NLP+Programming Reading Group @ UT Austin

Fall 2020 Meetings

The reading group meetings have been moved online. Schedules will be posted in the mailing list.

Date	Topic
9/21/2020	Wei Ye, Rui Xie, Jinglei Zhang, Tianxiang Hu, Xiaoyin Wang, and Shikun Zhang. Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning In WWW 2020.
10/5/2020	Hung Viet Pham, Shangshu Qian, Jiannan Wang, Thibaud Lutellier, Jonathan Rosenthal, Lin Tan, Yaoliang Yu, Nachiappan Nagappan. Problems and Opportunities in Training Deep Learning Software Systems: An Analysis of Variance In ASE 2020.
10/19/2020	Prem Devanbu, Matthew Dwyer, Sebastian Elbaum, Michael Lowry, Kevin Moran, Denys Poshyvanyk, Baishakhi Ray, Rishabh Singh, and Xiangyu Zhang. Deep Learning & Software Engineering: State of Research and Future Directions In NSF Workshop on Deep Learning and Software Engineering.
11/02/2020	Jie Zhao, Huan Sun. Adversarial Training for Code Retrieval with Question-Description Relevance Regularization In Arxiv.
11/30/2020	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 Clement, Dawn Drain, Neel Sundaresan, Jian Yin, Daxin Jiang, Ming Zhou. GraphCodeBERT: Pre-training Code Representation with Data Flow In ICLR 2021 under review.

History Meetings

Date	Topic
Spring 2020
4/10/2020	Cody Watson, Michele Tufano, Kevin Moran, Gabriele Bavota, Denys Poshyvanyk. On Learning Meaningful Assert Statements for Unit Test Cases. In ICSE 2020.
3/27/2020	Vincent J. Hellendoorn, Charles Sutton, Rishabh Singh, Petros Maniatis, David Bieber. Global Relational Models of Source Code. In ICLR 2020. Zeyu Sun, Qihao Zhu, Yingfei Xiong, Yican Sun, Lili Mou, Lu Zhang. TreeGen: A Tree-Based Transformer Architecture for Code Generation. In AAAI 2020.
2/21/2020	Jiayi Wei, Maruth Goyal, Greg Durrett, Isil Dillig. LambdaNet: Probabilistic Type Inference using Graph Neural Networks. In ICLR 2020.
2/6/2020	Foivos Tsimpourlas, Ajitha Rajan, Miltiadis Allamanis. Learning to Encode and Classify Test Executions. 2020.
Fall 2019
11/25/2019	Marko Vasic, Aditya Kanade, Petros Maniatis, David Bieber, Rishabh Singh. Neural Program Repair by Jointly Learning to Localize and Repair. In ICLR 2019.
10/28/2019	Bolin Wei, Ge Li, Xin Xia, Zhiyi Fu, Zhi Jin. Code Generation as a Dual Task of Code Summarization. In NeurIPS 2019.
10/14/2019	Sheena Panthaplackel, Miltiadis Allamanis, Marc Brockschmidt. Copy That! Editing Sequences by Copying Spans. 2019.
Fall 2018
11/30/2018	Literature Review Session: NLP & Software Testing (2nd half).
11/20/2018	Literature Review Session: NLP & Software Testing (1st half).
11/2/2018	Xiaodong Gu, Hongyu Zhang, Sunghun Kim. Deep Code Search. In ICSE 2018.
10/19/2018	Dana Movshovitz-Attias, William W Cohen. Natural Language Models for Predicting Programming Comments. In ACL 2013.
10/5/2018	Xing Hu, Ge Li, Xin Xia, David Lo, Zhi Jin. Deep Code Comment Generation. In ICPC 2018.
9/20/2018	Literature Review Session: Comment Generation.
Summer 2018
8/01/2018	Arianna Blasi, Alberto Goffi, Konstantin Kuznetsov, Alessandra Gorla, Michael D. Ernst, Mauro Pezzè, Sergio Delgado Castellanos. Translating Code Comments to Procedure Specifications. In ISSTA 2018.
7/25/2018	Pengcheng Yin, Bowen Deng, Edgar Chen, Bogdan Vasilescu, Graham Neubig. Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow . In MSR 2018.
7/18/2018	Vijayaraghavan Murali, Letao Qi, Swarat Chaudhuri, Chris Jermaine. Neural Sketch Learning for Conditional Program Generation. In ICLR 2018.
7/04/2018	Miltiadis Allamanis, Marc Brockschmidt, Mahmoud Khademi. Learning to Represent Programs with Graphs. In ICLR 2018.
6/27/2018	Miltiadis Allamanis, Earl T Barr, Premkumar Devanbu, Charles Sutton. A Survey of Machine Learning for Big Code and Naturalness . 2017.
6/13/2018	NLP Final Project Reports
5/30/2018	Alessandra Gorla, Ilaria Tavecchia, Florian Gross, Andreas Zeller. Checking App Behavior Against App Descriptions. In ICSE 2014.
Spring 2018
5/15/2018	NLP Final Project Reports
4/24/2018	Ziyu Yao, Daniel S. Weld, Wei-Peng Chen, Huan Sun. StaQC: A Systematically Mined Question-Code Dataset from Stack Overflow. In WWW 2018.
4/10/2018	Rahul Gupta, Soham Pal, Aditya Kanade, Shirish K. Shevade. DeepFix: Fixing Common C Language Errors by Deep Learning. In AAAI 2017.
3/27/2018	Xinyun Chen, Chang Liu, Dawn Song. Tree-to-tree Neural Networks for Program Translation. 2018.
3/06/2018	Vincent J Hellendoorn, Premkumar Devanbu. Are Deep Neural Networks the Best Choice for Modeling Source Code?. In FSE 2017.
2/27/2018	Xi Victoria Lin, Chenglong Wang, Luke Zettlemoyer, Michael D. Ernst. NL2Bash: A Corpus and Semantic Parser for Natural Language Interface to the Linux Operating System. In LREC 2018.
2/13/2018	Pengcheng Yin, Graham Neubig. A Syntactic Neural Model for General-Purpose Code Generation. In ACL 2017.
1/30/2018	Pablo Loyola, Edison Marrese-Taylor, Yutaka Matsuo. A Neural Architecture for Generating Natural Language Descriptions from Source Code Changes. In ACL 2017.

Prior to Spring 2018: see Software Engineering Seminar.

Suggestions

Please send suggestions for papers you would like to discuss to pynie@utexas.edu or spantha@cs.utexas.edu.