Variability Understanding
Variability Understanding is a methodological construct in data interpretation that identifies and quantifies the extent, sources, and implications of variation within datasets to distinguish systematic patterns from random fluctuations.
41
Publications
2.6K
Citations
88
Authors
52
Institutions
Publications per year
2017–2026
8
Parents
41
A survey of variability modeling in industrial practice
Thorsten Berger, Ralf Rublack, D. Nair et al. · 2013 · 395 citations
Understanding Variation: The Key to Managing Chaos
Joseph O. Voelkel · Technometrics · 1994 · 161 citations
The variability debate: More statistics, more linguistics
Dan Drai, Yosef Grodzinsky · Brain and Language · 2005 · 113 citations
1–5 of 41
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Fraunhofer Institute for Experimental Software Engineering, Germany
2 publications · 416 citations
2
h-index
1–5 of 88
52
University of Haifa
Haifa, Israel
4 h-index
4 publications
225 citations
University of Minnesota System
Minneapolis, United States
2 h-index
2 publications
121 citations

IT University of Copenhagen
Copenhagen, Denmark
2 h-index
2 publications
449 citations

University of Waterloo
Waterloo, Canada
2 h-index
6 publications
1.3K citations
University of Michigan
Ann Arbor, United States
2 h-index
2 publications
26 citations
Fraunhofer Institute for Experimental Software Engineering
Kaiserslautern, Germany
2 h-index
3 publications
437 citations
Rochester Institute of Technology
Rochester, United States
2 h-index
2 publications
174 citations
University of California, Los Angeles
Los Angeles, United States
1 h-index
1 publications
38 citations
1–8 of 52
8 publications · 360 citations
8
h-index
2 publications · 174 citations
2
h-index
2 publications · 26 citations
2
h-index
BRM · 1 publications · 24 citations
1
h-index
1 publications · 10 citations
1
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1–5