Papers List
- A General Path-Based Representation for Predicting Program Properties.[pdf]
- Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav. PLDI, 2018.
- Characterizing the Natural Language Descriptions in Software Logging Statements.[pdf][code]
- Pinjia He, Zhuangbin Chen, Shilin He, Michael R. Lyu. ASE, 2018.
- code2vec: Learning Distributed Representations of Code.[pdf][code]
- Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav. POPL, 2019.
- code2seq: Generating Sequences from Structured Representations of Code.[pdf][code]
- Uri Alon, Shaked Brody, Omer Levy, Eran Yahav. ICLR, 2019.
- Machine Learning Based Recommendation of Method Names: How Far are We.[pdf][code]
- Lin Jiang, Hui Liu, He Jiang. ASE, 2019.
- Mercem: Method Name Recommendation Based on Call Graph Embedding.[pdf][code]
- Hiroshi Yonai, Yasuhiro Hayase, Hiroyuki Kitagawa. APSEC, 2019.
- Method Name Suggestion with Hierarchical Attention Networks.[pdf][code]
- Sihan Xu, Sen Zhang, Weijing Wang, Xinya Cao, Chenkai Guo, Jing Xu. PEPM@POPL, 2019.
- Recovering Variable Names for Minified Code with Usage Contexts.[pdf][code]
- Hieu Tran, Ngoc M. Tran, Son Nguyen, Hoan Nguyen, Tien N. Nguyen. ICSE, 2019.
- Embedding Java Classes with code2vec: Improvements from Variable Obfuscation.[pdf][code]
- Rhys Compton, Eibe Frank, Panos Patros, Abigail Koay. MSR, 2020.
- Learning Semantic Program Embeddings with Graph Interval Neural Network.[pdf][code]
- Yu Wang, Ke Wang, Fengjuan Gao, Linzhang Wang. OOPSLA, 2020.
- Towards Demystifying Dimensions of Source Code Embeddings.[pdf][code]
- Md. Rafiqul Islam Rabin, Arjun Mukherjee, Omprakash Gnawali, Mohammad Amin Alipour. arXiv, 2020.
- Suggesting Natural Method Names to Check Name Consistencies.[pdf][code]
- Son Nguyen, Hung Phan, Trinh Le, Tien N. Nguyen:. ICSE, 2020.
- Blended, Precise Semantic Program Embeddings.[pdf]
- Ke Wang, Zhendong Su. PLDI, 2020.
- InferCode: Self-Supervised Learning of Code Representations by Predicting Subtrees.[pdf][code]
- Nghi D. Q. Bui, Yijun Yu, Lingxiao Jiang. ICSE, 2021.
- A Mocktail of Source Code Representations.[pdf][code]
- Dheeraj Vagavolu, Karthik Chandra Swarna, Sridhar Chimalakonda. ASE, 2021.
- A Lightweight Framework for Function Name Reassignment Based on Large-scale Stripped Binaries.[pdf][code]
- Han Gao, Shaoyin Cheng, Yinxing Xue, Weiming Zhang. ISSTA, 2021.
- PSIMiner: A Tool for Mining Rich Abstract Syntax Trees from Code.[pdf][code]
- Egor Spirin, Egor Bogomolov, Vladimir Kovalenko, Timofey Bryksin. MSR, 2021.
- A Hybrid Code Representation Learning Approach for Predicting Method Names.[pdf][code]
- Fengyi Zhang, Bihuan Chen, Rongfan Li, Xin Peng. Journal of Systems and Software, 2021.
- Universal Representation for Code.[pdf][code]
- Linfeng Liu, Hoan Nguyen, George Karypis, Srinivasan Sengamedu. PAKDD, 2021.
- Lightweight Global and Local Contexts Guided Method Name Recommendation with Prior Knowledge.[pdf][code]
- Shangwen Wang, Ming Wen, Bo Lin, Xiaoguang Mao. FSE, 2021.
- A Context-based Automated Approach for Method Name Consistency Checking and Suggestion.[pdf][code]
- Yi Li, Shaohua Wang, Tien N. Nguyen. ICSE, 2021.
- Thinking Like a Developer? Comparing the Attention of Humans with Neural Models of Code.[pdf][code]
- Matteo Paltenghi, Michael Pradel. ASE, 2021.
- Learning to Find Naming Issues with Big Code and Small Supervision.[pdf][code]
- Jingxuan He, Cheng-Chun Lee, Veselin Raychev, Martin T. Vechev. PLDI, 2021.
- GraphCode2Vec: Generic Code Embedding via Lexical and Program Dependence Analyses.[pdf][code]
- Wei Ma, Mengjie Zhao, Ezekiel O. Soremekun, Qiang Hu, Jie M. Zhang, Mike Papadakis, Maxime Cordy, Xiaofei Xie, Yves Le Traon. MSR, 2022.
- Learning to Represent Programs with Heterogeneous Graphs.[pdf][code]
- Kechi Zhang, Wenhan Wang, Huangzhao Zhang, Ge Li, Zhi Jin. ICPC, 2022.
- Multilingual Training for Software Engineering.[pdf][code]
- Toufique Ahmed, Premkumar T. Devanbu. ICSE, 2022.
- Learning to Recommend Method Names with Global Context.[pdf]
- Fang Liu, Ge Li, Zhiyi Fu, Shuai Lu, Yiyang Hao, Zhi Jin. ICSE, 2022.
- SymLM: Predicting Function Names in Stripped Binaries via Context-Sensitive Execution-Aware Code Embeddings.[pdf][code]
- Xin Jin, Kexin Pei, Jun Yeon Won, Zhiqiang Lin. CCS, 2022.
- Method Name Prediction for Automatically Generated Unit Tests.[pdf][code]
- Maxim Petukhov, Evelina Gudauskayte, Arman Kaliyev, Mikhail Oskin, Dmitry Ivanov, Qianxiang Wang. ICCQ, 2022.
- A Naming Pattern Based Approach for Method Name Recommendation.[pdf][code]
- Yanping Yang, Ling Xu, Meng Yan, Zhou Xu, Zhongyang Deng. ISSRE, 2022.
- A Review on Source Code Documentation.[pdf]
- Sawan Rai, Ramesh Chandra Belwal, Atul Gupta. ACM Transactions on Intelligent Systems and Technology, 2022.
- Method name recommendation based on source code metrics.[pdf][code]
- Saeed Parsa, Morteza Zakeri Nasrabadi, Masoud Ekhtiarzadeh, Mohammad Ramezani. Journal of Computer Languages, 2023.
- Fold2Vec: Towards a Statement-Based Representation of Code for Code Comprehension.[pdf][code]
- Francesco Bertolotti, Walter Cazzola. ACM Transactions on Software Engineering and Methodology, 2023.