(2019)."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","unstructured":"Suzana Ili\u0107 Edison Marrese-Taylor Jorge\u00a0A Balazs and Yutaka Matsuo. 2018. Deep contextualized word representations for detecting sarcasm and irony. arXiv preprint arXiv:1809.09795(2018).","DOI":"10.18653\/v1\/W18-6202"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3238147.3238177"},{"key":"e_1_3_2_1_36_1","volume-title":"ZEUS: Analyzing Safety of Smart Contracts.. In Ndss. 1\u201312.","author":"Kalra Sukrit","year":"2018","unstructured":"Sukrit Kalra, Seep Goel, Mohan Dhawan, and Subodh Sharma. 2018. ZEUS: Analyzing Safety of Smart Contracts.. In Ndss. 1\u201312."},{"key":"e_1_3_2_1_37_1","unstructured":"Aditya Kanade Petros Maniatis Gogul Balakrishnan and Kensen Shi. 2019. Pre-trained contextual embedding of source code. (2019)."},{"key":"e_1_3_2_1_38_1","volume-title":"Scelmo: Source code embeddings from language models. arXiv preprint arXiv:2004.13214(2020).","author":"Karampatsis Rafael-Michael","year":"2020","unstructured":"Rafael-Michael Karampatsis and Charles Sutton. 2020. Scelmo: Source code embeddings from language models. arXiv preprint arXiv:2004.13214(2020)."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE43902.2021.00026"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/2931037.2931051"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3293882.3330574"},{"key":"e_1_3_2_1_42_1","volume-title":"Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692(2019).","author":"Liu Yinhan","year":"2019","unstructured":"Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. Roberta: A robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692(2019)."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3095196"},{"key":"e_1_3_2_1_44_1","unstructured":"Ting-gan Lua. 2022. tree-sitter. https:\/\/tree-sitter.github.io\/tree-sitter\/."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978309"},{"key":"e_1_3_2_1_46_1","unstructured":"Christoph Molnar. 2020. Interpretable machine learning. Lulu. com."},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE.2019.00133"},{"key":"e_1_3_2_1_48_1","unstructured":"B Mueller. 2017. Mythril-Reversing and bug hunting framework for the Ethereum blockchain."},{"key":"e_1_3_2_1_49_1","volume-title":"Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review(2008), 21260.","author":"Nakamoto Satoshi","year":"2008","unstructured":"Satoshi Nakamoto. 2008. Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review(2008), 21260."},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/2001420.2001445"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2969429"},{"key":"e_1_3_2_1_52_1","unstructured":"Alec Radford Karthik Narasimhan Tim Salimans and Ilya Sutskever. 2018. Improving language understanding by generative pre-training. (2018)."},{"key":"e_1_3_2_1_53_1","unstructured":"Colin Raffel Noam Shazeer Adam Roberts Katherine Lee Sharan Narang Michael Matena Yanqi Zhou Wei Li and Peter\u00a0J Liu. 2019. Exploring the limits of transfer learning with a unified text-to-text transformer. arXiv preprint arXiv:1910.10683(2019)."},{"key":"e_1_3_2_1_54_1","volume-title":"Sereum: Protecting existing smart contracts against re-entrancy attacks. arXiv preprint arXiv:1812.05934(2018).","author":"Rodler Michael","year":"2018","unstructured":"Michael Rodler, Wenting Li, Ghassan\u00a0O Karame, and Lucas Davi. 2018. Sereum: Protecting existing smart contracts against re-entrancy attacks. arXiv preprint arXiv:1812.05934(2018)."},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/IWBOSE50093.2020.9050260"},{"key":"e_1_3_2_1_56_1","volume-title":"Understanding the DAO Attack. Retrieved June 13(2016)","author":"Siegel David","year":"2018","unstructured":"David Siegel. 2016. Understanding the DAO Attack. Retrieved June 13(2016), 2018."},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3368089.3417058"},{"key":"e_1_3_2_1_58_1","unstructured":"A Tann Xing\u00a0Jie Han Sourav\u00a0Sen Gupta and Yew-Soon Ong. 2018. Towards safer smart contracts: A sequence learning approach to detecting vulnerabilities. arXiv preprint arXiv:1811.06632(2018) 1371\u20131385."},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3194113.3194115"},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1145\/3274694.3274737"},{"key":"e_1_3_2_1_61_1","volume-title":"Proceedings of the 28th USENIX Security Symposium (USENIX Security 19)","author":"Torres Christof\u00a0Ferreira","year":"2019","unstructured":"Christof\u00a0Ferreira Torres, Mathis Steichen, 2019. The art of the scam: Demystifying honeypots in ethereum smart contracts. In Proceedings of the 28th USENIX Security Symposium (USENIX Security 19). 1591\u20131607."},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3243780"},{"key":"e_1_3_2_1_63_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan\u00a0N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-70278-0_19"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISSRE52982.2021.00047"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSME.2016.67"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/3324884.3416553"},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2020.2978819"},{"key":"e_1_3_2_1_69_1","unstructured":"R. Ying D. Bourgeois J. You M. Zitnik and J. Leskovec. 2019. GNNExplainer: Generating Explanations for Graph Neural Networks. Advances in neural information processing systems 32 (2019) 9240\u20139251."},{"key":"e_1_3_2_1_70_1","volume-title":"Gnnexplainer: Generating explanations for graph neural networks. Advances in neural information processing systems 32","author":"Ying Zhitao","year":"2019","unstructured":"Zhitao Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, and Jure Leskovec. 2019. Gnnexplainer: Generating explanations for graph neural networks. Advances in neural information processing systems 32 (2019)."},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1109\/SANER.2019.8668002"},{"key":"e_1_3_2_1_72_1","volume-title":"Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence (IJCAI). 3283\u20133290","author":"Zhuang Yuan","year":"2021","unstructured":"Yuan Zhuang, Zhenguang Liu, Peng Qian, Qi Liu, Xiang Wang, and Qinming He. 2021. Smart contract vulnerability detection using graph neural networks. In Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence (IJCAI). 3283\u20133290."}],"event":{"name":"ASE '22: 37th IEEE\/ACM International Conference on Automated Software Engineering","location":"Rochester MI USA","acronym":"ASE '22"},"container-title":["Proceedings of the 37th IEEE\/ACM International Conference on Automated Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3551349.3560428","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3551349.3560428","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T07:58:56Z","timestamp":1755849536000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3551349.3560428"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,10]]},"references-count":72,"alternative-id":["10.1145\/3551349.3560428","10.1145\/3551349"],"URL":"https:\/\/doi.org\/10.1145\/3551349.3560428","relation":{},"subject":[],"published":{"date-parts":[[2022,10,10]]},"assertion":[{"value":"2023-01-05","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}