{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:51:20Z","timestamp":1742914280826,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031545207"},{"type":"electronic","value":"9783031545214"}],"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\/978-3-031-54521-4_16","type":"book-chapter","created":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T06:02:31Z","timestamp":1708581751000},"page":"284-302","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enrich Code Search Query Semantics with\u00a0Raw Descriptions"],"prefix":"10.1007","author":[{"given":"Xiangzheng","family":"Liu","sequence":"first","affiliation":[]},{"given":"Jianxun","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Haize","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Yi","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,23]]},"reference":[{"key":"16_CR1","doi-asserted-by":"crossref","unstructured":"Cambronero, J., Li, H., Kim, S., Sen, K., Chandra, S.: When deep learning met code search. In: Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp. 964\u2013974 (2019)","DOI":"10.1145\/3338906.3340458"},{"key":"16_CR2","doi-asserted-by":"crossref","unstructured":"Chen, Q., Zhou, M.: A neural framework for retrieval and summarization of source code. In: Proceedings of the 33rd ACM\/IEEE International Conference on Automated Software Engineering, pp. 826\u2013831 (2018)","DOI":"10.1145\/3238147.3240471"},{"key":"16_CR3","doi-asserted-by":"crossref","unstructured":"Cheng, Y., Kuang, L.: CSRS: code search with relevance matching and semantic matching. In: Proceedings of the 30th IEEE\/ACM International Conference on Program Comprehension, pp. 533\u2013542 (2022)","DOI":"10.1145\/3524610.3527889"},{"key":"16_CR4","unstructured":"Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"16_CR5","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"},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Gu, X., Zhang, H., Kim, S.: Deep code search. In: Proceedings of the 40th International Conference on Software Engineering, pp. 933\u2013944 (2018)","DOI":"10.1145\/3180155.3180167"},{"key":"16_CR7","unstructured":"Guo, D., et al.: GraphCodeBERT: pre-training code representations with data flow. arXiv preprint arXiv:2009.08366 (2020)"},{"key":"16_CR8","doi-asserted-by":"crossref","unstructured":"Haiduc, S., Aponte, J., Marcus, A.: Supporting program comprehension with source code summarization. In: Proceedings of the 32nd ACM\/IEEE International Conference on Software Engineering, vol. 2, pp. 223\u2013226 (2010)","DOI":"10.1145\/1810295.1810335"},{"key":"16_CR9","doi-asserted-by":"crossref","unstructured":"Haiduc, S., Bavota, G., Marcus, A., Oliveto, R., De Lucia, A., Menzies, T.: Automatic query reformulations for text retrieval in software engineering. In: 2013 35th International Conference on Software Engineering (ICSE), pp. 842\u2013851. IEEE (2013)","DOI":"10.1109\/ICSE.2013.6606630"},{"key":"16_CR10","doi-asserted-by":"crossref","unstructured":"Huang, Q., Yang, Y., Cheng, M.: Deep learning the semantics of change sequences for query expansion, vol. 49, pp. 1600\u20131617. Wiley Online Library (2019)","DOI":"10.1002\/spe.2736"},{"key":"16_CR11","unstructured":"Husain, H., Wu, H.-H., Gazit, T., Allamanis, M., Brockschmidt, M.: CodeSearchNet challenge: evaluating the state of semantic code search. arXiv preprint arXiv:1909.09436 (2019)"},{"issue":"7","key":"16_CR12","doi-asserted-by":"publisher","first-page":"654","DOI":"10.1109\/TSE.2002.1019480","volume":"28","author":"T Kamiya","year":"2002","unstructured":"Kamiya, T., Kusumoto, S., Inoue, K.: CCFinder: a multilinguistic token-based code clone detection system for large scale source code. IEEE Trans. Softw. Eng. 28(7), 654\u2013670 (2002)","journal-title":"IEEE Trans. Softw. Eng."},{"key":"16_CR13","doi-asserted-by":"crossref","unstructured":"Le, T.-D.B., Wang, S., Lo, D.: Multi-abstraction concern localization. In: 2013 IEEE International Conference on Software Maintenance, pp. 364\u2013367. IEEE (2013)","DOI":"10.1109\/ICSM.2013.48"},{"key":"16_CR14","doi-asserted-by":"crossref","unstructured":"LeClair, A., Haque, S., Wu, L., McMillan, C.: Improved code summarization via a graph neural network. In: Proceedings of the 28th International Conference on Program Comprehension, pp. 184\u2013195 (2020)","DOI":"10.1145\/3387904.3389268"},{"key":"16_CR15","doi-asserted-by":"crossref","unstructured":"Ling, C., Lin, Z., Zou, Y., Xie, B.: Adaptive deep code search. In: Proceedings of the 28th International Conference on Program Comprehension, pp. 48\u201359 (2020)","DOI":"10.1145\/3387904.3389278"},{"issue":"2","key":"16_CR16","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1007\/s10618-008-0118-x","volume":"18","author":"E Linstead","year":"2009","unstructured":"Linstead, E., Bajracharya, S., Ngo, T., Rigor, P., Lopes, C., Baldi, P.: Sourcerer: mining and searching internet-scale software repositories. Data Min. Knowl. Disc. 18(2), 300\u2013336 (2009)","journal-title":"Data Min. Knowl. Disc."},{"key":"16_CR17","doi-asserted-by":"crossref","unstructured":"Liu, J., Kim, S., Murali, V., Chaudhuri, S., Chandra, S.: Neural query expansion for code search. In: Proceedings of the 3rd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, pp. 29\u201337 (2019)","DOI":"10.1145\/3315508.3329975"},{"key":"16_CR18","doi-asserted-by":"publisher","first-page":"2839","DOI":"10.1109\/TSE.2022.3233901","volume":"49","author":"S Liu","year":"2023","unstructured":"Liu, S., Xie, X., Siow, J., Ma, L., Meng, G., Liu, Y.: GraphSearchNet: enhancing GNNs via capturing global dependencies for semantic code search. IEEE Trans. Software Eng. 49, 2839\u20132855 (2023)","journal-title":"IEEE Trans. Software Eng."},{"key":"16_CR19","doi-asserted-by":"crossref","unstructured":"Lu, M., Sun, X., Wang, S., Lo, D., Duan, Y.: Query expansion via wordnet for effective code search. In: 2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER), pp. 545\u2013549. IEEE (2015)","DOI":"10.1109\/SANER.2015.7081874"},{"key":"16_CR20","doi-asserted-by":"crossref","unstructured":"Lv, F., Zhang, H., Lou, J., Wang, S., Zhang, D., Zhao, J.: CodeHow: effective code search based on API understanding and extended boolean model (E). In: 2015 30th IEEE\/ACM International Conference on Automated Software Engineering (ASE), pp. 260\u2013270. IEEE (2015)","DOI":"10.1109\/ASE.2015.42"},{"issue":"4","key":"16_CR21","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1111\/0938-8982.t01-1-00018","volume":"16","author":"P McCardle","year":"2001","unstructured":"McCardle, P., Cooper, J.A., Houle, G.R., Karp, N., Paul-Brown, D.: Emergent and early literacy: current status and research directions-introduction. Learn. Disabil. Res. Pract. 16(4), 183\u2013185 (2001)","journal-title":"Learn. Disabil. Res. Pract."},{"key":"16_CR22","doi-asserted-by":"crossref","unstructured":"McMillan, C., Grechanik, M., Poshyvanyk, D., Xie, Q., Fu, C.: Portfolio: finding relevant functions and their usage. In: Proceedings of the 33rd International Conference on Software Engineering, pp. 111\u2013120 (2011)","DOI":"10.1145\/1985793.1985809"},{"key":"16_CR23","doi-asserted-by":"crossref","unstructured":"Nguyen, A.T., Nguyen, T.T., Al-Kofahi, J., Nguyen, H.V., Nguyen, T.N.: A topic-based approach for narrowing the search space of buggy files from a bug report. In: 2011 26th IEEE\/ACM International Conference on Automated Software Engineering (ASE 2011), pp. 263\u2013272. IEEE (2011)","DOI":"10.1109\/ASE.2011.6100062"},{"issue":"5","key":"16_CR24","doi-asserted-by":"publisher","first-page":"771","DOI":"10.1109\/TSC.2016.2560165","volume":"9","author":"L Nie","year":"2016","unstructured":"Nie, L., Jiang, H., Ren, Z., Sun, Z., Li, X.: Query expansion based on crowd knowledge for code search. IEEE Trans. Serv. Comput. 9(5), 771\u2013783 (2016)","journal-title":"IEEE Trans. Serv. Comput."},{"key":"16_CR25","doi-asserted-by":"crossref","unstructured":"Poshyvanyk, D., Petrenko, M., Marcus, A., Xie, X., Liu, D.: Source code exploration with google. In: 2006 22nd IEEE International Conference on Software Maintenance, pp. 334\u2013338. IEEE (2006)","DOI":"10.1109\/ICSM.2006.60"},{"issue":"8","key":"16_CR26","first-page":"9","volume":"1","author":"A Radford","year":"2019","unstructured":"Radford, A., et al.: Language models are unsupervised multitask learners. OpenAI Blog 1(8), 9 (2019)","journal-title":"OpenAI Blog"},{"key":"16_CR27","doi-asserted-by":"crossref","unstructured":"Shuai, J., Xu, L., Liu, C., Yan, M., Xia, X., Lei, Y.: Improving code search with co-attentive representation learning. In: Proceedings of the 28th International Conference on Program Comprehension, pp. 196\u2013207 (2020)","DOI":"10.1145\/3387904.3389269"},{"key":"16_CR28","doi-asserted-by":"crossref","unstructured":"Tian, Y., Lo, D., Lawall, J.: Automated construction of a software-specific word similarity database. In: 2014 Software Evolution Week-IEEE Conference on Software Maintenance, Reengineering, and Reverse Engineering (CSMR-WCRE), pp. 44\u201353. IEEE (2014)","DOI":"10.1109\/CSMR-WCRE.2014.6747213"},{"key":"16_CR29","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"16_CR30","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/j.neunet.2021.09.025","volume":"145","author":"C Wang","year":"2022","unstructured":"Wang, C., et al.: Enriching query semantics for code search with reinforcement learning. Neural Netw. 145, 22\u201332 (2022)","journal-title":"Neural Netw."},{"issue":"4","key":"16_CR31","first-page":"1","volume":"29","author":"W Wang","year":"2020","unstructured":"Wang, W., Li, G., Shen, S., Xia, X., Jin, Z.: Modular tree network for source code representation learning. ACM Trans. Softw. Eng. Methodol. (TOSEM) 29(4), 1\u201323 (2020)","journal-title":"ACM Trans. Softw. Eng. Methodol. (TOSEM)"},{"key":"16_CR32","doi-asserted-by":"crossref","unstructured":"Xu, L., et al.: Two-stage attention-based model for code search with textual and structural features. In: 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 342\u2013353. IEEE (2021)","DOI":"10.1109\/SANER50967.2021.00039"},{"key":"16_CR33","doi-asserted-by":"crossref","unstructured":"Yao, Z., Peddamail, J.R., Sun, H.: CoaCor: code annotation for code retrieval with reinforcement learning. In: The World Wide Web Conference, pp. 2203\u20132214 (2019)","DOI":"10.1145\/3308558.3313632"},{"key":"16_CR34","doi-asserted-by":"crossref","unstructured":"Zhang, J., Wang, X., Zhang, H., Sun, H., Wang, K., Liu, X.: A novel neural source code representation based on abstract syntax tree. In: 2019 IEEE\/ACM 41st International Conference on Software Engineering (ICSE), pp. 783\u2013794. IEEE (2019)","DOI":"10.1109\/ICSE.2019.00086"}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Collaborative Computing: Networking, Applications and Worksharing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-54521-4_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T05:48:52Z","timestamp":1731390532000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-54521-4_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031545207","9783031545214"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-54521-4_16","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"23 February 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CollaborateCom","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Collaborative Computing: Networking, Applications and Worksharing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Corfu","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","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":"4 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"colcom2023","order":10,"name":"conference_id","label":"Conference ID","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":"Cony +","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"176","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":"72","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":"41% - 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":"3","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}