{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T16:54:05Z","timestamp":1771952045069,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T00:00:00Z","timestamp":1740441600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","award":["01"],"award-info":[{"award-number":["01"]}]},{"name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","award":["02"],"award-info":[{"award-number":["02"]}]},{"name":"Minas Gerais State Agency for Research and Development - FAPEMIG","award":["03"],"award-info":[{"award-number":["03"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,2,25]]},"DOI":"10.1145\/3708493.3712680","type":"proceedings-article","created":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T17:02:04Z","timestamp":1740502924000},"page":"13-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["A Comparative Study on the Accuracy and the Speed of Static and Dynamic Program Classifiers"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8588-8197","authenticated-orcid":false,"given":"Anderson","family":"Faustino da Silva","sequence":"first","affiliation":[{"name":"State University of Maring\u00e1, Maring\u00e1, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5007-445X","authenticated-orcid":false,"given":"Jeronimo","family":"Castrillon","sequence":"additional","affiliation":[{"name":"TU Dresden, Dresden, Germany"},{"name":"SCADS.AI, Dresden, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0375-1657","authenticated-orcid":false,"given":"Fernando Magno Quint\u00e3o","family":"Pereira","sequence":"additional","affiliation":[{"name":"Federal University of Minas Gerais, Belo Horizonte, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,2,25]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3212695"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290353"},{"key":"e_1_3_2_1_3_1","volume-title":"1998 USENIX Annual Technical Conference (USENIX ATC 98)","author":"Brenda","year":"1998","unstructured":"Brenda S. Baker and Udi Manber. 1998. Deducing Similarities in Java Sources from Bytecodes. In 1998 USENIX Annual Technical Conference (USENIX ATC 98). USENIX Association, New Orleans, LA. https:\/\/www.usenix.org\/conference\/1998-usenix-annual-technical-conference\/deducing-similarities-java-sources-bytecodes"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/3327144.3327276"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","unstructured":"Alexander Brauckmann Andr\u00e9s Goens and Jeronimo Castrillon. 2020. ComPy-Learn: A Toolbox for Exploring Machine Learning Representations for Compilers. In FD). 1\u20134. https:\/\/doi.org\/10.1109\/FDL50818.2020.9232946 10.1109\/FDL50818.2020.9232946","DOI":"10.1109\/FDL50818.2020.9232946"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377555.3377894"},{"key":"e_1_3_2_1_7_1","volume-title":"An infrastructure for adaptive dynamic optimization","author":"Bruening Derek","year":"1913","unstructured":"Derek Bruening, Timothy Garnett, and Saman Amarasinghe. 2003. An infrastructure for adaptive dynamic optimization. In CGO. IEEE Computer Society, USA. 265\u2013275. isbn:076951913X"},{"key":"e_1_3_2_1_8_1","unstructured":"B Jack Copeland. 1997. The church-turing thesis. Available at https:\/\/plato.stanford.edu\/ENTRIES\/church-turing\/"},{"key":"e_1_3_2_1_9_1","volume-title":"A Cross-Platform Binary Diff. https:\/\/www.drdobbs.com\/embedded-systems\/a-cross-platform-binary-diff\/184409550 [Online","author":"Coppieters Krish","year":"2023","unstructured":"Krish Coppieters. [n.d.]. A Cross-Platform Binary Diff. https:\/\/www.drdobbs.com\/embedded-systems\/a-cross-platform-binary-diff\/184409550 [Online; accessed 12-Nov-2023]."},{"key":"e_1_3_2_1_10_1","first-page":"2244","article-title":"ProGraML","author":"Cummins Chris","year":"2021","unstructured":"Chris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Michael F P O\u2019Boyle, and Hugh Leather. 2021. ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations. In ICML. 139, PMLR, Baltimore, Maryland, USA. 2244\u20132253.","journal-title":"In ICML. 139, PMLR, Baltimore, Maryland, USA."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","unstructured":"Anderson Faustino da Silva. 2025. Rouxinol. https:\/\/doi.org\/10.5281\/zenodo.14645411 Accessed: 2025-01-17. 10.5281\/zenodo.14645411","DOI":"10.5281\/zenodo.14645411"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cola.2022.101171"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3579990.3580012"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3062341.3062387"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/SPE.3146"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1002\/SPE.3146"},{"key":"e_1_3_2_1_17_1","first-page":"58","article-title":"discovRE: Efficient Cross-Architecture Identification of Bugs in Binary Code","volume":"52","author":"Eschweiler Sebastian","year":"2016","unstructured":"Sebastian Eschweiler, Khaled Yakdan, and Elmar Gerhards-Padilla. 2016. discovRE: Efficient Cross-Architecture Identification of Bugs in Binary Code.. In Ndss. 52, 58\u201379.","journal-title":"Ndss."},{"key":"e_1_3_2_1_18_1","unstructured":"Nguyen Anh Quynh et al.. 2024. Capstone Engine. https:\/\/www.capstone-engine.org\/"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978370"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.3390\/fi15090314"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3446371"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/359581.359603"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-54830-7_1"},{"key":"e_1_3_2_1_24_1","volume-title":"Obfuscator-LLVM \u2013 software protection for the masses","author":"Junod Pascal","unstructured":"Pascal Junod, Julien Rinaldini, Johan Wehrli, and Julie Michielin. 2015. Obfuscator-LLVM \u2013 software protection for the masses. In SPRO. IEEE, Washington, DC, US. 3\u20139."},{"key":"e_1_3_2_1_25_1","volume-title":"Awesome Binary Similarity \u2013 The online github collection. https:\/\/github.com\/SystemSecurityStorm\/Awesome-Binary-Similarity [Online","author":"Liu Song","year":"2024","unstructured":"Song Liu. [n.d.]. Awesome Binary Similarity \u2013 The online github collection. https:\/\/github.com\/SystemSecurityStorm\/Awesome-Binary-Similarity [Online; accessed 29-Jan-2024]."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/1065010.1065034"},{"key":"e_1_3_2_1_27_1","volume-title":"Convolutional Neural Networks over Tree Structures for Programming Language Processing","author":"Mou Lili","unstructured":"Lili Mou, Ge Li, Lu Zhang, Tao Wang, and Zhi Jin. 2016. Convolutional Neural Networks over Tree Structures for Programming Language Processing. In AAAI. AAAI Press, Palo Alto, CA, US. 1287\u20131293."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/1250734.1250746"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"crossref","unstructured":"Marcelo Nogueira and S\u00e9rgio Medeiros. 2024. Classifying C++ Solutions Based on Their Energy Profile. In SBLP. SBC Porto Alegre RS Brasil. 98\u2013101. https:\/\/sol.sbc.org.br\/index.php\/sblp\/article\/view\/30263","DOI":"10.5753\/sblp.2024.3693"},{"key":"e_1_3_2_1_30_1","volume-title":"Marina Meila and Tong Zhang (Eds.) (Proceedings of Machine Learning Research","volume":"8486","author":"Peng Dinglan","year":"2021","unstructured":"Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, and Tie-Yan Liu. 2021. How could Neural Networks understand Programs? In ICML, Marina Meila and Tong Zhang (Eds.) (Proceedings of Machine Learning Research, Vol. 139). PMLR, Online. 8476\u20138486. http:\/\/proceedings.mlr.press\/v139\/peng21b.html"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2015.49"},{"key":"e_1_3_2_1_32_1","volume-title":"Project CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks. CoRR, abs\/2105.12655","author":"Puri Ruchir","year":"2021","unstructured":"Ruchir Puri, David S. Kung, Geert Janssen, Wei Zhang, Giacomo Domeniconi, Vladimir Zolotov, Julian Dolby, Jie Chen, Mihir R. Choudhury, Lindsey Decker, Veronika Thost, Luca Buratti, Saurabh Pujar, and Ulrich Finkler. 2021. Project CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks. CoRR, abs\/2105.12655 (2021), arXiv:2105.12655. arxiv:2105.12655"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3453483.3454035"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1090\/S0002-9947-1953-0053041-6"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1002\/spe.2907"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3418463"},{"key":"e_1_3_2_1_37_1","volume-title":"Fernando Magno Quint\u00e3o Pereira, and Ramakrishna Upadrasta","author":"VenkataKeerthy S.","year":"2024","unstructured":"S. VenkataKeerthy, Soumya Banerjee, Sayan Dey, Yashas Andaluri, Raghul PS, Subrahmanyam Kalyanasundaram, Fernando Magno Quint\u00e3o Pereira, and Ramakrishna Upadrasta. 2024. VEXIR2Vec: An Architecture-Neutral Embedding Framework for Binary Similarity. arxiv:2312.00507. arxiv:2312.00507"},{"key":"e_1_3_2_1_38_1","first-page":"1","article-title":"Bmat-a binary matching tool for stale profile propagation","volume":"2","author":"Wang Zheng","year":"2000","unstructured":"Zheng Wang, Ken Pierce, and Scott McFarling. 2000. Bmat-a binary matching tool for stale profile propagation. The Journal of Instruction-Level Parallelism, 2 (2000), 1\u201320.","journal-title":"The Journal of Instruction-Level Parallelism"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2023.3240118"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3640337"}],"event":{"name":"CC '25: 34th ACM SIGPLAN International Conference on Compiler Construction","location":"Las Vegas NV USA","acronym":"CC '25","sponsor":["SIGPLAN SIGPLAN Programming Languages"]},"container-title":["Proceedings of the 34th ACM SIGPLAN International Conference on Compiler Construction"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3708493.3712680","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3708493.3712680","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:09:54Z","timestamp":1750295394000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3708493.3712680"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,25]]},"references-count":40,"alternative-id":["10.1145\/3708493.3712680","10.1145\/3708493"],"URL":"https:\/\/doi.org\/10.1145\/3708493.3712680","relation":{},"subject":[],"published":{"date-parts":[[2025,2,25]]},"assertion":[{"value":"2025-02-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}