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.
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References
Cukic B (2005) The virtues of assessing software reliability early. IEEE Software, May/June 2005, pp 50–53
Gokhale S (2005) Software reliability analysis incorporating second-order architectural statistics. Intl. Journal of Reliability, Quality and Safety Engineering, 12(3):267–290
Gokhale S, Trivedi KS (2006) Analytical models for architecture–based software reliability prediction: A unifcation framework. IEEE Trans. on Reliability, December 2006, 55(4):578–590
Goseva-Popstojanova K, Hamill M, Perugupalli R (2005) Large empirical case study of architecture-based software reliability. In: Proc. of Intl. Symposium on Software Reliability Engineering (ISSRE), November 2005, pp 43–52
Goseva-Popstojanova K, Kamavaram S (2003) Assessing uncertainty in reliability of component–based software systems. In: Proc. of Intl. Symposium on Software Reliability Engineering (ISSRE), November 2003, pp 307–320
Krishnamurthy S, Mathur AP (1997) On the estimation of reliability of a software system using reliabilities of its components. In: Proc. of Eighth Intl. Symosium on Software Reliability Engineering (ISSRE), November 1997, Albuquerque, New Mexico, pp 146–155
Yacoub S, Cukic B, Ammar HH (2004) A scenario based reliability analysis approach for component based software. IEEE Trans. on Reliability, December 2004, 53(4):465–480
Kemeny JG, Snell JL (1960) Finite Markov Chains. Van Nostrand Reinhold, New York
Trivedi KS (2001) Probability and Statistics with Reliability, Queuing and Computer Science Applications. John Wiley, 2nd edition
Dennis JE, Schnabel R (1983) Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Prentice Hall, Englewood Cliffs, NJ, USA
Luenberger DG (1984) Linear and Nonlinear Programming, Second Edition. Addison-Wesley, Reading, Massachusetts
Cormen T, Leiserson C, Rivest R (1991) Introduction to algorithms. McGraw Hill Inc.
Greiner R (1992) Probabilistic hill-climbing: Theory and applications. In: Proc. of the Ninth Canadian Conference on Artifcial Intelligence, pp 60–67, Vancouver, 1992. Morgan Kaufmann
Fogel LJ, Owens A, Walsh MJ (1966) Artifcial Intelligence Through Simulated Evolution. Wiley Publishing, New York
Holland JH (1975) Adaptation in Natural and Artifcial Systems. University of Michigan Press, Ann Arbor
Glover F, Laguna F (1997) Tabu Search. Kluwer Academic Publishers, Norwell, MA, USA
Lee Y, Ellis JH (1996) Comparison of algorithms for nonlinear integer optimization: Application to monitoring network design. Journal of Environmental Engineering, pp 524–529
Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by Simulated Annealing. Science, Number 4598, 13 May 1983, 220, 4598:671–680
Battiti R, Tecchiolli G (1994) Simulated annealing and tabu search in the long run: A comparison on qap tasks. Computer Math. Applic., 28(6):1–8
Paulli J (1993) Information utilization in simulated annealing and tabu search. COAL Bulletin, 22(28–34)
Bain LJ, Engelhardt M (1980) Introduction to Probability and Mathematical Statistics. Duxbury Press, Belmont, CA, 1980.
Anagnostopoulos A, Michel L, Hentenryck PV, Vergados Y (2003) A simulated annealing approach to the traveling tournament problem. In: Proc. of Intl. Conference on the Integration of Constraint Programming, Artifcial Intelligence and Operations Research
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Lipton, M., Gokhale, S. (2008). Heuristic Component Placement for Maximizing Software Reliability. In: Pham, H. (eds) Recent Advances in Reliability and Quality in Design. Springer Series in Reliability Engineering. Springer, London. https://doi.org/10.1007/978-1-84800-113-8_15
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DOI: https://doi.org/10.1007/978-1-84800-113-8_15
Publisher Name: Springer, London
Print ISBN: 978-1-84800-112-1
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