  Software repositories are rich sources of qualitative artifacts, including
source code comments, commit messages, issue descriptions, and documentation.
These artifacts offer many interesting insights when analyzed through
quantitative methods, as outlined in the chapter on mining software
repositories. This chapter shifts the focus towards interpreting these
artifacts using various qualitative data analysis techniques. We introduce
qualitative coding as an iterative process, which is crucial not only for
educational purposes but also to enhance the credibility and depth of research
findings. Various coding methods are discussed along with the strategic design
of a coding guide to ensure consistency and accuracy in data interpretation.
The chapter also discusses quality assurance in qualitative data analysis,
emphasizing principles such as credibility, transferability, dependability, and
confirmability. These principles are vital to ensure that the findings are
robust and can be generalized in different contexts. By sharing best practices
and lessons learned, we aim to equip all readers with the tools necessary to
conduct rigorous qualitative research in the field of software engineering.
