© 2014


Foundations, Applications, and Roadmaps

  • Nelly Bencomo
  • Robert France
  • Betty H. C. Cheng
  • Uwe Aßmann

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8378)

Table of contents

  1. Front Matter
  2. Roadmap Chapters

    1. Uwe Aßmann, Sebastian Götz, Jean-Marc Jézéquel, Brice Morin, Mario Trapp
      Pages 1-18
    2. Amel Bennaceur, Robert France, Giordano Tamburrelli, Thomas Vogel, Pieter J. Mosterman, Walter Cazzola et al.
      Pages 19-46
    3. Holger Giese, Nelly Bencomo, Liliana Pasquale, Andres J. Ramirez, Paola Inverardi, Sebastian Wätzoldt et al.
      Pages 47-100
    4. Betty H. C. Cheng, Kerstin I. Eder, Martin Gogolla, Lars Grunske, Marin Litoiu, Hausi A. Müller et al.
      Pages 101-136
  3. Normal Chapters

    1. Scott A. DeLoach, Xinming Ou, Rui Zhuang, Su Zhang
      Pages 137-161
    2. Marco Autili, Davide Di Ruscio, Paola Inverardi, Patrizio Pelliccione, Massimo Tivoli
      Pages 162-187
    3. Yijun Yu, Thein Than Tun, Arosha K. Bandara, Tian Zhang, Bashar Nuseibeh
      Pages 188-207
    4. David Redlich, Gordon Blair, Awais Rashid, Thomas Molka, Wasif Gilani
      Pages 208-236
    5. Walter Cazzola, Nicole Alicia Rossini, Phillipa Bennett, Sai Pradeep Mandalaparty, Robert France
      Pages 237-258
    6. Walter Cazzola
      Pages 259-278
    7. Mario Trapp, Daniel Schneider
      Pages 279-318
  4. Back Matter

About this book


Traditionally, 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.


MDE MDSD applied computing assurance techniques enterprise computing model-driven engineering model-driven software development process modeling reference architecture reference models runtime models security self-adaptive software self-adaptive systems software creation and management software engineering software extra-functional properties software safety software system models uncertainty

Editors and affiliations

  • Nelly Bencomo
    • 1
  • Robert France
    • 2
  • Betty H. C. Cheng
    • 3
  • Uwe Aßmann
    • 4
  1. 1.School of Engineering and Applied ScienceAston UniversityBirminghamUK
  2. 2.Department of Computer ScienceColorado State UniversityFort CollinsUSA
  3. 3.Department of Computer Science and EngineeringMichigan State UniversityEast LansingUSA
  4. 4.Institut für Software- und MultimediatechnikTechnische Universität DresdenDresdenGermany

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