Family-based performance analysis of variant-rich software systems (bibtex)
by Kowal, Matthias, Schaefer, Ina and Tribastone, Mirco
Abstract:
We study models of software systems with variants that stem from a specific choice of configuration parameters with a direct impact on performance properties. Using UML activity diagrams with quantitative annotations, we model such systems as a product line. The efficiency of a product-based evaluation is typically low because each product must be analyzed in isolation, making difficult the re-use of computations across variants. Here, we propose a family-based approach based on symbolic computation. A numerical assessment on large activity diagrams shows that this approach can be up to three orders of magnitude faster than product-based analysis in large models, thus enabling computationally efficient explorations of large parameter spaces.
Reference:
Family-based performance analysis of variant-rich software systems (Kowal, Matthias, Schaefer, Ina and Tribastone, Mirco), Chapter in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Gnesi, Stefania, Rensink, Arend, eds.), Springer Berlin Heidelberg, volume 8411 LNCS, 2014.
Bibtex Entry:
@incollection{KST14,
abstract = {We study models of software systems with variants that stem from a specific choice of configuration parameters with a direct impact on performance properties. Using UML activity diagrams with quantitative annotations, we model such systems as a product line. The efficiency of a product-based evaluation is typically low because each product must be analyzed in isolation, making difficult the re-use of computations across variants. Here, we propose a family-based approach based on symbolic computation. A numerical assessment on large activity diagrams shows that this approach can be up to three orders of magnitude faster than product-based analysis in large models, thus enabling computationally efficient explorations of large parameter spaces. },
author = {Kowal, Matthias and Schaefer, Ina and Tribastone, Mirco},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-642-54804-8_7},
editor = {Gnesi, Stefania and Rensink, Arend},
isbn = {9783642548031},
issn = {16113349},
keywords = {daps},
mendeley-tags = {daps},
pages = {94--108},
publisher = {Springer Berlin Heidelberg},
series = {Lecture Notes in Computer Science},
title = {{Family-based performance analysis of variant-rich software systems}},
url = {http://dx.doi.org/10.1007/978-3-642-54804-8_7},
volume = {8411 LNCS},
year = {2014}
}
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