Neural code synthesis has reached a point where snippet generation is accurate enough to be considered for integration into human software development workflows. Commercial products aim to increase programmers' productivity, without being able to measure it directly. In this case study, we asked users of GitHub Copilot about its impact on their productivity, and sought to find a reflection of their perception in directly measurable user data. We find that the rate with which shown suggestions are accepted, rather than more specific metrics regarding the persistence of completions in the code over time, drives developers' perception of productivity.
翻译:神经代码合成已经到了足够准确的碎片生成可被考虑纳入人类软件开发工作流程的地步。 商业产品旨在提高程序员的生产率,但又无法直接计量。 在这次案例研究中,我们询问GitHub Copilot用户其生产率受到的影响,并试图在直接可测量的用户数据中找到反映其观点的反映。 我们发现,所显示的建议被接受的速度,而不是关于代码中持续完成的更具体的衡量标准,会驱动开发商对生产率的看法。