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The JavaScript ecosystem is evolving dramatically. Nowadays, the language is no longer confined to the boundaries of the browser and is now running in both sides of the Web stack. At the same time, JavaScript it’s starting to play also an important role in desktop and mobile applications development. These facts are leading companies to massively adopt JavaScript in their Web/mobile projects and schools to augment the language spectrum among their courses curricula. Several platforms appeared in recent years aiming to foster the learning of the JavaScript language. Those platforms are mainly characterized with sophisticated UI which allow users to learn JavaScript in a playful and interactive way. Despite its apparent success, these environments are not suitable to be integrated in existent educational platforms. Beyond these interoperability issues, most of these platforms are rigid not allowing teachers to contribute with new exercises, organize the existent exercises in more suitable and modular activities to be deployed in their courses, neither keep track of student’s progress. This paper presents LearnJS as a simple and flexible platform to teach and learn JavaScript. In this platform, instructors can contribute with new exercises and combine them with expositive resources (e.g videos) to define specific course activities. These activities can be gamified with the injection of dynamic attributes to reward the most successful attempts. Finally, instructors can deploy activities in their educational platforms. On the other hand, learners can solve exercises and receive immediate feedback on their solutions through static and dynamic analyzers. Since we are in the early stages of implementation, the paper focus on the presentation of the LearnJS architecture, their main components and their data and integration models. Nevertheless, a prototype of the platform is available in a GitHub repository. © Ricardo Queirós

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Finitary matching problems are those that have finitely many solutions. Pattern calculi generalize the lambda-calculus, replacing the abstraction over variables by an abstraction over terms that are called patterns. Consequently, reduction requires solving a pattern matching problem. The framework described in this paper considers the case when such problems are finitary. It is parametrized by the solving function, which is responsible for computing solutions to the matching problems. A concrete instance of the function gives a concrete version of the pattern calculus. We impose conditions on the solving function, obtaining a generic confluence proof for a class of pattern calculi with finitary matching. Instances of the solving function are presented.

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This special issue collects selected articles from the Third International Workshop on Linearity (LINEARITY 2014), which was held in Vienna, on July 13th, 2014. The workshop was a one-day satellite event of FLoC 2014, the sixth Federated Logic Conference, which was held as part of the 2014 Vienna Summer of Logic. Copyright © Cambridge University Press 2016

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