Program Synthesis Using Natural Language

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 pr...

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Vydáno v:Proceedings / International Conference on Software Engineering s. 345 - 356
Hlavní autoři: Desai, Aditya, Gulwani, Sumit, Hingorani, Vineet, Jain, Nidhi, Karkare, Amey, Marron, Mark, R., Sailesh, Roy, Subhajit
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: ACM 01.05.2016
Témata:
Automata
Benchmark testing
Domain Specific Languages
DSL
End-user Programming
Natrual Language Programming
Natural languages
Program Synthesis
Synthesizers
Training
Training data
User Intent
ISSN:1558-1225
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Shrnutí: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.
ISSN:1558-1225
DOI:10.1145/2884781.2884786