A next application prediction service using the BaranC framework

Predicting user behaviour enables user assistant services provide personalized services to the users. This requires a comprehensive user model that can be created by monitoring user interactions and activities. BaranC is a framework that performs user interface (UI) monitoring (and collects all associated context data), builds a user model, and supports services that make use of the user model. A prediction service, Next-App, is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts, based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic, reflecting the current context, and is also dynamic in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service

Model-Checking-based vs. SMT-based Consistency Analysis of Industrial Embedded Systems Requirements: Application and Experience

Industry relies predominantly on manual peer-review techniques for assessing the correctness of system specifications. However, with the ever increasing size, complexity and intricacy of the specifications, it becomes difficult to assure their correctness with respect to certain criteria such as consistency. To cope with this challenge, a set of techniques based on formal methods, called \textit{sanity checks} have been proposed to automatically assess the quality of system specifications in a systematic and rigorous manner. The predominant way of assessing the sanity of system specifications is by model checking, which in literature is reported to be expensive for analysis as it takes a long time for the procedure to terminate. Recently, another approach for checking the consistency of a system's specification using Satisfiability Modulo Theories has been proposed in order to reduce the analysis time. In this paper, we compare the two approaches for consistency analysis, by applying them on a relevant industrial use case, using the same definition for consistency and the same set of requirements. The comparison is carried out with respect to: i) time for generating the model and the latter's complexity, and ii) consistency analysis time. Contrary to the currently available data, our preliminary results show no significant difference in analysis time when applied on the same system specification under the same definition of consistency, but show significant difference in the time of creating the model for analysis

Opinion Mining for Software Development: A Systematic Literature Review

Opinion mining, sometimes referred to as sentiment analysis, has gained increasing attention in software engineering (SE) studies. SE researchers have applied opinion mining techniques in various contexts, such as identifying developers’ emotions expressed in code comments and extracting users’ critics toward mobile apps. Given the large amount of relevant studies available, it can take considerable time for researchers and developers to figure out which approaches they can adopt in their own studies and what perils these approaches entail. We conducted a systematic literature review involving 185 papers. More specifically, we present 1) well-defined categories of opinion mining-related software development activities, 2) available opinion mining approaches, whether they are evaluated when adopted in other studies, and how their performance is compared, 3) available datasets for performance evaluation and tool customization, and 4) concerns or limitations SE researchers might need to take into account when applying/customizing these opinion mining techniques. The results of our study serve as references to choose suitable opinion mining tools for software development activities, and provide critical insights for the further development of opinion mining techniques in the SE domain

Revolutionizing Crowdworking Campaigns: Conquering Adverse Selection and Moral Hazard with the Help of Smart Contracts

Crowdworking is increasingly being applied by companies to outsource tasks beyond their core competencies flexibly and cost-effectively to an unknown group. However, the anonymous and financially incentivized nature of crowdworkers creates information asymmetries and conflicts of interest, leading to inefficiencies and intensifying the principal-agent problem. Our paper offers a solution to the widespread problem of inefficient Crowdworking campaigns. We first derive the currently applied Crowdworking campaign process based on a qualitative study. Subsequently, we identify the broadest adverse selection and moral hazard problems in the process. We then analyze how the blockchain application of smart contracts can counteract those challenges and develop a process model that maps a Crowdworking campaign using smart contracts. We explain how our developed process significantly reduces adverse selection and moral hazard at each stage. Thus, our research provides approaches to make online labor more attractive and transparent for companies and online workers

On Line Service Composition in the Integrated Clinical Environment for eHealth and Medical Systems

Medical and eHealth systems are progressively realized in the context of standardized architectures that support safety and ease the integration of the heterogeneous (and often proprietary) medical devices and sensors. The Integrated Clinical Environment (ICE) architecture appeared recently with the goal of becoming a common framework for defining the structure of the medical applications as concerns the safe integration of medical devices and sensors.This research was partly supported by iLand (EU ARTEMIS-1-00026) granted by the ARTEMIS JUand the Spanish Ministry of Industry, Commerce and Tourism. It has also been partly funded by the REM4VSS (TIN2011-28339) project grant of the Spanish Ministry of Economy and Competitiveness and by Universidad Carlos III de Madrid. The authors would also like to mention the large development team of the iLand reference implementation that performed an outstanding role to achieve a software proven also on commercial applications, and they thank them for their valuable efforts and work.Publicad