@proceedings {1903,
	title = {Release Early, Release Often and Release on Time. An Empirical Case Study of Release Management},
	volume = {496},
	year = {2017},
	month = {05/2017},
	pages = {167-181},
	publisher = {Springer},
	abstract = {The dictum of {\textquotedblleft}Release early, release often.{\textquotedblright} by Eric Raymond as the Linux modus operandi highlights the importance of release management in open source software development. Nevertheless, there are very few empirical studies addressing release management in open source software development. It is already known that most open source software communities adopt either feature-based or time-based release strategies. Each of these has its advantages and disadvantages that are context-specific. Recent research reported that many prominent open source software projects have moved from feature-based to time-based releases. In this longitudinal case study, we narrate how OpenStack shifted towards a liberal six-month release cycle. If prior research discussed why projects should adopt time-based releases and how they can adopt such a strategy, we discuss how OpenStack adapted its software development processes, its organizational design and its tools toward a hybrid release management strategy {\textemdash} a strive for balancing the benefits and drawbacks of feature-based and time-based release strategies.},
	keywords = {openstack, release management},
	doi = {10.1007/978-3-319-57735-7_16},
	url = {https://link.springer.com/chapter/10.1007/978-3-319-57735-7_16},
	author = {Teixeira, Jose}
}
@proceedings {1750,
	title = {Co-evolution of Infrastructure and Source Code - An Empirical Study},
	year = {2015},
	month = {05/2015},
	abstract = {Infrastructure-as-code automates the process of
configuring and setting up the environment (e.g., servers, VMs
and databases) in which a software system will be tested and/or
deployed, through textual specification files in a language like
Puppet or Chef. Since the environment is instantiated automatically
by the infrastructure languages{\textquoteright} tools, no manual
intervention is necessary apart from maintaining the infrastructure
specification files. The amount of work involved with such
maintenance, as well as the size and complexity of infrastructure
specification files, have not yet been studied empirically. Through
an empirical study of the version control system of 265 OpenStack
projects, we find that infrastructure files are large and churn
frequently, which could indicate a potential of introducing bugs.
Furthermore, we found that the infrastructure code files are
coupled tightly with the other files in a project, especially test files,
which implies that testers often need to change infrastructure
specifications when making changes to the test framework and
tests.},
	keywords = {openstack},
	url = {http://mcis.polymtl.ca/publications/2015/msrjojo.pdf},
	attachments = {https://flosshub.org/sites/flosshub.org/files/msrjojo.pdf},
	author = {Yujuan Jiang and Adams, Bram}
}
@booklet {1781,
	title = {Lessons Learned from Applying Social Network Analysis on an Industrial Free/Libre/Open Source Software Ecosystem},
	year = {2015},
	abstract = {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., homophony) 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.},
	keywords = {business models, cloud computing, homophily, open source, Open-Coopetition, openstack, social network analysis, Software ecosystems},
	url = {http://arxiv.org/abs/1507.04587},
	author = {Teixeira, Jose and Gregorio Robles and Jesus M. Gonzalez-Barahona}
}
@proceedings {roblesestimating,
	title = {Estimating Development Effort in Free/Open Source Software Projects by Mining Software Repositories: A Case Study of OpenStack},
	year = {2014},
	month = {05/2014},
	abstract = {Because of the distributed and collaborative nature of free/open source software (FOSS) projects, the development effort invested in a project is usually unknown, even after the software has been released. However, this information is becoming of major interest, especially - but not only- because of the growth in the number of companies for which FOSS has become relevant for their business strategy. In this paper we present a novel approach to estimate effort by considering data from source code management repositories. We apply our model to the OpenStack project, a FOSS
project with more than 1,000 authors, in which several tens of companies cooperate. Based on data from its repositories and together with the input from a survey answered by more than 100 developers, we show that the model offers a simple, but sound way of obtaining software development estimations
with bounded margins of error.},
	keywords = {effort estimation, openstack},
	url = {http://gsyc.urjc.es/~grex/repro/2014-msr-effort/msr14-robles-estimating-effort.pdf},
	attachments = {https://flosshub.org/sites/flosshub.org/files/msr14-robles-estimating-effort.pdf},
	author = {Gregorio Robles and Gonz{\'a}lez-Barahona, Jesus M and Cervig{\'o}n, Carlos and Capiluppi, Andrea}
}
@conference {Robles:2014:EDE:2597073.2597107,
	title = {Estimating Development Effort in Free/Open Source Software Projects by Mining Software Repositories: A Case Study of OpenStack},
	booktitle = {Proceedings of the 11th Working Conference on Mining Software Repositories},
	series = {MSR 2014},
	year = {2014},
	pages = {222{\textendash}231},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Because of the distributed and collaborative nature of free / open source software (FOSS) projects, the development effort invested in a project is usually unknown, even after the software has been released. However, this information is becoming of major interest, especially ---but not only--- because of the growth in the number of companies for which FOSS has become relevant for their business strategy. In this paper we present a novel approach to estimate effort by considering data from source code management repositories. We apply our model to the OpenStack project, a FOSS project with more than 1,000 authors, in which several tens of companies cooperate. Based on data from its repositories and together with the input from a survey answered by more than 100 developers, we show that the model offers a simple, but sound way of obtaining software development estimations with bounded margins of error.
},
	keywords = {effort estimation, free software, mining software repositories, open source, openstack},
	isbn = {978-1-4503-2863-0},
	doi = {10.1145/2597073.2597107},
	url = {http://doi.acm.org/10.1145/2597073.2597107},
	attachments = {https://flosshub.org/sites/flosshub.org/files/robles_0.pdf},
	author = {Gregorio Robles and Gonz{\'a}lez-Barahona, Jes{\'u}s M. and Cervig{\'o}n, Carlos and Capiluppi, Andrea and Izquierdo-Cort{\'a}zar, Daniel}
}
@article {1554,
	title = {Using software analytics to understand how companies interact in free software communities},
	journal = {IEEE Software},
	year = {2013},
	month = {2013},
	pages = {1 - 1},
	abstract = {

Free, open source software development communities may become large and complex. They may also be a focus of interest for competing companies relying on their outcomes, with their employees joining the development and maintenance effort. In those cases it is specially important for both companies and communities to understand how this collaboration is working, and how it matches their policies and expectations. In this paper we show two cases (OpenStack and WebKit) which we have studied using analytics techniques on the data obtained from their software development repositories. From them, we conclude that analytics on this data can improve the factual knowledge about how development communities are performing in aspects which are of interest to companies, and fundamental to ensure transparency and fairness.
},
	keywords = {openstack, webkit},
	issn = {0740-7459},
	doi = {10.1109/MS.2013.95},
	author = {Gonzalez-Barahona, Jesus and Izquierdo, Daniel and Maffulli, Stefano and Gregorio Robles}
}
