Natural Language for Software Engineering
The ability to translate instructions expressed in natural language directly to executable software is of considerable use in many applications such as personal assistants, as well as in making computers and automated systems more accessible to users unfamiliar with computer programming. Our work has focused on using semantic parsing and dialog to interpret English "if this then that" (IFTTT) instructions and using the evolution of comments and code in open source software repositories and a combination of NLP and program analysis methods to automate various software engineering tasks.
Associating Natural Language Comment and Source Code Entities 2020
Sheena Panthaplackel, Milos Gligoric, Raymond J. Mooney and Junyi Jessy Li, To Appear In The AAAI Conference on Artificial Intelligence (AAAI) 2020.
A Framework for Writing Trigger - Action Todo Comments in Executable Format 2019
Pengyu Nie, Rishabh Rai, Junyi Jessy Li, Sarfraz Khurshid, Raymond J. Mooney, Milos Gligoric, In Proceedings of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), Tallinn, Estonia, August 2019. Distinguished Paper ...
Natural Language Processing and Program Analysis for Supporting Todo Comments as Software Evolves 2018
Pengyu Nie, Junyi Jessy Li, Sarfraz Khurshid, Raymond Mooney, Milos Gligoric, In In Proceedings of the AAAI Workshop on NLP for Software Engineering, February 2018.
Dialog for Language to Code 2017
Shobhit Chaurasia and Raymond J. Mooney, In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), pp. 175-180, Taipei, Taiwan, November 2017.
Dialog for Natural Language to Code 2017
Shobhit Chaurasia, Masters Thesis, Computer Science Department, University of Texas at Austin.
Improved Semantic Parsers For If-Then Statements 2016
I. Beltagy and Chris Quirk, To Appear In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-16), Berlin, Germany 2016.
Language to Code: Learning Semantic Parsers for If-This-Then-That Recipes 2015
Chris Quirk, Raymond Mooney, and Michel Galley, In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-15), pp. 878--888, Beijing, China, July 2015.