{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T18:46:38Z","timestamp":1761417998416,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":71,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,27]],"date-time":"2024-10-27T00:00:00Z","timestamp":1729987200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62202414"],"award-info":[{"award-number":["62202414"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,27]]},"DOI":"10.1145\/3691620.3695057","type":"proceedings-article","created":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T15:39:19Z","timestamp":1729265959000},"page":"606-618","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Snopy: Bridging Sample Denoising with Causal Graph Learning for Effective Vulnerability Detection"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3688-4437","authenticated-orcid":false,"given":"Sicong","family":"Cao","sequence":"first","affiliation":[{"name":"Yangzhou University, Yangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5165-5080","authenticated-orcid":false,"given":"Xiaobing","family":"Sun","sequence":"additional","affiliation":[{"name":"Yangzhou University, Yangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-5432-651X","authenticated-orcid":false,"given":"Xiaoxue","family":"Wu","sequence":"additional","affiliation":[{"name":"Yangzhou University, Yangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4367-7201","authenticated-orcid":false,"given":"David","family":"Lo","sequence":"additional","affiliation":[{"name":"Singapore Management University, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7267-4923","authenticated-orcid":false,"given":"Lili","family":"Bo","sequence":"additional","affiliation":[{"name":"Yangzhou University, Yangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8500-9917","authenticated-orcid":false,"given":"Bin","family":"Li","sequence":"additional","affiliation":[{"name":"Yangzhou University, Yangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8510-4025","authenticated-orcid":false,"given":"Xiaolei","family":"Liu","sequence":"additional","affiliation":[{"name":"China Academy of Engineering Physics, Mianyang, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5048-2516","authenticated-orcid":false,"given":"Xingwei","family":"Lin","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8503-4063","authenticated-orcid":false,"given":"Wei","family":"Liu","sequence":"additional","affiliation":[{"name":"Yangzhou University, Yangzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2024,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3510003.3510113"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP46215.2023.10179377"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.infsof.2021.106576"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3510003.3510219"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3624744"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE48619.2023.00044"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3597503.3639168"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2021.3087402"},{"key":"e_1_3_2_1_9_1","unstructured":"Checkmarx. 2024. https:\/\/www.checkmarx.com."},{"volume-title":"Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses (RAID). ACM, 654--668","author":"Chen Yizheng","key":"e_1_3_2_1_10_1","unstructured":"Yizheng Chen, Zhoujie Ding, Lamya Alowain, Xinyun Chen, and David A. Wagner. 2023. DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability Detection. In Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses (RAID). ACM, 654--668."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3436877"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/W14-4012"},{"key":"e_1_3_2_1_13_1","unstructured":"Common Vulnerabilities and Exposures. 2024. https:\/\/cve.mitre.org\/."},{"key":"e_1_3_2_1_14_1","unstructured":"Common Weakness Enumeration. 2024. https:\/\/cwe.mitre.org\/index.html."},{"volume-title":"Proceedings of the 45th IEEE\/ACM International Conference on Software Engineering (ICSE). IEEE, 121--133","author":"Croft Roland","key":"e_1_3_2_1_15_1","unstructured":"Roland Croft, Muhammad Ali Babar, and M. Mehdi Kholoosi. 2023. Data Quality for Software Vulnerability Datasets. In Proceedings of the 45th IEEE\/ACM International Conference on Software Engineering (ICSE). IEEE, 121--133."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2022.3171202"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2018.2881961"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.436"},{"key":"e_1_3_2_1_19_1","volume-title":"Vulnerability Detection with Code Language Models: How Far Are We? arXiv preprint arXiv: 2403.18624","author":"Ding Yangruibo","year":"2024","unstructured":"Yangruibo Ding, Yanjun Fu, Omniyyah Ibrahim, Chawin Sitawarin, Xinyun Chen, Basel Alomair, David A. Wagner, Baishakhi Ray, and Yizheng Chen. 2024. Vulnerability Detection with Code Language Models: How Far Are We? arXiv preprint arXiv: 2403.18624 (2024)."},{"volume-title":"Proceedings of the 17th International Conference on Mining Software Repositories (MSR). ACM, 508--512","author":"Fan Jiahao","key":"e_1_3_2_1_20_1","unstructured":"Jiahao Fan, Yi Li, Shaohua Wang, and Tien N. Nguyen. 2020. A C\/C++ Code Vulnerability Dataset with Code Changes and CVE Summaries. In Proceedings of the 17th International Conference on Mining Software Repositories (MSR). ACM, 508--512."},{"key":"e_1_3_2_1_21_1","volume-title":"CodeBERT: A Pre-Trained Model for Programming and Natural Languages. arXiv preprint arXiv","author":"Feng Zhangyin","year":"2002","unstructured":"Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, and Ming Zhou. 2020. CodeBERT: A Pre-Trained Model for Programming and Natural Languages. arXiv preprint arXiv: 2002.08155 (2020)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/24039.24041"},{"key":"e_1_3_2_1_23_1","unstructured":"Flawfinder. 2024. http:\/\/www.dwheeler.com\/FlawFinder."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3524842.3528452"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3627106.3627188"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.499"},{"key":"e_1_3_2_1_27_1","volume-title":"Proceedings of the 31st International Joint Conference on Neural Networks (IJCNN). IEEE, 1--8.","author":"Hanif Hazim","year":"2022","unstructured":"Hazim Hanif and Sergio Maffeis. 2022. VulBERTa: Simplified Source Code PreTraining for Vulnerability Detection. In Proceedings of the 31st International Joint Conference on Neural Networks (IJCNN). IEEE, 1--8."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1986.10478354"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3597926.3598145"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","unstructured":"Arnold Johnson Kelley Dempsey Ron Ross Sarbari Gupta Dennis Bailey et al. 2011. Guide for Security-Focused Configuration Management of Information Systems. NIST special publication 800 128 (2011) 16--16.","DOI":"10.6028\/NIST.SP.800-128-2011"},{"volume-title":"Proceedings of the 33rd International Conference on Software Engineering (ICSE). ACM, 351--360","author":"Kawrykow David","key":"e_1_3_2_1_32_1","unstructured":"David Kawrykow and Martin P. Robillard. 2011. Non-Essential Changes in Version Histories. In Proceedings of the 33rd International Conference on Software Engineering (ICSE). ACM, 351--360."},{"volume-title":"Proceedings of the 3rd International Conference on Learning Representations (ICLR).","author":"Diederik","key":"e_1_3_2_1_33_1","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In Proceedings of the 3rd International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134072"},{"volume-title":"Proceedings of the 4th International Conference on Learning Representations (ICLR).","author":"Li Yujia","key":"e_1_3_2_1_35_1","unstructured":"Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard S. Zemel. 2016. Gated Graph Sequence Neural Networks. In Proceedings of the 4th International Conference on Learning Representations (ICLR)."},{"volume-title":"Proceeding of the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC\/FSE). ACM, 292--303","author":"Li Yi","key":"e_1_3_2_1_36_1","unstructured":"Yi Li, Shaohua Wang, and Tien N. Nguyen. 2021. Vulnerability Detection with Fine-Grained Interpretations. In Proceeding of the 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC\/FSE). ACM, 292--303."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE56229.2023.00164"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2021.3051525"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2018.23158"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3533767.3534380"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE48619.2023.00040"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/ESEM.2013.19"},{"key":"e_1_3_2_1_43_1","volume-title":"Proceedings of the 32nd USENIX Security Symposium (Security). 6557--6574","author":"Mirsky Yisroel","year":"2023","unstructured":"Yisroel Mirsky, George Macon, Michael D. Brown, Carter Yagemann, Matthew Pruett, Evan Downing, Sukarno Mertoguno, and Wenke Lee. 2023. VulChecker: Graph-based Vulnerability Localization in Source Code. In Proceedings of the 32nd USENIX Security Symposium (Security). 6557--6574."},{"key":"e_1_3_2_1_44_1","unstructured":"National Vulnerability Database. 2024. https:\/\/nvd.nist.gov\/."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3611643.3616358"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3468264.3473122"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2024.3379943"},{"key":"e_1_3_2_1_48_1","volume-title":"Proceedings of the 33rd Annual Conference on Neural Information Processing Systems (NeurIPS). 8024--8035","author":"Paszke Adam","year":"2019","unstructured":"Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas K\u00f6pf, Edward Z. Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019. PyTorch: An Imperative Style, High-Performance Deep Learning Library. In Proceedings of the 33rd Annual Conference on Neural Information Processing Systems (NeurIPS). 8024--8035."},{"key":"e_1_3_2_1_49_1","volume-title":"Reasoning and Inference","author":"Pearl Judea","year":"2000","unstructured":"Judea Pearl. 2000. Models, Reasoning and Inference. Cambridge, UK: Cambridge University Press 19, 2 (2000), 3."},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3597503.3639170"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSME58846.2023.00040"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/1082983.1083147"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.5555\/2627435.2670313"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE48619.2023.00188"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539366"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/3468264.3468545"},{"key":"e_1_3_2_1_57_1","first-page":"291","article-title":"The Multilayer Perceptron As An Approximation to A Bayes Optimal Discriminant Function","volume":"1","author":"Suter Bruce W","year":"1990","unstructured":"Bruce W Suter. 1990. The Multilayer Perceptron As An Approximation to A Bayes Optimal Discriminant Function. IEEE Transactions on Neural Networks 1, 4 (1990), 291.","journal-title":"IEEE Transactions on Neural Networks"},{"key":"e_1_3_2_1_58_1","volume-title":"Proceedings of the 31st Annual Conference on Neural Information Processing Systems (NeurIPS). 5998--6008","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is All you Need. In Proceedings of the 31st Annual Conference on Neural Information Processing Systems (NeurIPS). 5998--6008."},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.3044773"},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.1984.5010248"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE48619.2023.00191"},{"key":"e_1_3_2_1_62_1","volume-title":"Proceedings of the 31st USENIX Security Symposium (Security). 3037--3053","author":"Woo Seunghoon","year":"2022","unstructured":"Seunghoon Woo, Hyunji Hong, Eunjin Choi, and Heejo Lee. 2022. MOVERY: A Precise Approach for Modified Vulnerable Code Clone Discovery from Modified Open-Source Software Components. In Proceedings of the 31st USENIX Security Symposium (Security). 3037--3053."},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1145\/3611643.3616351"},{"key":"e_1_3_2_1_64_1","volume-title":"Proceedings of the 29th USENIX Security Symposium (Security). 1165--1182","author":"Xiao Yang","year":"2020","unstructured":"Yang Xiao, Bihuan Chen, Chendong Yu, Zhengzi Xu, Zimu Yuan, Feng Li, Binghong Liu, Yang Liu, Wei Huo, Wei Zou, and Wenchang Shi. 2020. MVP: Detecting Vulnerabilities using Patch-Enhanced Vulnerability Signatures. In Proceedings of the 29th USENIX Security Symposium (Security). 1165--1182."},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2014.44"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3510003.3510146"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2023.3286586"},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2024.3354049"},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2024.3384846"},{"key":"e_1_3_2_1_70_1","volume-title":"Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI).","author":"Zhang Jiale","year":"2021","unstructured":"Jiale Zhang, Chengcheng Zhu, Di Wu, Xiaobing Sun, Jianming Yong, and Guodong Long. 2021. BadFSS: Backdoor Attacks on Federated Self-Supervised Learning. In Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI)."},{"key":"e_1_3_2_1_71_1","volume-title":"Proceedings of the 33rd Annual Conference on Neural Information Processing Systems (NeurIPS). 10197--10207","author":"Zhou Yaqin","year":"2019","unstructured":"Yaqin Zhou, Shangqing Liu, Jing Kai Siow, Xiaoning Du, and Yang Liu. 2019. Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks. In Proceedings of the 33rd Annual Conference on Neural Information Processing Systems (NeurIPS). 10197--10207."}],"event":{"name":"ASE '24: 39th IEEE\/ACM International Conference on Automated Software Engineering","sponsor":["SIGAI ACM Special Interest Group on Artificial Intelligence","SIGSOFT ACM Special Interest Group on Software Engineering","IEEE CS"],"location":"Sacramento CA USA","acronym":"ASE '24"},"container-title":["Proceedings of the 39th IEEE\/ACM International Conference on Automated Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3691620.3695057","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3691620.3695057","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:04:07Z","timestamp":1750291447000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3691620.3695057"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,27]]},"references-count":71,"alternative-id":["10.1145\/3691620.3695057","10.1145\/3691620"],"URL":"https:\/\/doi.org\/10.1145\/3691620.3695057","relation":{},"subject":[],"published":{"date-parts":[[2024,10,27]]},"assertion":[{"value":"2024-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}