  Context. Software Engineering (SE) has low female representation due to
gender bias that men are better at programming. Pair programming (PP) is common
in industry and can increase student interest in SE, especially women; but if
gender bias affects PP, it may discourage women from joining the field.
  Objective. We explore gender bias in PP. In a remote setting where students
cannot see their peers' gender, we study how perceived productivity, technical
competency and collaboration/interaction behaviors of SE students vary by
perceived gender of their remote partner.
  Method. We developed an online PP platform (twincode) with a collaborative
editing window and a chat pane. Control group had no gender information about
their partner, while treatment group saw a gendered avatar as a man or woman.
Avatar gender was swapped between tasks to analyze 45 variables on
collaborative coding behavior, chat utterances and questionnaire responses of
46 pairs in original study at the University of Seville and 23 pairs in the
replication at the University of California, Berkeley.
  Results. No significant effect of gender bias treatment or interaction
between perceived partner's gender and subject's gender in any variable in
original study. In replication, significant effects with moderate to large
sizes in four variables within experimental group comparing subjects' actions
when partner was male vs female.
