rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Software Engineering for Self-Adaptive Systems
  name:
    name part: Cheng, Betty H. C.
    role:
      role term: editor.
  name:
    name part: Lemos, Rogério de.
    role:
      role term: editor.
  name:
    name part: Giese, Holger.
    role:
      role term: editor.
  name:
    name part: Inverardi, Paola.
    role:
      role term: editor.
  name:
    name part: Magee, Jeff.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2009
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 261 p. online resource.
  abstract: Although the self-adaptability of systems has been studied in a wide range of disciplines, from biology to robotics, only recently has the software engineering community recognised its key role in enabling the development of future software systems that are able to self-adapt to changes that may occur in the system, its requirements, or the environment in which it is deployed. The 12 carefully reviewed papers included in this state-of-the-art survey originate from the International Seminar on Software Engineering for Self-Adaptive Systems, held in Dagstuhl Castle, Germany, in January 2008. They examine the current state-of-the-art in the field, describing a wide range of approaches coming from different strands of software engineering, and present future challenges facing this ever-resurgent and challenging field of research. Also included in this book is an invited roadmap paper on the research challenges facing self-adaptive systems within the area of software engineering, based on discussions at the Dagstuhl Seminar and put together by several of its participants. The papers have been divided into topical sections on architecture-based self-adaptation, context-aware and model-driven self-adaptation, and self-healing. These are preceded by three research roadmap papers. .
  table of contents: 1: Research Roadmap -- Software Engineering for Self-Adaptive Systems: A Research Roadmap -- Modeling Dimensions of Self-Adaptive Software Systems -- Engineering Self-Adaptive Systems through Feedback Loops -- 2: Architecture-Based Self-Adaptation -- Improving Architecture-Based Self-Adaptation through Resource Prediction -- Policy-Based Architectural Adaptation Management: Robotics Domain Case Studies -- A Case Study in Goal-Driven Architectural Adaptation -- 3: Context-Aware and Model-Driven Self-Adaptation -- Model-Centric, Context-Aware Software Adaptation -- Modeling of Context-Aware Self-Adaptive Applications in Ubiquitous and Service-Oriented Environments -- MUSIC: Middleware Support for Self-Adaptation in Ubiquitous and Service-Oriented Environments -- Using Architecture Models to Support the Generation and Operation of Component-Based Adaptive Systems -- Model-Driven Assessment of QoS-Aware Self-Adaptation -- 4: Self-Healing -- Automatic Generation of Runtime Failure Detectors from Property Templates -- Using Filtered Cartesian Flattening and Microrebooting to Build Enterprise Applications with Self-adaptive Healing.
  note: edited by Betty H. C. Cheng, Rogério de Lemos, Holger Giese, Paola Inverardi, Jeff Magee.
  subject:
    topic: Computer science
  subject:
    topic: Software engineering
  subject:
    topic: Computer programming
  subject:
    topic: Programming languages (Electronic computers)
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer simulation
  subject:
    topic: Computer Science
  subject:
    topic: Software Engineering/Programming and Operating Systems
  subject:
    topic: Software Engineering
  subject:
    topic: Programming Languages, Compilers, Interpreters
  subject:
    topic: Programming Techniques
  subject:
    topic: Simulation and Modeling
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  classification: QA76.758
  classification: 005.1
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 5525
  identifier: 9783642021619
  identifier: http://dx.doi.org/10.1007/978-3-642-02161-9
  record info:
    record creation date: 100301
    record change date: 20170107173333.0
    record identifier: 978-3-642-02161-9