129,613 research outputs found
Importance of Social Networks for Knowledge Sharing and the Impact of Collaboration on Network Innovation in Online Communities
Innovation results from interactions between different sources of knowledge, where these sources aggregate into groups interacting within (intra) and between (inter) groups. Interaction among groups for innovation generation is defined as the process by which an innovation is communicated through certain channels over time among members of a social system. Apart from the discussion about knowledge management within organizations and the discussion about social network analysis of organizations on the topic of innovation and talks about various trade-offs between strength of ties and bridging ties between different organizational groups, within the topic of open source software (OSS) development researchers have used social network theories to investigate OSS phenomenon including communication among developers. It is already known that OSS groups are more networked than the most organizational communities; In OSS network, programmers can join, participate and leave a project at any time, and in fact developers can collaborate not only within the same project but also among different projects or teams. One distinguished feature of the open source software (OSS) development model is the cooperation and collaboration among the members, which will cause various social networks to emerge. In this chapter, the existing gap in the literature with regard to the analysis of cluster or group structure as an input and cluster or group innovation as an output will be addressed, where the focus is on “impact of network cluster structure on cluster innovation and growth” by Behfar et al., that is, how intra- and inter-cluster coupling, structural holes and tie strength impact cluster innovation and growth, and “knowledge management in OSS communities: relationship between dense and sparse network structures.” by Behfar et al., that is, knowledge transfer in dense network (inside groups) impacts on knowledge transfer in sparse network (between groups)
git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories
Data from software repositories have become an important foundation for the
empirical study of software engineering processes. A recurring theme in the
repository mining literature is the inference of developer networks capturing
e.g. collaboration, coordination, or communication from the commit history of
projects. Most of the studied networks are based on the co-authorship of
software artefacts defined at the level of files, modules, or packages. While
this approach has led to insights into the social aspects of software
development, it neglects detailed information on code changes and code
ownership, e.g. which exact lines of code have been authored by which
developers, that is contained in the commit log of software projects.
Addressing this issue, we introduce git2net, a scalable python software that
facilitates the extraction of fine-grained co-editing networks in large git
repositories. It uses text mining techniques to analyse the detailed history of
textual modifications within files. This information allows us to construct
directed, weighted, and time-stamped networks, where a link signifies that one
developer has edited a block of source code originally written by another
developer. Our tool is applied in case studies of an Open Source and a
commercial software project. We argue that it opens up a massive new source of
high-resolution data on human collaboration patterns.Comment: MSR 2019, 12 pages, 10 figure
Research Agenda for Studying Open Source II: View Through the Lens of Referent Discipline Theories
In a companion paper [Niederman et al., 2006] we presented a multi-level research agenda for studying information systems using open source software. This paper examines open source in terms of MIS and referent discipline theories that are the base needed for rigorous study of the research agenda
Detecting Coordination Problems in Collaborative Software Development Environments
Software development is rarely an individual effort and generally involves teams of developers collaborating to generate good reliable code. Among the software code there exist technical dependencies that arise from software components using services from other components. The different ways of assigning the design, development, and testing of these software modules to people can cause various coordination problems among them. We claim\ud
that the collaboration of the developers, designers and testers must be related to and governed by the technical task structure. These collaboration practices are handled in what we call Socio-Technical Patterns.\ud
The TESNA project (Technical Social Network Analysis) we report on in this paper addresses this issue. We propose a method and a tool that a project manager can use in order to detect the socio-technical coordination problems. We test the method and tool in a case study of a small and innovative software product company
TESNA: A Tool for Detecting Coordination Problems
Detecting problems in coordination can prove to be very difficult. This is especially true in large globally distributed environments where the Software Development can quickly go out of the Project Manager’s control. In this paper we outline a methodology to analyse the socio-technical coordination structures. We also show how this can be made easier with the help of a tool called TESNA that we have developed
Exploring the Impact of Socio-Technical Core-Periphery Structures in Open Source Software Development
In this paper we apply the social network concept of core-periphery structure
to the sociotechnical structure of a software development team. We propose a
socio-technical pattern that can be used to locate emerging coordination
problems in Open Source projects. With the help of our tool and method called
TESNA, we demonstrate a method to monitor the socio-technical core-periphery
movement in Open Source projects. We then study the impact of different
core-periphery movements on Open Source projects. We conclude that a steady
core-periphery shift towards the core is beneficial to the project, whereas
shifts away from the core are clearly not good. Furthermore, oscillatory shifts
towards and away from the core can be considered as an indication of the
instability of the project. Such an analysis can provide developers with a good
insight into the health of an Open Source project. Researchers can gain from
the pattern theory, and from the method we use to study the core-periphery
movements
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