Software Engineering for Collective Autonomic Systems

1. Front Matter

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2. Language and Verification for Collective Autonomic Systems

   1. Front Matter

      Pages 1-1

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   2. The SCEL Language: Design, Implementation, Verification

      • Rocco De Nicola, Diego Latella, Alberto Lluch Lafuente, Michele Loreti, Andrea Margheri, Mieke Massink et al.

      Pages 3-71

   3. Reconfigurable and Software-Defined Networks of Connectors and Components

      • Roberto Bruni, Ugo Montanari, Matteo Sammartino

      Pages 73-106

   4. Correctness of Service Components and Service Component Ensembles

      • Jacques Combaz, Saddek Bensalem, Francesco Tiezzi, Andrea Margheri, Rosario Pugliese, Jan Kofroň

      Pages 107-159

3. Modeling and Theory of Adaptive and Self-aware Systems

   1. Front Matter

      Pages 161-161

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   2. Reconciling White-Box and Black-Box Perspectives on Behavioral Self-adaptation

      • Roberto Bruni, Andrea Corradini, Fabio Gadducci, Matthias Hölzl, Alberto Lluch Lafuente, Andrea Vandin et al.

      Pages 163-184

   3. From Local to Global Knowledge and Back

      • Nicklas Hoch, Giacoma Valentina Monreale, Ugo Montanari, Matteo Sammartino, Alain Tcheukam Siwe

      Pages 185-220

   4. Knowledge Representation for Adaptive and Self-aware Systems

      • Emil Vassev, Mike Hinchey

      Pages 221-247

   5. Reasoning and Learning for Awareness and Adaptation

      • Matthias Hölzl, Thomas Gabor

      Pages 249-290

   6. Supporting Performance Awareness in Autonomous Ensembles

      • Lubomír Bulej, Tomáš Bureš, Ilias Gerostathopoulos, Vojtěch Horký, Jaroslav Keznikl, Lukáš Marek et al.

      Pages 291-322

4. Engineering Techniques for Collective Autonomic Systems

   1. Front Matter

      Pages 323-323

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   2. The Ensemble Development Life Cycle and Best Practices for Collective Autonomic Systems

      • Matthias Hölzl, Nora Koch, Mariachiara Puviani, Martin Wirsing, Franco Zambonelli

      Pages 325-354

   3. Methodological Guidelines for Engineering Self-organization and Emergence

      • Victor Noël, Franco Zambonelli

      Pages 355-378

   4. Engineering Requirements for Autonomy Features

      • Emil Vassev, Mike Hinchey

      Pages 379-403

   5. The Invariant Refinement Method

      • Tomáš Bureš, Ilias Gerostathopoulos, Petr Hnetynka, Jaroslav Keznikl, Michal Kit, Frantisek Plasil

      Pages 405-428

   6. Tools for Ensemble Design and Runtime

      • Dhaminda B. Abeywickrama, Jacques Combaz, Vojtěch Horký, Jaroslav Keznikl, Jan Kofroň, Alberto Lluch Lafuente et al.

      Pages 429-448

5. Case Studies: Challenges and Feedback

   1. Front Matter

      Pages 449-449

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   2. The ASCENS Case Studies: Results and Common Aspects

      • Nikola Šerbedžija

      Pages 451-469

   3. Adaptation and Awareness in Robot Ensembles: Scenarios and Algorithms

      • Carlo Pinciroli, Michael Bonani, Francesco Mondada, Marco Dorigo

      Pages 471-494

A collective autonomic system consists of collaborating autonomic entities which are able to adapt at runtime, adjusting to the state of the environment and incorporating new knowledge into their behavior. These highly dynamic systems are also known as ensembles. To ensure correct behavior of ensembles it is necessary to support their development through appropriate methods and tools which can guarantee that an autonomic system lives up to its intended purpose; this includes respecting important constraints of the environment. This State-of-the-Art Survey addresses the engineering of such systems by presenting the methods, tools and theories developed within the ASCENS project. ASCENS was an integrated project funded in the period 2010-2015 by the 7th Framework Programme (FP7) of the European Commission as part of the Future Emerging Technologies Proactive Initiative (FET Proactive). The 17 contributions included in this book are organized in four parts corresponding to the research areas of the project and their concrete applications: (I) language and verification for self-awareness and self-expression, (II) modeling and theory of self-aware and adaptive systems, (III) engineering techniques for collective autonomic systems, and last but not least, (IV) challenges and feedback provided by the case studies of the project in the areas of swarm robotics, cloud computing and e-mobility.

• adaptive systems
• autonomic computing
• cloud computing
• constraint porgramming
• dynamic programming
• ensemble-oriented systems
• formal methods
• knowledge representation
• mobile robotics
• model-checking
• modeling
• optimization
• peer-to-peer computing
• performance
• programming lanuages
• real-life systems
• reinforcement learning
• self-organization
• swarm robotics
• verification

• , Institut für Informatik, Ludwig-Maximilians-Universität, München, Germany

  Martin Wirsing

• Institut für Informatik, Ludwig-Maximilians-Universität, München, Germany

  Matthias Hölzl, Nora Koch, Philip Mayer

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