Title :
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
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;
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
DOI :
10.1109/ICSEA.2010.79
