Can Humans Teach Machines to Code?

Abstract

The goal of inductive program synthesis is for a machine to automatically generate a program from user-supplied 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 input-output examples (i) from a human group, (ii) from a gold standard set, and (iii) randomly sampled. Our results suggest that human-provided examples are typically insufficient for a program synthesis system to learn an accurate program.