Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/88482
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Type: Conference paper
Title: Middleware architecture evaluation for dependable self-managing systems
Author: Liu, Y.
Babar, M.
Gorton, I.
Citation: Lecture Notes in Artificial Intelligence, 2008 / Becker, S., Plasil, F., Reussner, R. (ed./s), vol.5281 LNCS, pp.189-204
Publisher: Springer
Issue Date: 2008
Series/Report no.: Lecture Notes in Computer Science; 5281
ISBN: 3540878785
9783540878797
ISSN: 0302-9743
1611-3349
Conference Name: 4th International Conference on the Quality of Software-Architectures (QoSA 2008) (14 Oct 2008 - 17 Oct 2008 : Karlsruhe, Germany)
Editor: Becker, S.
Plasil, F.
Reussner, R.
Statement of
Responsibility: 
Yan Liu, Muhammad Ali Babar, and Ian Gorton
Abstract: Middleware provides infrastructure support for creating dependable software systems. A specific middleware implementation plays a critical role in determining the quality attributes that satisfy a system's dependability requirements. Evaluating a middleware architecture at an early development stage can help to pinpoint critical architectural challenges and optimize design decisions. In this paper, we present a method and its application to evaluate middleware architectures, driven by emerging architecture patterns for developing self-managing systems. Our approach focuses on two key attributes of dependability, reliability and maintainability by means of fault tolerance and fault prevention. We identify the architectural design patterns necessary to build an adaptive self-managing architecture that is capable of preventing or recovering from failures. These architectural patterns and their impacts on quality attributes create the context for middleware evaluation. Our approach is demonstrated by an example application - failover control of a financial application on an enterprise service bus.
Rights: © 2008 Springer Berlin Heidelberg
DOI: 10.1007/978-3-540-87879-7_12
Published version: http://dx.doi.org/10.1007/978-3-540-87879-7_12
Appears in Collections:Aurora harvest 7
Computer Science publications

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