Every year several contributions to the model-based testing (MBT) field are published. Therefore, to follow the evolution and trends of several tools and models available is difficult. Moreover, since the variety of models and tools that became available in recent years, choosing an approach to support the MBT process is a challenging activity. The main objective of this study is to provide an overview on MBT tools and models used by those tools. Furthermore, the authors' study can help academic researchers and companies to understand the topics involving MBT. Therefore, a systematic mapping study was conducted in which 1197 distinct papers were evaluated. At the end, 87 primary studies were selected to be analysed in a quantitative and qualitative way. As a result, they classified the tools and models that are currently used to support MBT. Moreover, they identified 70 MBT tools, as well as different domains in which MBT is already applied to. Therefore, there are some evidence that MBT continues to be a broad and ‘alive’ research field since every year a significant number of papers presenting different kinds of contributions are published.

The authors present an approach to complex adaptive mobile applications modelling and implementation, able to dynamically change according to changed behavioural properties, state and/or context variables and user's preference. To this aim, they design a metamodel made up of an action repository (AR) to store triples composed by logical propositions to define criteria for selecting actions to be executed. An algorithm has been devised to retrieve a set of possible actions – apps, services or components – to be executed from the AR. The selection of a single action to be executed depends on a user's model. The metamodel validation is carried out through an instantiation in two real scenarios: a proximity environment and a smartphone.

The agents of a distributed adaptive system perceive the current state of their environment and make decisions which action to perform. The actions are both reactive and proactive. Reactivity can be supported by the availability of real-time data and proactivity can be supported by anticipatory techniques. Recent investigations proved that if the agents use selfish strategy, then in some situations sometimes the system maybe worst off with real-time data than without real-time data, even if anticipatory techniques are applied to predict the future state of the environment. This study investigates that version of the Braess paradox, where each subsequent agent of the flow may select a different route, using real-time data and anticipatory techniques. The authors contribute to the state-of-the-art by proving that the traffic distribution in this Braess paradox approximates the Nash equilibrium.

Recent advances in mobile technologies have led to improved quality of multimedia services (QoMS) in a variety of mobile devices. Because multimedia has become a major form of content consumption for mobile users, satisfying user expectation on QoMS in energy-restricted mobile devices is critical. This need has motivated us to develop an aggressive and conservative low-power work demand analysis with multi-granularity (lpWDA-MG-AGG/CON) algorithm, designed to minimise power consumption in mobile devices by utilising a dynamic voltage scaling technique while simultaneously ensuring QoMS based on a resource reservation scheme. In addition, the authors analytically showed the schedulability of the proposed scheme under the rate monotonic scheduling policy. For performance evaluation, the authors implemented the two lpWDA-MG algorithms and several existing algorithms in a Linux operating system. Specifically, the authors measured power consumption with a power metre and determined that the proposed algorithms consume about 40% less dynamic power than the other existing algorithms. Moreover, the authors found that the proposed algorithms ensure acceptable QoMS.

Different modelling approaches have been proposed to automate the process of design and development of data warehouse. Some of them use the model driven architecture, however they are more focused on designing platform independent model (PIM) and platform specific model (PSM) and reserved unfortunately few efforts for requirements modelling and design computational independent model (CIM). This situation can be explained essentially by the presence of mature technologies and methods used for the representation of PIM and PSM models. Moreover, there are no standards to build CIM. Within this context, data warehousing projects fail due to not much attention paid on the requirement analysis phase. To overcome this problem, this study provides an approach to build a CIM architecture for modelling data warehouse requirements using an unified modelling language (UML) profile that extends the use cases and business process models, and proposes requirements specifications using SBVR structured English.

Surveys on the Model-Driven Engineering (MDE) adoption agree that resources such as model transformations need customisation before introduction in a target context. This study highlights an emerging scenario for reuse named ‘MDE as Service’ (MDEaaS), i.e. a business opportunity characterised by requests from application-independent contexts for customisations in MDE resources. In response for the increasing interest of some professionals in this opportunity and due to the absence of studies establishing reuse foundations for this scenario, it is presented here the authors’ background in the Feature-Oriented Model-Driven Architecture (FOMDA) approach: an implementation of MDEaaS assisted by an integrated reuse mechanism to test, compose, check the consistency, and adapt these resources. By including an analysis of three cross-application domains composed by resources developed in support for model-based systems engineering, this work shows the suitability and limitations of this approach. They therefore contribute to the foundation of MDEaaS through a longitudinal study, including key findings from their analysis of this reuse scenario.