Can Humans Teach Machines to Code?
Céline Hocquette, Johannes Langer, Andrew Cropper, Ute Schmid
Abstract
The goal of inductive program synthesis is for a machine to automatically generate a program from usersupplied examples. A key underlying assumption is that humans can provide sufficient examples to teach a concept to a machine. To evaluate the validity of this assumption, we conduct a study where human participants provide examples for six programming concepts, such as finding the maximum element of a list. We evaluate the generalisation performance of five program synthesis systems trained on inputoutput examples (i) from non-expert humans, (ii) from a human expert, and (iii) randomly sampled. Our results suggest that non-experts typically do not provide sufficient examples for a program synthesis system to learn an accurate program.
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