VarCLR-Reference-Cited by-同舟云学术

VarCLR

Published:2022-05-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 44th International Conference on Software Engineering
language:
Short-container-title:

Author:

Chen Qibin¹,Lacomis Jeremy¹,Schwartz Edward J.¹,Neubig Graham¹,Vasilescu Bogdan¹,Goues Claire Le¹

Affiliation:

1. Carnegie Mellon University

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3510003.3510162

Reference88 articles.

1. Daniel Adiwardana Minh-Thang Luong David R So Jamie Hall Noah Fiedel Romal Thoppilan Zi Yang Apoorv Kulshreshtha Gaurav Nemade Yifeng Lu etal 2020. Towards a human-like open-domain chatbot. arXiv preprint arXiv:2001.09977 (2020). Daniel Adiwardana Minh-Thang Luong David R So Jamie Hall Noah Fiedel Romal Thoppilan Zi Yang Apoorv Kulshreshtha Gaurav Nemade Yifeng Lu et al. 2020. Towards a human-like open-domain chatbot. arXiv preprint arXiv:2001.09977 (2020).

2. Eneko Agirre Enrique Alfonseca Keith Hall Jana Kravalova Marius Pasca and Aitor Soroa. 2009. A study on similarity and relatedness using distributional and wordnet-based approaches. (2009). Eneko Agirre Enrique Alfonseca Keith Hall Jana Kravalova Marius Pasca and Aitor Soroa. 2009. A study on similarity and relatedness using distributional and wordnet-based approaches. (2009).

3. Miltiadis Allamanis , Earl T Barr , Christian Bird , and Charles Sutton . 2014 . Learning Natural Coding Conventions. In Symposium on the Foundations of Software Engineering (FSE). 281--293 . Miltiadis Allamanis, Earl T Barr, Christian Bird, and Charles Sutton. 2014. Learning Natural Coding Conventions. In Symposium on the Foundations of Software Engineering (FSE). 281--293.

4. Suggesting accurate method and class names

5. R. Bavishi M. Pradel and K. Sen. 2017. Context2Name: A Deep Learning-Based Approach to Infer Natural Variable Names from Usage Contexts. Technical Report. TU Darmstadt Department of Computer Science. R. Bavishi M. Pradel and K. Sen. 2017. Context2Name: A Deep Learning-Based Approach to Infer Natural Variable Names from Usage Contexts. Technical Report. TU Darmstadt Department of Computer Science.

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. VarGAN: Adversarial Learning of Variable Semantic Representations;IEEE Transactions on Software Engineering;2024-06

2. Inference for Ever-Changing Policy of Taint Analysis;Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice;2024-04-14

3. KnowLog: Knowledge Enhanced Pre-trained Language Model for Log Understanding;Proceedings of the IEEE/ACM 46th International Conference on Software Engineering;2024-02-06

4. Distinguishing Look-Alike Innocent and Vulnerable Code by Subtle Semantic Representation Learning and Explanation;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

5. LExecutor: Learning-Guided Execution;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30