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. © 2014 Springer-Verlag.
CITATION STYLE
Kowal, M., Schaefer, I., & Tribastone, M. (2014). Family-based performance analysis of variant-rich software systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8411 LNCS, pp. 94–108). Springer Verlag. https://doi.org/10.1007/978-3-642-54804-8_7
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