In model transformation (MT) testing, test data generation is of key importance. However, test suites are not available out of the box, and existing approaches to generate them require to provide not only the metamodel to ...

There are numerous domains in which information systems need to deal with uncertain information. These uncertainties may originate from different reasons such as vagueness, imprecision, incompleteness, or inconsistencies, ...

The energy consumption of mobile apps is a trending topic and researchers are actively investigating the role of coding practices on energy consumption. Recent studies suggest that design choices can conflict with energy ...

The virtualization and softwarization of network functions is the networking industry's latest achievement. Software-Defined Networks (SDN) and Network Function Virtualization (NFV) propose novel software architectures and ...

Querying large models efficiently often imposes high demands on system resources such as memory, processing time, disk access or network latency. The situation becomes more complicated when data are highly interconnected, ...

Recent advances in wireless technologies have given rise to the emergence of vehicular ad hoc networks (VANETs). In such networks, the limited coverage of WiFi and the high mobility of the nodes generate frequent topology ...

Typically, deep learning models for image segmentation tasks are trained using large datasets of images annotated at the pixel level, which can be expensive and highly time-consuming. A way to reduce the amount of annotated ...

Context: An essential requirement for the design and development of any engineering application that deals with real-world physical systems is the formal representation and processing of physical quantities, comprising ...

This paper provides a comprehensive overview and analysis of research work on how uncertainty is currently represented in software models. The survey presents the definitions and current research status of different proposals ...