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Code summarization, the task of generating useful comments given the code, has long been of interest.
Bleu: a Method for Automatic Evaluation of Machine Translation. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, July 6-12, 2002, Philadelphia, PA, USA . 311–318
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. [n. d.] · 2002
Earlier work this paper cites.
DeepSumm - Deep Code Summaries using Neural Transformer Architecture
Vivek Gupta. 2020 · 2004
Earlier work this paper cites.
ROUGE: A package for automatic evaluation of summaries. In Text summarization branches out . 74–81
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments. In Proceedings of the Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization@ACL 2005 . 65–72
Satanjeev Banerjee and Alon Lavie. [n. d.] · 2005
Earlier work this paper cites.
The Sorting Techniques: A Tutorial Paper on Card Sorts, Picture Sorts and Item Sorts
Gordon Rugg and Peter McGeorge. 2005 · 2005
Earlier work this paper cites.
Supporting program comprehension with source code summarization. In 2010 acm/ieee 32nd international conference on software engineering , Vol. 2. IEEE, 223–226
Sonia Haiduc, Jairo Aponte, and Andrian Marcus. 2010 · 2010
Earlier work this paper cites.
Towards automatically generating summary comments for java methods. In Proceedings of the IEEE/ACM international conference on Automated software engineering . 43–52
Giriprasad Sridhara, Emily Hill, Divya Muppaneni, Lori Pollock, and K Vijay-Shanker. 2010 · 2010
Earlier work this paper cites.
Evaluating source code summarization techniques: Replication and expansion. In 2013 21st International Conference on Program Comprehension (ICPC) . 13–22
Brian P Eddy, Jeffrey A Robinson, Nicholas A Kraft, and Jeffrey C Carver. 2013 · 2013
Earlier work this paper cites.
Automatic generation of natural language summaries for java classes. In 2013 21st International Conference on Program Comprehension (ICPC) . IEEE, 23–32
Laura Moreno, Jairo Aponte, Giriprasad Sridhara, Andrian Marcus, Lori Pollock, and K Vijay-Shanker. 2013 · 2013
Earlier work this paper cites.
Quality analysis of source code comments. In IEEE 21st International Conference on Program Comprehension, ICPC 2013, San Francisco, CA, USA, 20-21 May, 2013 . IEEE Computer Society, 83–92
Daniela Steidl, Benjamin Hummel, and Elmar Jürgens. 2013 · 2013
Earlier work this paper cites.
Five reasons for including technical debt in the software engineering curriculum. In Proceedings of the 2015 European Conference on Software Architecture Workshops . 1–4
Davide Falessi and Philippe Kruchten. 2015 · 2015
Earlier work this paper cites.
CIDEr: Consensus-based image description evaluation. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, June 7-12, 2015 . IEEE Computer Society, 4566–4575
Ramakrishna Vedantam, C. Lawrence Zitnick, and Devi Parikh. 2015 · 2015
Earlier work this paper cites.
Clocom: Mining existing source code for automatic comment generation. In 2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER) . IEEE, 380–389
Edmund Wong, Taiyue Liu, and Lin Tan. 2015 · 2015
Earlier work this paper cites.
Deep API learning. In Proceedings of the 2016 24th ACM SIGSOFT international symposium on foundations of software engineering . 631–642
Xiaodong Gu, Hongyu Zhang, Dongmei Zhang, and Sunghun Kim. 2016 · 2016
Earlier work this paper cites.
SourcererCC: scaling code clone detection to big-code. In Proceedings of the 38th International Conference on Software Engineering, ICSE 2016, Austin, TX, USA, May 14-22, 2016 . 1157–1168
Hitesh Sajnani, Vaibhav Saini, Jeffrey Svajlenko, Chanchal K. Roy, and Cristina V. Lopes. [n. d.] · 2016
Earlier work this paper cites.
Examining the impact of self-admitted technical debt on software quality. In 2016 IEEE 23Rd international conference on software analysis, evolution, and reengineering (SANER) , Vol. 1. IEEE, 179–188
Sultan Wehaibi, Emad Shihab, and Latifa Guerrouj. 2016 · 2016
Earlier work this paper cites.
PCSD Dataset Download
2017 · 2017
Earlier work this paper cites.
Automatically generating commit messages from diffs using neural machine translation. In 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 135–146
Siyuan Jiang, Ameer Armaly, and Collin McMillan. 2017 · 2017
Earlier work this paper cites.
Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J Liu, and Christopher D Manning. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
TLC Dataset Download
2018 · 2018
Earlier work this paper cites.
A neural framework for retrieval and summarization of source code. In 2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 826–831
Qingying Chen and Minghui Zhou. 2018 · 2018
Earlier work this paper cites.
Coherence of comments and method implementations: a dataset and an empirical investigation
Anna Corazza, Valerio Maggio, and Giuseppe Scanniello. 2018 · 2018
Earlier work this paper cites.
Deep code comment generation. In 2018 IEEE/ACM 26th International Conference on Program Comprehension (ICPC) . IEEE, 200–20010
Xing Hu, Ge Li, Xin Xia, David Lo, and Zhi Jin. 2018a · 2018
Earlier work this paper cites.
Summarizing source code with transferred api knowledge
Xing Hu, Ge Li, Xin Xia, David Lo, Shuai Lu, and Zhi Jin. 2018b · 2018
Earlier work this paper cites.
Neural-machine-translation-based commit message generation: how far are we?. In Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering . 373–384
Zhongxin Liu, Xin Xia, Ahmed E Hassan, David Lo, Zhenchang Xing, and Xinyu Wang. 2018 · 2018
Earlier work this paper cites.
Improving automatic source code summarization via deep reinforcement learning. In Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering . 397–407
Yao Wan, Zhou Zhao, Min Yang, Guandong Xu, Haochao Ying, Jian Wu, and Philip S Yu. 2018 · 2018
Cited alongside, same era.
The adverse effects of code duplication in machine learning models of code. In Proceedings of the 2019 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software, Onward! 2019 . 143–153
Miltiadis Allamanis. [n. d.] · 2019
Cited alongside, same era.
code2seq: Generating Sequences from Structured Representations of Code. In 7th International Conference on Learning Representations, ICLR 2019
Uri Alon, Shaked Brody, Omer Levy, and Eran Yahav. [n. d.] · 2019
Cited alongside, same era.
Codesearchnet challenge: Evaluating the state of semantic code search
Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltiadis Allamanis, and Marc Brockschmidt. 2019 · 2019
Cited alongside, same era.
GraphCodeBERT: Pre-training Code Representations with Data Flow. In 9th International Conference on Learning Representations, ICLR 2021
Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang, Shujie Liu, Long Zhou, Nan Duan, Alexey Svyatkovskiy, Shengyu Fu, Michele Tufano, Shao Kun Deng, Colin B. Clement, Dawn Drain, Neel Sundaresan, Jian Yin, Daxin Jiang, and Ming Zhou. [n. d.] · 2021
Later among the works it cites.
Action Word Prediction for Neural Source Code Summarization. In 28th IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2021 . 330–341
Sakib Haque, Aakash Bansal, Lingfei Wu, and Collin McMillan. [n. d.] · 2021
Later among the works it cites.
CoDesc: A Large Code-Description Parallel Dataset. In Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021 (Findings of ACL, Vol. ACL/IJCNLP 2021) . 210–218
Masum Hasan, Tanveer Muttaqueen, Abdullah Al Ishtiaq, Kazi Sajeed Mehrab, Md. Mahim Anjum Haque, Tahmid Hasan, Wasi Uddin Ahmad, Anindya Iqbal, and Rifat Shahriyar. [n. d.] · 2021
Later among the works it cites.
What do pre-trained code models know about code?. In 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 1332–1336
Anjan Karmakar and Romain Robbes. 2021 · 2021
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A neural model for generating natural language summaries of program subroutines. In 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) . 795–806
Alexander LeClair, Siyuan Jiang, and Collin McMillan. [n. d.]b · 2019
Cited alongside, same era.
Code generation as a dual task of code summarization
Bolin Wei, Ge Li, Xin Xia, Zhiyi Fu, and Zhi Jin. 2019 · 2019
Cited alongside, same era.
SIGSOFT Open Science Policies
2020 · 2020
Cited alongside, same era.
A Transformer-based Approach for Source Code Summarization. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020 . 4998–5007
Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, and Kai-Wei Chang. [n. d.] · 2020
Cited alongside, same era.
TAG: Type auxiliary guiding for code comment generation
Ruichu Cai, Zhihao Liang, Boyan Xu, Zijian Li, Yuexing Hao, and Yao Chen. 2020 · 2020
Cited alongside, same era.
CodeBERT: A Pre-Trained Model for Programming and Natural Languages. In Findings of the Association for Computational Linguistics: EMNLP 2020, Online Event, 16-20 November 2020 (Findings of ACL, Vol. EMNLP 2020) . 1536–1547
Zhangyin Feng, Daya Guo, Duyu Tang, Nan Duan, Xiaocheng Feng, Ming Gong, Linjun Shou, Bing Qin, Ting Liu, Daxin Jiang, and Ming Zhou. [n. d.] · 2020
Cited alongside, same era.
Code to Comment "Translation": Data, Metrics, Baselining & Evaluation. In 35th IEEE/ACM International Conference on Automated Software Engineering, ASE 2020, Melbourne, Australia, September 21-25, 2020 . 746–757
David Gros, Hariharan Sezhiyan, Prem Devanbu, and Zhou Yu. [n. d.] · 2020
Cited alongside, same era.
Improved automatic summarization of subroutines via attention to file context. In Proceedings of the 17th International Conference on Mining Software Repositories . 300–310
Sakib Haque, Alexander LeClair, Lingfei Wu, and Collin McMillan. 2020 · 2020
Cited alongside, same era.
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Ensemble Models for Neural Source Code Summarization of Subroutines. In IEEE International Conference on Software Maintenance and Evolution, ICSME 2021 . 286–297
Alexander LeClair, Aakash Bansal, and Collin McMillan. [n. d.]a · 2021
Later among the works it cites.
EditSum: A Retrieve-and-Edit Framework for Source Code Summarization. In 36th IEEE/ACM International Conference on Automated Software Engineering, ASE 2021 . 155–166
Jia Li, Yongmin Li, Ge Li, Xing Hu, Xin Xia, and Zhi Jin. [n. d.] · 2021
Later among the works it cites.
Improving Code Summarization with Block-wise Abstract Syntax Tree Splitting. In 29th IEEE/ACM International Conference on Program Comprehension, ICPC 2021 . 184–195
Chen Lin, Zhichao Ouyang, Junqing Zhuang, Jianqiang Chen, Hui Li, and Rongxin Wu. [n. d.] · 2021
Later among the works it cites.
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
Shuai Lu, Daya Guo, Shuo Ren, Junjie Huang, Alexey Svyatkovskiy, Ambrosio Blanco, Colin B. Clement, Dawn Drain, Daxin Jiang, Duyu Tang, Ge Li, Lidong Zhou, Linjun Shou, Long Zhou, Michele Tufano, Ming Gong, Ming Zhou, Nan Duan, Neel Sundaresan, Shao Kun Deng, Shengyu Fu, and Shujie Liu. 2021 · 2021
Later among the works it cites.
Code to Comment Translation: A Comparative Study on Model Effectiveness & Errors
Junayed Mahmud, Fahim Faisal, Raihan Islam Arnob, Antonios Anastasopoulos, and Kevin Moran. 2021 · 2021
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Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks. In 43rd IEEE/ACM International Conference on Software Engineering, ICSE 2021, Madrid, Spain, 22-30 May 2021 . IEEE, 336–347
Antonio Mastropaolo, Simone Scalabrino, Nathan Cooper, David Nader-Palacio, Denys Poshyvanyk, Rocco Oliveto, and Gabriele Bavota. 2021 · 2021
Later among the works it cites.
A Search-Based Testing Framework for Deep Neural Networks of Source Code Embedding. In 14th IEEE Conference on Software Testing, Verification and Validation, ICST 2021, Porto de Galinhas, Brazil, April 12-16, 2021 . IEEE, 36–46
Maryam Vahdat Pour, Zhuo Li, Lei Ma, and Hadi Hemmati. 2021 · 2021
Later among the works it cites.
Do Comments follow Commenting Conventions? A Case Study in Java and Python. In 21st IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2021, Luxembourg, September 27-28, 2021 . IEEE, 165–169
Pooja Rani, Suada Abukar, Nataliia Stulova, Alexandre Bergel, and Oscar Nierstrasz. 2021 · 2021
Later among the works it cites.
Reassessing automatic evaluation metrics for code summarization tasks. In ESEC/FSE ’21: 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Athens, Greece, August 23-28, 2021 , Diomidis Spinellis, Georgios Gousios, Marsha Chechik, and Massimiliano Di Penta (Eds.). ACM, 1105–1116
Devjeet Roy, Sarah Fakhoury, and Venera Arnaoudova. 2021 · 2021
Later among the works it cites.
API2Com: On the Improvement of Automatically Generated Code Comments Using API Documentations. In 29th IEEE/ACM International Conference on Program Comprehension, ICPC 2021, Madrid, Spain, May 20-21, 2021 . IEEE, 411–421
Ramin Shahbazi, Rishab Sharma, and Fatemeh H. Fard. 2021 · 2021
Later among the works it cites.
Neural Code Summarization: How Far Are We?
Ensheng Shi, Yanlin Wang, Lun Du, Junjie Chen, Shi Han, Hongyu Zhang, Dongmei Zhang, and Hongbin Sun. 2021 · 2021
Later among the works it cites.
CAST: Enhancing Code Summarization with Hierarchical Splitting and Reconstruction of Abstract Syntax Trees. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021 . 4053–4062
Ensheng Shi, Yanlin Wang, Lun Du, Hongyu Zhang, Shi Han, Dongmei Zhang, and Hongbin Sun. [n. d.] · 2021
Later among the works it cites.
CoCoSum: Contextual Code Summarization with Multi-Relational Graph Neural Network
Yanlin Wang, Ensheng Shi, Lun Du, Xiaodi Yang, Yuxuan Hu, Shi Han, Hongyu Zhang, and Dongmei Zhang. 2021 · 2021
Later among the works it cites.
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021, pages = 8696–8708,
Yue Wang, Weishi Wang, Shafiq R. Joty, and Steven C. H. Hoi. [n. d.] · 2021
Later among the works it cites.
Code Summarization with Structure-induced Transformer. In Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, Online Event, August 1-6, 2021 (Findings of ACL, Vol. ACL/IJCNLP 2021) , Chengqing Zong, Fei Xia, Wenjie Li, and Roberto Navigli (Eds.). Association for Computational Linguistics, 1078–1090
Hongqiu Wu, Hai Zhao, and Min Zhang. 2021 · 2021
Later among the works it cites.
Yet Another Combination of IR-and Neural-based Comment Generation
Huang Yuchao, Wei Moshi, Wang Song, Wang Junjie, and Wang Qing. 2021 · 2021
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Adversarial Robustness of Deep Code Comment Generation
Yu Zhou, Xiaoqing Zhang, Juanjuan Shen, Tingting Han, Taolue Chen, and Harald C. Gall. 2021b · 2021
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Adversarial training and ensemble learning for automatic code summarization
Ziyi Zhou, Huiqun Yu, and Guisheng Fan. 2021a · 2021
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CAT Python Library
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On the Importance of Building High-quality Training Datasets for Neural Code Search
Zhensu Sun, Li Li, Yan Liu, Xiaoning Du, and Li Li. 2022 · 2022
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Summarizing source code using a neural attention model. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 2073–2083
Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, and Luke Zettlemoyer. 2016 · 2083
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