LEADER 02373oam 2200457zu 450 001 9910141055103321 005 20241212220151.0 010 $a9781457709241 010 $a1457709244 010 $a9781457709234 010 $a1457709236 035 $a(CKB)2670000000131718 035 $a(SSID)ssj0000669695 035 $a(PQKBManifestationID)12287958 035 $a(PQKBTitleCode)TC0000669695 035 $a(PQKBWorkID)10716256 035 $a(PQKB)10195044 035 $a(NjHacI)992670000000131718 035 $a(EXLCZ)992670000000131718 100 $a20160829d2011 uy 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$a2011 IEEE 19th International Conference on Requirements Engineering 210 31$a[Place of publication not identified]$cIEEE$d2011 215 $a1 online resource 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a9781457709210 311 08$a145770921X 330 $aThe requirements and design level identification and representation of dynamic variability for adaptive systems is a challenging task. This requires time and effort to identify and model the relevant elements as well as the need to consider the large number of potentially possible system configurations. Typically, each individual variability dimension needs to identified and modelled by enumerating each possible alternative. The full set of requirements needs to be reviewed to extract all potential variability dimensions. Moreover, each possible configuration of an adaptive system needs to be validated before use. In this demonstration, we present a tool suite that is able to manage dynamic variability in adaptive systems and tame such system complexity. This tool suite is able to automatically identify dynamic variability attributes such as variability dimensions, context, adaptation rules, and soft/hard goals from requirements documents. It also supports modelling of these artefacts as well as their run-time verification and validation. 606 $aSystems engineering$vCongresses 615 0$aSystems engineering 676 $a620.001171 702 $aIEEE Staff 801 0$bPQKB 906 $aPROCEEDING 912 $a9910141055103321 996 $a2011 IEEE 19th International Conference on Requirements Engineering$92400934 997 $aUNINA