Abstract
Nowadays, web applications play an important role in our society and in the business world. Many companies earn a large part of their revenues through web applications that provide support services that must be maintained and improved over time. Most of these services operate on a large scale and are in constant change due to the environment in which they operate and due to the rapid technological evolution as we strive to improve our everyday lives. Due to this constantly changing environment, it is difficult to estimate the impact of changes; to maintain the software requirements documents updated; and to build and maintain a test suit for regression testing. Regression tests must be updated continually in order to test the current behavior after requested changes are implemented. REQAnalytics is a tool that aims to solve these problems. This paper presents REQAnalytics and an extension to generate test cases from the usage of a SaaS platform in order to diminish the effort in building and maintaining regression tests that are useful to check if the SaaS platform remains working as expected.

Abstract
Testing is one of the most important activities to ensure the quality of a software system. This paper proposes and discusses the TSL (Test Specification Language) that adopts a model-based testing approach for both human-readable and computer-executable specifications of test cases. TSL is strongly inspired on the grammar, nomenclature and writing style as defined by the RSLingo RSL, which is a rigorous requirements specification language. Both RSL and TSL are controlled natural languages that share common concepts such as data entities, use cases and state machines. However, by applying black-box functional testing design techniques, TSL includes and supports four complementary testing strategies, namely: domain analysis testing; use case tests; state machine testing; and acceptance criteria. This paper focuses on the first three testing strategies of TSL. Finally, a simple but effective case study illustrates the overall approach and supports the discussion.

Abstract
A patient's health literacy has a direct impact on their health, but more than a third of the USA population has "basic" or "below basic" levels of health literacy. An individual's wellbeing is also affected by the communication with their physician, as the use of technical terminology may hinder the patient's understanding. A patient's ability to, later on, recall or retrieve helpful information could reduce these comprehension problems and this can be improved by a good management of personal health information. To help overcome some of these problems, we created HealthTalks, a mobile app that empowers the patients, easing their daily health tasks and self-care ability. It does so by recording the audio of a medical appointment, transcribing its dialogue, giving more information about medical concepts employed, and allowing information associated with medical appointments to be easily managed by the patient. Usability tests were conducted with elderly people, ranging from the icons used to the general user experience. Results were very positive, with users accomplishing most tasks successfully and often with the least amount of clicks. We also evaluated the speech recognition software used, Google Cloud Speech API, reaching an error rate of 12 percent in medical texts.

Abstract
The importance of research data management is widely recognized. Dendro is an ontology-based platform that allows researchers to describe datasets using generic and domain-specific descriptors from ontologies. Selecting or building the right ontologies for each research domain or group requires meetings between curators and researchers in order to capture the main concepts of their research. Envisioning a tool to assist curators through the automatic extraction of key concepts from research documents, we propose 2 concept extraction methods and compare them with a term extraction method. To compare the three approaches, we use as ground truth an ontology previously created by human curators.

Abstract
Health information is highly sought on the Web by users that naturally have different levels of expertise in the topics they search for. Assisting users with query formulation is important when users are searching for topics about which they have little knowledge or familiarity. To assist users with health query formulation, we developed a query suggestion system that provides alternative queries combining Portuguese and English language with lay and medico-scientific terminology. Here, we analyze how this system affects the precision of search sessions. Results show that a system providing these suggestions tends to perform better than a system without them. On specific groups of users, clicking on suggestions has positive effects on precision while using them as sources of new terms has the opposite effect. This suggests that a personalized suggestion system might have a good impact on precision.

Abstract
This paper reports the participation of the InfoLab at the TREC Precision Medicine Track 2018. InfoLab is an informal group that brings together researchers with interest in the information area and is located at Faculty of Engineering of University of Porto. The experiments made in this participation include query expansion approaches for the disease and gene concepts. The expansion of the disease terms was done using Unified Medical Language System (UMLS). UMLS is a repository that provides the mapping between a large number of vocabularies. The gene terms were expanded using Ensembl. Ensembl provides a genome browser that maps genes to their synonyms. An additional layer was developed on top of Terrier to provide the execution of a large batch of experiments. Multiple runs were evaluated in order to measure the influence of each expansion approach.