Git repositories are an important source of empirical software engineering product and process data. Running the Git command line tool and processing its output with other Unix tools allows the incremental construction of sophisticated and highly efficient data processing pipelines. Git data analytics on the command line can be systematically presented through a pattern that involves fetching, selection, processing, summarization, and reporting. For each part of the processing pipeline, the technical briefing examines the tools and techniques that can be most effectively used to perform the task at hand.

A broad section of the software engineering community can benefit from this briefing. The presented techniques are not widely known but can be easily applied, initially to get a feeling of version control repository data at hand and then also for extracting empirical results.

The speakers have applied the presented methods in empirical software engineering research settings and have written about them extensively. Importantly, they have first hand experience of the shortcomings of more heavyweight tools and approaches, which led them to come up with the techniques presented in this workshop. They are both active toolsmiths and have been teaching students on how to effectively use the command line for more than 20 years.