Abstract
In the Web realm, the adoption of Cascading Style Sheets (CSS) is unanimous, being widely used for styling web documents. Despite their intensive use, this W3C specification was written for web designers with limit programming background. Thus, it lack several programming constructs, such as variables, conditional and repetitive blocks, and functions. This absence a ects negatively code reuse, and consequently, the maintenance of the styling code. In the last decade, several languages (e.g. Sass, Less) appeared to extend CSS, defined as CSS preprocessors, with the ultimate goal to bring those missing constructs and to foster stylesheets structured programming. The paper provides an introductory survey on CSS Preprocessors. It gathers information on a specific set of preprocessors, categorizes them and compares their features regarding a set of predefined criteria such as: maturity, coverage and performance. © Ricardo Queirós

Abstract

Abstract
We propose the use of modern proof assistants to specify, implement, and verify password quality checkers. We use the proof assistant Coq, focusing on Linux PAM, a widely-used implementation of pluggable authentication modules for Linux. We show how password quality policies can be expressed in Coq and how to use Coq’s code extraction features to automatically encode these policies as PAM modules that can readily be used by any Linux system. We implemented the default password quality policy shared by two widely-used PAM modules: pam_cracklib and pam_pwquality. We then compared our implementation with the original modules by running them against a random sample of 100,000 leaked passwords obtained from a publicly available database. In doing this, we demonstrated a potentially serious bug in the original modules. The bug was reported to the maintainers of Linux PAM and is now fixed. © Springer International Publishing AG 2017.

Abstract
The advent of Internet and ubiquitous technologies has been fostering the appearance of intelligent mobile applications aware of their environment and the objects nearby. Despite its popularity, mobile developers are often required to write large and disorganized amounts of code, mixing UI with business logic and interact, in a ad-hoc fashion, with sensor devices and services. These habits hinder the code maintenance, refactoring and testing, while negatively influencing the consistency and performance of mobile applications. In this paper we present Magni as an abstract framework for the design and implementation of personalized and context-aware mobile applications. The corner stone of the framework is its architectural pattern based on the Model-View-Presenter pattern in the UI layer relying in REST services the majority of the app features. This paradigm fosters the modular design, implementing the separation of concerns concept and allowing an easier implementation of unit tests. In order to validate the framework, we present a prototype for an healthcare automotive app. The main goal of the app is to facilitate the access to health related points of interest such as hospitals, clinics and pharmacies.

Abstract

Abstract