  Effective ownership of software artifacts, particularly code, is crucial for
accountability, knowledge sharing, and code quality enhancement. Researchers
have proposed models linking ownership of software artifacts with developer
performance and code quality. Our study aims to systematically examine various
ownership models and provide a structured literature overview. Conducting a
systematic literature review, we identified 79 relevant papers published
between 2005 and 2022. We developed a taxonomy of ownership artifacts based on
type, owners, and degree of ownership, along with compiling modeling variables
and analytics types used in each study. Additionally, we assessed the
replication status of each study. As a result, we identified nine distinct
software artifacts whose ownership has been discussed in the literature, with
"Code" being the most frequently analyzed artifact. We found that only three
papers (3.79%) provided code and data, whereas nine papers (11.4%) provided
only data. Using our systematic literature review results, we replicated
experiments on nine priority projects at \texttt{Brightsquid}. The company
aimed to compare its code quality against ownership factors in other teams, so
we conducted a replication study using their data. Unlike prior studies, we
found no strong correlation between minor contributors and bug numbers.
Surprisingly, we found no strong link between the total number of developers
modifying a file and bug counts, contrasting previous findings. However, we
observed a significant correlation between major contributors and bug counts,
diverging from earlier research.
