Can humans teach machines to code?

Céline Hocquette, Johannes Langer, Andrew Cropper, Ute Schmid
4/30/2024
cs.HCcs.LG

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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 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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Cite this paper

@article{hocquette2024humans,
  title  = {Can humans teach machines to code?},
  author = {Céline Hocquette and Johannes Langer and Andrew Cropper and Ute Schmid},
  year   = {2024},
  eprint = {2404.19397},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.19397v2}
}

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