Taking Flight with Copilot

Q3 Computer Science Queue Pub Date : 2022-12-31 DOI:10.1145/3582083
C. Bird, Denae Ford, Thomas Zimmermann, Nicole Forsgren, Eirini Kalliamvakou, Travis Lowdermilk, Idan Gazit
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引用次数: 7

Abstract

Over the next five years, AI-powered tools likely will be helping developers in many diverse tasks. For example, such models may be used to improve code review, directing reviewers to parts of a change where review is most needed or even directly providing feedback on changes. Models such as Codex may suggest fixes for defects in code, build failures, or failing tests. These models are able to write tests automatically, helping to improve code quality and downstream reliability of distributed systems. This study of Copilot shows that developers spend more time reviewing code than actually writing code. As AI-powered tools are integrated into more software development tasks, developer roles will shift so that more time is spent assessing suggestions related to the task than doing the task itself.
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与副驾驶一起飞行
在接下来的五年里,人工智能工具可能会帮助开发人员完成许多不同的任务。例如,这样的模型可以用于改进代码评审,将评审人员引导到最需要评审的变更部分,甚至直接提供对变更的反馈。Codex等模型可能会建议修复代码中的缺陷、构建失败或测试失败。这些模型能够自动编写测试,有助于提高代码质量和分布式系统的下游可靠性。Copilot的这项研究表明,开发人员花在审查代码上的时间比实际编写代码的时间要多。随着人工智能工具被集成到更多的软件开发任务中,开发人员的角色将发生变化,因此与任务本身相比,花在评估与任务相关的建议上的时间将更多。
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来源期刊
Queue
Queue Computer Science-Computer Science (all)
CiteScore
1.80
自引率
0.00%
发文量
23
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