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).