{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T21:06:44Z","timestamp":1772312804360,"version":"3.50.1"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T00:00:00Z","timestamp":1744329600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T00:00:00Z","timestamp":1744329600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"crossref","award":["71972102"],"award-info":[{"award-number":["71972102"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"crossref","award":["71972102"],"award-info":[{"award-number":["71972102"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"the Universities Natural Science Research Project of Jiangsu Province","award":["20KJA520002"],"award-info":[{"award-number":["20KJA520002"]}]},{"name":"the Universities Natural Science Research Project of Jiangsu Province","award":["20KJA520002"],"award-info":[{"award-number":["20KJA520002"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"DOI":"10.1007\/s11227-025-07186-x","type":"journal-article","created":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T05:56:29Z","timestamp":1744350989000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Smart contract generation model based on code annotation and AST-LSTM tuning"],"prefix":"10.1007","volume":"81","author":[{"given":"Chen","family":"Yong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hu","family":"Defeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Chao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Nannan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liu","family":"Jianbo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,4,11]]},"reference":[{"issue":"7","key":"7186_CR1","doi-asserted-by":"publisher","first-page":"5033","DOI":"10.1007\/s00521-021-05800-6","volume":"35","author":"F Ullah","year":"2023","unstructured":"Ullah F, Al-Turjman F (2023) A conceptual framework for blockchain smart contract adoption to manage real estate deals in smart cities. Neural Comput Appl 35(7):5033\u20135054","journal-title":"Neural Comput Appl"},{"key":"7186_CR2","doi-asserted-by":"publisher","first-page":"110891","DOI":"10.1016\/j.jss.2020.110891","volume":"174","author":"A Vacca","year":"2021","unstructured":"Vacca A, Di Sorbo A, Visaggio CA et al (2021) A systematic literature review of blockchain and smart contract development: Techniques, tools, and open challenges. J Syst Softw 174:110891","journal-title":"J Syst Softw"},{"issue":"10","key":"7186_CR3","doi-asserted-by":"publisher","first-page":"2084","DOI":"10.1109\/TSE.2019.2942301","volume":"47","author":"W Zou","year":"2019","unstructured":"Zou W, Lo D, Kochhar PS et al (2019) Smart contract development: challenges and opportunities. IEEE Trans Softw Eng 47(10):2084\u20132106","journal-title":"IEEE Trans Softw Eng"},{"key":"7186_CR4","doi-asserted-by":"publisher","first-page":"73131","DOI":"10.1109\/ACCESS.2019.2920776","volume":"7","author":"D Mao","year":"2019","unstructured":"Mao D, Wang F, Wang Y et al (2019) Visual and user-defined smart contract designing system based on automatic coding. IEEE Access 7:73131\u201373143","journal-title":"IEEE Access"},{"issue":"5","key":"7186_CR5","first-page":"21","volume":"2020","author":"Gao Yichen ZZZhao Bin","year":"2020","unstructured":"Gao Yichen ZZZhao Bin (2020) Research and implementation of the automatic smart contract generation method for Ethereum. J East China Normal Univ (Natural Science Edition) 2020(5):21","journal-title":"J East China Normal Univ (Natural Science Edition)"},{"key":"7186_CR6","doi-asserted-by":"crossref","unstructured":"Dwivedi V, Norta A (2022) Auto-generation of smart contracts from a domain-specific xml-based language. In: Intelligent Data Engineering and Analytics: Proceedings of the 9th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA 2021), Springer, pp 549\u2013564","DOI":"10.1007\/978-981-16-6624-7_54"},{"key":"7186_CR7","unstructured":"Vaswani A, Shazeer N, Parmar N et\u00a0al (2017) Attention is all you need. Advances in neural information processing systems 30"},{"key":"7186_CR8","doi-asserted-by":"crossref","unstructured":"Koco\u0144 J, Cichecki I, Kaszyca O et\u00a0al (2023) Chatgpt: Jack of all trades, master of none. Information Fusion, p 101861","DOI":"10.1016\/j.inffus.2023.101861"},{"key":"7186_CR9","doi-asserted-by":"publisher","first-page":"100017","DOI":"10.1016\/j.metrad.2023.100017","volume":"1","author":"Y Liu","year":"2023","unstructured":"Liu Y, Han T, Ma S et al (2023) Summary of chatgpt-related research and perspective towards the future of large language models. Meta Radiol 1:100017","journal-title":"Meta Radiol"},{"key":"7186_CR10","doi-asserted-by":"publisher","first-page":"111734","DOI":"10.1016\/j.jss.2023.111734","volume":"203","author":"AM Dakhel","year":"2023","unstructured":"Dakhel AM, Majdinasab V, Nikanjam A et al (2023) Github copilot AI pair programmer: Asset or liability? J Syst Softw 203:111734","journal-title":"J Syst Softw"},{"key":"7186_CR11","unstructured":"Roziere B, Gehring J, Gloeckle F et\u00a0al (2023) arXiv preprint arXiv:2308.12950"},{"key":"7186_CR12","doi-asserted-by":"crossref","unstructured":"Petrovi\u0107 N, Al-Azzoni I (2023) Model-driven smart contract generation leveraging chatgpt. In: International Conference On Systems Engineering, Springer, pp 387\u2013396","DOI":"10.1007\/978-3-031-40579-2_37"},{"key":"7186_CR13","doi-asserted-by":"crossref","unstructured":"Zhao J, Chen X, Yang G et\u00a0al (2023) Automatic smart contract comment generation via large language models and in-context learning. arXiv preprint arXiv:2311.10388","DOI":"10.1016\/j.infsof.2024.107405"},{"key":"7186_CR14","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1007\/978-981-15-2930-6_3","volume":"12","author":"S Majumdar","year":"2020","unstructured":"Majumdar S, Papdeja S, Das PP et al (2020) Comment-mine-a semantic search approach to program comprehension from code comments. Adv Comput Syst Secur 12:29\u201342","journal-title":"Adv Comput Syst Secur"},{"key":"7186_CR15","doi-asserted-by":"crossref","unstructured":"Shinyama Y, Arahori Y, Gondow K (2018) Analyzing code comments to boost program comprehension. In: 2018 25th Asia-Pacific Software Engineering Conference (APSEC), IEEE, pp 325\u2013334","DOI":"10.1109\/APSEC.2018.00047"},{"key":"7186_CR16","doi-asserted-by":"crossref","unstructured":"Zhang J, Wang X, Zhang H et\u00a0al (2019) A novel neural source code representation based on abstract syntax tree. In: 2019 IEEE\/ACM 41st International Conference on Software Engineering (ICSE), IEEE, pp 783\u2013794","DOI":"10.1109\/ICSE.2019.00086"},{"key":"7186_CR17","doi-asserted-by":"crossref","unstructured":"Tai KS, Socher R, Manning CD (2015) Improved semantic representations from tree-structured long short-term memory networks. arXiv preprint arXiv:1503.00075","DOI":"10.3115\/v1\/P15-1150"},{"key":"7186_CR18","doi-asserted-by":"publisher","first-page":"126453","DOI":"10.1016\/j.neucom.2023.126453","volume":"555","author":"Y Chu","year":"2023","unstructured":"Chu Y, Cao H, Diao Y et al (2023) Refined sbert: Representing sentence bert in manifold space. Neurocomputing 555:126453","journal-title":"Neurocomputing"},{"key":"7186_CR19","unstructured":"Chang Y, Wang X, Wang J et\u00a0al (2023) A survey on evaluation of large language models. arXiv preprint arXiv:2307.03109"},{"issue":"8","key":"7186_CR20","doi-asserted-by":"publisher","first-page":"1930","DOI":"10.1038\/s41591-023-02448-8","volume":"29","author":"AJ Thirunavukarasu","year":"2023","unstructured":"Thirunavukarasu AJ, Ting DSJ, Elangovan K et al (2023) Large language models in medicine. Nat Med 29(8):1930\u20131940","journal-title":"Nat Med"},{"key":"7186_CR21","doi-asserted-by":"publisher","first-page":"102274","DOI":"10.1016\/j.lindif.2023.102274","volume":"103","author":"E Kasneci","year":"2023","unstructured":"Kasneci E, Se\u00dfler K, K\u00fcchemann S et al (2023) Chatgpt for good? On opportunities and challenges of large language models for education. Learn Individ Differ 103:102274","journal-title":"Learn Individ Differ"},{"key":"7186_CR22","unstructured":"Touvron H, Lavril T, Izacard G et\u00a0al (2023a) Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971"},{"key":"7186_CR23","unstructured":"Touvron H, Martin L, Stone K et\u00a0al (2023b) Llama 2: Open foundation and fine-tuned chat models. arXiv preprint arXiv:2307.09288"},{"key":"7186_CR24","unstructured":"Zeng A, Liu X, Du Z et\u00a0al (2022) Glm-130b: An open bilingual pre-trained model. arXiv preprint arXiv:2210.02414"},{"key":"7186_CR25","unstructured":"Yang A, Xiao B, Wang B et\u00a0al (2023) Baichuan 2: Open large-scale language models. arXiv preprint arXiv:2309.10305"},{"key":"7186_CR26","unstructured":"Hu EJ, Shen Y, Wallis P et\u00a0al (2021) Lora: Low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685"},{"key":"7186_CR27","unstructured":"Dettmers T, Pagnoni A, Holtzman A et\u00a0al (2023) Qlora: Efficient finetuning of quantized llms. arXiv preprint arXiv:2305.14314"},{"key":"7186_CR28","doi-asserted-by":"crossref","unstructured":"Li XL, Liang P (2021) Prefix-tuning: Optimizing continuous prompts for generation. arXiv preprint arXiv:2101.00190","DOI":"10.18653\/v1\/2021.acl-long.353"},{"key":"7186_CR29","doi-asserted-by":"crossref","unstructured":"Liu X, Ji K, Fu Y et\u00a0al (2022) P-tuning: Prompt tuning can be comparable to fine-tuning across scales and tasks. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, (Volume 2: Short Papers), pp 61\u201368","DOI":"10.18653\/v1\/2022.acl-short.8"},{"key":"7186_CR30","doi-asserted-by":"crossref","unstructured":"Liu X, Ji K, Fu Y et\u00a0al (2021) P-tuning v2: Prompt tuning can be comparable to fine-tuning universally across scales and tasks. arXiv preprint arXiv:2110.07602","DOI":"10.18653\/v1\/2022.acl-short.8"},{"key":"7186_CR31","unstructured":"Cui J, Li Z, Yan Y et\u00a0al (2023) Chatlaw: Open-source legal large language model with integrated external knowledge bases. arXiv preprint arXiv:2306.16092"},{"key":"7186_CR32","unstructured":"Wang H, Liu C, Xi N et\u00a0al (2023) Huatuo: tuning llama model with Chinese medical knowledge. arXiv preprint arXiv:2304.06975"},{"key":"7186_CR33","doi-asserted-by":"publisher","first-page":"101227","DOI":"10.1016\/j.pmcj.2020.101227","volume":"67","author":"M Almakhour","year":"2020","unstructured":"Almakhour M, Sliman L, Samhat AE et al (2020) Verification of smart contracts: a survey. Pervasive Mob Comput 67:101227","journal-title":"Pervasive Mob Comput"},{"key":"7186_CR34","unstructured":"Samreen NF, Alalfi MH (2021) A survey of security vulnerabilities in ethereum smart contracts. arXiv preprint arXiv:2105.06974"},{"key":"7186_CR35","unstructured":"Praitheeshan P, Pan L, Yu J et\u00a0al (2019) Security analysis methods on ethereum smart contract vulnerabilities: a survey. arXiv preprint arXiv:1908.08605"},{"key":"7186_CR36","doi-asserted-by":"publisher","first-page":"12178","DOI":"10.1109\/JIOT.2023.3241544","volume":"10","author":"D He","year":"2023","unstructured":"He D, Wu R, Li X et al (2023) Detection of vulnerabilities of blockchain smart contracts. IEEE Internet Things J 10:12178","journal-title":"IEEE Internet Things J"},{"issue":"7","key":"7186_CR37","first-page":"24","volume":"32","author":"C Xiang","year":"2021","unstructured":"Xiang C, Zhanqi C, Zan MGW, Guang Y (2021) Summary of automated generation methods for code annotation. J Softw 32(7):24","journal-title":"J Softw"},{"issue":"6","key":"7186_CR38","doi-asserted-by":"publisher","first-page":"2515","DOI":"10.1016\/j.jksuci.2020.04.001","volume":"34","author":"T Iqbal","year":"2022","unstructured":"Iqbal T, Qureshi S (2022) The survey: text generation models in deep learning. J King Saud Univ Comput Inf Sci 34(6):2515\u20132528","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"7186_CR39","unstructured":"Roziere B, Gehring J, Gloeckle F et\u00a0al (2023) Code llama: Open foundation models for code. arXiv preprint arXiv:2308.12950"},{"key":"7186_CR40","doi-asserted-by":"crossref","unstructured":"Zheng Q, Xia X, Zou X et\u00a0al (2023) Codegeex: A pre-trained model for code generation with multilingual evaluations on humaneval-x. arXiv preprint arXiv:2303.17568","DOI":"10.1145\/3580305.3599790"},{"key":"7186_CR41","unstructured":"Li R, Allal LB, Zi Y et\u00a0al (2023) Starcoder: may the source be with you! arXiv preprint arXiv:2305.06161"},{"key":"7186_CR42","doi-asserted-by":"crossref","unstructured":"Feng H, Fu X, Sun H et\u00a0al (2020) Efficient vulnerability detection based on abstract syntax tree and deep learning. In: IEEE INFOCOM 2020-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE, pp 722\u2013727","DOI":"10.1109\/INFOCOMWKSHPS50562.2020.9163061"},{"key":"7186_CR43","doi-asserted-by":"publisher","first-page":"4689","DOI":"10.1007\/s00521-018-3817-2","volume":"32","author":"T Zhang","year":"2020","unstructured":"Zhang T, Mouch\u00e8re H, Viard-Gaudin C (2020) A tree-BLSTM-based recognition system for online handwritten mathematical expressions. Neural Comput Appl 32:4689\u20134708","journal-title":"Neural Comput Appl"},{"key":"7186_CR44","doi-asserted-by":"publisher","first-page":"14344","DOI":"10.1109\/ACCESS.2020.2965964","volume":"8","author":"W Yu","year":"2020","unstructured":"Yu W, Yi M, Huang X et al (2020) Make it directly: event extraction based on tree-LSTM and BI-GRU. IEEE Access 8:14344\u201314354","journal-title":"IEEE Access"},{"key":"7186_CR45","doi-asserted-by":"crossref","unstructured":"Zhou X, Lu L (2020) Defect prediction via lstm based on sequence and tree structure. 2020 IEEE 20th International Conference on Software Quality. IEEE, Reliability and Security (QRS), pp 366\u2013373","DOI":"10.1109\/QRS51102.2020.00055"},{"key":"7186_CR46","doi-asserted-by":"crossref","unstructured":"Zhao M, Hamarneh G (2019) Tree-lstm: using lstm to encode memory in anatomical tree prediction from 3d images. In: International Workshop on Machine Learning in Medical Imaging, Springer, pp 637\u2013645","DOI":"10.1007\/978-3-030-32692-0_73"},{"key":"7186_CR47","unstructured":"Harer J, Reale C, Chin P (2019) Tree-transformer: A transformer-based method for correction of tree-structured data. arXiv preprint arXiv:1908.00449"},{"issue":"8","key":"7186_CR48","doi-asserted-by":"publisher","first-page":"1295","DOI":"10.3390\/electronics9081295","volume":"9","author":"M Ahmed","year":"2020","unstructured":"Ahmed M, Seraj R, Islam SMS (2020) The k-means algorithm: a comprehensive survey and performance evaluation. Electronics 9(8):1295","journal-title":"Electronics"},{"key":"7186_CR49","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1007\/s10489-017-0972-6","volume":"48","author":"J Garc\u00eda","year":"2018","unstructured":"Garc\u00eda J, Crawford B, Soto R et al (2018) A k-means binarization framework applied to multidimensional knapsack problem. Appl Intel 48:357\u2013380","journal-title":"Appl Intel"},{"key":"7186_CR50","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1007\/s00521-022-07554-1","volume":"37","author":"P Olukanmi","year":"2022","unstructured":"Olukanmi P, Nelwamondo F, Marwala T (2022) k-means-mind: comparing seeds without repeated k-means runs. Neural Comput Appl 37:723","journal-title":"Neural Comput Appl"},{"issue":"5","key":"7186_CR51","first-page":"4907","volume":"53","author":"J Liao","year":"2023","unstructured":"Liao J, Li H, Feng A et al (2023) Domestic pig sound classification based on transformercnn. Appl Intel 53(5):4907\u20134923","journal-title":"Appl Intel"},{"issue":"4","key":"7186_CR52","doi-asserted-by":"publisher","first-page":"4302","DOI":"10.1007\/s10489-022-03563-8","volume":"53","author":"L Kang","year":"2023","unstructured":"Kang L, He S, Wang M et al (2023) Bilingual attention based neural machine translation. Appl Intel 53(4):4302\u20134315","journal-title":"Appl Intel"},{"key":"7186_CR53","doi-asserted-by":"crossref","unstructured":"Wieting J, Berg-Kirkpatrick T, Gimpel K et\u00a0al (2019) Beyond bleu: training neural machine translation with semantic similarity. arXiv preprint arXiv:1909.06694","DOI":"10.18653\/v1\/P19-1427"},{"key":"7186_CR54","unstructured":"Cao Y, Kang Y, Sun L (2023) Instruction mining: High-quality instruction data selection for large language models. arXiv preprint arXiv:2307.06290 1(3):6"},{"key":"7186_CR55","doi-asserted-by":"crossref","unstructured":"Feng Z, Guo D, Tang D et\u00a0al (2020) Codebert: A pre-trained model for programming and natural languages. arXiv preprint arXiv:2002.08155","DOI":"10.18653\/v1\/2020.findings-emnlp.139"},{"key":"7186_CR56","unstructured":"Guo D, Ren S, Lu S et\u00a0al (2020) Graphcodebert: Pre-training code representations with data flow. arXiv preprint arXiv:2009.08366"},{"key":"7186_CR57","doi-asserted-by":"crossref","unstructured":"Ahmad WU, Chakraborty S, Ray B et\u00a0al (2021) Unified pre-training for program understanding and generation. arXiv preprint arXiv:2103.06333","DOI":"10.18653\/v1\/2021.naacl-main.211"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07186-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-025-07186-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07186-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T05:56:52Z","timestamp":1744351012000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-025-07186-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,11]]},"references-count":57,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2025,4]]}},"alternative-id":["7186"],"URL":"https:\/\/doi.org\/10.1007\/s11227-025-07186-x","relation":{},"ISSN":["1573-0484"],"issn-type":[{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,11]]},"assertion":[{"value":"13 March 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 April 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no relevant financial or non-financial interests to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article contains no studies with human or animal participants conducted by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"No involving human participants and\/or animals.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human or animal rights"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}],"article-number":"731"}}