Abstract
This paper reports on the development and validation of a formal model for an automotive adaptive exterior lights system (ELS) with multiple variants in Electrum, a lightweight formal specification language that extends Alloy with mutable relations and temporal logic. We explore different strategies to address variability, one in pure Electrum and another through an annotative language extension. We then show how Electrum and its Analyzer can be used to validate systems of this nature, namely by checking that the reference scenarios are admissible, and to automatically verify whether the established requirements hold. A prototype was developed to translate the provided validation sequences into Electrum and back to further automate the validation process. The resulting ELS model was validated against the provided validation sequences and verified for most of requirements for all variants.

Abstract
Robots are currently deployed in safety-critical domains but proper techniques to assess the functional safety of their software are yet to be adopted. This is particularly critical in ROS, where highly configurable robots are built by composing third-party modules. To promote adoption, we advocate the use of lightweight formal methods, automatic techniques with minimal user input and intuitive feedback. This paper proposes a technique to automatically verify system-wide safety properties of ROS-based applications at static time. It is based in the formalization of ROS architectural models and node behaviour in Electrum, over which system-wide specifications are subsequently model checked. To automate the analysis, it is deployed as a plug-in for HAROS, a framework for the assessment of ROS software quality aimed at the ROS community. The technique is evaluated in a real robot, AgRob V16, with positive results.

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Abstract
Robotics is very appealing and is long recognized as a great way to teach programming, while drawing inspiring connections to other branches of engineering and science such as maths, physics or electronics. Although this symbiotic relationship between robotics and programming is perceived as largely beneficial, educational approaches often feel the need to hide the underlying complexity of the robotic system, but as a result fail to transmit the reactive essence of robot programming to the roboticists and programmers of the future. This paper presents ROSY, a novel language for teaching novice programmers through robotics. Its functional style is both familiar with a high-school algebra background and a materialization of the inherent reactive nature of robotic programming. Working at a higher-level of abstraction also teaches valuable design principles of decomposition of robotics software into collections of interacting controllers. Despite its simplicity, ROSY is completely valid Haskell code compatible with the ROS ecosystem. We make a convincing case for our language by demonstrating how non-trivial applications can be expressed with ease and clarity, exposing its sound functional programming foundations, and developing a web-enabled robot programming environment.

Abstract
Data is everywhere and in everything we do. Most of the time, usable information is hidden in raw data and because of that, there is an increasing demand for people capable of working creatively with it. To fully understand how we can assist data science workers to become more productive in their jobs, we first need to understand who they are, how they work, what are the skills they hold and lack, and which tools they need. In this paper, we present the results of the analysis of several interviews conducted with data scientists. Our research allowed us to conclude that the heterogeneity between these professionals is still understudied, which makes the development of methodologies and tools more challenging and error prone. The results of this research are particularly useful for both the scientific community and industry to propose adequate solutions for these professionals.