SACRE: A tool for dealing with uncertainty in contextual requirements at runtime
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
Self-adaptive systems are capable of dealing with uncertainty at runtime handling complex issues as resource variability, changing user needs, and system intrusions or faults. If the requirements depend on context, runtime uncertainty will affect the execution of these contextual requirements. This work presents SACRE, a proof-of-concept implementation of an existing approach, ACon, developed by researchers of the Univ. of Victoria (Canada) in collaboration with the UPC (Spain). ACon uses a feedback loop to detect contextual requirements affected by uncertainty and data mining techniques to determine the best operationalization of contexts on top of sensed data. The implementation is placed in the domain of smart vehicles and the contextual requirements provide functionality for drowsy drivers.
© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
CitationZavala, E., Franch, X., Marco, J., Knauss, A., Damian, D. SACRE: A tool for dealing with uncertainty in contextual requirements at runtime. A: IEEE International Requirements Engineering Conference. "2015 IEEE 23rd International Requirements Engineering Conference (RE): proceedings". Ottawa: Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 278-279.