DocumentCode
1317307
Title
Scalable Differential Analysis of Process Algebra Models
Author
Tribastone, Mirco ; Gilmore, Stephen ; Hillston, Jane
Author_Institution
Lab. for Foundations of Comput. Sci., Univ. of Edinburgh, Edinburgh, UK
Volume
38
Issue
1
fYear
2012
Firstpage
205
Lastpage
219
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.
Keywords
Markov processes; differential equations; multi-threading; process algebra; software engineering; Markov chain model; PEPA; discrete-state approach; distributed multithreaded application; large-scale software systems; ordinary differential equations; scalable differential analysis; stochastic process algebra; Approximation methods; Computational modeling; Markov methods; Mathematical model; Numerical models; Semantics; Stochastic processes; Markov processes.; Modeling and prediction; ordinary differential equations;
fLanguage
English
Journal_Title
Software Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0098-5589
Type
jour
DOI
10.1109/TSE.2010.82
Filename
5567115
Link To Document