Programa de Pós-Graduação em Sistemas de Informação e Gestão do Conhecimento | Universidade FUMEC


recomendado pela CAPES

Lessons Learned from Applying Social Network Analysis on an Industrial Free/Libre/Open Source Software Ecosystem. (arXiv:1507.04587v2 [cs.SI] UPDATED)

Many software projects are no longer done in-house by a single organization.
Instead, we are in a new age where software is developed by a networked
community of individuals and organizations, which base their relations to each
other on mutual interest. Paradoxically, recent research suggests that software
development can actually be jointly-developed by rival firms. For instance, it
is known that the mobile-device makers Apple and Samsung kept collaborating in
open source projects while running expensive patent wars in the court. Taking a
case study approach, we explore how rival firms collaborate in the open source
arena by employing a multi-method approach that combines qualitative analysis
of archival data (QA) with mining software repositories (MSR) and Social
Network Analysis (SNA). While exploring collaborative processes within the
OpenStack ecosystem, our research contributes to Software Engineering research
by exploring the role of groups, sub-communities and business models within a
high-networked open source ecosystem. Surprising results point out that
competition for the same revenue model (i.e., operating conflicting business
models) does not necessary affect collaboration within the ecosystem. Moreover,
while detecting the different sub-communities of the OpenStack community, we
found out that the expected social tendency of developers to work with
developers from same firm (i.e., homophily) did not hold within the OpenStack
ecosystem. Furthermore, while addressing a novel, complex and unexplored open
source case, this research also contributes to the management literature in
coopetition strategy and high-tech entrepreneurship with a rich description on
how heterogeneous actors within a high-networked ecosystem (involving
individuals, startups, established firms and public organizations)
joint-develop a complex infrastructure for big-data in the open source arena.