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.

翻译：软件制品（特别是代码）的有效所有权对于责任归属、知识共享和代码质量提升至关重要。研究者已提出多种将软件制品所有权与开发者绩效及代码质量相关联的模型。本研究旨在系统性地检视各类所有权模型，并提供结构化的文献综述。通过系统性文献综述方法，我们识别出2005年至2022年间发表的79篇相关论文。我们基于所有权类型、所有者及所有权程度构建了所有权制品的分类体系，同时汇总了各项研究使用的建模变量与分析类型。此外，我们还评估了每项研究的可复现性状况。研究发现，文献中共讨论了九类不同的软件制品所有权，其中"代码"是最常被分析的对象。仅有三篇论文（3.79%）提供了代码与数据，九篇论文（11.4%）仅提供了数据。基于系统性文献综述的结果，我们对\texttt{Brightsquid}公司的九个优先项目进行了实验复现。该公司希望将其代码质量与其他团队的所有权因素进行对比，因此我们利用其数据开展了复现研究。与先前研究不同，我们发现次要贡献者与缺陷数量之间不存在强相关性。令人惊讶的是，修改文件的开发者总数与缺陷数量也未呈现显著关联，这与既往结论相悖。然而，我们观察到主要贡献者与缺陷数量之间存在显著相关性，这一发现与早期研究存在差异。