A proposal for a predictive analysis model for bike-sharing systems based on a mixed model of statistical and machine-learning approaches.The model assumes a Poisson distribution on bike station arrival and departures.

Complex applications, which include microservices, computationally intensive batch jobs, and sophisticated interaction with the external environment, demand for heterogeneous computational infrastructures that range from cloud to HPC and edge computing.

16th International Conference on Open Source Systems

This paper presents an overview of the ECSEL 1 project entitled “MegaModelling at runtime – Scalable model-based framework for continuous development and runtime validation of complex systems” (MegaM@Rt2), whose aim is to address the challenges facing MDE.

Successful software evolution heavily depends on the selection of the right features to be included in the next release. Such selection is difficult, and companies often report bad experiences about user acceptance.

Software Product Lines (SPLs) capture commonalities and variability of product families, typically represented by means of feature models.

Software Product Lines (SPLs) capture commonalities and variability of product families, typically represented by means of feature models.

Over the past decade, cloud services emerged as one of the most promising technologies in IT.