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Borg, M., Chatzipetrou, P., Wnuk, K., Alégroth, E., Gorschek, T., Papatheocharous, E., . . . Axelsson, J. (2018). Selecting Software Component Sourcing Options: Detailed Survey Description and Analysis.
Open this publication in new window or tab >>Selecting Software Component Sourcing Options: Detailed Survey Description and Analysis
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2018 (English)Report (Other academic)
Abstract [en]

Component-based software engineering (CBSE) is a common approach to develop and evolve contemporary software systems. When evolving a system based on components, make-or-buy decisions are frequent, i.e., whether to develop components internally or to acquire them fromexternal sources. In CBSE, several different sourcing options are available: 1) developing software in-house, 2) outsourcing development, 3) buying commercial-off-the-shelf software, and 4) integrating open source software components. Unfortunately, there is little available research on howorganizations select component sourcing options (CSO) in industry practice. In this work, we seek to contribute empirical evidence to CSO selection. Method: We conduct a cross-domain survey on CSO selection in industry, implemented as an online questionnaire. Based on 188 responses, we find that most organizations consider multiple CSOs during software evolution, and that the CSO decisions in industry are dominated by expert judgment. When choosing between candidate components, functional suitability acts as an initial filter, then reliability is the most important quality. We stress that future solution-oriented work on decision support has to account for the dominance of expert judgment in industry. Moreover, we identify considerable variation in CSO decision processes in industry. Finally, we encourage software development organizations to reflect on their decision processes when choosing whether to make or buy components, and we recommend using our survey for a first benchmarking.

Publisher
p. 36
Series
RISE Report ; 2018:71
Keywords
Component-based software engineering, sourcing, software architecture, decision making, survey
National Category
Software Engineering
Identifiers
urn:nbn:se:oru:diva-72566 (URN)978-91-88907-15-8 (ISBN)
Projects
Orion
Funder
Knowledge Foundation, 20140218
Available from: 2019-04-23 Created: 2019-04-23 Last updated: 2019-06-18Bibliographically approved
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-7879-4371

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