Gesellschaft für Informatik e.V.

Lecture Notes in Informatics


Software Engineering 2016 P-252, 33-34 (2016).

Gesellschaft für Informatik, Bonn
2016


Copyright © Gesellschaft für Informatik, Bonn

Contents

Scaling size and parameter spaces in variability-aware software performance models

Matthias Kowal , Max Tschaikowski , Mirco Tribastone and Ina Schaefer

Abstract


Model-based software performance engineering often requires the analysis of many instances of a model to find optimizations or to do capacity planning. These performance predictions get increasingly more difficult with larger models due to state space explosion as well as large parameter spaces since each configuration has its own performance model and must be analyzed in isolation (product-based (PB) analysis). We propose an efficient family-based (FB) analysis using UML activity diagrams with performance annotations. The FB analysis enables us to analyze all configurations at once using symbolic computation. Previous work has already shown that a FB analysis is significant faster than its PB counterpart. This work is an extension of our previous research lifting several limitations.


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Gesellschaft für Informatik, Bonn
ISBN 978-3-88579-646-6


Last changed 25.02.2016 18:38:59