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Determining context factors for hybrid development methods with trained models

  • Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. To extend the so far statistical construction of hybrid development methods, we analyze 829 data points to investigate which context factors influence the choice of methods or practices. Using exploratory factor analysis, we derive five base clusters consisting of up to 10 methods. Logistic regression analysis then reveals which context factors have an influence on the integration of methods from these clusters in the development process. Our results indicate that only a few context factors including project/product size and target application domain significantly influence the choice. This summary refers to the paper “Determining Context Factors for Hybrid Development Methods with Trained Models”. This paper was published in the proceedings of the International Conference on Software and System Process in 2020.

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Metadaten
Author of HS ReutlingenMünch, Jürgen
URN:urn:nbn:de:bsz:rt2-opus4-29650
DOI:https://doi.org/10.18420/SE2021_21
ISBN:978-3-88579-704-3
ISSN:1617-5468
Erschienen in:Software Engineering 2021
Publisher:Gesellschaft für Informatik
Place of publication:Bonn
Editor:Anne Koziolek, Ina Schaefer, Christoph Seidl
Document Type:Part of a Book
Language:English
Year of Publication:2021
Page Number:2
First Page:65
Last Page:66
DDC classes:004 Informatik
Open Access?:Ja
Licence (German):License Logo  Creative Commons - CC BY-SA - Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International