Dialog for Natural Language to Code (2017)
Generating computer code from natural language descriptions has been a longstanding problem in computational linguistics. Prior work in this domain has restricted itself to generating code in one shot from a single description. To overcome this limitation, we propose a system that can engage users in a dialog to clarify their intent until it is confident that it has all the information to produce correct and complete code. Further, we demonstrate how the dialog conversations can be leveraged for continuous improvement of the dialog system. To evaluate the efficacy of dialog in code generation, we focus on synthesizing conditional statements in the form of IFTTT recipes. IFTTT (if-this-then-that) is a web-service that provides event-driven automation, enabling control of smart devices and web-applications based on user-defined events.
Masters Thesis, Computer Science Department, University of Texas at Austin.

Shobhit Chaurasia Masters Student shobhit [at] cs utexas edu