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Engineering Adaptive Embedded Software: Managing Complexity and Evolution

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Model-Based Design of Adaptive Embedded Systems

Part of the book series: Embedded Systems ((EMSY,volume 22))

Abstract

Software plays an increasingly important role in the development of electronic systems. In particular, software is used to control the behaviour of systems in advanced ways that enable system features that would not be feasible otherwise. Making such an embedded system adaptive can improve its performance in certain situations, or extend its applicability to a broader range of situations. In this chapter we explain why this is the case, and how adaptivity can provide a competitive advantage. However, realising and maintaining adaptive embedded software brings its own challenges, sometimes even so prohibitive that the benefits of adaptivity are given up. We explain how adaptivity compromises the ability to manage software complexity and the ability to maintain evolving embedded software. To improve on this, we present our approach of a systematic method towards the development of adaptive embedded software. Two case studies explain two concrete applications of this approach: The first application is a method and corresponding tool set for developing flexible (adaptive) schedulers. It is shown how to use this method to develop application-specific schedulers in a modular way, exploiting a domain-specific language for concisely describing schedulers. We demonstrate that evolving requirements can be handled conveniently. The second application is a method that supports the development of Multi-Objective Optimisations, especially for physical control problems. We discuss the software engineering challenges involved in developing such systems, and explain the various steps and domain-specific languages of the method. Then we illustrate how this method was applied to an industrial case.

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Notes

  1. 1.

    In listings, scheDL language keywords are shown in bold.

  2. 2.

    A video demonstrating the application of our method in the case study can be found at the Octopus homepage of the University of Twente: http://www.utwente.nl/ewi/trese/research_projects/Octopus.doc/.

  3. 3.

    This is a property of the chosen optimisation algorithm: When the solution space of the MOO problem is empty, this algorithm drops constraints until there is a solution. Additional configuration of this algorithm is done so that it drops the 100 W power margin constraint first. This property is not part of the MO2 method; the method leaves open what should happen when the solution space of the MOO problem is empty.

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Acknowledgements

This work has been carried out as part of the Octopus project with Océ-Technologies B.V. under the responsibility of the Embedded Systems Institute. This project is partially supported by the Netherlands Ministry of Economic Affairs, Agriculture, and Innovation under the BSIK program.

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Authors and Affiliations

  1. Software Engineering group, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, 217, 7500 AE, Enschede, The Netherlands

    Kardelen Hatun, Arjan de Roo, Lodewijk Bergmans, Christoph Bockisch & Mehmet Akşit

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  1. Kardelen Hatun
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  2. Arjan de Roo
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  3. Lodewijk Bergmans
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  4. Christoph Bockisch
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  5. Mehmet Akşit
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Correspondence to Kardelen Hatun .

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Editors and Affiliations

  1. Embedded Systems Institute, Den Dolech 2 2, Eindhoven, 5612 AZ, Netherlands

    Twan Basten

  2. Embedded Systems Institute, Eindhoven, 5600 MB, Netherlands

    Roelof Hamberg

  3. Embedded Systems Institute, Den Dolech 2, Eindhoven, 5612 AZ, Netherlands

    Frans Reckers

  4. Embedded Systems Institute, Eindhoven, 5600 MB, Netherlands

    Jacques Verriet

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Hatun, K., de Roo, A., Bergmans, L., Bockisch, C., Akşit, M. (2013). Engineering Adaptive Embedded Software: Managing Complexity and Evolution. In: Basten, T., Hamberg, R., Reckers, F., Verriet, J. (eds) Model-Based Design of Adaptive Embedded Systems. Embedded Systems, vol 22. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4821-1_8

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  • DOI: https://doi.org/10.1007/978-1-4614-4821-1_8

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