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Variability Identification by Selective Targeting of Significant Nodes

Authors:
Anilloy Frank
Eugen Brenner

Keywords: Design Tools; Embedded Systems; Feature Extraction; Software Reusability; Variability Management;

Abstract:
The automotive industry is characterized by numerous product variants, often driven by embedded software. With ever increasing complexity of embedded software, the electrical/electronic models in automotive applications are getting enormously unmanageable. Significant concepts for modeling and management of variability in the software architecture are under development. Models are hugely hierarchical in nature with numerous composite components deeply embedded within projects comprising of Simulink models, implementations in legacy C, and other formats. Hence, it is often necessary to define a mechanism to identify reusable components from these that are embedded deep within. The proposed approach is selectively targeting the component-feature model (CF) instead of an inclusive search to improve the identification. We explore the components and their features from a predefined component node list and the features node vector respectively. It addresses the issues to identify commonality in identification, specification and realization of variants within a product development. Since the approach does not depend on the depth of the components or on its order, it serves well with all the scenarios, thereby exhibiting a generic nature. The results obtained are faster and more accurate compared to other methods.

Pages: 148 to 153

Copyright: Copyright (c) IARIA, 2012

Publication date: June 24, 2012

Published in: conference

ISSN: 2308-4529

ISBN: 978-1-61208-202-8

Location: Venice, Italy

Dates: from June 24, 2012 to June 29, 2012