  Social network research has focused on hyperlink graphs, bibliographic
citations, friend/follow patterns, influence spread, etc. Large software
repositories also form a highly valuable networked artifact, usually in the
form of a collection of packages, their developers, dependencies among them,
and bug reports. This "social network of code" is rarely studied by social
network researchers. We introduce two new problems in this setting. These
problems are well-motivated in the software engineering community but not
closely studied by social network scientists. The first is to identify packages
that are most likely to be troubled by bugs in the immediate future, thereby
demanding the greatest attention. The second is to recommend developers to
packages for the next development cycle. Simple autoregression can be applied
to historical data for both problems, but we propose a novel method to
integrate network-derived features and demonstrate that our method brings
additional benefits. Apart from formalizing these problems and proposing new
baseline approaches, we prepare and contribute a substantial dataset connecting
multiple attributes built from the long-term history of 20 releases of Ubuntu,
growing to over 25,000 packages with their dependency links, maintained by over
3,800 developers, with over 280k bug reports.
