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Assurances for Self-Adaptive Systems: Principles, Models, and Techniques

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Personen und Körperschaften: Cámara, Javier (VerfasserIn), Lemos, Rogério (Sonstige), Ghezzi, Carlo (Sonstige), Lopes, Antónia (Sonstige)
Titel: Assurances for Self-Adaptive Systems: Principles, Models, and Techniques/ edited by Javier Cámara, Rogério Lemos, Carlo Ghezzi, Antónia Lopes
Format: E-Book Konferenzbericht
Sprache: Englisch
veröffentlicht:
Berlin, Heidelberg Springer 2013
Gesamtaufnahme: SpringerLink
Lecture notes in computer science ; 7740
Schlagwörter:
Verfügbar auch als: Druck-Ausgabe Assurances for self-adaptive systems, Berlin : Springer, 2013, X, 330 S.
Quelle: Verbunddaten SWB
Zugangsinformationen: Elektronischer Volltext - Campuslizenz
Details
Zusammenfassung: The increasing complexity of systems and the growing uncertainty in their operational environments have created a critical need to develop systems able to improve their operation, adapt to change, and recover from failures autonomously. This situation has led to recent advances in self-adaptive systems able to reconfigure their structure and modify their behavior at run-time to adapt to environmental changes. Despite these advances, one key aspect of self-adaptive systems that remains to be tackled in depth is "assurances": the provision of evidence that the system satisfies its stated functional and non-functional requirements during its operation in the presence of self-adaptation. This book is one of the outcomes of the ESEC/FSE 2011 Workshop on Assurances for Self-Adaptive Systems (ASAS), held in Szeged, Hungary, in September 2011. It contains extended versions of some of the papers presented during the workshop, as well as invited papers from recognized experts. The 12 refereed papers were thoroughly reviewed and selected. The book consists of four parts: formal verification, models and middleware, failure prediction, and assurance techniques
Beschreibung: Literaturangaben
Umfang: Online-Ressource (X, 341 p. 94 illus, digital)
ISBN: 9783642362491
DOI: 10.1007/978-3-642-36249-1