Predicting Data Access Patterns in Object-Oriented Applications Based on Markov Chains

Author

Garbatov, Stoyan ; Cachopo, João

Author_Institution

Software Eng. Group, Inst. de Eng. de Sist. e Comput. Investigacao e Desenvolvimento, INESC-id, Lisbon, Portugal

fYear

2010

fDate

22-27 Aug. 2010

Firstpage

465

Lastpage

470

Abstract

This work aims to create an innovative system for analyzing and predicting the behaviour of object-oriented applications, with respect to the domain objects they manipulate, based on Markov Chains. The results are validated by the execution of the TPC-W and oo7 benchmarks. The oo7 benchmark has been modelled as a stochastic process through Monte Carlo simulations. The system is sufficiently flexible to be applied to a broad spectrum of object-oriented applications. The results are precise, regarding the observed behaviour, and the overheads introduced by the data acquisition are low.

Keywords

Markov processes; Monte Carlo methods; data acquisition; information retrieval; object-oriented programming; Markov chains; Monte Carlo simulations; data access pattern prediction; data acquisition; innovative system; object-oriented applications; Benchmark testing; Context; Instruments; Markov processes; Memory management; Object oriented modeling; Prefetching; Markov Chains; Monte Carlo; data access;

fLanguage

English

Publisher

ieee

Conference_Titel

Software Engineering Advances (ICSEA), 2010 Fifth International Conference on

Conference_Location

Nice

Print_ISBN

978-1-4244-7788-3

Electronic_ISBN

978-0-7695-4144-0

Type

conf

DOI

10.1109/ICSEA.2010.79

Filename

5615137