Smart Analyser of Variability Requirements of Unknown Spaces (SAVRUS) Dataset of a study with 5 real-world large numerical variability models.

The publications and research associated to cite is in:
https://doi.org/10.1016/j.knosys.2023.110558
In that research we detail the Smart Analyser of Variability Requirements of Unknown Spaces (SAVRUS) approach, and provide a web-tool prototype in https://hadas.caosd.lcc.uma.es/savrus
In the study, we model 5 different real-world software product lines to then analysed them with SAVRUS:
Detailed real-world variability models ordered by their search space size, of which GEC QA is incompletely measured NVM Description #Booleans #Numericals Space QA #Measurements 
Dune1

Multi-grid solver

11

3

2,304

Complex..

2,304

HSMGP1

Stencil-grid solver

14

3

3,456

..equation..

3,456

HiPAcc1

Image processing framework

33

2

13,485

..solving..

13,485

Trimesh2

Triangle mesh library

13

4

239,360

..time

239,360

GEC

Generic edge computing

552

2

~5.3*108

Energy Consumption

132500

The dataset zip file contains:

5 numerical variability models in Clafer format (.txt) for each software product line.
5 CSV files with the respective quality attribute measurements
An .xlsx file containing SAVRUS scalability results divided in different tabs.
References:
[1] N. Siegmund, A. Grebhahn, S. Apel, C. Kastner, Performance-influence models for highly configurable systems, in: Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, ESEC/FSE 2015, Association for Computing Machinery, New York, NY, USA, 2015, p.284–294. doi:10.1145/2786805.2786845.
[2] M. Bauer, A comparison of six constraint solvers for variability analysis, Tech. rep., University of Passau (2019).