Towards the statistical construction of hybrid development methods
- ,
- Jil Klünder,
- Steffen Küpper,
- David Raffo,
- Stephen MacDonell,
- Jürgen Münch
- ,
- Leibniz University Hannover,
- Clausthal University of Technology,
- Portland State University,
- Auckland University of Technology,
- Reutlingen University
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-reviewOpen access
Publication Information
Output type
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-reviewOriginal language
EnglishJournal (Volume, Issue Number)
Journal of Software: Evolution and Process (Volume 33, Issue 1)Publication milestones
- Published - 2021
Publication status
Published - 2021
ISSN
1532-060XPublication IDs
- Scopus: 85096761266
Abstract
Hardly any software development process is used as prescribed by authors or standards. Regardless of company size or industry sector, a majority of project teams and companies use hybrid development methods (short: hybrid methods) that combine different development methods and practices. Even though such hybrid methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this article, we make a first step towards a statistical construction procedure for hybrid methods. Grounded in 1467 data points from a large‐scale practitioner survey, we study the question: What are hybrid methods made of and how can they be systematically constructed? Our findings show that only eight methods and few practices build the core of modern software development. Using an 85% agreement level in the participants' selections, we provide examples illustrating how hybrid methods can be characterized by the practices they are made of. Furthermore, using this characterization, we develop an initial construction procedure, which allows for defining a method frame and enriching it incrementally to devise a hybrid method using ranked sets of practice.
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Accepted author manuscript, 1.06 MB
