{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T16:48:04Z","timestamp":1761324484565,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":37,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T00:00:00Z","timestamp":1667779200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,11,7]]},"DOI":"10.1145\/3558489.3559075","type":"proceedings-article","created":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T20:08:53Z","timestamp":1668024533000},"page":"92-101","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["API + code = better code summary? insights from an exploratory study"],"prefix":"10.1145","author":[{"given":"Prantik Parashar","family":"Sarmah","sequence":"first","affiliation":[{"name":"IIT Tirupati, India"}]},{"given":"Sridhar","family":"Chimalakonda","sequence":"additional","affiliation":[{"name":"IIT Tirupati, India"}]}],"member":"320","published-online":{"date-parts":[[2022,11,9]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","unstructured":"Wasi Uddin Ahmad Saikat Chakraborty Baishakhi Ray and Kai-Wei Chang. 2020. A transformer-based approach for source code summarization. arXiv preprint arXiv:2005.00653 https:\/\/doi.org\/10.48550\/arXiv.2005.00653","DOI":"10.48550\/arXiv.2005.00653"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3291636"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","unstructured":"Junyan Cheng Iordanis Fostiropoulos and Barry Boehm. 2021. GN-Transformer: Fusing Sequence and Graph Representation for Improved Code Summarization. arXiv preprint arXiv:2111.08874 https:\/\/doi.org\/10.48550\/arXiv.2111.08874","DOI":"10.48550\/arXiv.2111.08874"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-1078"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2889160.2889171"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2104.09340"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","unstructured":"Yuexiu Gao and Chen Lyu. 2022. M2TS: Multi-Scale Multi-Modal Approach Based on Transformer for Source Code Summarization. arXiv preprint arXiv:2203.09707 https:\/\/doi.org\/10.48550\/arXiv.2203.09707","DOI":"10.48550\/arXiv.2203.09707"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","unstructured":"Sonia Haiduc Jairo Aponte and Andrian Marcus. 2010. Supporting program comprehension with source code summarization. In 2010 acm\/ieee 32nd international conference on software engineering. 2 223\u2013226. https:\/\/doi.org\/10.1145\/1810295.1810335 10.1145\/1810295.1810335","DOI":"10.1145\/1810295.1810335"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1908.00449"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3196321.3196334"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","unstructured":"Xing Hu Ge Li Xin Xia David Lo Shuai Lu and Zhi Jin. 2018. Summarizing source code with transferred api knowledge. https:\/\/doi.org\/10.24963\/ijcai.2018\/314 10.24963\/ijcai.2018\/314","DOI":"10.24963\/ijcai.2018"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2011.09.019"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-1195"},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, Cassio de Campos and Marloes H. Maathuis (Eds.) (Proceedings of Machine Learning Research","volume":"63","author":"Jiang Xue","year":"2021","unstructured":"Xue Jiang, Zhuoran Zheng, Chen Lyu, Liang Li, and Lei Lyu. 2021. TreeBERT: A tree-based pre-trained model for programming language. In Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, Cassio de Campos and Marloes H. Maathuis (Eds.) (Proceedings of Machine Learning Research, Vol. 161). PMLR, 54\u201363. https:\/\/proceedings.mlr.press\/v161\/jiang21a.html"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1134285.1134355"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.3115\/1626355.1626389"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3387904.3389268"},{"key":"e_1_3_2_1_18_1","unstructured":"Chin-Yew Lin. 2004. Text Summarization Branches Out chapter ROUGE: A Package for Automatic Evaluation of Summaries."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.3115\/1073445.1073465"},{"key":"e_1_3_2_1_20_1","volume-title":"International Conference on Learning Representations. https:\/\/doi.org\/10","author":"Liu Shangqing","year":"2020","unstructured":"Shangqing Liu, Yu Chen, Xiaofei Xie, Jing Kai Siow, and Yang Liu. 2020. Retrieval-Augmented Generation for Code Summarization via Hybrid GNN. In International Conference on Learning Representations. https:\/\/doi.org\/10.48550\/arXiv.2006.05405"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2015.2465386"},{"key":"e_1_3_2_1_22_1","volume-title":"Proceedings of the 40th annual meeting of the Association for Computational Linguistics. 311\u2013318","author":"Papineni Kishore","year":"2002","unstructured":"Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics. 311\u2013318."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICPC52881.2021.00049"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-19811-3_29"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8851751"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/MS.2010.95"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/1858996.1859006"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","unstructured":"Kai Sheng Tai Richard Socher and Christopher D Manning. 2015. Improved semantic representations from tree-structured long short-term memory networks. arXiv preprint arXiv:1503.00075 https:\/\/doi.org\/10.48550\/arXiv.1503.00075","DOI":"10.48550\/arXiv.1503.00075"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/2597008.2597799"},{"key":"e_1_3_2_1_30_1","volume-title":"\u0141 ukasz Kaiser, and Illia Polosukhin","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141 ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems, 30 (2017)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","unstructured":"Yu Wang Yu Dong Xuesong Lu and Aoying Zhou. 2022. GypSum: Learning Hybrid Representations for Code Summarization. arXiv preprint arXiv:2204.12916 https:\/\/doi.org\/10.48550\/arXiv.2204.12916","DOI":"10.48550\/arXiv.2204.12916"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/SANER.2015.7081848"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","unstructured":"Hongqiu Wu Hai Zhao and Min Zhang. 2020. Code summarization with structure-induced transformer. arXiv preprint arXiv:2012.14710 https:\/\/doi.org\/10.48550\/arXiv.2012.14710","DOI":"10.48550\/arXiv.2012.14710"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2017.2734091"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/2491411.2494587"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377811.3380383"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2017.2782280"}],"event":{"name":"PROMISE '22: 18th International Conference on Predictive Models and Data Analytics in Software Engineering","sponsor":["SIGSOFT ACM Special Interest Group on Software Engineering","NUS NUS"],"location":"Singapore Singapore","acronym":"PROMISE '22"},"container-title":["Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3558489.3559075","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3558489.3559075","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:47:08Z","timestamp":1750178828000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3558489.3559075"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,7]]},"references-count":37,"alternative-id":["10.1145\/3558489.3559075","10.1145\/3558489"],"URL":"https:\/\/doi.org\/10.1145\/3558489.3559075","relation":{},"subject":[],"published":{"date-parts":[[2022,11,7]]},"assertion":[{"value":"2022-11-09","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}