{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T19:47:51Z","timestamp":1769284071179,"version":"3.49.0"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,6,5]],"date-time":"2025-06-05T00:00:00Z","timestamp":1749081600000},"content-version":"vor","delay-in-days":4,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"2021 Annual Youth Scientific and Technological Talents Cultivation Program of AHTCM, China","award":["No.2021qnyc131"],"award-info":[{"award-number":["No.2021qnyc131"]}]},{"name":"Ministry of Education Transn-Language Network Industry-Academia Collaboration Collaborative Education Project","award":["No.241000630295929"],"award-info":[{"award-number":["No.241000630295929"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J. King Saud Univ. Comput. Inf. Sci."],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s44443-025-00075-6","type":"journal-article","created":{"date-parts":[[2025,6,5]],"date-time":"2025-06-05T08:37:43Z","timestamp":1749112663000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["EduFuncSum: a function-wise progressive transformer for code summarization in undergraduate programming education"],"prefix":"10.1007","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-1777-3853","authenticated-orcid":false,"given":"Yi","family":"Rong","sequence":"first","affiliation":[]},{"given":"Manping","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Roubing","family":"Li","sequence":"additional","affiliation":[]},{"given":"Lin","family":"Xin","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5695-3187","authenticated-orcid":false,"given":"Wenting","family":"Bao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,5]]},"reference":[{"key":"75_CR1","doi-asserted-by":"crossref","unstructured":"Ahmad WU, Chakraborty S, Ray B, Chang K-W (2020) A transformer-based approach for source code summarization. arXiv:2005.00653","DOI":"10.18653\/v1\/2020.acl-main.449"},{"key":"75_CR2","doi-asserted-by":"crossref","unstructured":"Ahmad WU, Chakraborty S, Ray B, Chang K-W (2021) Unified pre-training for program understanding and generation. arXiv:2103.06333","DOI":"10.18653\/v1\/2021.naacl-main.211"},{"issue":"8","key":"75_CR3","doi-asserted-by":"publisher","first-page":"3490","DOI":"10.3390\/en16083490","volume":"16","author":"N Albarella","year":"2023","unstructured":"Albarella N, Lui DG, Petrillo A, Santini S (2023) A hybrid deep reinforcement learning and optimal control architecture for autonomous highway driving. Energies 16(8):3490","journal-title":"Energies"},{"issue":"4","key":"75_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3212695","volume":"51","author":"M Allamanis","year":"2018","unstructured":"Allamanis M, Barr ET, Devanbu P, Sutton C (2018) A survey of machine learning for big code and naturalness. ACM Computing Surveys (CSUR). 51(4):1\u201337","journal-title":"ACM Computing Surveys (CSUR)."},{"key":"75_CR5","doi-asserted-by":"crossref","unstructured":"Allamanis M, Barr ET, Bird C, Sutton C (2014) Learning natural coding conventions. In: Proceedings of the 22nd Acm Sigsoft International Symposium on Foundations of Software Engineering, pp. 281\u2013293","DOI":"10.1145\/2635868.2635883"},{"key":"75_CR6","doi-asserted-by":"crossref","unstructured":"Allamanis M, Barr ET, Bird C, Sutton C (2014) Learning natural coding conventions. In: Proceedings of the 22nd Acm Sigsoft International Symposium on Foundations of Software Engineering, pp. 281\u2013293","DOI":"10.1145\/2635868.2635883"},{"key":"75_CR7","unstructured":"Allamanis M, Peng H, Sutton C (2016) A convolutional attention network for extreme summarization of source code. In: International Conference on Machine Learning, pp. 2091\u20132100. PMLR"},{"key":"75_CR8","unstructured":"Alon U, Brody S, Levy O, Yahav E (2018) code2seq: Generating sequences from structured representations of code. arXiv:1808.01400"},{"key":"75_CR9","unstructured":"Anil R, Dai AM, Firat O, Johnson M, Lepikhin D, Passos A, Shakeri S, Taropa E, Bailey P, Chen Z et\u00a0al (2023) Palm 2 technical report. arXiv:2305.10403"},{"key":"75_CR10","unstructured":"Bahdanau D, Cho K, Bengio Y (2014) Neural machine translation by jointly learning to align and translate. arXiv:1409.0473"},{"issue":"4","key":"75_CR11","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1080\/08993400600997096","volume":"16","author":"S Bergin","year":"2006","unstructured":"Bergin S, Reilly R (2006) Predicting introductory programming performance: A multi-institutional multivariate study. Comput Sci Educ 16(4):303\u2013323","journal-title":"Comput Sci Educ"},{"key":"75_CR12","doi-asserted-by":"crossref","unstructured":"Chen Q, Hu H, Liu Z (2019) Code summarization with abstract syntax tree. In: Neural Information Processing: 26th International Conference, ICONIP 2019, Sydney, NSW, Australia, December 12\u201315, 2019, Proceedings, Part V 26, pp. 652\u2013660. Springer","DOI":"10.1007\/978-3-030-36802-9_69"},{"key":"75_CR13","unstructured":"Chen M, Tworek J, Jun H, Yuan Q, Pinto HPDO, Kaplan J, Edwards H, Burda Y, Joseph N, Brockman G et\u00a0al (2021) Evaluating large language models trained on code. arXiv:2107.03374"},{"key":"75_CR14","unstructured":"Dacey ME (2018) A Study of Novice Programmer Performance and Programming Pedagogy. University of Wales Trinity Saint David (United Kingdom), ???"},{"key":"75_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.chbr.2022.100213","volume":"7","author":"DK Davis","year":"2022","unstructured":"Davis DK, Zhu F (2022) Analysis of software developers\u2019 coding behavior: A survey of visualization analysis techniques using eye trackers. Computers in Human Behavior Reports. 7:100213","journal-title":"Computers in Human Behavior Reports."},{"key":"75_CR16","unstructured":"Devlin J, Chang M-W, Lee K, Toutanova K (2019) Bert: Pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (long and Short Papers), pp. 4171\u20134186"},{"key":"75_CR17","doi-asserted-by":"crossref","unstructured":"Feng Z, Guo D, Tang D, Duan N, Feng X, Gong M, Shou L, Qin B, Liu T, Jiang D et\u00a0al (2020) Codebert: A pre-trained model for programming and natural languages. arXiv:2002.08155","DOI":"10.18653\/v1\/2020.findings-emnlp.139"},{"key":"75_CR18","unstructured":"Guo D, Ren S, Lu S, Feng Z, Tang D, Liu S, Zhou L, Duan N, Svyatkovskiy A, Fu S et\u00a0al (2020) Graphcodebert: Pre-training code representations with data flow. arXiv:2009.08366"},{"key":"75_CR19","doi-asserted-by":"crossref","unstructured":"Haiduc S, Aponte J, Moreno L, Marcus A (2010) On the use of automated text summarization techniques for summarizing source code. In: 2010 17th Working Conference on Reverse Engineering, pp. 35\u201344. IEEE","DOI":"10.1109\/WCRE.2010.13"},{"key":"75_CR20","unstructured":"Haldar R, Hockenmaier J (2024) Analyzing the performance of large language models on code summarization. arXiv:2404.08018"},{"key":"75_CR21","doi-asserted-by":"crossref","unstructured":"Haque S, LeClair A, Wu L, McMillan C (2020) Improved automatic summarization of subroutines via attention to file context. In: Proceedings of the 17th International Conference on Mining Software Repositories, pp. 300\u2013310","DOI":"10.1145\/3379597.3387449"},{"issue":"5","key":"75_CR22","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1145\/2902362","volume":"59","author":"A Hindle","year":"2016","unstructured":"Hindle A, Barr ET, Gabel M, Su Z, Devanbu P (2016) On the naturalness of software. Commun ACM 59(5):122\u2013131","journal-title":"Commun ACM"},{"key":"75_CR23","doi-asserted-by":"crossref","unstructured":"Hu X, Li G, Xia X, Lo D, Jin Z (2018) Deep code comment generation. In: Proceedings of the 26th Conference on Program Comprehension, pp. 200\u2013210","DOI":"10.1145\/3196321.3196334"},{"key":"75_CR24","unstructured":"Husain H, Wu H-H, Gazit T, Allamanis M, Brockschmidt M (2019) Codesearchnet challenge: Evaluating the state of semantic code search. arXiv preprint arXiv:1909.09436"},{"key":"75_CR25","unstructured":"Husain H, Wu H-H, Gazit T, Allamanis M, Brockschmidt M (2019) Codesearchnet challenge: Evaluating the state of semantic code search. arXiv:1909.09436"},{"key":"75_CR26","doi-asserted-by":"crossref","unstructured":"Hu X, Xia X, Lo D, Wan Z, Chen Q, Zimmermann T (2022) Practitioners\u2019 expectations on automated code comment generation. In: Proceedings of the 44th International Conference on Software Engineering, pp. 1693\u20131705","DOI":"10.1145\/3510003.3510152"},{"key":"75_CR27","doi-asserted-by":"crossref","unstructured":"Hu X, Xia X, Lo D, Wan Z, Chen Q, Zimmermann T (2022) Practitioners\u2019 expectations on automated code comment generation. In: Proceedings of the 44th International Conference on Software Engineering, pp. 1693\u20131705","DOI":"10.1145\/3510003.3510152"},{"key":"75_CR28","doi-asserted-by":"crossref","unstructured":"Iyer S, Konstas I, Cheung A, Zettlemoyer L (2016a) Summarizing source code using a neural attention model. In: 54th Annual Meeting of the Association for Computational Linguistics 2016, pp. 2073\u20132083. Association for Computational Linguistics","DOI":"10.18653\/v1\/P16-1195"},{"key":"75_CR29","doi-asserted-by":"crossref","unstructured":"Iyer S, Konstas I, Cheung A, Zettlemoyer L (2016b) Summarizing source code using a neural attention model. In: 54th Annual Meeting of the Association for Computational Linguistics 2016, pp. 2073\u20132083. Association for Computational Linguistics","DOI":"10.18653\/v1\/P16-1195"},{"key":"75_CR30","unstructured":"Kanade A, Maniatis P, Balakrishnan G, Shi K (2019) Pre-trained contextual embedding of source code"},{"key":"75_CR31","unstructured":"Kanade A, Maniatis P, Balakrishnan G, Shi K (2020) Learning and evaluating contextual embedding of source code. In: International Conference on Machine Learning, pp. 5110\u20135121. PMLR"},{"key":"75_CR32","doi-asserted-by":"crossref","unstructured":"LeClair A, Jiang S, McMillan C (2019) A neural model for generating natural language summaries of program subroutines. In: 2019 IEEE\/ACM 41st International Conference on Software Engineering (ICSE), pp. 795\u2013806. IEEE","DOI":"10.1109\/ICSE.2019.00087"},{"key":"75_CR33","unstructured":"Lin C-Y (2004) Rouge: A package for automatic evaluation of summaries. In: Text Summarization Branches Out, pp. 74\u201381"},{"key":"75_CR34","doi-asserted-by":"crossref","unstructured":"Loyola P, Marrese-Taylor E, Matsuo Y (2017) A neural architecture for generating natural language descriptions from source code changes. arXiv:1704.04856","DOI":"10.18653\/v1\/P17-2045"},{"key":"75_CR35","unstructured":"Lu S, Guo D, Ren S, Huang J, Svyatkovskiy A, Blanco A, Clement CB, Drain D, Jiang D, Tang D, Li G, Zhou L, Shou L, Zhou L, Tufano M, Gong M, Zhou M, Duan N, Sundaresan N, Deng SK, Fu S, Liu S (2021) Codexglue: A machine learning benchmark dataset for code understanding and generation. CoRR. fabs\/2102.04664"},{"key":"75_CR36","doi-asserted-by":"crossref","unstructured":"Malhotra M, Chhabra JK (2018) Class level code summarization based on dependencies and micro patterns. In: 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), pp. 1011\u20131016. IEEE","DOI":"10.1109\/ICICCT.2018.8473199"},{"key":"75_CR37","doi-asserted-by":"crossref","unstructured":"McBurney PW, McMillan C (2014) Automatic documentation generation via source code summarization of method context. In: Proceedings of the 22nd International Conference on Program Comprehension, pp. 279\u2013290","DOI":"10.1145\/2597008.2597149"},{"key":"75_CR38","doi-asserted-by":"crossref","unstructured":"Mou L, Li G, Zhang L, Wang T, Jin Z (2016) Convolutional neural networks over tree structures for programming language processing. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 30","DOI":"10.1609\/aaai.v30i1.10139"},{"key":"75_CR39","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.neucom.2021.05.039","volume":"459","author":"LY Nie","year":"2021","unstructured":"Nie LY, Gao C, Zhong Z, Lam W, Liu Y, Xu Z (2021) Coregen: Contextualized code representation learning for commit message generation. Neurocomputing 459:97\u2013107","journal-title":"Neurocomputing"},{"issue":"6","key":"75_CR40","doi-asserted-by":"publisher","first-page":"4833","DOI":"10.1007\/s10664-020-09870-3","volume":"25","author":"S Panichella","year":"2020","unstructured":"Panichella S, Zaugg N (2020) An empirical investigation of relevant changes and automation needs in modern code review. Empir Softw Eng 25(6):4833\u20134872","journal-title":"Empir Softw Eng"},{"key":"75_CR41","doi-asserted-by":"crossref","unstructured":"Panthaplackel S, Nie P, Gligoric M, Li JJ, Mooney RJ (2020) Learning to update natural language comments based on code changes. arXiv:2004.12169","DOI":"10.18653\/v1\/2020.acl-main.168"},{"key":"75_CR42","doi-asserted-by":"crossref","unstructured":"Papineni K, Roukos S, Ward T, Zhu W-J (2002) Bleu: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pp. 311\u2013318","DOI":"10.3115\/1073083.1073135"},{"key":"75_CR43","doi-asserted-by":"crossref","unstructured":"Pennington J, Socher R, Manning CD (2014) Glove: Global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532\u20131543","DOI":"10.3115\/v1\/D14-1162"},{"key":"75_CR44","doi-asserted-by":"crossref","unstructured":"Roy D, Fakhoury S, Arnaoudova V (2021) Reassessing automatic evaluation metrics for code summarization tasks. In: Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp. 1105\u20131116","DOI":"10.1145\/3468264.3468588"},{"key":"75_CR45","unstructured":"Schonholtz D (2023) A review of repository level prompting for llms. arXiv:2312.10101"},{"key":"75_CR46","doi-asserted-by":"crossref","unstructured":"Shi E, Wang Y, Du L, Zhang H, Han S, Zhang D, Sun H (2021) Cast: Enhancing code summarization with hierarchical splitting and reconstruction of abstract syntax trees. arXiv:2108.12987","DOI":"10.18653\/v1\/2021.emnlp-main.332"},{"key":"75_CR47","doi-asserted-by":"publisher","first-page":"11340","DOI":"10.1609\/aaai.v36i10.21385","volume":"36","author":"Z Song","year":"2022","unstructured":"Song Z, King I (2022) Hierarchical heterogeneous graph attention network for syntax-aware summarization. Proceedings of the AAAI Conference on Artificial Intelligence 36:11340\u201311348","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"75_CR48","doi-asserted-by":"publisher","first-page":"111411","DOI":"10.1109\/ACCESS.2019.2931579","volume":"7","author":"X Song","year":"2019","unstructured":"Song X, Sun H, Wang X, Yan J (2019) A survey of automatic generation of source code comments: Algorithms and techniques. IEEE access. 7:111411\u2013111428","journal-title":"IEEE access."},{"key":"75_CR49","doi-asserted-by":"crossref","unstructured":"Stapleton S, Gambhir Y, LeClair A, Eberhart Z, Weimer W, Leach K, Huang Y (2020) A human study of comprehension and code summarization. In: Proceedings of the 28th International Conference on Program Comprehension, pp. 2\u201313","DOI":"10.1145\/3387904.3389258"},{"key":"75_CR50","doi-asserted-by":"crossref","unstructured":"Stapleton S, Gambhir Y, LeClair A, Eberhart Z, Weimer W, Leach K, Huang Y (2020) A human study of comprehension and code summarization. In: Proceedings of the 28th International Conference on Program Comprehension, pp. 2\u201313","DOI":"10.1145\/3387904.3389258"},{"key":"75_CR51","doi-asserted-by":"crossref","unstructured":"Steinmacher I, Silva MAG, Gerosa MA (2014) Barriers faced by newcomers to open source projects: a systematic review. In: Open Source Software: Mobile Open Source Technologies: 10th IFIP WG 2.13 International Conference on Open Source Systems, OSS 2014, San Jos\u00e9, Costa Rica, May 6-9, 2014. Proceedings 10, pp. 153\u2013163. Springer","DOI":"10.1007\/978-3-642-55128-4_21"},{"key":"75_CR52","doi-asserted-by":"crossref","unstructured":"Storey M-A (2005) Theories, methods and tools in program comprehension: past, present and future. In: 13th International Workshop on Program Comprehension (IWPC\u201905), pp. 181\u2013191. IEEE","DOI":"10.1109\/WPC.2005.38"},{"key":"75_CR53","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser \u0141, Polosukhin I (2017) Attention is all you need. Advances in Neural Information Processing Systems. 30"},{"key":"75_CR54","doi-asserted-by":"crossref","unstructured":"Wang Y, Wang W, Joty S, Hoi SC (2021) Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation. arXiv:2109.00859","DOI":"10.18653\/v1\/2021.emnlp-main.685"},{"key":"75_CR55","doi-asserted-by":"crossref","unstructured":"Wan Y, Zhao Z, Yang M, Xu G, Ying H, Wu J, Yu PS (2018) Improving automatic source code summarization via deep reinforcement learning. In: Proceedings of the 33rd ACM\/IEEE International Conference on Automated Software Engineering, pp. 397\u2013407","DOI":"10.1145\/3238147.3238206"},{"key":"75_CR56","doi-asserted-by":"crossref","unstructured":"Xin D, Wu EY, Lee DJ-L, Salehi N, Parameswaran A (2021) Whither automl? understanding the role of automation in machine learning workflows. In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, pp. 1\u201316","DOI":"10.1145\/3411764.3445306"},{"issue":"6","key":"75_CR57","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1007\/s10664-024-10553-6","volume":"29","author":"X Zhang","year":"2024","unstructured":"Zhang X, Hou X, Qiao X, Song W (2024) A review of automatic source code summarization. Empir Softw Eng 29(6):162","journal-title":"Empir Softw Eng"},{"key":"75_CR58","doi-asserted-by":"crossref","unstructured":"Zhang M, Zhu H, Chang X, Wang Z, Wang H (2023) Astnn-based system for auditing php code. In: 2023 IEEE 3rd International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB), pp. 139\u2013143. IEEE","DOI":"10.1109\/ICEIB57887.2023.10170290"},{"key":"75_CR59","unstructured":"Zhu Y, Pan M (2019) Automatic code summarization: A systematic literature review. arXiv:1909.04352"}],"container-title":["Journal of King Saud University Computer and Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44443-025-00075-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44443-025-00075-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44443-025-00075-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T13:03:08Z","timestamp":1751893388000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44443-025-00075-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6]]},"references-count":59,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["75"],"URL":"https:\/\/doi.org\/10.1007\/s44443-025-00075-6","relation":{},"ISSN":["1319-1578","2213-1248"],"issn-type":[{"value":"1319-1578","type":"print"},{"value":"2213-1248","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6]]},"assertion":[{"value":"24 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 May 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 June 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 June 2025","order":4,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Update","order":5,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The original online version of this article was revised: In this article \u2018Anhui University of Chinese Medicine, Hefei 230012, China\u2019 should have been listed as main affiliation due to Open Access funding.","order":6,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}}],"article-number":"61"}}