2026-04-05T12:46:03Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/777612025-07-23T02:00:38Zcom_2072_1033col_2072_452951

urn:hdl:2117/77761 Dealing with uncertainty in contextual requirements at runtime: A proof of concept Zavala Rodríguez, Edith Berenice Àrees temàtiques de la UPC::Informàtica Self-adaptive software self-adaptive systems contextual requirements data mining smart vehicles drowsy drivers Programari autoadaptable 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. 2015-07-07 Master thesis Open Access Universitat Politècnica de Catalunya