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A tailored participatory action research for foss communities.

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Title: A tailored participatory action research for foss communities.
Authors: Alami, Adam1 adaa@itu.dk, Nielsen, Peter Axel2, Wa̧sowski, Andrzej1
Source: Empirical Software Engineering. Sep2020, Vol. 25 Issue 5, p3639-3670. 32p.
Subjects: Community-based participatory research, Quality assurance, Volunteers, Computer operating systems, Computer software
Abstract: Participatory Action Research (PAR) is an established method to implement change in organizations. However, it cannot be applied in the open source (FOSS) communities, without adaptation to their particularities, especially to the specific control mechanisms developed in FOSS. FOSS communities are self-managed, and rely on consensus to reach decisions. This study proposes a PAR framework specifically tailored to FOSS communities. We successfully applied the framework to implement a set of quality assurance interventions in the Robot Operating System community. The framework we proposed is composed of three components, interventions design, democratization, and execution. We believe that this process will work for other FOSS communities too. We have learned that changing a particular aspect of a FOSS community is arduous. To achieve success the change must rally the community around it for support and attract motivated volunteers to implement the interventions. [ABSTRACT FROM AUTHOR]
Copyright of Empirical Software Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: A tailored participatory action research for foss communities.
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  Data: <searchLink fieldCode="JN" term="%22Empirical+Software+Engineering%22">Empirical Software Engineering</searchLink>. Sep2020, Vol. 25 Issue 5, p3639-3670. 32p.
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  Data: <searchLink fieldCode="DE" term="%22Community-based+participatory+research%22">Community-based participatory research</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+assurance%22">Quality assurance</searchLink><br /><searchLink fieldCode="DE" term="%22Volunteers%22">Volunteers</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+operating+systems%22">Computer operating systems</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software%22">Computer software</searchLink>
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  Data: Participatory Action Research (PAR) is an established method to implement change in organizations. However, it cannot be applied in the open source (FOSS) communities, without adaptation to their particularities, especially to the specific control mechanisms developed in FOSS. FOSS communities are self-managed, and rely on consensus to reach decisions. This study proposes a PAR framework specifically tailored to FOSS communities. We successfully applied the framework to implement a set of quality assurance interventions in the Robot Operating System community. The framework we proposed is composed of three components, interventions design, democratization, and execution. We believe that this process will work for other FOSS communities too. We have learned that changing a particular aspect of a FOSS community is arduous. To achieve success the change must rally the community around it for support and attract motivated volunteers to implement the interventions. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Empirical Software Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10664-020-09849-0
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      – SubjectFull: Quality assurance
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      – SubjectFull: Volunteers
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              Text: Sep2020
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