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Model-Based Testing of Highly Configurable Embedded Systems
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Author(s): Detlef Streitferdt (Technische Universität Ilmenau, Germany), Florian Kantz (ABB Corporate Research, Germany), Philipp Nenninger (ABB Automation Products, Germany), Thomas Ruschival (Datacom Telematica, Brazil), Holger Kaul (ABB Corporate Research, Germany), Thomas Bauer (Fraunhofer IESE, Germany), Tanvir Hussain (The Mathworks GmbH, Germany)and Robert Eschbach (ITK Engineering AG, Germany)
Copyright: 2018
Pages: 28
Source title:
Computer Systems and Software Engineering: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-3923-0.ch023
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Abstract
This chapter reports the results of a cycle computer case study and a previously conducted industrial case study from the automation domain. The key result is a model-based testing process for highly configurable embedded systems. The initial version of the testing process was built upon parameterizeable systems. The cycle computer case study adds the configuration using the product line concept and a feature model to store the parameterizable data. Thus, parameters and their constraints can be managed in a very structured way. Escalating demand for flexibility has made modern embedded software systems highly adjustable. This configurability is often realized through parameters and a highly configurable system possesses a handful of those. Small changes in parameter values can often account for significant changes in the system's behavior, whereas in some other cases, changed parameters may not result in any perceivable reaction. The case studies address the challenge of applying model-based testing to configurable embedded software systems in order to reduce development effort. As a result of the case studies, a model-based testing process was developed. This process integrates existing model-based testing methods and tools such as combinatorial design and constraint processing as well as the product line engineering approach. The testing process was applied as part of the case studies and analyzed in terms of its actual saving potentials, which turned out to reduce the testing effort by more than a third.
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