The ModelCC Model-Driven Parser Generator

Syntax-directed translation tools require the specification of a language by means of a formal grammar. This grammar must conform to the specific requirements of the parser generator to be used. This grammar is then annotated with semantic actions for the resulting system to perform its desired function. In this paper, we introduce ModelCC, a model-based parser generator that decouples language specification from language processing, avoiding some of the problems caused by grammar-driven parser generators. ModelCC receives a conceptual model as input, along with constraints that annotate it. It is then able to create a parser for the desired textual syntax and the generated parser fully automates the instantiation of the language conceptual model. ModelCC also includes a reference resolution mechanism so that ModelCC is able to instantiate abstract syntax graphs, rather than mere abstract syntax trees.Comment: In Proceedings PROLE 2014, arXiv:1501.0169

Bangladesh: A Quantitative Review of Household Strategies in a Time of High Food Price Volatility for the Ensuring food and nutrition security in a time of volatility project

DFI

“Leave Me and My Facebook Alone!” Understanding College Students’ Relationship with Facebook and its Use for Academic Purposes

Facebook is by far the most ubiquitous social network in the world. While it has been studied extensively in its native social context, only recently has its use for academic purposes begun to be examined in earnest. In this study we utilize both qualitative and quantitative methodologies in multiple sections of required freshmen and senior courses at a liberal arts college (n = 245). To help delineate factors that cause students to accept (or resist) the use of Facebook by their professors, we draw from the well-established technology acceptance literature, adapting constructs known to predict acceptance and use of technology. Further, we develop new measures of “appropriateness” and “social purposes” to account for the unique context of integrating Facebook into college coursework. We provide recommendations for best practices, find a possible negative “Facebook Effect,” and show that the use of technology acceptance models is a promising avenue for future research