dc.contributor
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació
dc.contributor
Franch Gutiérrez, Javier
dc.contributor
Marco Gómez, Jordi
dc.contributor.author
Zavala Rodríguez, Edith Berenice
dc.date.issued
2015-07-07
dc.identifier
https://hdl.handle.net/2117/77761
dc.description.abstract
This work presents SACRE, a proof-of-concept implementation of an existing approach, ACon. 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.
dc.format
application/pdf
dc.publisher
Universitat Politècnica de Catalunya
dc.subject
Àrees temàtiques de la UPC::Informàtica
dc.subject
Self-adaptive software
dc.subject
self-adaptive systems
dc.subject
contextual requirements
dc.subject
smart vehicles
dc.subject
drowsy drivers
dc.subject
Programari autoadaptable
dc.title
Dealing with uncertainty in contextual requirements at runtime: A proof of concept
