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Book Article: BibTeX citation key:  Cheng2014a
B. H. C. Cheng, K. I. Eder, M. Gogolla, L. Grunske, M. Litoiu, H. A. Müller, P. Pelliccione, A. Perini, N. A. Qureshi, B. Rumpe, D. Schneider, F. Trollmann and N. M. Villegas, "Using Models at Runtime to Address Assurance for Self-Adaptive Systems" in Models@run.time - Foundations, Applications, and Roadmaps, ser. LNCS, no. 8378, N. Bencomo, R. B. France, B. H. C. Cheng and U. Aßmann, Eds. Berlin, Germany: Springer, 2014, pp. 101–136.
Added by: Angela Schramm 2014-12-03 20:41:08    Last edited by: Angela Schramm 2014-12-03 20:41:51
Categories: AG-Gogolla, SQuIS
Creators: Aßmann, Bencomo, Cheng, Cheng, Eder, France, Gogolla, Grunske, Litoiu, Müller, Pelliccione, Perini, Qureshi, Rumpe, Schneider, Trollmann, Villegas
Publisher: Springer, (Berlin, Germany)
Collection: {Models@run.time - Foundations, Applications, and Roadmaps}

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Self-adaptive software systems modify their behaviour at runtime in response to changes in the system or its environment. The fulfilment of the system requirements and reachability of the system goals needs to be guaranteed even in the presence of adaptations. Thus, a key challenge for self-adaptive software systems is assurance. Traditionally, confidence in the correctness of a system is gained during system development. Evidence to support assurance is collected based on a variety of activities and processes performed at development time. In the presence of self-adaptation, however, some of the assurance tasks need to be performed at runtime. This calls for continuous assurance throughout the software life cycle. One of the most promising avenues of research in this area is to use models at runtime as a foundation for developing runtime assurance techniques. This chapter focuses on investigating the use of models at runtime for assurance of self-adaptive software systems. It defines what we understand by a model at runtime, specifically for the purpose of assurance, and puts this definition into the context of existing work. We then outline selected research challenges. The chapter concludes with an exploration of selected application areas where models at runtime could contribute a considerable value proposition compared to existing techniques.
Added by: Angela Schramm    Last edited by: Angela Schramm

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