构建个性化编码风格的隐式矢量表示
Building Implicit Vector Representations of Individual Coding Style
摘要：
为了促进团队协作，我们提出了一种新的方法来构建向量表示的个人开发人员通过捕捉他们的个人贡献风格，或编码风格。这种表示可以在下一代软件开发团队协作工具中找到用途，例如通过使工具能够跟踪团队中的知识转移。我们的方法的关键思想是避免使用显式定义的编码风格指标，而是通过训练一个用于作者身份识别的模型并从训练的模型中提取单个开发人员的表示来构建表示。通过经验评估我们的方法的输出，我们发现，隐式建立的个人表示反映了团队结构的一些属性：开发人员谁报告从对方学习表示更接近对方。
英文摘要：
With the goal of facilitating team collaboration, we propose a new approach to building vector representations of individual developers by capturing their individual contribution style, or coding style. Such representations can find use in the next generation of software development team collaboration tools, for example by enabling the tools to track knowledge transfer in teams. The key idea of our approach is to avoid using explicitly defined metrics of coding style and instead build the representations through training a model for authorship recognition and extracting the representations of individual developers from the trained model. By empirically evaluating the output of our approach, we find that implicitly built individual representations reflect some properties of team structure: developers who report learning from each other are represented closer to each other.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
