Software selection in large-scale software engineering: A model and criteria based on interactive rapid reviews
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| Názov: | Software selection in large-scale software engineering: A model and criteria based on interactive rapid reviews |
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| Autori: | Bjarnason, Elizabeth, Åberg, Patrik, Ali, Nauman bin, Dr. |
| Zdroj: | ELLIIT eLLIIT – The Linköping – Lund Initiative on IT and Mobile Communication Empirical Software Engineering. 28(2) |
| Predmety: | Computer software selection and evaluation, Software design, CBSE, Component based, Component selection, Ericsson, Informed decision, Large-scales, Rapid review, Software component selections, Software selection, Tool selection, Iterative methods, Component-based |
| Popis: | Context: Software selection in large-scale software development continues to be ad hoc and ill-structured. Previous proposals for software component selection tend to be technology-specific and/or do not consider business or ecosystem concerns. Objective: Our main aim is to develop an industrially relevant technology-agnostic method that can support practitioners in making informed decisions when selecting software components for use in tools or in products based on a holistic perspective of the overall environment. Method: We used method engineering to iteratively develop a software selection method for Ericsson AB based on a combination of published research and practitioner insights. We used interactive rapid reviews to systematically identify and analyse scientific literature and to support close cooperation and co-design with practitioners from Ericsson. The model has been validated through a focus group and by practical use at the case company. Results: The model consists of a high-level selection process and a wide range of criteria for assessing and for evaluating software to include in business products and tools. Conclusions: We have developed an industrially relevant model for component selection through active engagement from a company. Co-designing the model based on previous knowledge demonstrates a viable approach to industry-academia collaboration and provides a practical solution that can support practitioners in making informed decisions based on a holistic analysis of business, organisation and technical factors. © 2023, The Author(s). |
| Popis súboru: | electronic |
| Prístupová URL adresa: | https://urn.kb.se/resolve?urn=urn:nbn:se:bth-24374 https://doi.org/10.1007/s10664-023-10288-w |
| Databáza: | SwePub |
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Nájsť tento článok vo Web of Science | Abstrakt: | Context: Software selection in large-scale software development continues to be ad hoc and ill-structured. Previous proposals for software component selection tend to be technology-specific and/or do not consider business or ecosystem concerns. Objective: Our main aim is to develop an industrially relevant technology-agnostic method that can support practitioners in making informed decisions when selecting software components for use in tools or in products based on a holistic perspective of the overall environment. Method: We used method engineering to iteratively develop a software selection method for Ericsson AB based on a combination of published research and practitioner insights. We used interactive rapid reviews to systematically identify and analyse scientific literature and to support close cooperation and co-design with practitioners from Ericsson. The model has been validated through a focus group and by practical use at the case company. Results: The model consists of a high-level selection process and a wide range of criteria for assessing and for evaluating software to include in business products and tools. Conclusions: We have developed an industrially relevant model for component selection through active engagement from a company. Co-designing the model based on previous knowledge demonstrates a viable approach to industry-academia collaboration and provides a practical solution that can support practitioners in making informed decisions based on a holistic analysis of business, organisation and technical factors. © 2023, The Author(s). |
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| ISSN: | 13823256 15737616 |
| DOI: | 10.1007/s10664-023-10288-w |