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Capturing ambiguity in artifacts to support requirements engineering for self-adaptive systems

: Muñoz-Fernández, J.C.; Knauss, A.; Castaneda, L.; Derakhshanmanesh, M.; Heinrich, R.; Becker, M.; Taherimakhsousi, N.

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Knauss, Eric (Ed.); Susi, Angelo (Ed.); Ameller, David (Ed.); Berry, Daniel M. (Ed.); Dalpiaz, Fabiano (Ed.); Daneva, Maya (Ed.); Daun, Marian (Ed.); Dieste, Oscar (Ed.); Forbrig, Peter (Ed.); Groen, Eduard C. (Ed.); Herrmann, Andrea (Ed.); Horkoff, Jennifer (Ed.); Kifetew, Fitsum Meshesha (Ed.); Kirikova, Marite (Ed.); Knauss, Alessia (Ed.); Maeder, Patrick (Ed.); Massacci, Fabio (Ed.); Palomares, Cristina (Ed.); Ralyté, Jolita (Ed.); Seffah, Ahmed (Ed.); Siena, Alberto (Ed.); Tenbergen, Bastian (Ed.):
REFSQ-JP 2017. REFSQ Joint Proceedings of the Co-Located Events. Online resource : Joint Proceedings of REFSQ-2017 Workshops, Doctoral Symposium, Research Method Track, and Poster Track, co-located with the 22nd International Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 2017), Essen, Germany, February 27, 2017
Essen, 2017 (CEUR Workshop Proceedings Vol-1796)
URN: nbn:de:0074-1796-0
Paper 1, 6 pp.
International Conference on Requirements Engineering - Foundation for Software Quality (REFSQ) <22, 2017, Essen>
International Workshop on Requirements Engineering for Self-Adaptive & Cyber Physical Systems (RESACS) <3, 2017, Essen>
Conference Paper, Electronic Publication
Fraunhofer IEM ()

Self-adaptive systems (SAS) automatically adjust their behavior at runtime in order to manage changes in their user requirements and operating context. To achieve this goal, a SAS needs to carry knowledge in artifacts (e.g., contextual goal models) at runtime. However, identifying, representing, and refining requirements and their context to create and maintain such artifacts at runtime is a challenging task, especially if the runtime environment is not very well known. In this short paper, we present an early concept to requirements engineering for the implementation of SAS in the context of uncertainty. Especially the wide variety of knowledge materialized in artifacts created during software engineering activities at design time is considered. We propose to start with a list of ambiguous requirements - or under-specified requirements -, leaving the ambiguity in the requirements, which will in the later steps be resolved further as more information is known. In contrast to conventional requirements engineering approaches, not all ambiguous requirements will be resolved. Instead, ambiguities serve as key input for self-adaptation. We present five steps for the resolution of the ambiguity. For each step, we describe its purpose, identified challenges, and resolution ideas.