Variability is the ability of a software system to be changed for a specific context, in a preplanned manner. As such, to facilitate the instantiation of a software architecture the variability concern needs to be explicitly ...

We introduce a Bayesian construction for deep neural networks that is amenable to mean field variational inference that operates solely by closed-form update rules. Hence, it does not require any learning rate to be manually ...

A test oracle automation approach proposed for systems that produce visual output.Root causes of accuracy issues analyzed for test oracles based on image comparison.Image processing techniques employed to improve the ...

In streaming media, it is imperative to deliver a good viewer experience to preserve customer loyalty. Prior research has shown that this is rather difficult when shared Internet resources struggle to meet the demand from ...

Artificial Neural Networks (ANNs) are known as state-of-the-art techniques in Machine Learning (ML) and have achieved outstanding results in data-intensive applications, such as recognition, classification, and segmentation. ...

Live streaming remains a challenge in the adaptive streaming space due to the stringent requirements for not just quality and rebuffering, but also latency. Many solutions have been proposed to tackle streaming in general, ...

The fast increase in mobile device and bandwidth usage is generating big workloads on the IT infrastructures of mobile service providers and increasing management costs. These providers collect log files continuously and ...