Studying the language and structure in non-programmers' solutions to programming problems
International Journal of Human-Computer Studies
Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
On the Foolishness of "Natural Language Programming"
Program Construction, International Summer Schoo
Programming in natural language: “NLC” as a prototype
ACM '79 Proceedings of the 1979 annual conference
Metafor: visualizing stories as code
Proceedings of the 10th international conference on Intelligent user interfaces
Programmatic semantics for natural language interfaces
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Learning to transform natural to formal languages
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
No Code Required: Giving Users Tools to Transform the Web
No Code Required: Giving Users Tools to Transform the Web
Proceedings of the 10th SIGPLAN symposium on New ideas, new paradigms, and reflections on programming and software
The continuing quest for abstraction
ECOOP'06 Proceedings of the 20th European conference on Object-Oriented Programming
User-driven modelling: Visualisation and systematic interaction for end-user programming
Journal of Visual Languages and Computing
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Natural Language Processing holds great promise for making computer interfaces that are easier to use for people, since people will (hopefully) be able to talk to the computer in their own language, rather than learn a specialized language of computer commands. For programming, however, the necessity of a formal programming language for communicating with a computer has always been taken for granted. We would like to challenge this assumption. We believe that modern Natural Language Processing techniques can make possible the use of natural language to (at least partially) express programming ideas, thus drastically increasing the accessibility of programming to non-expert users. To demonstrate the feasibility of Natural Language Programming, this paper tackles what are perceived to be some of the hardest cases: steps and loops. We look at a corpus of English descriptions used as programming assignments, and develop some techniques for mapping linguistic constructs onto program structures, which we refer to as programmatic semantics.