{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T02:19:19Z","timestamp":1772504359110,"version":"3.50.1"},"reference-count":61,"publisher":"Association for Computing Machinery (ACM)","issue":"ISSTA","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U24A20337, 62372228"],"award-info":[{"award-number":["U24A20337, 62372228"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Shenzhen-Hong Kong-Macau Technology Research Programme","award":["Grant No.SGDX20230821091559018"],"award-info":[{"award-number":["Grant No.SGDX20230821091559018"]}]},{"name":"the Fundamental Research Funds for the Central Universities","award":["14380029"],"award-info":[{"award-number":["14380029"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. ACM Softw. Eng."],"published-print":{"date-parts":[[2025,6,22]]},"abstract":"<jats:p>\n            Watermarking is a technique to help identify the source of data points, which can be used to help prevent the misuse of protected datasets. Existing methods on code watermarking, leveraging the idea from the backdoor research, embed stealthy triggers as watermarks. Despite their high resilience against dilution attacks and backdoor detections, the robustness has not been fully evaluated. To fill this gap, we propose\n            <jats:bold>DeCoMa<\/jats:bold>\n            , a dual-channel approach to\n            <jats:bold>De<\/jats:bold>\n            tect and purify\n            <jats:bold>Co<\/jats:bold>\n            de dataset water\n            <jats:bold>Ma<\/jats:bold>\n            rks. To overcome the high barrier created by the stealthy and hidden nature of code watermarks, DeCoMa leverages dual-channel constraints on code to generalize and map code samples into standardized templates. Subsequently, DeCoMa extracts hidden watermarks by identifying outlier associations between paired elements within the standardized templates. Finally, DeCoMa purifies the watermarked dataset by removing all samples containing the detected watermark, enabling the silent appropriation of protected code. We conduct extensive experiments to evaluate the effectiveness and efficiency of DeCoMa, covering 14 types of code watermarks and 3 representative intelligent code tasks (a total of 14 scenarios). Experimental results demonstrate that DeCoMa achieves a stable recall of 100% in 14 code watermark detection scenarios, significantly outperforming the baselines. Additionally, DeCoMa effectively attacks code watermarks with embedding rates as low as 0.1%, while maintaining comparable model performance after training on the purified dataset. Furthermore, as DeCoMa requires no model training for detection, it achieves substantially higher efficiency than all baselines, with a speedup ranging from 31.5 to 130.9\u00d7. The results call for more advanced watermarking techniques for code models, while DeCoMa can serve as a baseline for future evaluation.\n          <\/jats:p>","DOI":"10.1145\/3728952","type":"journal-article","created":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T10:52:56Z","timestamp":1750589576000},"page":"1701-1724","source":"Crossref","is-referenced-by-count":1,"title":["DeCoMa: Detecting and Purifying Code Dataset Watermarks through Dual Channel Code Abstraction"],"prefix":"10.1145","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3166-8007","authenticated-orcid":false,"given":"Yuan","family":"Xiao","sequence":"first","affiliation":[{"name":"Nanjing University, Nanjing, China"},{"name":"Nanjing University, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3380-5564","authenticated-orcid":false,"given":"Yuchen","family":"Chen","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1551-8948","authenticated-orcid":false,"given":"Shiqing","family":"Ma","sequence":"additional","affiliation":[{"name":"University of Massachusetts at Amherst, Amherst, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3854-5647","authenticated-orcid":false,"given":"Haocheng","family":"Huang","sequence":"additional","affiliation":[{"name":"Soochow University, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9930-7111","authenticated-orcid":false,"given":"Chunrong","family":"Fang","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"},{"name":"Nanjing University, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6451-1878","authenticated-orcid":false,"given":"Yanwei","family":"Chen","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9236-8264","authenticated-orcid":false,"given":"Weisong","family":"Sun","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2122-3011","authenticated-orcid":false,"given":"Yunfeng","family":"Zhu","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8667-0456","authenticated-orcid":false,"given":"Xiaofang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Soochow University, Suzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9592-7022","authenticated-orcid":false,"given":"Zhenyu","family":"Chen","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"},{"name":"Nanjing University, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,6,22]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Amazon Web Services","author":"Inc.","year":"2023","unstructured":"Inc. Amazon Web Services. 2023. CodeWhisperer. site:. https:\/\/aws.amazon.com\/codewhisperer\/"},{"key":"e_1_2_1_2_1","unstructured":"Anonymous. 2024. DeCoMa. https:\/\/anonymous.4open.science\/r\/DeCoMa-C00B"},{"key":"e_1_2_1_3_1","volume-title":"Proceedings of the 5th International Conference on Electronic Commerce Research. ICECR","author":"Arboit Genevieve","year":"2002","unstructured":"Genevieve Arboit. 2002. A Method for Watermarking Java Programs via Opaque Predicates. In Proceedings of the 5th International Conference on Electronic Commerce Research. ICECR, Montreal, Canada. 102\u2013110."},{"key":"e_1_2_1_4_1","volume-title":"Beijing Guixin Technology","author":"Inc.","year":"2022","unstructured":"Inc. Beijing Guixin Technology. 2022. aiXcoder. site:. https:\/\/www.aixcoder.com\/"},{"key":"e_1_2_1_5_1","volume-title":"Prem Devanbu, and Emily Morgan.","author":"Casalnuovo Casey","year":"2020","unstructured":"Casey Casalnuovo, Earl T. Barr, Santanu Kumar Dash, Prem Devanbu, and Emily Morgan. 2020. A theory of dual channel constraints. https:\/\/dl.acm.org\/doi\/10.1145\/3377816.3381720 In Proceedings of the ACM\/IEEE 42nd International Conference on Software Engineering: New Ideas and Emerging Results. Association for Computing Machinery, 25\u201328."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3540250.3549162"},{"key":"e_1_2_1_7_1","volume-title":"Workshop on Artificial Intelligence Safety 2019 co-located with the Thirty-Third AAAI Conference on Artificial Intelligence 2019 (AAAI-19) (CEUR Workshop Proceedings","volume":"18","author":"Chen Bryant","year":"2019","unstructured":"Bryant Chen, Wilka Carvalho, Nathalie Baracaldo, Heiko Ludwig, Benjamin Edwards, Taesung Lee, Ian M. Molloy, and Biplav Srivastava. 2019. Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering. In Workshop on Artificial Intelligence Safety 2019 co-located with the Thirty-Third AAAI Conference on Artificial Intelligence 2019 (AAAI-19) (CEUR Workshop Proceedings, Vol. 2301). CEUR-WS.org, Honolulu, Hawaii. https:\/\/ceur-ws.org\/Vol-2301\/paper_18.pdf"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-64861-3_81"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/292540.292569"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2024.3422274"},{"key":"e_1_2_1_11_1","unstructured":"Inc. GitHub. 2022. GitHub Copilot. site:. https:\/\/copilot.github.com\/"},{"key":"e_1_2_1_12_1","unstructured":"Yoav Goldberg. 2014. word2vec Explained: deriving Mikolov et al.\u2019s negative-sampling word-embedding method. arxiv:1402.3722 arXiv preprint arXiv:1402.3722."},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.1969.10490657"},{"key":"e_1_2_1_14_1","volume-title":"2011 World Congress on Internet Security, WorldCIS","author":"George Hamilton James Alexander","year":"2011","unstructured":"James Alexander George Hamilton and Sebastian Danicic. 2011. A survey of static software watermarking. In 2011 World Congress on Internet Security, WorldCIS 2011. IEEE, London, UK,. 100\u2013107. https:\/\/ieeexplore.ieee.org\/document\/5749891\/"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3576915.3623175"},{"key":"e_1_2_1_16_1","unstructured":"Inc. Hugging Face. 2016. Hugging Face. site:. https:\/\/huggingface.co\/"},{"key":"e_1_2_1_17_1","volume-title":"CodeSearchNet Challenge: Evaluating the State of Semantic Code Search. arXiv, abs\/1909.09436","author":"Husain Hamel","year":"2019","unstructured":"Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltiadis Allamanis, and Marc Brockschmidt. 2019. CodeSearchNet Challenge: Evaluating the State of Semantic Code Search. arXiv, abs\/1909.09436 (2019), arXiv:1909.09436. arxiv:1909.09436"},{"key":"e_1_2_1_18_1","volume-title":"Proceedings of the 3rd International Conference on Learning Representations","author":"Diederik","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In Proceedings of the 3rd International Conference on Learning Representations. San Diego, CA, USA. arxiv:1412.6980"},{"key":"e_1_2_1_19_1","volume-title":"International Conference on Machine Learning (Proceedings of Machine Learning Research","volume":"17084","author":"Kirchenbauer John","year":"2023","unstructured":"John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, and Tom Goldstein. 2023. A Watermark for Large Language Models. In International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 202). PMLR, Honolulu, Hawaii, USA. 17061\u201317084. https:\/\/proceedings.mlr.press\/v202\/kirchenbauer23a\/kirchenbauer23a.pdf"},{"key":"e_1_2_1_20_1","volume-title":"Fifth international workshop on intelligent data analysis in medicine and pharmacology. 1, 20\u201324","author":"Laurikkala Jorma","year":"2000","unstructured":"Jorma Laurikkala, Martti Juhola, Erna Kentala, N Lavrac, S Miksch, and B Kavsek. 2000. Informal identification of outliers in medical data. In Fifth international workshop on intelligent data analysis in medicine and pharmacology. 1, 20\u201324."},{"key":"e_1_2_1_21_1","volume-title":"Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics","author":"Lee Taehyun","year":"2024","unstructured":"Taehyun Lee, Seokhee Hong, Jaewoo Ahn, Ilgee Hong, Hwaran Lee, Sangdoo Yun, Jamin Shin, and Gunhee Kim. 2024. Who Wrote this Code? Watermarking for Code Generation. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Bangkok, Thailand. 4890\u20134911. https:\/\/aclanthology.org\/2024.acl-long.268"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3630008"},{"key":"e_1_2_1_23_1","first-page":"2023","volume-title":"Transactions on Machine Learning Research","author":"Li Raymond","year":"2023","unstructured":"Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, and Jenny Chim. 2023. StarCoder: may the source be with you!. Transactions on Machine Learning Research, 2023 (2023), https:\/\/openreview.net\/forum?id=KoFOg41haE"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.18653\/V1\/2023.ACL-LONG.399"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","unstructured":"Yi Li Aashish Yadavally Jiaxing Zhang Shaohua Wang and Tien N Nguyen. 2023. DeMinify: Neural Variable Name Recovery and Type Inference. https:\/\/doi.org\/10.1145\/3611643.3616368 In Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering. 758\u2013770. 10.1145\/3611643.3616368","DOI":"10.1145\/3611643.3616368"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3324884.3416591"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2019.2908071"},{"key":"e_1_2_1_28_1","volume-title":"M.Dong,  V.Panteleev,  ikrima,  S.Kalt,  K.Lampe,  A.Pinkus,  M.Schmitz,  M.Krupcale,  narpfel,  S.Gallegos,  V.Mart\u00ed,  Edgar, and  G.Fraser.","author":"Brunsfeld M.","year":"2020","unstructured":"M.Brunsfeld, P.Thomson, A.Hlynskyi, J.Vera, P.Turnbull, T.Clem, D.Creager, A.Helwer, R.Rix, H.van Antwerpen, M.Davis, Ika, T.-A.Nguyen, S.Brunk, N.Hasabnis, bfredl, M.Dong, V.Panteleev, ikrima, S.Kalt, K.Lampe, A.Pinkus, M.Schmitz, M.Krupcale, narpfel, S.Gallegos, V.Mart\u00ed, Edgar, and G.Fraser. 2020. Tree-sitter: An incremental parsing system for programming tools. https:\/\/github.com\/tree-sitter\/tree-sitter"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1301.3781"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACSAC.2000.898885"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.3115\/1073083.1073135"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP46214.2022.9833571"},{"key":"e_1_2_1_33_1","volume-title":"Glove: Global vectors for word representation. https:\/\/aclanthology.org\/D14-1162\/ In Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP). 1532\u20131543.","author":"Pennington Jeffrey","year":"2014","unstructured":"Jeffrey Pennington, Richard Socher, and Christopher D Manning. 2014. Glove: Global vectors for word representation. https:\/\/aclanthology.org\/D14-1162\/ In Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP). 1532\u20131543."},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.3758\/s13423-014-0585-6"},{"key":"e_1_2_1_35_1","unstructured":"Pyminifie. 2014. Pyminifie. https:\/\/github.com\/liftoff\/pyminifier"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR56361.2022.9956690"},{"key":"e_1_2_1_37_1","volume-title":"CodeBLEU: a Method for Automatic Evaluation of Code Synthesis. arXiv, abs\/2009.10297","author":"Ren Shuo","year":"2020","unstructured":"Shuo Ren, Daya Guo, Shuai Lu, Long Zhou, Shujie Liu, Duyu Tang, Neel Sundaresan, Ming Zhou, Ambrosio Blanco, and Shuai Ma. 2020. CodeBLEU: a Method for Automatic Evaluation of Code Synthesis. arXiv, abs\/2009.10297 (2020), arxiv:2009.10297"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1993.10476408"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","unstructured":"Baptiste Rozi\u00e8re Jonas Gehring Fabian Gloeckle Sten Sootla Itai Gat Xiaoqing Ellen Tan Yossi Adi Jingyu Liu Tal Remez J\u00e9r\u00e9my Rapin Artyom Kozhevnikov Ivan Evtimov Joanna Bitton Manish Bhatt Cristian Canton-Ferrer Aaron Grattafiori Wenhan Xiong Alexandre D\u00e9fossez Jade Copet Faisal Azhar Hugo Touvron Louis Martin Nicolas Usunier Thomas Scialom and Gabriel Synnaeve. 2023. Code Llama: Open Foundation Models for Code. arXiv abs\/2308.12950 (2023) https:\/\/doi.org\/10.48550\/arXiv.2308.12950 10.48550\/arXiv.2308.12950","DOI":"10.48550\/arXiv.2308.12950"},{"key":"e_1_2_1_40_1","volume-title":"Proceedings of the 32nd USENIX Security Symposium. USENIX Association","author":"Sandoval Gustavo","year":"2023","unstructured":"Gustavo Sandoval, Hammond Pearce, Teo Nys, Ramesh Karri, Siddharth Garg, and Brendan Dolan-Gavitt. 2023. Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants. In Proceedings of the 32nd USENIX Security Symposium. USENIX Association, Anaheim, CA, USA. 2205\u20132222. https:\/\/www.usenix.org\/conference\/usenixsecurity23\/presentation\/sandoval"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.18653\/V1\/2023.ACL-LONG.540"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3510003.3510140"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3632742"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3611643.3616297"},{"key":"e_1_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512225"},{"key":"e_1_2_1_46_1","volume-title":"Proceedings of the 34th International Conference on Machine Learning (Proceedings of Machine Learning Research","volume":"3328","author":"Sundararajan Mukund","year":"2017","unstructured":"Mukund Sundararajan, Ankur Taly, and Qiqi Yan. 2017. Axiomatic Attribution for Deep Networks. In Proceedings of the 34th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 70). PMLR, Sydney, NSW, Australia. 3319\u20133328. http:\/\/proceedings.mlr.press\/v70\/sundararajan17a.html"},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSME.2014.77"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330699"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.2307.09288"},{"key":"e_1_2_1_50_1","volume-title":"Spectral Signatures in Backdoor Attacks. In Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems. Curran Associates","author":"Tran Brandon","year":"2018","unstructured":"Brandon Tran, Jerry Li, and Aleksander Madry. 2018. Spectral Signatures in Backdoor Attacks. In Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems. Curran Associates, Montr\u00e9al, Canada. 8011\u20138021. https:\/\/proceedings.neurips.cc\/paper\/2018\/hash\/280cf18baf4311c92aa5a042336587d3-Abstract.html"},{"key":"e_1_2_1_51_1","volume-title":"From frequency to meaning: Vector space models of semantics. arxiv:1003.1141 Journal of artificial intelligence research, 37","author":"Turney Peter D","year":"2010","unstructured":"Peter D Turney and Patrick Pantel. 2010. From frequency to meaning: Vector space models of semantics. arxiv:1003.1141 Journal of artificial intelligence research, 37 (2010), 141\u2013188."},{"key":"e_1_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE.2019.00012"},{"key":"e_1_2_1_53_1","volume-title":"Recode: Robustness evaluation of code generation models. arxiv:2212.10264 arXiv preprint arXiv:2212.10264.","author":"Wang Shiqi","year":"2022","unstructured":"Shiqi Wang, Zheng Li, Haifeng Qian, Chenghao Yang, Zijian Wang, Mingyue Shang, Varun Kumar, Samson Tan, Baishakhi Ray, and Parminder Bhatia. 2022. Recode: Robustness evaluation of code generation models. arxiv:2212.10264 arXiv preprint arXiv:2212.10264."},{"key":"e_1_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.18653\/V1\/2021.EMNLP-MAIN.685"},{"key":"e_1_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3674399.3674447"},{"key":"e_1_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP54263.2024.00097"},{"key":"e_1_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2024.3361661"},{"key":"e_1_2_1_58_1","article-title":"Stealthy backdoor attack for code models","author":"Yang Zhou","year":"2024","unstructured":"Zhou Yang, Bowen Xu, Jie M Zhang, Hong Jin Kang, Jieke Shi, Junda He, and David Lo. 2024. Stealthy backdoor attack for code models. IEEE Transactions on Software Engineering.","journal-title":"IEEE Transactions on Software Engineering."},{"key":"e_1_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2022.111304"},{"key":"e_1_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1007\/11427995_42"},{"key":"e_1_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.4324\/9781315009421"}],"container-title":["Proceedings of the ACM on Software Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3728952","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T16:48:01Z","timestamp":1752684481000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3728952"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,22]]},"references-count":61,"journal-issue":{"issue":"ISSTA","published-print":{"date-parts":[[2025,6,22]]}},"alternative-id":["10.1145\/3728952"],"URL":"https:\/\/doi.org\/10.1145\/3728952","relation":{},"ISSN":["2994-970X"],"issn-type":[{"value":"2994-970X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,22]]}}}