Abstract
The functional verification of software systems should not be separate from system performance evaluation. Any software architecture should be designed by having in mind the satisfaction of functional and nonfunctional requirements, and efforts should be made in order to understand whether the performance of a specific design can be improved. In addition to that, performance criteria should guide the choice among several alternative designs each of which is functionally correct. In this chapter, we present a procedure for the prediction, improvement, and comparison of the performance of architectural designs called PerfSel. It relies on the combined use of process algebraic architectural descriptions and queueing network models for assessing typical performance indices both at the system level and at the component level. Its application is exemplified through the performance comparison of three different architectures for a compiler system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
G.D. Abowd, R. Allen, and D. Garlan, Formalizing Style to Understand Descriptions of Software Architecture, ACM Transactions on Software Engineering and Methodology 4:319–364, 1995.
S. Abramsky, Observational Equivalence as a Testing Equivalence, Theoretical Computer Science 53:225–241, 1987.
L. Aceto and D. Murphy, Timing and Causality in Process Algebra, Acta Informatica 33:317–350, 1996.
A. Aldini and M. Bernardo, Mixing Logics and Rewards for the Component-Oriented Specification of Performance Measures, Theoretical Computer Science 382:3–23, 2007.
F. Aquilani, S. Balsamo, and P. Inverardi, Performance Analysis at the Software Architectural Design Level, Performance Evaluation 45:205–221, 2001.
C. Baier, B. Haverkort, H. Hermanns, and J.-P. Katoen, Automated Performance and Dependability Evaluation Using Model Checking, in Performance Evaluation of Complex Systems: Techniques and Tools, Springer, LNCS 2459:261–289, Berlin (Germany), 2002.
S. Balsamo, M. Bernardo, and M. Simeoni, Performance Evaluation at the Software Architecture Level, in Formal Methods for Software Architectures, Springer, LNCS 2804:207–258, Heidelberg (Germany), 2003.
F. Baskett, K.M. Chandy, R.R. Muntz, and G. Palacios, Open, Closed, and Mixed Networks of Queues with Different Classes of Customers, Journal of the ACM 22:248–260, 1975.
M. Bernardo, L. Donatiello, and P. Ciancarini, Stochastic Process Algebra: From an Algebraic Formalism to an Architectural Description Language, in Performance Evaluation of Complex Systems: Techniques and Tools, Springer, LNCS 2459:236–260, Berlin (Germany), 2002.
J.P. Buzen, Computational Algorithms for Closed Queueing Networks with Exponential Servers, Communications of the ACM 16:527–531, 1973.
K.M. Chandy and C.H. Sauer, Computational Algorithms for Product Form Queueing Networks, Communications of the ACM 23:573–583, 1980.
G. Clark, S. Gilmore, J. Hillston, and M. Ribaudo, Exploiting Modal Logic to Express Performance Measures, in Proc. of the 11th Int. Conf. on Modeling Techniques and Tools for Computer Performance Evaluation (PERFORMANCE TOOLS 2000), Springer, LNCS 1786: 247–261, Schaumburg (IL), 2000.
A.E. Conway and N.D. Georganas, RECAL – A New Efficient Algorithm for the Exact Analysis of Multiple-Chain Closed Queueing Networks, Journal of the ACM 33:786–791, 1986.
D. Ferrari, Considerations on the Insularity of Performance Evaluation, IEEE Transactions on Software Engineering 12:678–683, 1986.
B.R. Haverkort and K.S. Trivedi, Specification Techniques for Markov Reward Models, Discrete Event Dynamic Systems: Theory and Applications 3:219–247, 1993.
R.A. Howard, Dynamic Probabilistic Systems, Wiley, New York (NY), 1971.
L. Kleinrock, Queueing Systems, Wiley, New York (NY), 1975.
E.D. Lazowska, J. Zahorjan, G. Scott Graham, and K.C. Sevcik, Quantitative System Performance: Computer System Analysis Using Queueing Network Models, Prentice-Hall, Englewood Cliffs (NJ), 1984.
M.F. Neuts, Matrix-Geometric Solutions in Stochastic Models – An Algorithmic Approach, John Hopkins University Press, Baltimore (MD), 1981.
M. Reiser and S.S. Lavenberg, Mean-Value Analysis of Closed Multichain Queueing Networks, Journal of the ACM 27:313–322, 1980.
W.H. Sanders and J.F. Meyer, A Unified Approach for Specifying Measures of Performance, Dependability, and Performability, Dependable Computing and Fault Tolerant Systems 4:215–237, 1991.
C. Smith, Performance Engineering of Software Systems, Addison-Wesley, Reading (MA), 1990.
C.M. Woodside, J.E. Neilson, D.C. Petriu, and S. Majumdar, The Stochastic Rendezvous Network Model for Performance of Synchronous Client-Server-Like Distributed Software, IEEE Transactions on Computers 44:20–34, 1995.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2010 Springer-Verlag London
About this chapter
Cite this chapter
Aldini, A., Corradini, F., Bernardo, M. (2010). Component-Oriented Performance Evaluation. In: A Process Algebraic Approach to Software Architecture Design. Springer, London. https://doi.org/10.1007/978-1-84800-223-4_6
Download citation
DOI: https://doi.org/10.1007/978-1-84800-223-4_6
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-84800-222-7
Online ISBN: 978-1-84800-223-4
eBook Packages: Computer ScienceComputer Science (R0)