A model-driven approach to teaching concurrency

We present an undergraduate course on concurrent programming where formal models are used in different stages of the learning process. The main practical difference with other approaches lies in the fact that the ability to develop correct concurrent software relies on a systematic transformation of formal models of inter-process interaction (so called shared resources), rather than on the specific constructs of some programming language. Using a resource-centric rather than a language-centric approach has some benefits for both teachers and students. Besides the obvious advantage of being independent of the programming language, the models help in the early validation of concurrent software design, provide students and teachers with a lingua franca that greatly simplifies communication at the classroom and during supervision, and help in the automatic generation of tests for the practical assignments. This method has been in use, with slight variations, for some 15 years, surviving changes in the programming language and course length. In this article, we describe the components and structure of the current incarnation of the course?which uses Java as target language?and some tools used to support our method. We provide a detailed description of the different outcomes that the model-driven approach delivers (validation of the initial design, automatic generation of tests, and mechanical generation of code) from a teaching perspective. A critical discussion on the perceived advantages and risks of our approach follows, including some proposals on how these risks can be minimized. We include a statistical analysis to show that our method has a positive impact in the student ability to understand concurrency and to generate correct code.

Bilingual Polytechnic Dictionary of Metaphors: Spanish to English

This paper provides an overview of an ongoing research project work: “A Polytechnical Bilingual Dictionary of Metaphors: Spanish-English/English-Spanish” done by the UPM consolidated research group “DISCYT” (Estudios Cognitivos del Discurso Científico-Técnico). A detailed explanation of the method adopted to identify key metaphors collected from the different subject areas is included. Drawing from recognized empirical methods (Pragglejaz 2007, Cameron 2007, Steen 2007), the examples have been examined according to the main tenets of conceptual metaphor and conceptual integration theory (Deignan 2005, Gibbs 2008, Lakoff 1993, Lakoff & Johnson 1999, Steen 2007, Fauconnier & Turner 2008). This forthcoming dictionary comprises metaphors of over 10 scientific and technical areas such as Aeronautical engineering, Agronomy, Architecture, Biotechnology, Civil engineering, Geology and Mining, Mechanical engineering, Nanotechnology, Naval and Maritime engineering, Sports and Telecommunications. In this paper, we focus on the study of examples taken from civil engineering, materials engineering and naval engineering. Representative cases are analyzed from several points of view (multimodal metaphor, linguistic information strategies and translation into target language) highlighting cross linguistic variations between Spanish and English.

Reversible language extensions and their application in debugging

A range of methodologies and techniques are available to guide the design and implementation of language extensions and domainspecific languages. A simple yet powerful technique is based on source-tosource transformations interleaved across the compilation passes of a base language. Despite being a successful approach, it has the main drawback that the input source code is lost in the process. When considering the whole workflow of program development (warning and error reporting, debugging, or even program analysis), program translations are no more powerful than a glorified macro language. In this paper, we propose an augmented approach to language extensions for Prolog, where symbolic annotations are included in the target program. These annotations allow selectively reversing the translated code. We illustrate the approach by showing that coupling it with minimal extensions to a generic Prolog debugger allows us to provide users with a familiar, source-level view during the debugging of programs which use a variety of language extensions, such as functional notation, DCGs, or CLP{Q,R}.