Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model selection criterion, often based on an estimator of...
Software performance based on performance models can be applied at early phases of the software development cycle to characterize the quantitative behavior of software systems. We...
We propose a two-phase methodology for quantifying the performability (performance and availability) of cluster-based Internet services. In the first phase, evaluators use a fault...
Irregular and sparse scientific computing programs frequently experience performance losses due to inefficient use of the memory system in most machines. Previous work has shown t...
Michelle Mills Strout, Nissa Osheim, Dave Rostron,...
Even with todays hardware improvements, performance problems are still common in many software systems. An approach to tackle this problem for component-based software architectur...