Abstract
By 2050 it is expected that 66% of the world population will reside in cities, compared to 54% in 2014. One particular challenge associated to urban population growth refers to transportation systems, and as an approach to face it, governments are investing significant efforts enhancing public transport services. An important aspect of public transport is ensuring that licensing of such services fulfill existing government regulations. Due to the differences in government regulations, and to the difficulties in ensuring the fulfillment of their specific features, many local governments develop tailored Information and Communication Technology (ICT) solutions to automate the licensing of public transport services. In this paper we propose an ontology for licensing such services following the REFSENO methodology. In particular, the ontology captures common concepts involved in the application and processing stage of licensing public bus passenger services. The main contribution of the proposed ontology is to define a common vocabulary to share knowledge between domain experts and software engineers, and to support the definition of a software product line for families of public transport licensing services.

Abstract
Software Product Lines (SPLs) are families of systems that share a high number of common assets while differing in others. In component-based systems, components themselves can be SPLs, i.e., each component can be seen as a family of variations, with different interfaces and functionalities, typically parameterized by a set of features and a feature model that specifies the valid combinations of features. This paper explores how to safely replace such families of components with more refined ones. We propose a notion of refinement for Interface Featured Timed Automata (IFTA), a formalism to model families of timed automata with support for multi-action transitions. We separate the notion of IFTA refinement into behavioral and variability refinement, i.e., the refinement of the underlying timed automata and feature model. Furthermore, we define behavioral refinement for the semantic level, i.e., transition systems, as an alternating simulation between systems, and lift this definition to IFTA refinement. We illustrate this notion with examples throughout the text and show that refinement is a pre-order and compositional.

Abstract
Featured Timed Automata (FTA) is a formalism that enables the verification of an entire Software Product Line (SPL), by capturing its behavior in a single model instead of product-by-product. However, it disregards compositional aspects inherent to SPL development. This paper introduces Interface FTA (IFTA), which extends FTA with variable interfaces that restrict the way automata can be composed, and with support for transitions with atomic multiple actions, simplifying the design. To support modular composition, a set of Reo connectors are modelled as IFTA. This separation of concerns increases reusability of functionality across products, and simplifies modelling, maintainability, and extension of SPLs. We show how IFTA can be easily translated into FTA and into networks of Timed Automata supported by UPPAAL. We illustrate this with a case study from the electronic government domain.

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Abstract
Adapting technological environments to users is a concern since Mark Weiser launched the concept of ubiquitous computing and, in order to do that, is necessary to understand users' characteristics. In this context, the purpose of this paper is to present a study about students' mobility habits within a university campus, having the intention of getting insights towards the best place to set an interactive public display and of predicting the main characteristics of the audience that will be present on that spot in forthcoming periods. Thus, the envisioned results of this work will allow the adaptation of the contents exhibited on the device to the audience. To perform the study, a set of logs of accesses to the university's Wi-Fi was used, data mining techniques were implemented and forecasting models were built, using the line of work suggested by the CRISP-DM methodology. As result, students profile were built based on past wireless accesses and on their scholar schedules, and three time series models were used (Holt-Winters, Seasonal Naive and Simple Exponential Smoothing) to predict the presence of students on the envisioned spot in future periods.

Abstract