Abstract
The ageing population and the increasing longevity of individuals is a challenging reality for healthcaretoday. Longevity often leads to increased dependence and the need for continued care, whichis often left to informal caregivers given the inability of the elderly care network to provide. The informal care provided to the dependent elderly occurs either at the caregiver’s or the elderly person’s home. Technology application in healthcare has been attracting the attention of engineers for a long time, especially in providing support for health recovery and maintaining therapy practices. Due to major advances in technology, particularly in movement capture optic systems and information extraction through digital image analysis, support systems are being created to monitorhow therapeutic plans are carried out, as well as to evaluate people’s physical recovery or to assist healthcare professionals and informal caregiver to provide care for dependent elders. This paper reports on the accomplishments of a project with the general objective of using information and communication technologies to develop a prototype for a system focused on monitoring and assisting the execution of a therapeutic plan integrating physical mobilization and medication. © 2019, Springer Nature Switzerland AG.

Abstract
Viticulturists need to obtain the estimation of productivity map during the grape vine harvesting, to understand in detail the vineyard variability. An accurate productivity map will support the farmer to take more informed and accurate intervention in the vineyard in line with the precision viticulture concept. This work presents a novel solution to measure the productivity during vineyard harvesting operation realized by a grape harvesting machine. We propose 2D LIDAR sensor attached to low cost IoT module located inside the harvesting machine, to estimate the volume of grapes. Besides, it is proposed data methodology to process data collected and productivity map, considering GIS software, expecting to support the winemakers decisions. A PCD map is also used to validate the method developed by comparison. © Springer Nature Switzerland AG 2019.

Abstract
In a growing number of domains, such as IoT for e-health and smart cities, the provisioning of end-to-end services to the users depends on the proper interoperation of multiple systems, forming a new distributed system, often subject to timing constraints. To ensure interoperability and integrity, it is important to conduct integration tests that verify the interactions with the environment and between the system components in key scenarios. To solve the test automation challenges, we propose algorithms for decentralized conformance checking and test input generation, and for checking and enforcing the conditions (local observability and controllability) that allow decentralized test execution. With this, we expect to improve the fault detection and localization capabilities and reduce the communication overhead comparatively to other model-based testing approaches. Our approach will be validated using real case studies from industrial partners.

Abstract
Mobile applications have some specific characteristics not found on web and desktop applications. The mobile testing tools available may not be prepared to detect problems related to those specificities. So, it is important to assess the quality of the test cases generated/executed by mobile testing tools in order to check if they are able to find those specific problems. One way to assess the quality of a test suite is through mutation testing. This paper presents new mutation operators created to inject faults leading to known failures related to the non-preservation of users transient UI state when mobile applications go to background and then come back to foreground. A set of mutation operators is presented and the rational behind its construction is explained. A case study illustrates the approach to evaluate a mobile testing tool. In this study, the tool used is called iMPAcT tool, however any other mobile testing tool could be used. The experiments are performed over mobile applications publicly available on the Google Play store. The results are presented and discussed. Finally, some improvements are suggested for the iMPAcT tool in order to be able to generate test cases that can kill more mutants and so, hopefully, detect more failures in the future.

Abstract
Mobile applications are increasingly present in our daily lives. Being increasingly dependent on apps, we all want to make sure apps work as expected. One way to increase confidence and quality of software is through testing. However, the existing approaches and tools still do not provide sufficient solutions for testing mobile apps with features different from the ones found in desktop or web applications. In particular, there are guidelines that mobile developers should follow and that may be tested automatically but, as far as we know, there are no tools that are able do it. The iMPAcT tool combines exploration, reverse engineering and testing to check if mobile apps follow best practices to implement specific behavior called UI Patterns. Examples of UI Patterns within this catalog are: orientation, background-foreground, side drawer, tab-scroll, among others. For each of these behaviors (UI Patterns), the iMPAcT tool has a corresponding Test Pattern that checks if the UI Pattern implementation follows the guidelines. This paper presents an extension to iMPAcT tool. It enables to test if Android apps work properly after receiving an incoming call, i.e., if the state of the screen after the call is the same as before getting the call. It formalizes the problem, describes the overall approach, describes the architecture of the tool and reports an experiment performed over 61 public mobile apps.

Abstract
This paper presents iMPAcT tool that tests recurring common behavior on Android mobile applications. The process followed combines exploration, reverse engineering and testing to automatically test Android mobile applications. The tool explores automatically the App by firing UI events. After each event fired, the tool checks if there are UI patterns present using a reverse engineering process. If a UI pattern is present, the tool runs the corresponding testing strategy (Test Pattern). During reverse engineering the tool uses a catalog of UI Patterns which describes recurring behavior (UI Patterns) to test and the corresponding test strategies (Test Patterns). This catalog may be extended in the future as needed (e.g., to deal with new interaction trends). This paper describes the implementation details of the iMPAcT tool, the catalog of patterns used, the outputs produced by the tool and the results of experiments performed in order to evaluate the overall testing approach. These results show that the overall testing approach is capable of finding failures on existing Android mobile applications.