Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/46030
Título: | Industry-academia collaborations in software engineering: An empirical analysis of challenges, patterns and anti-patterns in research projects |
Autor(es): | Garousi, Vahid Felderer, Michael Fernandes, João M. Pfahl, Dietmar Mäntylä, Mika V. |
Palavras-chave: | software engineering industry-academia collaborations research empirical study success factors challenges patterns anti-patterns |
Data: | Jun-2017 |
Editora: | ACM |
Citação: | Vahid Garousi, Michael Felderer, João M. Fernandes, Dietmar Pfahl, and Mika V. Mäntylä. 2017. Industry-academia collaborations in so ware engineering. In Proceedings of EASE’17, Karlskrona, Sweden, June 15-16, 2017, 6 pages. DOI: http://dx.doi.org/10.1145/3084226.3084279 |
Resumo(s): | Research collaboration between industry and academia supports improvement and innovation in industry and helps to ensure industrial relevance in academic research. However, many researchers and practitioners believe that the level of joint industry-academia collaboration (IAC) in software engineering (SE) research is still relatively low, compared to the amount of activity in each of the two communities. The goal of the empirical study reported in this paper is to exploratory characterize the state of IAC with respect to a set of challenges, patterns and anti-patterns identified by a recent Systematic Literature Review study. To address the above goal, we gathered the opinions of researchers and practitioners w.r.t. their experiences in IAC projects. Our dataset includes 47 opinion data points related to a large set of projects conducted in 10 different countries. We aim to contribute to the body of evidence in the area of IAC, for the benefit of researchers and practitioners in conducting future successful IAC projects in SE. As an output, the study presents a set of empirical findings and evidence-based recommendations to increase the success of IAC projects. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/46030 |
ISBN: | 978-1-4503-4804-1 |
DOI: | 10.1145/3084226.3084279 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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2017-EASE-ACM.pdf | 2,14 MB | Adobe PDF | Ver/Abrir |