{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T05:14:36Z","timestamp":1784351676385,"version":"3.55.0"},"reference-count":123,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2024,10,11]],"date-time":"2024-10-11T00:00:00Z","timestamp":1728604800000},"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":"crossref","award":["61932012, 62372228, 62141215"],"award-info":[{"award-number":["61932012, 62372228, 62141215"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Program of the China Scholarship Council","award":["202306190140"],"award-info":[{"award-number":["202306190140"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Comput. Surv."],"published-print":{"date-parts":[[2025,2,28]]},"abstract":"<jats:p>Actionable Warning Identification (AWI) plays a crucial role in improving the usability of static code analyzers. With recent advances in Machine Learning (ML), various approaches have been proposed to incorporate ML techniques into AWI. These ML-based AWI approaches, benefiting from ML\u2019s strong ability to learn subtle and previously unseen patterns from historical data, have demonstrated superior performance. However, a comprehensive overview of these approaches is missing, which could hinder researchers and practitioners from understanding the current process and discovering potential for future improvement in the ML-based AWI community. In this article, we systematically review the state-of-the-art ML-based AWI approaches. First, we employ a meticulous survey methodology and gather 51 primary studies from January 1, 2000 to January 9, 2023. Then, we outline a typical ML-based AWI workflow, including warning dataset preparation, preprocessing, AWI model construction, and evaluation stages. In such a workflow, we categorize ML-based AWI approaches based on the warning output format. In addition, we analyze the key techniques used in each stage, along with their strengths, weaknesses, and distribution. Finally, we provide practical research directions for future ML-based AWI approaches, focusing on aspects such as data improvement (e.g., enhancing the warning labeling strategy) and model exploration (e.g., exploring large language models for AWI).<\/jats:p>","DOI":"10.1145\/3696352","type":"journal-article","created":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T10:58:26Z","timestamp":1726743506000},"page":"1-35","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Machine Learning for Actionable Warning Identification: A Comprehensive Survey"],"prefix":"10.1145","volume":"57","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3683-7374","authenticated-orcid":false,"given":"Xiuting","family":"Ge","sequence":"first","affiliation":[{"name":"Nanjing University, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9930-7111","authenticated-orcid":false,"given":"Chunrong","family":"Fang","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4580-2046","authenticated-orcid":false,"given":"Xuanye","family":"Li","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"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":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3752-0718","authenticated-orcid":false,"given":"Daoyuan","family":"Wu","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5017-8016","authenticated-orcid":false,"given":"Juan","family":"Zhai","sequence":"additional","affiliation":[{"name":"University of Massachusetts Amherst, Amherst, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9726-3434","authenticated-orcid":false,"given":"Shang-Wei","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8850-5583","authenticated-orcid":false,"given":"Zhihong","family":"Zhao","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7300-9215","authenticated-orcid":false,"given":"Yang","family":"Liu","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9592-7022","authenticated-orcid":false,"given":"Zhenyu","family":"Chen","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,10,11]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"crossref","first-page":"5137","DOI":"10.1007\/s10664-020-09880-1","article-title":"A longitudinal study of static analysis warning evolution and the effects of PMD on software quality in Apache open source projects","volume":"25","author":"Herbold Jens Grabowski, Alexander Trautsch, and Steffen","year":"2020","unstructured":"Jens Grabowski, Alexander Trautsch, and Steffen Herbold. 2020. A longitudinal study of static analysis warning evolution and the effects of PMD on software quality in Apache open source projects. Empirical Software Engineering (EMSE) 25 (2020), 5137\u20135192.","journal-title":"Empirical Software Engineering (EMSE)"},{"key":"e_1_3_3_3_2","doi-asserted-by":"crossref","DOI":"10.1093\/acprof:oso\/9780199665266.001.0001","volume-title":"The Syntax of Roots and the Roots of Syntax","author":"Alexiadou Artemis","year":"2014","unstructured":"Artemis Alexiadou, Hagit Borer, and Florian Sch\u00e4fer. 2014. The Syntax of Roots and the Roots of Syntax. Vol. 51. Oxford University Press."},{"key":"e_1_3_3_4_2","first-page":"1","volume-title":"Proceedings of the 15th IEEE\/ACS International Conference on Computer Systems and Applications (AICCSA\u201918)","author":"Alikhashashneh Enas A.","year":"2018","unstructured":"Enas A. Alikhashashneh, Rajeev R. Raje, and James H. Hill. 2018. Using machine learning techniques to classify and predict static code analysis tool warnings. In Proceedings of the 15th IEEE\/ACS International Conference on Computer Systems and Applications (AICCSA\u201918). IEEE, 1\u20138."},{"key":"e_1_3_3_5_2","first-page":"31","volume-title":"Proceedings of the 6th ACM SIGPLAN International Workshop on State of the Art in Program Analysis","author":"Andreasen Esben Sparre","year":"2017","unstructured":"Esben Sparre Andreasen, Anders M\u00f8ller, and Benjamin Barslev Nielsen. 2017. Systematic approaches for increasing soundness and precision of static analyzers. In Proceedings of the 6th ACM SIGPLAN International Workshop on State of the Art in Program Analysis. ACM, 31\u201336."},{"key":"e_1_3_3_6_2","first-page":"1322","volume-title":"Proceedings of the 18th IEEE International Conference on Machine Learning and Applications (ICMLA\u201919)","author":"Berman Maxwell","year":"2019","unstructured":"Maxwell Berman, Stephen Adams, Tim Sherburne, Cody Fleming, and Peter Beling. 2019. Active learning to improve static analysis. In Proceedings of the 18th IEEE International Conference on Machine Learning and Applications (ICMLA\u201919). IEEE, 1322\u20131327."},{"key":"e_1_3_3_7_2","first-page":"472","volume-title":"Proceedings of the 24th International Conference on Software Analysis, Evolution and Reengineering (SANER\u201917)","author":"Buckers Tim","year":"2017","unstructured":"Tim Buckers, Clinton Cao, Michiel Doesburg, Boning Gong, Sunwei Wang, Moritz Beller, and Andy Zaidman. 2017. UAV: Warnings from multiple automated static analysis tools at a glance. In Proceedings of the 24th International Conference on Software Analysis, Evolution and Reengineering (SANER\u201917). IEEE, 472\u2013476."},{"key":"e_1_3_3_8_2","first-page":"1051","volume-title":"Proceedings of the 28th International Conference on Software Engineering (ICSE\u201906)","author":"Budgen David","year":"2006","unstructured":"David Budgen and Pearl Brereton. 2006. Performing systematic literature reviews in software engineering. In Proceedings of the 28th International Conference on Software Engineering (ICSE\u201906). IEEE\/ACM, 1051\u20131052."},{"key":"e_1_3_3_9_2","first-page":"1","volume-title":"IEEE Smartworld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (Smartworld\/SCALCOM\/UIC\/ATC\/CBDcom\/IOP\/SCI\u201917)","author":"Chakraborty Supriyo","year":"2017","unstructured":"Supriyo Chakraborty, Richard Tomsett, Ramya Raghavendra, Daniel Harborne, Moustafa Alzantot, Federico Cerutti, Mani Srivastava, Alun Preece, Simon Julier, Raghuveer M. Rao, et\u00a0al. 2017. Interpretability of deep learning models: A survey of results. In IEEE Smartworld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (Smartworld\/SCALCOM\/UIC\/ATC\/CBDcom\/IOP\/SCI\u201917). IEEE, San Francisco, 1\u20136."},{"key":"e_1_3_3_10_2","first-page":"1154","volume-title":"Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESE\/FSE\u201921)","author":"Chen Tianyi","year":"2021","unstructured":"Tianyi Chen, Kihong Heo, and Mukund Raghothaman. 2021. Boosting static analysis accuracy with instrumented test executions. In Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESE\/FSE\u201921). ACM, 1154\u20131165."},{"key":"e_1_3_3_11_2","first-page":"238","volume-title":"Proceedings of the 4th ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages","author":"Cousot Patrick","year":"1977","unstructured":"Patrick Cousot and Radhia Cousot. 1977. Abstract interpretation: A unified lattice model for static analysis of programs by construction or approximation of fixpoints. In Proceedings of the 4th ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages. ACM, 238\u2013252."},{"key":"e_1_3_3_12_2","first-page":"530","volume-title":"Proceedings of the 42nd International Conference on Software Engineering (ICSE\u201920)","author":"Durieux Thomas","year":"2020","unstructured":"Thomas Durieux, Jo\u00e3o F. Ferreira, Rui Abreu, and Pedro Cruz. 2020. Empirical review of automated analysis tools on 47,587 Ethereum smart contracts. In Proceedings of the 42nd International Conference on Software Engineering (ICSE\u201920). IEEE\/ACM, 530\u2013541."},{"key":"e_1_3_3_13_2","first-page":"1","volume-title":"Proceedings of the 4th Conference on Symposium on Operating System Design & Implementation - Volume 4","author":"Engler Dawson","year":"2000","unstructured":"Dawson Engler, Benjamin Chelf, Andy Chou, and Seth Hallem. 2000. Checking system rules using system-specific, programmer-written compiler extensions. In Proceedings of the 4th Conference on Symposium on Operating System Design & Implementation - Volume 4. ACM, 1\u201316."},{"issue":"1","key":"e_1_3_3_14_2","first-page":"1536","article-title":"Codebert: A pre-trained model for programming and natural languages","volume":"1","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, et\u00a0al. 2020. Codebert: A pre-trained model for programming and natural languages. Findings of the Association for Computational Linguistics (ACL) 1, 1 (2020), 1536\u20131547.","journal-title":"Findings of the Association for Computational Linguistics (ACL)"},{"key":"e_1_3_3_15_2","first-page":"100","volume-title":"Proceedings of the 2nd IEEE\/ACM International Conference on Automation of Software Test (AST\u201921)","author":"Flynn Lori","year":"2021","unstructured":"Lori Flynn, William Snavely, and Zachary Kurtz. 2021. Test suites as a source of training data for static analysis alert classifiers. In Proceedings of the 2nd IEEE\/ACM International Conference on Automation of Software Test (AST\u201921). ACM, 100\u2013108."},{"key":"e_1_3_3_16_2","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1145\/3194095.3194100","volume-title":"Proceedings of the 1st International Workshop on Software Qualities and Their Dependencies (SQUADE\u201918)","author":"Flynn Lori","year":"2018","unstructured":"Lori Flynn, William Snavely, David Svoboda, Nathan VanHoudnos, Richard Qin, Jennifer Burns, David Zubrow, Robert Stoddard, and Guillermo Marce-Santurio. 2018. Prioritizing alerts from multiple static analysis tools, using classification models. In Proceedings of the 1st International Workshop on Software Qualities and Their Dependencies (SQUADE\u201918). IEEE\/ACM,, 13\u201320."},{"issue":"4","key":"e_1_3_3_17_2","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1109\/TSMCC.2011.2161285","article-title":"A review on ensembles for the class imbalance problem: Bagging-, boosting-, and hybrid-based approaches","volume":"42","author":"Galar Mikel","year":"2012","unstructured":"Mikel Galar, Alberto Fernandez, Edurne Barrenechea, Humberto Bustince, and Francisco Herrera. 2012. A review on ensembles for the class imbalance problem: Bagging-, boosting-, and hybrid-based approaches. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 42, 4 (2012), 463\u2013484.","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)"},{"issue":"4","key":"e_1_3_3_18_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2523813","article-title":"A survey on concept drift adaptation","volume":"46","author":"Gama Jo\u00e3o","year":"2014","unstructured":"Jo\u00e3o Gama, Indr\u0117 \u017dliobait\u0117, Albert Bifet, Mykola Pechenizkiy, and Abdelhamid Bouchachia. 2014. A survey on concept drift adaptation. ACM Computing Surveys (CSUR) 46, 4 (2014), 1\u201337.","journal-title":"ACM Computing Surveys (CSUR)"},{"issue":"4","key":"e_1_3_3_19_2","first-page":"1","article-title":"An empirical study of class rebalancing methods for actionable warning identification","volume":"72","author":"Ge Xiuting","year":"2023","unstructured":"Xiuting Ge, Chunrong Fang, Tongtong Bai, Jia Liu, and Zhihong Zhao. 2023. An empirical study of class rebalancing methods for actionable warning identification. IEEE Transactions on Reliability (TR) (Early Access) 72, 4 (2023), 1\u201315.","journal-title":"IEEE Transactions on Reliability (TR) (Early Access)"},{"key":"e_1_3_3_20_2","article-title":"Pre-trained model-based actionable warning identification: A feasibility study","author":"Ge Xiuting","year":"2024","unstructured":"Xiuting Ge, Chunrong Fang, Quanjun Zhang, Daoyuan Wu, Bowen Yu, Qirui Zheng, An Guo, Shangwei Lin, Zhihong Zhao, Yang Liu, et\u00a0al. 2024. Pre-trained model-based actionable warning identification: A feasibility study. arXiv preprint arXiv:2403.02716 (2024).","journal-title":"arXiv preprint arXiv:2403.02716"},{"key":"e_1_3_3_21_2","first-page":"81","volume-title":"Proceedings of the 21st International Conference on Software Quality, Reliability and Security (QRS\u201921)","author":"Ge Xiuting","year":"2021","unstructured":"Xiuting Ge, Yifan Huang, Zhanwei Hui, Xiaojuan Wang, and Xu Cao. 2021. Impact of datasets on machine learning based methods in Android malware detection: An empirical study. In Proceedings of the 21st International Conference on Software Quality, Reliability and Security (QRS\u201921). IEEE, 81\u201392."},{"issue":"4","key":"e_1_3_3_22_2","doi-asserted-by":"crossref","first-page":"2318","DOI":"10.1109\/TSE.2022.3216879","article-title":"Leveraging Android automated testing to assist crowdsourced testing","volume":"49","author":"Ge Xiuting","year":"2023","unstructured":"Xiuting Ge, Shengcheng Yu, Chunrong Fang, Qi Zhu, and Zhihong Zhao. 2023. Leveraging Android automated testing to assist crowdsourced testing. IEEE Transactions on Software Engineering (TSE) 49, 4 (2023), 2318\u20132336.","journal-title":"IEEE Transactions on Software Engineering (TSE)"},{"key":"e_1_3_3_23_2","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1145\/3395363.3397385","volume-title":"Proceedings of the 29th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA\u201920)","author":"Ghaleb Asem","year":"2020","unstructured":"Asem Ghaleb and Karthik Pattabiraman. 2020. How effective are smart contract analysis tools? Evaluating smart contract static analysis tools using bug injection. In Proceedings of the 29th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA\u201920). ACM, Virtual Event, 415\u2013427."},{"issue":"7524","key":"e_1_3_3_24_2","doi-asserted-by":"crossref","first-page":"1064","DOI":"10.1136\/bmj.38636.593461.68","article-title":"Effectiveness and efficiency of search methods in systematic reviews of complex evidence: Audit of primary sources","volume":"331","author":"Greenhalgh Trisha","year":"2005","unstructured":"Trisha Greenhalgh and Richard Peacock. 2005. Effectiveness and efficiency of search methods in systematic reviews of complex evidence: Audit of primary sources. BMJ 331, 7524 (2005), 1064\u20131065.","journal-title":"BMJ"},{"issue":"12","key":"e_1_3_3_25_2","doi-asserted-by":"crossref","first-page":"5154","DOI":"10.1109\/TSE.2023.3329667","article-title":"Mitigating false positive static analysis warnings: Progress, challenges, and opportunities","volume":"49","author":"Guo Zhaoqiang","year":"2023","unstructured":"Zhaoqiang Guo, Tingting Tan, Shiran Liu, Xutong Liu, Wei Lai, Yibiao Yang, Yanhui Li, Lin Chen, Wei Dong, and Yuming Zhou. 2023. Mitigating false positive static analysis warnings: Progress, challenges, and opportunities. IEEE Transactions on Software Engineering (TSE) 49, 12 (2023), 5154\u20135188.","journal-title":"IEEE Transactions on Software Engineering (TSE)"},{"key":"e_1_3_3_26_2","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.aiopen.2021.08.002","article-title":"Pre-trained models: Past, present and future","volume":"2","author":"Han Xu","year":"2021","unstructured":"Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Yuan Yao, Ao Zhang, Liang Zhang, et\u00a0al. 2021. Pre-trained models: Past, present and future. AI Open 2 (2021), 225\u2013250.","journal-title":"AI Open"},{"key":"e_1_3_3_27_2","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1145\/2597073.2597100","volume-title":"Proceedings of the 11th Working Conference on Mining Software Repositories (MSR\u201914)","author":"Hanam Quinn","year":"2014","unstructured":"Quinn Hanam, Lin Tan, Reid Holmes, and Patrick Lam. 2014. Finding patterns in static analysis alerts: Improving actionable alert ranking. In Proceedings of the 11th Working Conference on Mining Software Repositories (MSR\u201914). ACM, 152\u2013161."},{"key":"e_1_3_3_28_2","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1109\/ICST.2009.45","volume-title":"Proceedings of the 2rd International Conference on Software Testing Verification and Validation (ICST\u201909)","author":"Heckman Sarah","year":"2009","unstructured":"Sarah Heckman and Laurie Williams. 2009. A model building process for identifying actionable static analysis alerts. In Proceedings of the 2rd International Conference on Software Testing Verification and Validation (ICST\u201909). IEEE, 161\u2013170."},{"issue":"4","key":"e_1_3_3_29_2","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1016\/j.infsof.2010.12.007","article-title":"A systematic literature review of actionable alert identification techniques for automated static code analysis","volume":"53","author":"Heckman Sarah","year":"2011","unstructured":"Sarah Heckman and Laurie Williams. 2011. A systematic literature review of actionable alert identification techniques for automated static code analysis. Information and Software Technology (IST) 53, 4 (2011), 363\u2013387.","journal-title":"Information and Software Technology (IST)"},{"issue":"1","key":"e_1_3_3_30_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1349332.1349339","article-title":"Adaptively ranking alerts generated from automated static analysis","volume":"14","author":"Heckman Sarah Smith","year":"2007","unstructured":"Sarah Smith Heckman. 2007. Adaptively ranking alerts generated from automated static analysis. XRDS: Crossroads, The ACM Magazine for Students 14, 1 (2007), 1\u201311.","journal-title":"XRDS: Crossroads, The ACM Magazine for Students"},{"key":"e_1_3_3_31_2","first-page":"1","article-title":"A measurement framework of alert characteristics for false positive mitigation models","volume":"1","author":"Heckman Sarah Smith","year":"2008","unstructured":"Sarah Smith Heckman and Laurie Ann Williams. 2008. A measurement framework of alert characteristics for false positive mitigation models. North Carolina State University, Depth of Computer Science 1 (2008), 1\u20136.","journal-title":"North Carolina State University, Depth of Computer Science"},{"key":"e_1_3_3_32_2","doi-asserted-by":"crossref","first-page":"55090","DOI":"10.1109\/ACCESS.2022.3176865","article-title":"Static code analysis alarms filtering reloaded: A new real-world dataset and its ML-based utilization","volume":"10","author":"Heged\u0171s P\u00e9ter","year":"2022","unstructured":"P\u00e9ter Heged\u0171s and Rudolf Ferenc. 2022. Static code analysis alarms filtering reloaded: A new real-world dataset and its ML-based utilization. IEEE Access 10 (2022), 55090\u201355101.","journal-title":"IEEE Access"},{"key":"e_1_3_3_33_2","first-page":"519","volume-title":"Proceedings of the 39th International Conference on Software Engineering (ICSE\u201917)","author":"Heo Kihong","year":"2017","unstructured":"Kihong Heo, Hakjoo Oh, and Kwangkeun Yi. 2017. Machine-learning-guided selectively unsound static analysis. In Proceedings of the 39th International Conference on Software Engineering (ICSE\u201917). IEEE\/ACM, 519\u2013529."},{"key":"e_1_3_3_34_2","first-page":"561","volume-title":"Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI\u201919)","author":"Heo Kihong","year":"2019","unstructured":"Kihong Heo, Mukund Raghothaman, Xujie Si, and Mayur Naik. 2019. Continuously reasoning about programs using differential Bayesian inference. In Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI\u201919). ACM, 561\u2013575."},{"issue":"10","key":"e_1_3_3_35_2","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1145\/2500892","article-title":"Trends in computer science research","volume":"56","author":"Hoonlor Apirak","year":"2013","unstructured":"Apirak Hoonlor, Boleslaw K. Szymanski, and Mohammed J. Zaki. 2013. Trends in computer science research. Communications of the ACM 56, 10 (2013), 74\u201383.","journal-title":"Communications of the ACM"},{"issue":"5","key":"e_1_3_3_36_2","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1145\/359581.359603","article-title":"A fast algorithm for computing longest common subsequences","volume":"20","author":"Hunt James W.","year":"1977","unstructured":"James W. Hunt and Thomas G. Szymanski. 1977. A fast algorithm for computing longest common subsequences. Commun. ACM 20, 5 (1977), 350\u2013353.","journal-title":"Commun. ACM"},{"key":"e_1_3_3_37_2","first-page":"203","volume-title":"Proceedings of the 12th International Conference on Static Analysis (SAS\u201905)","author":"Jung Yungbum","year":"2005","unstructured":"Yungbum Jung, Jaehwang Kim, Jaeho Shin, and Kwangkeun Yi. 2005. Taming false alarms from a domain-unaware C analyzer by a Bayesian statistical post analysis. In Proceedings of the 12th International Conference on Static Analysis (SAS\u201905). ACM, 203\u2013217."},{"key":"e_1_3_3_38_2","first-page":"316","volume-title":"Proceedings of the 14th International Conference on Formal Engineering Methods (ICFEM\u201912)","author":"Junker Maximilian","year":"2012","unstructured":"Maximilian Junker, Ralf Huuck, Ansgar Fehnker, and Alexander Knapp. 2012. SMT-based false positive elimination in static program analysis. In Proceedings of the 14th International Conference on Formal Engineering Methods (ICFEM\u201912). IEEE, 316\u2013331."},{"key":"e_1_3_3_39_2","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1145\/3460319.3464832","volume-title":"Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA\u201921)","author":"Joshy Ashwin Kallingal","year":"2021","unstructured":"Ashwin Kallingal Joshy, Xueyuan Chen, Benjamin Steenhoek, and Wei Le. 2021. Validating static warnings via testing code fragments. In Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA\u201921). ACM, 540\u2013552."},{"key":"e_1_3_3_40_2","first-page":"698","volume-title":"Proceedings of the 44th IEEE\/ACM International Conference on Software Engineering (ICSE\u201922)","author":"Kang Hong Jin","year":"2022","unstructured":"Hong Jin Kang, Khai Loong Aw, and David Lo. 2022. Detecting false alarms from automatic static analysis tools: How far are we?. In Proceedings of the 44th IEEE\/ACM International Conference on Software Engineering (ICSE\u201922). IEEE\/ACM, 698\u2013709."},{"key":"e_1_3_3_41_2","doi-asserted-by":"crossref","unstructured":"Barbara Kitchenham and und Stuart Charters. 2007. Guidelines for performing systematic literature reviews in software engineering. Keele University and Durham University Joint Report (2007) 1\u201344.","DOI":"10.1049\/iet-sen:20060052"},{"key":"e_1_3_3_42_2","doi-asserted-by":"crossref","first-page":"1307","DOI":"10.1145\/3510003.3510153","volume-title":"Proceedings of the 44th International Conference on Software Engineering (ICSE\u201922)","author":"Kharkar Anant","year":"2022","unstructured":"Anant Kharkar, Roshanak Zilouchian Moghaddam, Matthew Jin, Xiaoyu Liu, Xin Shi, Colin Clement, and Neel Sundaresan. 2022. Learning to reduce false positives in analytic bug detectors. In Proceedings of the 44th International Conference on Software Engineering (ICSE\u201922). IEEE\/ACM, 1307\u20131316."},{"issue":"2","key":"e_1_3_3_43_2","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1214\/aoms\/1177706252","article-title":"Optimum designs in regression problems","volume":"30","author":"Kiefer Jack","year":"1959","unstructured":"Jack Kiefer and Jacob Wolfowitz. 1959. Optimum designs in regression problems. The Annals of Mathematical Statistics 30, 2 (1959), 271\u2013294.","journal-title":"The Annals of Mathematical Statistics"},{"key":"e_1_3_3_44_2","first-page":"194","volume-title":"Proceedings of the 1st Annual ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages (POPL\u201973)","author":"Kildall Gary A.","year":"1973","unstructured":"Gary A. Kildall. 1973. A unified approach to global program optimization. In Proceedings of the 1st Annual ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages (POPL\u201973). ACM, 194\u2013206."},{"key":"e_1_3_3_45_2","first-page":"1282","volume-title":"Proceedings of the 44th International Conference on Software Engineering (ICSE\u201922)","author":"Kim Hyunsu","year":"2022","unstructured":"Hyunsu Kim, Mukund Raghothaman, and Kihong Heo. 2022. Learning probabilistic models for static analysis alarms. In Proceedings of the 44th International Conference on Software Engineering (ICSE\u201922). IEEE\/ACM, 1282\u20131293."},{"key":"e_1_3_3_46_2","first-page":"45","volume-title":"Proceedings of the 6th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on The Foundations of Software Engineering (ESEC\/FSE\u201907)","author":"Kim Sunghun","year":"2007","unstructured":"Sunghun Kim and Michael D. Ernst. 2007. Which warnings should I fix first?. In Proceedings of the 6th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on The Foundations of Software Engineering (ESEC\/FSE\u201907). ACM, 45\u201354."},{"key":"e_1_3_3_47_2","first-page":"35","volume-title":"Proceedings of the 1st ACM SIGPLAN International Workshop on Machine Learning and Programming Languages (MAPL\u201917)","author":"Koc Ugur","year":"2017","unstructured":"Ugur Koc, Parsa Saadatpanah, Jeffrey S. Foster, and Adam A. Porter. 2017. Learning a classifier for false positive error reports emitted by static code analysis tools. In Proceedings of the 1st ACM SIGPLAN International Workshop on Machine Learning and Programming Languages (MAPL\u201917). ACM, 35\u201342."},{"key":"e_1_3_3_48_2","first-page":"288\u201499","volume-title":"Proceedings of the 12th IEEE Conference on Software Testing, Validation and Verification (ICST\u201919)","author":"Koc Ugur","year":"2019","unstructured":"Ugur Koc, Shiyi Wei, Jeffrey S. Foster, Marine Carpuat, and Adam A. Porter. 2019. An empirical assessment of machine learning approaches for triaging reports of a Java static analysis tool. In Proceedings of the 12th IEEE Conference on Software Testing, Validation and Verification (ICST\u201919). IEEE, 288\u201499."},{"key":"e_1_3_3_49_2","first-page":"1137","volume-title":"Proceedings of the 2nd International Joint Conference on Artificial Intelligence","volume":"14","author":"Kohavi Ron","year":"1995","unstructured":"Ron Kohavi. 1995. A study of cross-validation and bootstrap for accuracy estimation and model selection. In Proceedings of the 2nd International Joint Conference on Artificial Intelligence, Vol. 14. IEEE, 1137\u20131145."},{"key":"e_1_3_3_50_2","first-page":"83","volume-title":"Proceedings of the 12th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESE\/FSE\u201904)","author":"Kremenek Ted","year":"2004","unstructured":"Ted Kremenek, Ken Ashcraft, Junfeng Yang, and Dawson Engler. 2004. Correlation exploitation in error ranking. In Proceedings of the 12th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESE\/FSE\u201904). , 83\u201393."},{"key":"e_1_3_3_51_2","first-page":"295","volume-title":"Proceedings of the 10th International Conference on Static Analysis (SAS\u201903)","author":"Kremenek Ted","year":"2003","unstructured":"Ted Kremenek and Dawson Engler. 2003. Z-Ranking: Using statistical analysis to counter the impact of static analysis approximations. In Proceedings of the 10th International Conference on Static Analysis (SAS\u201903). ACM, 295\u2013315."},{"key":"e_1_3_3_52_2","first-page":"391","volume-title":"Proceedings of the 12th IEEE Conference on Software Testing, Validation and Verification (ICST\u201919)","author":"Lee Seongmin","year":"2019","unstructured":"Seongmin Lee, Shin Hong, Jungbae Yi, Taeksu Kim, Chul-Joo Kim, and Shin Yoo. 2019. Classifying false positive static checker alarms in continuous integration using convolutional neural networks. In Proceedings of the 12th IEEE Conference on Software Testing, Validation and Verification (ICST\u201919). IEEE, 391\u2013401."},{"key":"e_1_3_3_53_2","first-page":"1","article-title":"Maximum likelihood estimation of intrinsic dimension","volume":"17","author":"Levina Elizaveta","year":"2004","unstructured":"Elizaveta Levina and Peter Bickel. 2004. Maximum likelihood estimation of intrinsic dimension. Advances in Neural Information Processing Systems 17 (2004), 1\u20138.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_54_2","first-page":"135","volume-title":"Proceedings of the 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion\u201921)","author":"Li Junjie","year":"2021","unstructured":"Junjie Li. 2021. A better approach to track the evolution of static code warnings. In Proceedings of the 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion\u201921). IEEE\/ACM, 135\u2013137."},{"key":"e_1_3_3_55_2","first-page":"921","volume-title":"Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC\/FSE\u201924)","author":"Li Kaixuan","year":"2024","unstructured":"Kaixuan Li, Sen Chen, Lingling Fan, Ruitao Feng, Han Liu, Chengwei Liu, Yang Liu, and Yixiang Chen. 2024. Comparison and evaluation on Static Application Security Testing (SAST) tools for Java. In Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC\/FSE\u201924). ACM, 921\u2013933."},{"issue":"2","key":"e_1_3_3_56_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2656201","article-title":"Residual investigation: Predictive and precise bug detection","volume":"24","author":"Li Kaituo","year":"2014","unstructured":"Kaituo Li, Christoph Reichenbach, Christoph Csallner, and Yannis Smaragdakis. 2014. Residual investigation: Predictive and precise bug detection. ACM Transactions on Software Engineering and Methodology (TOSEM) 24, 2 (2014), 1\u201332.","journal-title":"ACM Transactions on Software Engineering and Methodology (TOSEM)"},{"key":"e_1_3_3_57_2","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1145\/1858996.1859013","volume-title":"Proceedings of the 25th International Conference on Automated Software Engineering (ASE\u201910)","author":"Liang Guangtai","year":"2010","unstructured":"Guangtai Liang, Ling Wu, Qian Wu, Qianxiang Wang, Tao Xie, and Hong Mei. 2010. Automatic construction of an effective training set for prioritizing static analysis warnings. In Proceedings of the 25th International Conference on Automated Software Engineering (ASE\u201910). IEEE\/ACM, 93\u2013102."},{"issue":"1","key":"e_1_3_3_58_2","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1109\/TSE.2018.2884955","article-title":"Mining fix patterns for findBugs violations","volume":"47","author":"Liu Kui","year":"2021","unstructured":"Kui Liu, Dongsun Kim, Tegawend\u00e9 F. Bissyand\u00e9, Shin Yoo, and Yves Le Traon. 2021. Mining fix patterns for findBugs violations. IEEE Transactions on Software Engineering (TSE) 47, 1 (2021), 165\u2013188.","journal-title":"IEEE Transactions on Software Engineering (TSE)"},{"issue":"9","key":"e_1_3_3_59_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3560815","article-title":"Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing","volume":"55","author":"Liu Pengfei","year":"2023","unstructured":"Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023. Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing. ACM Computing Surveys (CSUR) 55, 9 (2023), 1\u201335.","journal-title":"ACM Computing Surveys (CSUR)"},{"key":"e_1_3_3_60_2","first-page":"1","article-title":"RoBERTa: A robustly optimized BERT pretraining approach","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:1907.11692 (2019), 1\u201313.","journal-title":"arXiv:1907.11692"},{"key":"e_1_3_3_61_2","doi-asserted-by":"crossref","unstructured":"Wei Ma Shangqing Liu Mengjie Zhao Xiaofei Xie Wenhang Wang Qiang Hu Jie Zhang and Yang Liu. 2024. Unveiling code Pre-trained models: Investigating syntax and semantics capacities. ACM Transactions on Software Engineering Methodology (TOSEM) 33 7 (2024) 1\u201329.","DOI":"10.1145\/3664606"},{"key":"e_1_3_3_62_2","first-page":"462","volume-title":"Proceedings of the 10th Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC\/FSE\u201915)","author":"Mangal Ravi","year":"2015","unstructured":"Ravi Mangal, Xin Zhang, Aditya V. Nori, and Mayur Naik. 2015. A user-guided approach to program analysis. In Proceedings of the 10th Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC\/FSE\u201915). ACM, 462\u2013473."},{"key":"e_1_3_3_63_2","first-page":"63","volume-title":"Proceedings of the 23rd International Conference on World Wide Web (WWW\u201914)","author":"Medeiros Ib\u00e9ria","year":"2014","unstructured":"Ib\u00e9ria Medeiros, Nuno F. Neves, and Miguel Correia. 2014. Automatic detection and correction of web application vulnerabilities using data mining to predict false positives. In Proceedings of the 23rd International Conference on World Wide Web (WWW\u201914). ACM, 63\u201374."},{"key":"e_1_3_3_64_2","first-page":"1","article-title":"Assisting in auditing of buffer overflow vulnerabilities via machine learning","volume":"2017","author":"Meng Qingkun","year":"2017","unstructured":"Qingkun Meng, Chao Feng, Bin Zhang, Chaojing Tang, et\u00a0al. 2017. Assisting in auditing of buffer overflow vulnerabilities via machine learning. Mathematical Problems in Engineering 2017 (2017), 1\u201314.","journal-title":"Mathematical Problems in Engineering"},{"issue":"1","key":"e_1_3_3_65_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1044834.1044835","article-title":"Parameterized object sensitivity for points-to analysis for Java","volume":"14","author":"Milanova Ana","year":"2005","unstructured":"Ana Milanova, Atanas Rountev, and Barbara G. Ryder. 2005. Parameterized object sensitivity for points-to analysis for Java. ACM Transaction Software Engineering Methodology (TOSEM) 14, 1 (Jan2005), 1\u201341.","journal-title":"ACM Transaction Software Engineering Methodology (TOSEM)"},{"key":"e_1_3_3_66_2","first-page":"227","volume-title":"Proceedings of the 11th International Conference on Logic for Programming Artificial Intelligence and Reasoning (LPAR\u201906)","author":"Motik Boris","year":"2006","unstructured":"Boris Motik and Ulrike Sattler. 2006. A comparison of reasoning techniques for querying large description logic ABoxes. In Proceedings of the 11th International Conference on Logic for Programming Artificial Intelligence and Reasoning (LPAR\u201906). Springer, 227\u2013241."},{"key":"e_1_3_3_67_2","first-page":"157","volume-title":"Proceedings of the 16th International Working Conference on Source Code Analysis and Manipulation (SCAM\u201916)","author":"Muske Tukaram","year":"2016","unstructured":"Tukaram Muske and Alexander Serebrenik. 2016. Survey of approaches for handling static analysis alarms. In Proceedings of the 16th International Working Conference on Source Code Analysis and Manipulation (SCAM\u201916). IEEE, 157\u2013166."},{"issue":"3","key":"e_1_3_3_68_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3494521","article-title":"Survey of approaches for postprocessing of static analysis alarms","volume":"55","author":"Muske Tukaram","year":"2022","unstructured":"Tukaram Muske and Alexander Serebrenik. 2022. Survey of approaches for postprocessing of static analysis alarms. ACM Computing Survey (CSUR) 55, 3 (2022), 1\u201339.","journal-title":"ACM Computing Survey (CSUR)"},{"key":"e_1_3_3_69_2","first-page":"106","volume-title":"Proceedings of the 13th International Working Conference on Source Code Analysis and Manipulation (SCAM\u201913)","author":"Muske Tukaram B.","year":"2013","unstructured":"Tukaram B. Muske, Ankit Baid, and Tushar Sanas. 2013. Review efforts reduction by partitioning of static analysis warnings. In Proceedings of the 13th International Working Conference on Source Code Analysis and Manipulation (SCAM\u201913). ACM, 106\u2013115."},{"key":"e_1_3_3_70_2","first-page":"452","volume-title":"Proceedings of the 30th IEEE\/ACM International Conference on Automated Software Engineering (ASE\u201915)","author":"Nam Jaechang","year":"2015","unstructured":"Jaechang Nam and Sunghun Kim. 2015. CLAMI: Defect prediction on unlabeled datasets. In Proceedings of the 30th IEEE\/ACM International Conference on Automated Software Engineering (ASE\u201915). IEEE, 452\u2013463."},{"key":"e_1_3_3_71_2","first-page":"327","volume-title":"Proceedings of the 28th Asia-Pacific Software Engineering Conference (APSEC\u201921)","author":"Ngo Kien-Tuan","year":"2021","unstructured":"Kien-Tuan Ngo, Dinh-Truong Do, Thu-Trang Nguyen, and Hieu Dinh Vo. 2021. Ranking warnings of static analysis tools using representation learning. In Proceedings of the 28th Asia-Pacific Software Engineering Conference (APSEC\u201921). IEEE, 327\u2013337."},{"key":"e_1_3_3_72_2","first-page":"121","volume-title":"Proceedings of 13th European Dependable Computing Conference (EDCC\u201917)","author":"Nunes Paulo","year":"2017","unstructured":"Paulo Nunes, Ib\u00e9ria Medeiros, Jos\u00e9 Fonseca, Nuno Neves, Miguel Correia, and Marco Vieira. 2017. On combining diverse static analysis tools for web security: An empirical study. In Proceedings of 13th European Dependable Computing Conference (EDCC\u201917). ACM, 121\u2013128."},{"issue":"3","key":"e_1_3_3_73_2","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.1109\/TR.2018.2839339","article-title":"Benchmarking static analysis tools for web security","volume":"67","author":"Nunes Paulo","year":"2018","unstructured":"Paulo Nunes, Ib\u00e9ria Medeiros, Jos\u00e9 C. Fonseca, Nuno Neves, Miguel Correia, and Marco Vieira. 2018. Benchmarking static analysis tools for web security. IEEE Transactions on Reliability (TR) 67, 3 (2018), 1159\u20131175.","journal-title":"IEEE Transactions on Reliability (TR)"},{"issue":"5","key":"e_1_3_3_74_2","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1109\/32.286418","article-title":"Interprocedural def-use associations for c systems with single level pointers","volume":"20","author":"Pande Hemant D.","year":"1994","unstructured":"Hemant D. Pande, William A. Landi, and Barbara G. Ryder. 1994. Interprocedural def-use associations for c systems with single level pointers. IEEE Transactions on Software Engineering (TSE) 20, 5 (1994), 385\u2013403.","journal-title":"IEEE Transactions on Software Engineering (TSE)"},{"key":"e_1_3_3_75_2","first-page":"161","volume-title":"Proceedings of the 22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER\u201915)","author":"Panichella Sebastiano","year":"2015","unstructured":"Sebastiano Panichella, Venera Arnaoudova, Massimiliano Di Penta, and Giuliano Antoniol. 2015. Would static analysis tools help developers with code reviews?. In Proceedings of the 22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER\u201915). IEEE, 161\u2013170."},{"key":"e_1_3_3_76_2","first-page":"729","volume-title":"Proceedings of the 28th USENIX Security Symposium","author":"Pendlebury Feargus","year":"2019","unstructured":"Feargus Pendlebury, Fabio Pierazzi, Roberto Jordaney, Johannes Kinder, and Lorenzo Cavallaro. 2019. \\(\\lbrace\\) TESSERACT \\(\\rbrace\\) : Eliminating experimental bias in malware classification across space and time. In Proceedings of the 28th USENIX Security Symposium. USENIX Association, 729\u2013746."},{"key":"e_1_3_3_77_2","first-page":"1","volume-title":"Proceedings of the 9th Latin-American Symposium on Dependable Computing (LADC\u201919)","author":"Pereira Jose D\u2019Abruzzo","year":"2019","unstructured":"Jose D\u2019Abruzzo Pereira, Jo\u00e3o R. Campos, and Marco Vieira. 2019. An exploratory study on machine learning to combine security vulnerability alerts from static analysis tools. In Proceedings of the 9th Latin-American Symposium on Dependable Computing (LADC\u201919). IEEE, 1\u201310."},{"key":"e_1_3_3_78_2","first-page":"1","volume-title":"Proceedings of the 2021 17th European Dependable Computing Conference (EDCC\u201921)","author":"Pereira Jos\u00e9 D\u2019Abruzzo","year":"2021","unstructured":"Jos\u00e9 D\u2019Abruzzo Pereira, Jo\u00e3o R. Campos, and Marco Vieira. 2021. Machine learning to combine static analysis alerts with software metrics to detect security vulnerabilities: An empirical study. In Proceedings of the 2021 17th European Dependable Computing Conference (EDCC\u201921). ACM, 1\u20138."},{"key":"e_1_3_3_79_2","first-page":"60","volume-title":"2021 IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C\u201921)","author":"Qian Meiyuan","year":"2021","unstructured":"Meiyuan Qian, Jun Luo, Yu Ge, Chen Sun, Xiuting Ge, and Wanmin Huang. 2021. Semantic-based false alarm detection approach via machine learning. In 2021 IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C\u201921). IEEE, Guangzhou, 60\u201366."},{"key":"e_1_3_3_80_2","first-page":"685","volume-title":"Proceedings of the 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C\u201921)","author":"Qing Mingshuang","year":"2021","unstructured":"Mingshuang Qing, Xiang Feng, Jun Luo, Wanmin Huang, Jingui Zhang, Ping Wang, Yong Fan, Xiuting Ge, and Ya Pan. 2021. A machine learning-based static analysis warning prioritization. In Proceedings of the 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C\u201921). IEEE, 685\u2013690."},{"key":"e_1_3_3_81_2","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1145\/3192366.3192417","volume-title":"Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI\u201918)","author":"Raghothaman Mukund","year":"2018","unstructured":"Mukund Raghothaman, Sulekha Kulkarni, Kihong Heo, and Mayur Naik. 2018. User-guided program reasoning using Bayesian inference. In Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI\u201918). ACM, 722\u2013735."},{"issue":"4","key":"e_1_3_3_82_2","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1109\/TSE.2013.2297712","article-title":"Automatic summarization of bug reports","volume":"40","author":"Rastkar Sarah","year":"2014","unstructured":"Sarah Rastkar, Gail C. Murphy, and Gabriel Murray. 2014. Automatic summarization of bug reports. IEEE Transactions on Software Engineering (TSE) 40, 4 (2014), 366\u2013380.","journal-title":"IEEE Transactions on Software Engineering (TSE)"},{"key":"e_1_3_3_83_2","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1007\/978-3-319-92375-8_8","volume-title":"Open Source Systems: Enterprise Software and Solutions","author":"Ribeiro Athos","year":"2018","unstructured":"Athos Ribeiro, Paulo Meirelles, Nelson Lago, and Fabio Kon. 2018. Ranking source code static analysis warnings for continuous monitoring of floss repositories. In Open Source Systems: Enterprise Software and Solutions. Springer, Athens, 90\u2013101."},{"key":"e_1_3_3_84_2","first-page":"10","volume-title":"Proceedings of the 15th International Symposium on Open Collaboration (OpenSym\u201919)","author":"Ribeiro Athos","year":"2019","unstructured":"Athos Ribeiro, Paulo Meirelles, Nelson Lago, and Fabio Kon. 2019. Ranking warnings from multiple source code static analyzers via ensemble learning. In Proceedings of the 15th International Symposium on Open Collaboration (OpenSym\u201919). ACM, 10 pages."},{"issue":"2","key":"e_1_3_3_85_2","first-page":"358","article-title":"Classes of recursively enumerable sets and their decision problems","volume":"74","author":"Rice Henry Gordon","year":"1953","unstructured":"Henry Gordon Rice. 1953. Classes of recursively enumerable sets and their decision problems. Journal of Symbolic Logic 74, 2 (1953), 358\u2013366.","journal-title":"Journal of Symbolic Logic"},{"key":"e_1_3_3_86_2","first-page":"341","volume-title":"Proceedings of the 30th International Conference on Software Engineering (ICSE\u201908)","author":"Ruthruff Joseph R.","year":"2008","unstructured":"Joseph R. Ruthruff, John Penix, J. David Morgenthaler, Sebastian Elbaum, and Gregg Rothermel. 2008. Predicting accurate and actionable static analysis warnings: An experimental approach. In Proceedings of the 30th International Conference on Software Engineering (ICSE\u201908). IEEE\/ACM, 341\u2013350."},{"issue":"3","key":"e_1_3_3_87_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3442181","article-title":"Machine learning for detecting data exfiltration: A review","volume":"54","author":"Sabir Bushra","year":"2021","unstructured":"Bushra Sabir, Faheem Ullah, M. Ali Babar, and Raj Gaire. 2021. Machine learning for detecting data exfiltration: A review. ACM Computing Survey (CSUR) 54, 3 (2021), 1\u201347.","journal-title":"ACM Computing Survey (CSUR)"},{"issue":"4","key":"e_1_3_3_88_2","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1145\/3188720","article-title":"Lessons from building static analysis tools at Google","volume":"61","author":"Sadowski Caitlin","year":"2018","unstructured":"Caitlin Sadowski, Edward Aftandilian, Alex Eagle, Liam Miller-Cushon, and Ciera Jaspan. 2018. Lessons from building static analysis tools at Google. Communications of the ACM, 61, 4 (2018), 58\u201366.","journal-title":"Communications of the ACM,"},{"key":"e_1_3_3_89_2","first-page":"1293","volume-title":"Proceedings of the 34th International Conference on Software Engineering (ICSE\u201912)","author":"Shar Lwin Khin","year":"2012","unstructured":"Lwin Khin Shar and Hee Beng Kuan Tan. 2012. Mining input sanitization patterns for predicting SQL injection and cross site scripting vulnerabilities. In Proceedings of the 34th International Conference on Software Engineering (ICSE\u201912). IEEE\/ACM, 1293\u20131296."},{"key":"e_1_3_3_90_2","first-page":"299","volume-title":"Proceedings of the 4th IEEE International Conference on Software Testing, Verification and Validation (ICST\u201911)","author":"Shen Haihao","year":"2011","unstructured":"Haihao Shen, Jianhong Fang, and Jianjun Zhao. 2011. EFindBugs: Effective error ranking for findBugs. In Proceedings of the 4th IEEE International Conference on Software Testing, Verification and Validation (ICST\u201911). IEEE, 299\u2013308."},{"key":"e_1_3_3_91_2","first-page":"289\u2014305","volume-title":"Proceedings of the 21st Computational Science and Its Applications (ICCSA\u201921)","author":"Siavvas Miltiadis","year":"2021","unstructured":"Miltiadis Siavvas, Ilias Kalouptsoglou, Dimitrios Tsoukalas, and Dionysios Kehagias. 2021. A self-adaptive approach for assessing the criticality of security-related static analysis alerts. In Proceedings of the 21st Computational Science and Its Applications (ICCSA\u201921). Springer, 289\u2014305."},{"key":"e_1_3_3_92_2","first-page":"1433","volume-title":"Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESE\/FSE\u201920)","author":"Svyatkovskiy Alexey","year":"2020","unstructured":"Alexey Svyatkovskiy, Shao Kun Deng, Shengyu Fu, and Neel Sundaresan. 2020. Intellicode compose: Code generation using transformer. In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESE\/FSE\u201920). ACM, 1433\u20131443."},{"key":"e_1_3_3_93_2","first-page":"447","volume-title":"Proceedings of the 29th Asia-Pacific Software Engineering Conference (APSEC\u201922)","author":"Tran Kien T.","year":"2022","unstructured":"Kien T. Tran and Hieu Dinh Vo. 2022. SCAR: Smart contract alarm ranking. In Proceedings of the 29th Asia-Pacific Software Engineering Conference (APSEC\u201922). ACM, 447\u2013451."},{"key":"e_1_3_3_94_2","first-page":"762","volume-title":"Proceedings of the 22rd ACM SIGSAC Conference on Computer and Communications Security (CCS\u201914)","author":"Tripp Omer","year":"2014","unstructured":"Omer Tripp, Salvatore Guarnieri, Marco Pistoia, and Aleksandr Aravkin. 2014. ALETHEIA: Improving the usability of static security analysis. In Proceedings of the 22rd ACM SIGSAC Conference on Computer and Communications Security (CCS\u201914). ACM, 762\u2013774."},{"key":"e_1_3_3_95_2","first-page":"394","volume-title":"Proceedings of the 36th IEEE\/ACM International Conference on Automated Software Engineering (ASE\u201921)","author":"Tu Huy","year":"2021","unstructured":"Huy Tu and Tim Menzies. 2021. FRUGAL: Unlocking semi-supervised learning for software analytics. In Proceedings of the 36th IEEE\/ACM International Conference on Automated Software Engineering (ASE\u201921). IEEE\/ACM, 394\u2013406."},{"key":"e_1_3_3_96_2","first-page":"541","volume-title":"Proceedings of the 28th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER\u201921)","author":"Ueda Yuki","year":"2021","unstructured":"Yuki Ueda, Takashi Ishio, and Kenichi Matsumoto. 2021. Automatically customizing static analysis tools to coding rules really followed by developers. In Proceedings of the 28th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER\u201921). IEEE, 541\u2013545."},{"key":"e_1_3_3_97_2","doi-asserted-by":"crossref","first-page":"2043","DOI":"10.1145\/3510003.3510166","volume-title":"Proceedings of the 44th International Conference on Software Engineering (ICSE\u201922)","author":"Utture Akshay","year":"2022","unstructured":"Akshay Utture, Shuyang Liu, Christian Gram Kalhauge, and Jens Palsberg. 2022. Striking a balance: Pruning false-positives from static call graphs. In Proceedings of the 44th International Conference on Software Engineering (ICSE\u201922). IEEE\/ACM, 2043\u20132055."},{"issue":"3","key":"e_1_3_3_98_2","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1145\/545186.545188","article-title":"Token-based scanning of source code for security problems","volume":"5","author":"Viega John","year":"2002","unstructured":"John Viega, J. T. Bloch, Tadayoshi Kohno, and Gary McGraw. 2002. Token-based scanning of source code for security problems. ACM Transactions on Information and System Security 5, 3 (2002), 238\u2013261.","journal-title":"ACM Transactions on Information and System Security"},{"key":"e_1_3_3_99_2","first-page":"1","volume-title":"Proceedings of the 14th International Conference on Knowledge and Systems Engineering (KSE\u201922)","author":"Vu Thanh Trong","year":"2022","unstructured":"Thanh Trong Vu and Hieu Dinh Vo. 2022. Using multiple code representations to prioritize static analysis warnings. In Proceedings of the 14th International Conference on Knowledge and Systems Engineering (KSE\u201922). IEEE, 1\u20136."},{"key":"e_1_3_3_100_2","doi-asserted-by":"crossref","first-page":"2377","DOI":"10.1145\/3510003.3510050","volume-title":"Proceedings of the 44th International Conference on Software Engineering (ICSE\u201922)","author":"Wan Yao","year":"2022","unstructured":"Yao Wan, Wei Zhao, Hongyu Zhang, Yulei Sui, Guandong Xu, and Hai Jin. 2022. What do they capture? A structural analysis of pre-trained language models for source code. In Proceedings of the 44th International Conference on Software Engineering (ICSE\u201922). IEEE\/ACM, 2377\u20132388."},{"key":"e_1_3_3_101_2","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/978-3-030-04272-1_1","volume-title":"Software Analysis, Testing, and Evolution (SATE\u201918)","author":"Wang Han","year":"2018","unstructured":"Han Wang, Min Zhou, Xi Cheng, Guang Chen, Ming Gu, Lei Bu, and Yingfei Xiong. 2018. Which defect should be fixed first? Semantic prioritization of static analysis report. In Software Analysis, Testing, and Evolution (SATE\u201918). Springer, Shenzhen, 3\u201319."},{"key":"e_1_3_3_102_2","first-page":"516","volume-title":"Proceedings of the 30th International Conference on Program Comprehension (ICPC\u201922)","author":"Wang Junjie","year":"2022","unstructured":"Junjie Wang, Yuchao Huang, Song Wang, and Qing Wang. 2022. Find bugs in static bug finders. In Proceedings of the 30th International Conference on Program Comprehension (ICPC\u201922). IEEE\/ACM, Online, 516\u2013527."},{"key":"e_1_3_3_103_2","volume-title":"Proceedings of the 12th ACM\/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM\u201918)","author":"Wang Junjie","year":"2018","unstructured":"Junjie Wang, Song Wang, and Qing Wang. 2018. Is there a \u201cgolden\u201d feature set for static warning identification? An experimental evaluation. In Proceedings of the 12th ACM\/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM\u201918). ACM, Article 17, 10 pages."},{"key":"e_1_3_3_104_2","first-page":"672","volume-title":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering (FSE\u201917)","author":"Wei Lili","year":"2017","unstructured":"Lili Wei, Yepang Liu, and Shing-Chi Cheung. 2017. OASIS: Prioritizing static analysis warnings for Android apps based on app user reviews. In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering (FSE\u201917). ACM, 672\u2013682."},{"key":"e_1_3_3_105_2","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1109\/TSE.1984.5010248","article-title":"Program slicing","volume":"4","author":"Weiser Mark","year":"1984","unstructured":"Mark Weiser. 1984. Program slicing. IEEE Transactions on Software Engineering (TSE) 4 (1984), 352\u2013357.","journal-title":"IEEE Transactions on Software Engineering (TSE)"},{"key":"e_1_3_3_106_2","first-page":"44","volume-title":"Proceedings of the 21st IEEE Conference on Computer Applications (ICCA\u201923)","author":"Win Yu Yu","year":"2023","unstructured":"Yu Yu Win and Naw Lay Wah. 2023. Actionable static analysis code warnings identification with smote-based classification. In Proceedings of the 21st IEEE Conference on Computer Applications (ICCA\u201923). IEEE, 44\u201349."},{"key":"e_1_3_3_107_2","first-page":"1","volume-title":"Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering (EASE\u201914)","author":"Wohlin Claes","year":"2014","unstructured":"Claes Wohlin. 2014. Guidelines for snowballing in systematic literature studies and a replication in software engineering. In Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering (EASE\u201914). ACM, 1\u201310."},{"key":"e_1_3_3_108_2","doi-asserted-by":"crossref","first-page":"120152","DOI":"10.1016\/j.eswa.2023.120152","article-title":"An unsupervised feature selection approach for actionable warning identification","volume":"227","author":"Xiuting Ge","year":"2023","unstructured":"Ge Xiuting, Fang Chunrong, Liu Jia, Qing Mingshuang, Li Xuanye, and Zhao Zhihong. 2023. An unsupervised feature selection approach for actionable warning identification. Expert Systems with Applications 227 (2023), 120152.","journal-title":"Expert Systems with Applications"},{"key":"e_1_3_3_109_2","unstructured":"Xiuting et al. 2024. AWI Survey. Retrieved September 21 2024 from https:\/\/github.com\/xiaomoqi123\/AWISurvey"},{"key":"e_1_3_3_110_2","first-page":"1","article-title":"Learning to recognize actionable static code warnings (is intrinsically easy)","volume":"26","author":"Yang Xueqi","year":"2021","unstructured":"Xueqi Yang, Jianfeng Chen, Rahul Yedida, Zhe Yu, and Tim Menzies. 2021. Learning to recognize actionable static code warnings (is intrinsically easy). Empirical Software Engineering (EMSE) 26 (2021), 1\u201324.","journal-title":"Empirical Software Engineering (EMSE)"},{"key":"e_1_3_3_111_2","doi-asserted-by":"crossref","first-page":"114134","DOI":"10.1016\/j.eswa.2020.114134","article-title":"Understanding static code warnings: An incremental AI approach","volume":"167","author":"Yang Xueqi","year":"2021","unstructured":"Xueqi Yang, Zhe Yu, Junjie Wang, and Tim Menzies. 2021. Understanding static code warnings: An incremental AI approach. Expert Systems with Applications 167 (2021), 114134.","journal-title":"Expert Systems with Applications"},{"key":"e_1_3_3_112_2","first-page":"269","volume-title":"Proceedings of the 8th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM\u201908)","author":"Yang Zhao Hong","year":"2008","unstructured":"Zhao Hong Yang, Yun Zhan Gong, Qing Xiao, and Ya Wen Wang. 2008. DTS\u2014a software defects testing system. In Proceedings of the 8th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM\u201908). IEEE, 269\u2013270."},{"issue":"4","key":"e_1_3_3_113_2","doi-asserted-by":"crossref","first-page":"2856","DOI":"10.1109\/TSE.2023.3234206","article-title":"How to find actionable static analysis warnings: A case study with findBugs","volume":"49","author":"Yedida Rahul","year":"2023","unstructured":"Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, and Tim Menzies. 2023. How to find actionable static analysis warnings: A case study with findBugs. IEEE Transactions on Software Engineering (TSE) 49, 4 (2023), 2856\u20132872.","journal-title":"IEEE Transactions on Software Engineering (TSE)"},{"issue":"2","key":"e_1_3_3_114_2","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1007\/s10664-022-10253-z","article-title":"An empirical assessment of machine learning approaches for triaging reports of static analysis tools","volume":"28","author":"Yerramreddy Sai","year":"2023","unstructured":"Sai Yerramreddy, Austin Mordahl, Ugur Koc, Shiyi Wei, Jeffrey S. Foster, Marine Carpuat, and Adam A. Porter. 2023. An empirical assessment of machine learning approaches for triaging reports of static analysis tools. Empirical Software Engineering (EMSE) 28, 2 (2023), 28.","journal-title":"Empirical Software Engineering (EMSE)"},{"key":"e_1_3_3_115_2","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.ipl.2006.11.004","article-title":"An empirical study on classification methods for alarms from a bug-finding static C analyzer","volume":"102","author":"Yi Kwangkeun","year":"2007","unstructured":"Kwangkeun Yi, Hosik Choi, Jaehwang Kim, and Yongdai Kim. 2007. An empirical study on classification methods for alarms from a bug-finding static C analyzer. Information Processing Letters 102 (2007), 118\u2013123.","journal-title":"Information Processing Letters"},{"key":"e_1_3_3_116_2","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1109\/APSEC.2014.81","volume-title":"Proceedings of the 21st Asia-Pacific Software Engineering Conference (APSEC\u201914)","volume":"2","author":"Yoon Jongwon","year":"2014","unstructured":"Jongwon Yoon, Minsik Jin, and Yungbum Jung. 2014. Reducing false alarms from an industrial-strength static analyzer by SVM. In Proceedings of the 21st Asia-Pacific Software Engineering Conference (APSEC\u201914), Vol. 2. IEEE, 3\u20136."},{"key":"e_1_3_3_117_2","first-page":"1","volume-title":"Proceedings of the 45th International Conference on Software Engineering (ICSE\u201923)","author":"Yu Ping","year":"2023","unstructured":"Ping Yu, Yijian Wu, Xin Peng, Hahjia Peng, Jian Zhang, Peicheng Xie, and Wenyun Zhao. 2023. ViolationTracker: Building precise histories for static analysis violations. In Proceedings of the 45th International Conference on Software Engineering (ICSE\u201923). IEEE\/ACM, 1\u201312."},{"key":"e_1_3_3_118_2","doi-asserted-by":"crossref","first-page":"532","DOI":"10.1109\/ICSM.2013.89","volume-title":"Proceedings of the 29th IEEE International Conference on Software Maintenance (ICSM\u201913)","author":"Y\u00fcksel Ulas","year":"2013","unstructured":"Ulas Y\u00fcksel and Hasan S\u00f6zer. 2013. Automated classification of static code analysis alerts: A case study. In Proceedings of the 29th IEEE International Conference on Software Maintenance (ICSM\u201913). IEEE, 532\u2013535."},{"key":"e_1_3_3_119_2","first-page":"1","volume-title":"Proceedings of the 17th International Conference on Information Fusion (FUSION\u201914)","author":"Y\u00fcksel Ula\u015f","year":"2014","unstructured":"Ula\u015f Y\u00fcksel, Hasan S\u00f6zer, and Murat \u015eensoy. 2014. Trust-based fusion of classifiers for static code analysis. In Proceedings of the 17th International Conference on Information Fusion (FUSION\u201914). IEEE, 1\u20136."},{"key":"e_1_3_3_120_2","first-page":"237","volume-title":"Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC\/FSE\u201923)","author":"Zhang Huaien","year":"2023","unstructured":"Huaien Zhang, Yu Pei, Junjie Chen, and Shin Hwei Tan. 2023. Statfier: Automated testing of static analyzers via semantic-preserving program transformations. In Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC\/FSE\u201923). ACM, 237\u2013249."},{"key":"e_1_3_3_121_2","first-page":"27","volume-title":"Proceedings of the 1st ACM SIGPLAN International Workshop on Machine Learning and Programming Languages (MAPL\u201917)","author":"Zhang Xin","year":"2017","unstructured":"Xin Zhang, Xujie Si, and Mayur Naik. 2017. Combining the logical and the probabilistic in program analysis. In Proceedings of the 1st ACM SIGPLAN International Workshop on Machine Learning and Programming Languages (MAPL\u201917). ACM, 27\u201334."},{"key":"e_1_3_3_122_2","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s13042-010-0001-0","article-title":"Understanding bag-of-words model: A statistical framework","volume":"1","author":"Zhang Yin","year":"2010","unstructured":"Yin Zhang, Rong Jin, and Zhi-Hua Zhou. 2010. Understanding bag-of-words model: A statistical framework. International Journal of Machine Learning and Cybernetics 1 (2010), 43\u201352.","journal-title":"International Journal of Machine Learning and Cybernetics"},{"key":"e_1_3_3_123_2","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1007\/s00500-019-03942-3","article-title":"A variable-level automated defect identification model based on machine learning","volume":"24","author":"Zhang Yuwei","year":"2020","unstructured":"Yuwei Zhang, Ying Xing, Yunzhan Gong, Dahai Jin, Honghui Li, and Feng Liu. 2020. A variable-level automated defect identification model based on machine learning. Soft Computing 24 (2020), 1045\u20131061.","journal-title":"Soft Computing"},{"key":"e_1_3_3_124_2","first-page":"111","volume-title":"Proceedings of the 43rd International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP\u201921)","author":"Zheng Yunhui","year":"2021","unstructured":"Yunhui Zheng, Saurabh Pujar, Burn Lewis, Luca Buratti, Edward Epstein, Bo Yang, Jim Laredo, Alessandro Morari, and Zhong Su. 2021. D2A: A dataset built for AI-based vulnerability detection methods using differential analysis. In Proceedings of the 43rd International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP\u201921). ACM, 111\u2013120."}],"container-title":["ACM Computing Surveys"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3696352","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3696352","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:10:10Z","timestamp":1750295410000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3696352"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,11]]},"references-count":123,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,2,28]]}},"alternative-id":["10.1145\/3696352"],"URL":"https:\/\/doi.org\/10.1145\/3696352","relation":{},"ISSN":["0360-0300","1557-7341"],"issn-type":[{"value":"0360-0300","type":"print"},{"value":"1557-7341","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,11]]},"assertion":[{"value":"2023-11-29","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-09-12","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-10-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}