@inproceedings{desai2016program,
author = {Desai, Aditya and Gulwani, Sumit and Hingorani, Vineet and Jain, Nidhi and Karkare, Amey and Marron, Mark and R, Sailesh and Roy, Subhajit},
title = {Program Synthesis using Natural Language},
booktitle = {ICSE '16, Austin, TX, USA},
year = {2016},
month = {May},
abstract = {Interacting with computers is a ubiquitous activity for millions of people. Repetitive or specialized tasks often require creation of small, often one-off, programs. End-users struggle with learning and using the myriad of domain-specific languages (DSLs) to effectively accomplish these tasks.

We present a general framework for constructing program synthesizers that take natural language (NL) inputs and produce expressions in a target DSL. The framework takes as input a DSL definition and training data consisting of NL/DSL pairs. From these it constructs a synthesizer by learning optimal weights and classifiers (using NLP features) that rank the outputs of a keyword programming based translation. We applied our framework to three domains: repetitive text editing, an intelligent tutoring system, and flight information queries. On 1200+ English descriptions, the respective synthesizers rank the desired program as the top-1 and top-3 for 80% and 90% descriptions respectively.},
url = {http://approjects.co.za/?big=en-us/research/publication/program-synthesis-using-natural-language-2/},
}