Predicting Data Access Patterns in Object-Oriented Applications Based on Markov Chains
Stoyan Garbatov, João Cachopo · 2010
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.