  There is an emerging consensus in the scientific software community that
progress in scientific research is dependent on the "quality and accessibility
of software at all levels" (wssspe.researchcomputing.org.uk/). This progress
depends on embracing the best traditional---and emergent---practices in
software engineering, especially agile practices that intersect with the more
formal tradition of software engineering. As a first step in our larger
exploratory project to study in-process quality metrics for software
development projects in Computational Science and Engineering (CSE), we have
developed the Metrics Dashboard, a platform for producing and observing metrics
by mining open-source software repositories on GitHub. Unlike GitHub and
similar systems that provide individual performance metrics (e.g. commits), the
Metrics Dashboard focuses on metrics indicative of team progress and project
health. The Metrics Dashboard allows the user to submit the URL of a hosted
repository for batch analysis, whose results are then cached. Upon completion,
the user can interactively study various metrics over time (at varying
granularity), numerically and visually. The initial version of the system is up
and running as a public cloud service (SaaS) and supports project size (KLOC),
defect density, defect spoilage, and productivity. While our system is by no
means the first to support software metrics, we believe it may be one of the
first community-focused extensible resources that can be used by any hosted
project.
