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Heuristic Component Placement for Maximizing Software Reliability

In: Recent Advances in Reliability and Quality in Design

Author

Listed:
  • Michael W. Lipton

    (IBM Corporation)

  • Swapna S. Gokhale

    (University of Connecticut)

Abstract

In this chapter, we present a methodology for architecture-based software reliability analysis considering interface failures. The methodology generates an analytical reliability function that expresses application reliability in terms of the reliabilities and visit statistics of the components and interfaces comprising the application. Based on the analytical reliability function, we then present an optimization approach that produces a desirable deployment configuration of the application components given the application architecture and the component and interface reliabilities, subject to two types of constraints. The first type of constraint is the node size constraint and is concerned with the physical limit of the nodes, where a single node cannot accommodate more than a certain maximum number of components. The second type of constraint is the component location constraint, and is concerned with component deployment, where there are restrictions on which components can be deployed on which nodes due to reasons such as architectural mismatch. The optimization framework uses simulated annealing as the underlying optimization technique. We illustrate the value of the analysis and optimization methodologies using several examples.

Suggested Citation

  • Michael W. Lipton & Swapna S. Gokhale, 2008. "Heuristic Component Placement for Maximizing Software Reliability," Springer Series in Reliability Engineering, in: Hoang Pham (ed.), Recent Advances in Reliability and Quality in Design, chapter 15, pages 309-330, Springer.
    • Handle: RePEc:spr:ssrchp:978-1-84800-113-8_15
    DOI: 10.1007/978-1-84800-113-8_15
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    Cited by:

    1. Chetan Mutha & Carol Smidts, 2018. "Basis for non-propagation domains, their transformations and their impact on software reliability," Journal of Risk and Reliability, , vol. 232(6), pages 535-558, December.

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