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A systematic examination of knowledge loss in open source software projects

Rashid, Mehvish orcid logoORCID: 0000-0002-9824-5035, Clarke, Paul orcid logoORCID: 0000-0002-4487-627X and O'Connor, Rory orcid logoORCID: 0000-0001-9253-0313 (2018) A systematic examination of knowledge loss in open source software projects. International Journal of Information Management, 46 . pp. 104-123. ISSN 0268-4012

Abstract
Context Open Source Software (OSS) development is a knowledge focused activity which relies heavily on contributors who can be volunteers or paid workers and are geographically distributed. While working on OSS projects contributors acquire project related individualistic knowledge and gain experience and skills, which often remains unshared with others and is usually lost once contributors leave a project. All software development organisations face the problem of knowledge loss as employees leave, but this situation is exasperated in OSS projects where most contributors are volunteers with largely unpredictable engagement durations. Contributor turnover is inevitable due to the transient nature of OSS project workforces causing knowledge loss, which threatens the overall sustainability of OSS projects and impacts negatively on software quality and contributor productivity. Objective The objective of this work is to deeply and systematically investigate the phenomenon of knowledge loss due to contributor turnover in OSS projects as presented in the state-of-the-art literature and to synthesise the information presented on the topic. Furthermore, based on the learning arising from our investigation it is our intention to identify mechanisms to reduce the overall effects of knowledge loss in OSS projects. Methodology We use the snowballing methodology to identify the relevant literature on knowledge loss due to contributor turnover in OSS projects. This robust methodology for a literature review includes research question, search strategy, inclusion, exclusion, quality criteria, and data synthesis. The search strategy, and inclusion, exclusions and quality criteria are applied as a part of snowballing procedure. Snowballing is considered an efficient and reliable way to conduct a systematic literature review, providing a robust alternative to mechanically searching individual databases for given topics. Result Knowledge sharing in OSS projects is abundant but there is no evidence of a formal strategy or practice to manage knowledge. Due to the dynamic and diverse nature of OSS projects, knowledge management is considered a challenging task and there is a need for a proactive mechanism to share knowledge in the OSS community for knowledge to be reused in the future by the OSS project contributors. From the collection of papers found using snowballing, we consolidated various themes on knowledge loss due to contributor turnover in OSS projects and identified 11 impacts due to knowledge loss in OSS projects, and 10 mitigations to manage with knowledge loss in OSS projects. Conclusion In this paper, we propose future research directions to investigate integration of proactive knowledge retention practices with the existing OSS practices to reduce the current knowledge loss problem. We suggest that there is insufficient attention paid to KM in general in OSS, in particular there would appear to an absence of proactive measures to reduce the potential impact of knowledge loss. We also propose the need for a KM evaluation metric in OSS projects, similar to the ones that evaluate health of online communities, which should help to inform potential consumers of the OSS of the KM status on a project, something that is not existent today.
Metadata
Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:Open Source Software; Knowledge loss; Contributor turnover; Knowledge retention; Knowledge loss impact; Knowledge Management
Subjects:Computer Science > Computer software
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > Lero: The Irish Software Engineering Research Centre
Publisher:Elsevier
Official URL:https://doi.org/10.1016/j.ijinfomgt.2018.11.015
Copyright Information:© 2018 Elsevier
ID Code:29119
Deposited On:09 Oct 2023 11:05 by Thomas Murtagh . Last Modified 28 Nov 2023 12:28
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