{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T15:06:20Z","timestamp":1776783980820,"version":"3.51.2"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031545337","type":"print"},{"value":"9783031545344","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-54534-4_19","type":"book-chapter","created":{"date-parts":[[2024,3,19]],"date-time":"2024-03-19T10:39:18Z","timestamp":1710844758000},"page":"267-280","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Detecting Design Patterns in\u00a0Android Applications with\u00a0CodeBERT Embeddings and\u00a0CK Metrics"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4578-5011","authenticated-orcid":false,"given":"Gcinizwe","family":"Dlamini","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0005-6805-611X","authenticated-orcid":false,"given":"Usman","family":"Ahmad","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0001-9454-664X","authenticated-orcid":false,"given":"Lionel Randall","family":"Kharkrang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3289-8188","authenticated-orcid":false,"given":"Vladimir","family":"Ivanov","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,12]]},"reference":[{"key":"19_CR1","unstructured":"F droid website. f-droid (2019). https:\/\/fdroid.org\/en\/about\/. Accessed 17 Nov 17 2019"},{"key":"19_CR2","doi-asserted-by":"crossref","unstructured":"Ahmad, W.U., Chakraborty, S., Ray, B., Chang, K.W.: A transformer-based approach for source code summarization. arXiv preprint: arXiv:2005.00653 (2020)","DOI":"10.18653\/v1\/2020.acl-main.449"},{"issue":"7","key":"19_CR3","doi-asserted-by":"publisher","first-page":"1945","DOI":"10.1016\/j.jss.2013.03.063","volume":"86","author":"A Ampatzoglou","year":"2013","unstructured":"Ampatzoglou, A., Charalampidou, S., Stamelos, I.: Research state of the art on GoF design patterns: a mapping study. J. Syst. Softw. 86(7), 1945\u20131964 (2013)","journal-title":"J. Syst. Softw."},{"key":"19_CR4","unstructured":"Aniche, M.: Java code metrics calculator (CK) (2015). https:\/\/github.com\/mauricioaniche\/ck\/"},{"key":"19_CR5","doi-asserted-by":"crossref","unstructured":"Arcos-Medina, G., Men\u00e9ndez, J., Vallejo, J.: Comparative study of performance and productivity of MVC and MVVM design patterns. KnE Eng., 241\u2013252 (2018)","DOI":"10.18502\/keg.v1i2.1498"},{"key":"19_CR6","unstructured":"Ba, H.: Improving detection of credit card fraudulent transactions using generative adversarial networks. arXiv preprint: arXiv:1907.03355 (2019)"},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Chekhaba, C., Rebatchi, H., ElBoussaidi, G., Moha, N., Kpodjedo, S.: Coach: classification-based architectural patterns detection in android apps. In: Proceedings of the 36th Annual ACM Symposium on Applied Computing, pp. 1429\u20131438 (2021)","DOI":"10.1145\/3412841.3442018"},{"key":"19_CR8","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1016\/j.asoc.2014.10.027","volume":"26","author":"A Chihada","year":"2015","unstructured":"Chihada, A., Jalili, S., Hasheminejad, S.M.H., Zangooei, M.H.: Source code and design conformance, design pattern detection from source code by classification approach. Appl. Soft Comput. 26, 357\u2013367 (2015)","journal-title":"Appl. Soft Comput."},{"key":"19_CR9","doi-asserted-by":"crossref","unstructured":"Dabain, H., Manzer, A., Tzerpos, V.: Design pattern detection using finder. In: Proceedings of the 30th Annual ACM Symposium on Applied Computing, pp. 1586\u20131593 (2015)","DOI":"10.1145\/2695664.2695900"},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Daoudi, A., ElBoussaidi, G., Moha, N., Kpodjedo, S.: An exploratory study of MVC-based architectural patterns in android apps. In: Proceedings of the 34th ACM\/SIGAPP Symposium on Applied Computing, pp. 1711\u20131720 (2019)","DOI":"10.1145\/3297280.3297447"},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Feng, Z., et al.: CodeBERT: a pre-trained model for programming and natural languages. arXiv preprint: arXiv:2002.08155 (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.139"},{"issue":"1","key":"19_CR12","first-page":"23","volume":"1","author":"A Gupta","year":"2015","unstructured":"Gupta, A., Sharma, S.: Software maintenance: challenges and issues. Issues 1(1), 23\u201325 (2015)","journal-title":"Issues"},{"key":"19_CR13","unstructured":"Heidenreich, F., et al.: Model-driven modernisation of java programs with JaMoPP. In: Joint Proceedings of the First International Workshop on Model-Driven Software Migration (MDSM 2011) and the Fifth International Workshop on System Quality and Maintainability (SQM 2011), pp. 8\u201311 (2011)"},{"key":"19_CR14","unstructured":"Hua, W., Liu, G.: Transformer-based networks over tree structures for code classification. Appl. Intell., 1\u201315 (2022)"},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Hunt, J., Hunt, J.: Gang of four design patterns. Scala Des. Patterns: Patterns Pract. Reuse Des., 135\u2013136 (2013)","DOI":"10.1007\/978-3-319-02192-8_16"},{"issue":"7","key":"19_CR16","doi-asserted-by":"publisher","first-page":"1491","DOI":"10.3390\/sym14071491","volume":"14","author":"M Kouli","year":"2022","unstructured":"Kouli, M., Rasoolzadegan, A.: A feature-based method for detecting design patterns in source code. Symmetry 14(7), 1491 (2022)","journal-title":"Symmetry"},{"key":"19_CR17","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.jss.2016.11.030","volume":"125","author":"BB Mayvan","year":"2017","unstructured":"Mayvan, B.B., Rasoolzadegan, A., Yazdi, Z.G.: The state of the art on design patterns: a systematic mapping of the literature. J. Syst. Softw. 125, 93\u2013118 (2017)","journal-title":"J. Syst. Softw."},{"key":"19_CR18","doi-asserted-by":"publisher","first-page":"111179","DOI":"10.1016\/j.jss.2021.111179","volume":"185","author":"N Nazar","year":"2022","unstructured":"Nazar, N., Aleti, A., Zheng, Y.: Feature-based software design pattern detection. J. Syst. Softw. 185, 111179 (2022)","journal-title":"J. Syst. Softw."},{"issue":"21","key":"19_CR19","doi-asserted-by":"publisher","first-page":"2706","DOI":"10.3390\/electronics10212706","volume":"10","author":"I Paik","year":"2021","unstructured":"Paik, I., Wang, J.W.: Improving text-to-code generation with features of code graph on GPT-2. Electronics 10(21), 2706 (2021)","journal-title":"Electronics"},{"key":"19_CR20","unstructured":"Prokhorenkova, L., Gusev, G., Vorobev, A., Dorogush, A.V., Gulin, A.: CatBoost: unbiased boosting with categorical features. In: Advances in Neural Information Processing Systems, vol. 31 (2018)"},{"key":"19_CR21","unstructured":"Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I.: Language models are unsupervised multitask learners (2019)"},{"issue":"5500","key":"19_CR22","doi-asserted-by":"publisher","first-page":"2319","DOI":"10.1126\/science.290.5500.2319","volume":"290","author":"JB Tenenbaum","year":"2000","unstructured":"Tenenbaum, J.B., Silva, V.D., Langford, J.C.: A global geometric framework for nonlinear dimensionality reduction. Science 290(5500), 2319\u20132323 (2000)","journal-title":"Science"},{"key":"19_CR23","unstructured":"Wolf, T., et al.: Transformers: state-of-the-art natural language processing. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pp. 38\u201345. Association for Computational Linguistics (2020). https:\/\/www.aclweb.org\/anthology\/2020.emnlp-demos.6"},{"key":"19_CR24","doi-asserted-by":"publisher","first-page":"768","DOI":"10.1016\/j.future.2022.12.024","volume":"141","author":"L Yuan","year":"2023","unstructured":"Yuan, L., Yu, S., Yang, Z., Duan, M., Li, K.: A data balancing approach based on generative adversarial network. Futur. Gener. Comput. Syst. 141, 768\u2013776 (2023)","journal-title":"Futur. Gener. Comput. Syst."},{"key":"19_CR25","doi-asserted-by":"crossref","unstructured":"Zhang, H., Zhang, H., Pirbhulal, S., Wu, W., Albuquerque, V.H.C.D.: Active balancing mechanism for imbalanced medical data in deep learning-based classification models. ACM Trans. Multimedia Comput., Commun. Appl. (TOMM) 16(1s), 1\u201315 (2020)","DOI":"10.1145\/3357253"},{"key":"19_CR26","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1016\/j.patcog.2017.07.024","volume":"72","author":"T Zhu","year":"2017","unstructured":"Zhu, T., Lin, Y., Liu, Y.: Synthetic minority oversampling technique for multiclass imbalance problems. Pattern Recogn. 72, 327\u2013340 (2017)","journal-title":"Pattern Recogn."}],"container-title":["Lecture Notes in Computer Science","Analysis of Images, Social Networks and Texts"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-54534-4_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,19]],"date-time":"2024-03-19T10:42:50Z","timestamp":1710844970000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-54534-4_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031545337","9783031545344"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-54534-4_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"12 March 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIST","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Analysis of Images, Social Networks and Texts","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Yerevan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Armenia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aist2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aistconf.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easy Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"93","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1.62","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Out of the 93 submission, 17 were rejected before being sent to peer review.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}