  Developers perform online sensemaking on a daily basis, such as researching
and choosing libraries and APIs. Prior research has introduced tools that help
developers capture information from various sources and organize it into
structures useful for subsequent decision-making. However, it remains a
laborious process for developers to manually identify and clip content,
maintaining its provenance and synthesizing it with other content. In this
work, we introduce a new system called Crystalline that attempts to
automatically collect and organize information into tabular structures as the
user searches and browses the web. It leverages natural language processing to
automatically group similar criteria together to reduce clutter as well as
passive behavioral signals such as mouse movement and dwell time to infer what
information to collect and how to visualize and prioritize it. Our user study
suggests that developers are able to create comparison tables about 20% faster
with a 60% reduction in operational cost without sacrificing the quality of the
tables.
