A Large-Scale Survey on the Usability of AI Programming Assistants:
Successes and Challenges
- URL: http://arxiv.org/abs/2303.17125v2
- Date: Sun, 17 Sep 2023 04:36:05 GMT
- Title: A Large-Scale Survey on the Usability of AI Programming Assistants:
Successes and Challenges
- Authors: Jenny T. Liang, Chenyang Yang, Brad A. Myers
- Abstract summary: In practice, developers do not accept AI programming assistants' initial suggestions at a high frequency.
To understand developers' practices while using these tools, we administered a survey to a large population of developers.
We found that developers are most motivated to use AI programming assistants because they help developers reduce key-strokes, finish programming tasks quickly, and recall syntax.
We also found the most important reasons why developers do not use these tools are because these tools do not output code that addresses certain functional or non-functional requirements.
- Score: 23.467373994306524
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The software engineering community recently has witnessed widespread
deployment of AI programming assistants, such as GitHub Copilot. However, in
practice, developers do not accept AI programming assistants' initial
suggestions at a high frequency. This leaves a number of open questions related
to the usability of these tools. To understand developers' practices while
using these tools and the important usability challenges they face, we
administered a survey to a large population of developers and received
responses from a diverse set of 410 developers. Through a mix of qualitative
and quantitative analyses, we found that developers are most motivated to use
AI programming assistants because they help developers reduce key-strokes,
finish programming tasks quickly, and recall syntax, but resonate less with
using them to help brainstorm potential solutions. We also found the most
important reasons why developers do not use these tools are because these tools
do not output code that addresses certain functional or non-functional
requirements and because developers have trouble controlling the tool to
generate the desired output. Our findings have implications for both creators
and users of AI programming assistants, such as designing minimal cognitive
effort interactions with these tools to reduce distractions for users while
they are programming.
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