You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: On Using Network Science in Mining Developers Collaboration in Software Engineering: A Systematic Literature Review 
Chapter Title:  Discussion around RQ3: 
1. Abstract of Cited Paper (BIB001):  Ownership is a key aspect of large-scale software development. We examine the relationship between different ownership measures and software failures in two large software projects: Windows Vista and Windows 7. We find that in all cases, measures of ownership such as the number of low-expertise developers, and the proportion of ownership for the top owner have a relationship with both pre-release faults and post-release failures. We also empirically identify reasons that low-expertise developers make changes to components and show that the removal of low-expertise contributions dramatically decreases the performance of contribution based defect prediction. Finally we provide recommendations for source code change policies and utilization of resources such as code inspections based on our results. 
2. Abstract of Cited Paper (BIB002):  Developer teams may naturally emerge independent of managerial decisions, organizational structure, or work locations in large software. Such self organized collaboration teams of developers can be traced from the source code repositories. In this paper, we identify the developer teams in the collaboration network in order to present the work team evolution and the factors that affect team stability for a large, globally developed, commercial software. Our findings indicate that: a) Number of collaboration teams do not change over time, b) Size of the collaboration teams increases over time, c) Team activity is not related with team size, d) Factors related to team size, location and activity affect the stability of teams over time. 
3. Abstract of Cited Paper (BIB003):  Effective software engineering demands a coordinated effort. Unfortunately, a comprehensive view on developer coordination is rarely available to support software-engineering decisions, despite the significant implications on software quality, software architecture, and developer productivity. We present a fine-grained, verifiable, and fully automated approach to capture a view on developer coordination, based on commit information and source-code structure, mined from version-control systems. We apply methodology from network analysis and machine learning to identify developer communities automatically. Compared to previous work, our approach is fine-grained, and identifies statistically significant communities using order-statistics and a community-verification technique based on graph conductance. To demonstrate the scalability and generality of our approach, we analyze ten open-source projects with complex and active histories, written in various programming languages. By surveying 53 open-source developers from the ten projects, we validate the authenticity of inferred community structure with respect to reality. Our results indicate that developers of open-source projects form statistically significant community structures and this particular view on collaboration largely coincides with developers' perceptions of real-world collaboration.

Literature Review:
Classically, the random graphs null models are used to validate the significance of the results obtained from networks. For our PSs, only 14% of them, 5 PSs, BIB002 BIB001 BIB004  BIB003