Self-adaptation is emerging as an increasingly important capability for many applications, particularly those deployed in dynamically changing environments, such as ecosystem monitoring and disaster management. One key challenge posed by Dynamically Adaptive Systems (DASs) is the need to handle changes to the requirements and corresponding behavior of a DAS in response to varying environmental conditions. Berry et al. previously identified four levels of RE that should be performed for a DAS. In this paper, we propose the Levels of RE for Modeling that reify the original levels to describe RE modeling work done by DAS developers. Specifically, we identify four types of developers: the system developer, the adaptation scenario developer, the adaptation infrastructure developer, and the DAS research community. Each level corresponds to the work of a different type of developer to construct goal model(s) specifying their requirements. We then leverage the Levels of RE for Modeling to propose two complementary processes for performing RE for a DAS. We describe our experiences with applying this approach to GridStix, an adaptive flood warning system, deployed to monitor the River Ribble in Yorkshire, England.
|Title of host publication||15th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems, 2008. ECBS 2008|
|Number of pages||10|
|Publication status||Published - Mar 2008|
|Event||15th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems, 2008. ECBS 2008 - Belfast, United Kingdom|
Duration: 31 Mar 2008 → 4 Apr 2008
|Conference||15th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems, 2008. ECBS 2008|
|Period||31/03/08 → 4/04/08|
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Goldsby, H. J., Sawyer, P., Bencomo, N., Hughes, D., & Cheng, B. H. C. (2008). Goal-based modeling of dynamically adaptive system requirements. In 15th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems, 2008. ECBS 2008 (pp. 36-45). IEEE. https://doi.org/10.1109/ECBS.2008.22