Models@run.time: Foundations, Applications, and Roadmaps - download pdf or read online

By Nelly Bencomo, Robert B. France, Betty H.C. Cheng, Uwe Aßmann

ISBN-10: 3319089145

ISBN-13: 9783319089140

ISBN-10: 3319089153

ISBN-13: 9783319089157

Traditionally, examine on model-driven engineering (MDE) has usually thinking about using versions on the layout, implementation, and verification levels of improvement. This paintings has produced fairly mature innovations and instruments which are at the moment getting used in and academia. although, software program types even have the capability for use at runtime, to watch and confirm specific facets of runtime habit, and to enforce self-* functions (e.g., version applied sciences utilized in self-healing, self-managing, self-optimizing systems). A key advantage of utilizing versions at runtime is they grants a richer semantic base for runtime decision-making concerning runtime approach issues linked to autonomic and adaptive structures. This ebook is among the results of the Dagstuhl Seminar 11481 on models@run.time held in November/December 2011, discussing foundations, options, mechanisms, cutting-edge, learn demanding situations, and purposes for using runtime versions. The booklet contains 4 examine roadmaps, written by way of the unique contributors of the Dagstuhl Seminar over the process years following the seminar, and 7 learn papers from specialists within the zone. The roadmap papers offer insights to key gains of using runtime versions and establish the subsequent learn demanding situations: the necessity for a reference structure, uncertainty tackled by means of runtime types, mechanisms for leveraging runtime versions for self-adaptive software program, and using versions at runtime to handle coverage for self-adaptive systems.

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Extra info for Models@run.time: Foundations, Applications, and Roadmaps

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Thus, they enable formal reasoning [5, 77] in addition to their execution. Prominent approaches are Progress [81], Story Diagrams [35], AGG [88], and Henshin [3]. A graph transformation contains a left hand side and a right hand side which are both specified as graphs. If an occurrence of the left hand side is found in the host graph, that is, in the model, it is replaced by the right hand side. Several approaches have been developed to ensure structural constraints [5, 48] which can be used to ensure consistency.

A similar approach is proposed by JTL [20], a bidirectional model transformation language specifically designed to support non-bijective transformations and change propagation. In particular, the language propagates changes occurring in a model to one or more related models according to the specified transformation regardless of the transformation direction, that is, JTL transformations can generate all possible solutions at once. Both PROGRESS and JTL have the drawback of requiring human intervention: The former requires the designer to choose the rule to be applied among the candidate rules, whereas the latter requires the modeler to choose the correct model in the solution space.

On the Need for Megamodels. In: Proc. of the OOPSLA/GPCE Workshop on Best Practices for Model-Driven Software Development (2004) 11. time: Guest Editors’ Introduction. Computer 42(10), 22–27 (2009) Mechanisms for Leveraging Models at Runtime 41 12. : The role of software architecture in constraining adaptation in component-based middleware platforms. , Sventek, J. ) Middleware 2000. LNCS, vol. 1795, pp. 164–184. Springer, Heidelberg (2000) 13. : Engineering Self-Adaptive Systems through Feedback Loops.

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Models@run.time: Foundations, Applications, and Roadmaps by Nelly Bencomo, Robert B. France, Betty H.C. Cheng, Uwe Aßmann

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