Industry-academia collaboration for realism in software engineering research : Insights and recommendations
(2023) In Information and Software Technology 156.- Abstract
Context: Effective industry-academia collaboration may increase software engineering research relevance by increased realism, yet very challenging for reasons like confidentiality concerns, different objectives and priorities. Objective: We analyse industry-academia collaboration scenarios based on our own experiences as Ph.D. student and supervisor, and provide insights and recommendations to facilitate future collaborations with industry. Method: We first present our industry-academia collaboration experiences that span over two and a half years with different companies. Then, we analyse both facilitators and problems from those scenarios and synthesize recommendations based on that. Results: Five different scenarios are analysed,... (More)
Context: Effective industry-academia collaboration may increase software engineering research relevance by increased realism, yet very challenging for reasons like confidentiality concerns, different objectives and priorities. Objective: We analyse industry-academia collaboration scenarios based on our own experiences as Ph.D. student and supervisor, and provide insights and recommendations to facilitate future collaborations with industry. Method: We first present our industry-academia collaboration experiences that span over two and a half years with different companies. Then, we analyse both facilitators and problems from those scenarios and synthesize recommendations based on that. Results: Five different scenarios are analysed, including both success and failure scenarios. Reflections and insights into these experiences as well as some general recommendations are presented. Conclusion: We believe such experiences and insights are helpful for academic researchers to pursue industry-academia collaboration. We plan to continuously report our experience and provide our suggestions for effective collaboration with industry.
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- author
- Song, Qunying LU and Runeson, Per LU
- organization
- publishing date
- 2023-04
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Industry-academia collaboration, Software engineering
- in
- Information and Software Technology
- volume
- 156
- article number
- 107135
- publisher
- Elsevier
- external identifiers
-
- scopus:85144604352
- ISSN
- 0950-5849
- DOI
- 10.1016/j.infsof.2022.107135
- project
- Software testing of autonomous systems
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2022 The Author(s)
- id
- c26c37db-25b6-4ec1-b356-4749c031ac72
- date added to LUP
- 2023-01-09 08:09:30
- date last changed
- 2024-06-13 14:31:33
@article{c26c37db-25b6-4ec1-b356-4749c031ac72, abstract = {{<p>Context: Effective industry-academia collaboration may increase software engineering research relevance by increased realism, yet very challenging for reasons like confidentiality concerns, different objectives and priorities. Objective: We analyse industry-academia collaboration scenarios based on our own experiences as Ph.D. student and supervisor, and provide insights and recommendations to facilitate future collaborations with industry. Method: We first present our industry-academia collaboration experiences that span over two and a half years with different companies. Then, we analyse both facilitators and problems from those scenarios and synthesize recommendations based on that. Results: Five different scenarios are analysed, including both success and failure scenarios. Reflections and insights into these experiences as well as some general recommendations are presented. Conclusion: We believe such experiences and insights are helpful for academic researchers to pursue industry-academia collaboration. We plan to continuously report our experience and provide our suggestions for effective collaboration with industry.</p>}}, author = {{Song, Qunying and Runeson, Per}}, issn = {{0950-5849}}, keywords = {{Industry-academia collaboration; Software engineering}}, language = {{eng}}, publisher = {{Elsevier}}, series = {{Information and Software Technology}}, title = {{Industry-academia collaboration for realism in software engineering research : Insights and recommendations}}, url = {{http://dx.doi.org/10.1016/j.infsof.2022.107135}}, doi = {{10.1016/j.infsof.2022.107135}}, volume = {{156}}, year = {{2023}}, }