Abstract
Software has become so complex that it is increasingly hard to have a complete understanding of how a particular system will behave. Web applications, their user interfaces in particular, are built with a wide variety of technologies making them particularly hard to debug and maintain. Reverse engineering techniques, either through static analysis of the code or dynamic analysis of the running application, can be used to help gain this understanding. Each type of technique has its limitations. With static analysis it is difficult to have good coverage of highly dynamic applications, while dynamic analysis faces problems with guaranteeing that generated models fully capture the behavior of the system. This paper proposes a new hybrid approach for the reverse engineering of web applications' user interfaces. The approach combines dynamic analyzes of the application at runtime, with static analyzes of the source code of the event handlers found during interaction. Information derived from the source code is both directly added to the generated models, and used to guide the dynamic analysis. Copyright 2013 ACM.

Abstract
A repository of learning objects is a system that stores electronic resources in a technology-mediated learning process. The need for this kind of repository is growing as more educators become eager to use digital educational contents and more of it becomes available. The sharing and use of these resources relies on the use of content and communication standards as a means to describe and exchange educational resources, commonly known as learning objects. This paper presents the design and implementation of a service-oriented repository of learning objects called crimsonHex. This repository supports new definitions of learning objects for specialized domains and we illustrate this feature with the definition of programming exercises as learning objects and its validation by the repository. The repository is also fully compliant with existing communication standards and we propose extensions by adding new functions, formalizing message interchange and providing a REST interface. To validate the interoperability features of the repository, we developed a repository plug-in for Moodle that is expected to be included in the next release of this popular learning management system. Copyright (c) 2012 John Wiley & Sons, Ltd.

Abstract
QVT Relations (QVT-R) is the standard language proposed by the OMG to specify bidirectional model transformations. Unfortunately, in part due to ambiguities and omissions in the original semantics, acceptance and development of effective tool support has been slow. Recently, the checking semantics of QVT-R has been clarified and formalized. In this paper we propose a QVT-R tool that complies to such semantics. Unlike any other existing tool, it also supports meta-models enriched with OCL constraints (thus avoiding returning ill-formed models), and proposes an alternative enforcement semantics that works according to the simple and predictable "principle of least change". The implementation is based on an embedding of both QVT-R transformations and UML class diagrams (annotated with OCL) in Alloy, a lightweight formal specification language with support for automatic model finding via SAT solving.

Abstract
New governmental legislation introduced e-prescription as mandatory in the Portuguese health system. This changes consequences were not properly considered, which caused security problems related to patient and prescriber's data, such as digital identity fraud or access to prescriptions history to build clinical profiles. In order to evaluate the e-prescribing software users awareness to those risks, a survey took place, and the results revealed ignorance of certain obligations and procedures of the e-prescribing process. A significant part of doctors are not conscious about where the patient's data is stored neither about the risks related with prescription's information.

Abstract
Anomalies in data can cause a lot of problems in the data analysis processes. Thus, it is necessary to improve data quality by detecting and eliminating errors and inconsistencies in the data, known as the data cleaning process [1]. Since detection and correction of anomalies requires detailed domain knowledge, the involvement of experts in the field is essential to the success of the process of cleaning the data. However, considering the size of data to be processed, this process should be as automatic as possible so as to minimize the time spent [1]. © 2013 IEEE.

Abstract
Human motion capture systems are used by medical staff for detecting and identifying mobility impairments, early stages of certain pathologies and can also be used for evaluation of the effectiveness of surgical or rehabilitation intervention. Other applications may involve athlete's performance, occupational safety, among others. Presently there is a considerable number of solutions available, however these systems present some drawbacks, as they are often expensive, considerably complex, difficult to wear and use in a daily basis, and very uncomfortable for the patient. With the purpose of solving the above mentioned problems, a new wearable locomotion data capture system for gait analysis is under development. This system will allow the measurement of several locomotion-related parameters in a practical and non-invasive way, comfortable to the user, which will also be reusable that can be used by patients from light to severe impairments or disabilities. The present paper gives an overview of the research that is being developed, regarding the design of the wearable equipment, textile support, and communications.