Determining Context Factors for Hybrid Development Methods with Trained Models

Jil Klunder, Dzejlana Karajic, Paolo Tell, Oliver Karras, Christian Munkel, Jurgen Munch, Stephen G. MacDonell, Regina Hebig, Marco Kuhrmann

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. Every project is unique and, thus, many context factors have to be considered. Recent research took some initial steps towards statistically constructing hybrid development methods, yet, paid little attention to the peculiarities of context factors influencing method and practice selection. In this paper, we utilize exploratory factor analysis and logistic regression analysis to learn such context factors and to identify methods that are correlated with these factors. Our analysis is based on 829 data points from the HELENA dataset. We provide five base clusters of methods consisting of up to 10 methods that lay the foundation for devising hybrid development methods. The analysis of the five clusters using trained models reveals only a few context factors, e.g., project/product size and target application domain, that seem to significantly influence the selection of methods. An extended descriptive analysis of these practices in the context of the identified method clusters also suggests a consolidation of the relevant practice sets used in specific project contexts.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Software and System Processes
Place of PublicationNew York, NY, USA
PublisherAssociation for Computing Machinery
Publication date2020
ISBN (Print)9781450375122
Publication statusPublished - 2020


  • Development Method Selection
  • Context Factors
  • Hybrid Development Methods
  • Exploratory Factor Analysis
  • Logistic Regression Analysis


Dive into the research topics of 'Determining Context Factors for Hybrid Development Methods with Trained Models'. Together they form a unique fingerprint.

Cite this