Scalable differential analysis of process algebra models
Scalable differential analysis of process algebra models
The exact performance analysis of large-scale software systems with discrete-state approaches is difficult because of the well-known problem of state-space explosion. This paper considers this problem with regard to the stochastic process algebra PEPA, presenting a deterministic approximation to the underlying Markov chain model based on ordinary differential equations. The accuracy of the approximation is assessed by means of a substantial case study of a distributed multithreaded application.
205-219
Tribastone, Mirco
30bf9ef9-63ac-4940-9cc8-ed39b945f1de
Gilmore, Stephen
35827633-4caa-41ab-9808-fb4309530e3f
Hillston, Jane
75df46bf-ec2c-4552-a000-15cc39adbd6a
2012
Tribastone, Mirco
30bf9ef9-63ac-4940-9cc8-ed39b945f1de
Gilmore, Stephen
35827633-4caa-41ab-9808-fb4309530e3f
Hillston, Jane
75df46bf-ec2c-4552-a000-15cc39adbd6a
Tribastone, Mirco, Gilmore, Stephen and Hillston, Jane
(2012)
Scalable differential analysis of process algebra models.
IEEE Transactions on Software Engineering, 38 (1), .
(doi:10.1109/TSE.2010.82).
Abstract
The exact performance analysis of large-scale software systems with discrete-state approaches is difficult because of the well-known problem of state-space explosion. This paper considers this problem with regard to the stochastic process algebra PEPA, presenting a deterministic approximation to the underlying Markov chain model based on ordinary differential equations. The accuracy of the approximation is assessed by means of a substantial case study of a distributed multithreaded application.
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Published date: 2012
Organisations:
Electronic & Software Systems
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Local EPrints ID: 356798
URI: http://eprints.soton.ac.uk/id/eprint/356798
PURE UUID: c7cda4dc-efcc-4d5e-b39a-5cf3488a8bf3
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Date deposited: 13 Sep 2013 16:16
Last modified: 14 Mar 2024 14:52
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Author:
Mirco Tribastone
Author:
Stephen Gilmore
Author:
Jane Hillston
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