The goal of inductive program synthesis is for a machine to automatically generate a program from user-supplied examples of the desired behaviour of the program. A key underlying assumption is that humans can provide examples of sufficient quality to teach a concept to a machine. However, as far as we are aware, this assumption lacks both empirical and theoretical support. To address this limitation, we explore the question `Can humans teach machines to code?'. To answer this question, we conduct a study where we ask humans to generate examples for six programming tasks, such as finding the maximum element of a list. We compare the performance of a program synthesis system trained on (i) human-provided examples, (ii) randomly sampled examples, and (iii) expert-provided examples. Our results show that, on most of the tasks, non-expert participants did not provide sufficient examples for a program synthesis system to learn an accurate program. Our results also show that non-experts need to provide more examples than both randomly sampled and expert-provided examples.

能否通过人类提供的示例教机器编码的问题在程序综合研究中至关重要。进行了一个实验，要求人类为六个编程任务提供示例，并将非专家提供的示例与随机抽样的示例以及专家提供的示例进行对比。结果表明，非专家参与者提供的示例不足以使程序综合系统学习到准确的程序，并且非专家需要提供比随机抽样和专家提供的示例更多的示例。

人类能教机器编码吗？