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020 _a9783319089157
_9978-3-319-08915-7
024 7 _a10.1007/978-3-319-08915-7
_2doi
035 _ato000543800
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA76.758
072 7 _aUMZ
_2bicssc
072 7 _aCOM051230
_2bisacsh
082 0 4 _a005.1
_223
245 1 0 _aModels@run.time
_helectronic resource
_bFoundations, Applications, and Roadmaps /
_cedited by Nelly Bencomo, Robert France, Betty H. C. Cheng, Uwe Aßmann.
260 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aX, 319 p. 89 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v8378
505 0 _aA Reference Architecture and Roadmap for Models@run.time Systems -- Mechanisms for Leveraging Models at Runtime in Self-adaptive Software -- Living with Uncertainty in the Age of Runtime Models -- Using Models at Runtime to Address Assurance for Self-Adaptive Systems -- Model-Driven, Moving-Target Defense for Enterprise Network Security -- ModelLAND: Where Do Models Come from? -- From Model-Driven Software Development Processes to Problem Diagnoses at Runtime -- Research Challenges for Business Process Models at Runtime -- Fine-Grained Semi-automated Runtime Evolution -- Evolution as «Reflections on the Design» -- Safety Assurance of Open Adaptive Systems.
520 _aTraditionally, research on model-driven engineering (MDE) has mainly focused on the use of models at the design, implementation, and verification stages of development. This work has produced relatively mature techniques and tools that are currently being used in industry and academia. However, software models also have the potential to be used at runtime, to monitor and verify particular aspects of runtime behavior, and to implement self-* capabilities (e.g., adaptation technologies used in self-healing, self-managing, self-optimizing systems). A key benefit of using models at runtime is that they can provide a richer semantic base for runtime decision-making related to runtime system concerns associated with autonomic and adaptive systems. This book is one of the outcomes of the Dagstuhl Seminar 11481 on models@run.time held in November/December 2011, discussing foundations, techniques, mechanisms, state of the art, research challenges, and applications for the use of runtime models. The book comprises four research roadmaps, written by the original participants of the Dagstuhl Seminar over the course of two years following the seminar, and seven research papers from experts in the area. The roadmap papers provide insights to key features of the use of runtime models and identify the following research challenges: the need for a reference architecture, uncertainty tackled by runtime models, mechanisms for leveraging runtime models for self-adaptive software, and the use of models at runtime to address assurance for self-adaptive systems.
650 0 _aComputer Science.
_9155490
650 0 _aSoftware engineering.
_9566225
650 0 _aComputer simulation.
_9304569
650 0 _aInformation systems.
_9303226
650 1 4 _aComputer Science.
_9155490
650 2 4 _aSoftware Engineering.
_9566285
650 2 4 _aProgramming Techniques.
_9566312
650 2 4 _aManagement of Computing and Information Systems.
_9303227
650 2 4 _aSimulation and Modeling.
_9304570
700 1 _aBencomo, Nelly.
_eeditor.
_9451961
700 1 _aFrance, Robert.
_eeditor.
_9451962
700 1 _aCheng, Betty H. C.
_eeditor.
_9451963
700 1 _aAßmann, Uwe.
_eeditor.
_9412320
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
830 0 _aLecture Notes in Computer Science,
_9279505
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-08915-7
912 _aZDB-2-SCS
912 _aZDB-2-LNC
999 _c402151