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020 _a9783319089157
_9978-3-319-08915-7
024 7 _a10.1007/978-3-319-08915-7
_2doi
050 4 _aQA76.758
072 7 _aUMZ
_2bicssc
072 7 _aCOM051230
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072 7 _aUMZ
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082 0 4 _a005.1
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245 1 0 _aModels@run.time
_h[electronic resource] :
_bFoundations, Applications, and Roadmaps /
_cedited by Nelly Bencomo, Robert B. France, Betty H.C. Cheng, Uwe Aßmann.
250 _a1st ed. 2014.
264 1 _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
347 _atext file
_bPDF
_2rda
490 1 _aProgramming and Software Engineering,
_x2945-9168 ;
_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 _aSoftware engineering.
_94138
650 0 _aComputer programming.
_94169
650 0 _aElectronic data processing
_xManagement.
_9166092
650 0 _aComputer simulation.
_95106
650 1 4 _aSoftware Engineering.
_94138
650 2 4 _aProgramming Techniques.
_9166093
650 2 4 _aIT Operations.
_931703
650 2 4 _aComputer Modelling.
_9166094
700 1 _aBencomo, Nelly.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_9166095
700 1 _aFrance, Robert B.
_eeditor.
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_9166096
700 1 _aCheng, Betty H.C.
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_4http://id.loc.gov/vocabulary/relators/edt
_9166097
700 1 _aAßmann, Uwe.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9166098
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319089140
776 0 8 _iPrinted edition:
_z9783319089164
830 0 _aProgramming and Software Engineering,
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856 4 0 _uhttps://doi.org/10.1007/978-3-319-08915-7
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