论文标题
神经法规完成的生产力评估
Productivity Assessment of Neural Code Completion
论文作者
论文摘要
神经代码的综合已达到了摘要生成足够准确的地步，以便将其集成到人类软件开发工作流程中。商业产品旨在提高程序员的生产率，而无需直接衡量。在此案例研究中，我们向Github Copilot的用户询问了其对其生产力的影响，并试图在直接可测量的用户数据中找到对他们的看法的反映。我们发现，所显示的建议被接受的速率，而不是关于随着时间的时间的持续完成的更具体指标，可以推动开发人员对生产率的看法。
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.
