  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.
