On the customization of model management systems for file-centric IDEs

International audienceModel-based solutions are becoming more sophisticated because of the advent of new types of models, languages, and editors. To deal with this complexity, some of the current Integrated Development Environments (IDEs) offer Model Management Systems (MMSs) that provide functionalities to visualize, navigate, and search the modeling artifacts existing in a workspace. Each MMS defines the types of modeling artifacts that it supports and, commonly, furnish extensibility mechanisms for including new ones. However, the use of those mechanisms usually requires a big implementation effort. As a result, when an MMS does not support all the types of modeling artifacts that a model-driven engineer uses, he/she discards it and ends up manipulating his/her solution through file system views which is not appropriate when projects become larger. In this paper we present some of our preliminary results towards the construction of MoMS-DL, a domain-specific language to define (and automatically generate) customized Eclipse-based MMSs improv- ing the daily work of model-driven engineers

Modern Trends in the Automatic Generation of Content for Video Games

Attractive and realistic content has always played a crucial role in the penetration and popularity of digital games, virtual environments, and other multimedia applications. Procedural content generation enables the automatization of production of any type of game content including not only landscapes and narratives but also game mechanics and generation of whole games. The article offers a comparative analysis of the approaches to automatic generation of content for video games proposed in last five years. It suggests a new typology of the use of procedurally generated game content comprising of categories structured in three groups: content nature, generation process, and game dependence. Together with two other taxonomies – one of content type and the other of methods for content generation – this typology is used for comparing and discussing some specific approaches to procedural content generation in three promising research directions based on applying personalization and adaptation, descriptive languages, and semantic specifications

Using Graph Properties to Speed-up GPU-based Graph Traversal: A Model-driven Approach

While it is well-known and acknowledged that the performance of graph algorithms is heavily dependent on the input data, there has been surprisingly little research to quantify and predict the impact the graph structure has on performance. Parallel graph algorithms, running on many-core systems such as GPUs, are no exception: most research has focused on how to efficiently implement and tune different graph operations on a specific GPU. However, the performance impact of the input graph has only been taken into account indirectly as a result of the graphs used to benchmark the system. In this work, we present a case study investigating how to use the properties of the input graph to improve the performance of the breadth-first search (BFS) graph traversal. To do so, we first study the performance variation of 15 different BFS implementations across 248 graphs. Using this performance data, we show that significant speed-up can be achieved by combining the best implementation for each level of the traversal. To make use of this data-dependent optimization, we must correctly predict the relative performance of algorithms per graph level, and enable dynamic switching to the optimal algorithm for each level at runtime. We use the collected performance data to train a binary decision tree, to enable high-accuracy predictions and fast switching. We demonstrate empirically that our decision tree is both fast enough to allow dynamic switching between implementations, without noticeable overhead, and accurate enough in its prediction to enable significant BFS speedup. We conclude that our model-driven approach (1) enables BFS to outperform state of the art GPU algorithms, and (2) can be adapted for other BFS variants, other algorithms, or more specific datasets

Pathways to Fragmentation:User Flows and Web Distribution Infrastructures

This study analyzes how web audiences flow across online digital features. We construct a directed network of user flows based on sequential user clickstreams for all popular websites (n=1761), using traffic data obtained from a panel of a million web users in the United States. We analyze these data to identify constellations of websites that are frequently browsed together in temporal sequences, both by similar user groups in different browsing sessions as well as by disparate users. Our analyses thus render visible previously hidden online collectives and generate insight into the varied roles that curatorial infrastructures may play in shaping audience fragmentation on the web

Printed Circuit Board (PCB) design process and fabrication

This module describes main characteristics of Printed Circuit Boards (PCBs). A brief history of PCBs is introduced in the first chapter. Then, the design processes and the fabrication of PCBs are addressed and finally a study case is presented in the last chapter of the module.Peer ReviewedPostprint (published version

Experiences Teaching an FPGA-based Embedded Systems Class

I describe a two-year-old embedded systems design course I teach at Columbia University. In it, the students learn low-level C programming and VHDL coding to design and implement a project of their own choosing. The students implement their projects using Xilinx FPGAs and tools running on Linux workstations. The main challenges the students face are understanding and complying with complex and often poorly-documented interfaces and protocols, personal time management, and teamwork. While all real-world challenges, this class is often the first time the students encounter them, which makes the class quite challenging, but very practical. In this paper, I describe the structure of the class, the configuration of our teaching laboratory, some of the more successful projects, and give suggestions to instructors wishing to implement the class elsewhere

Searching for surprise

Inspired by the notion of surprise for unconventional discovery in computational creativity, we introduce a general search algorithm we name surprise search. Surprise search is grounded in the divergent search paradigm and is fabricated within the principles of metaheuristic (evolutionary) search. The algorithm mimics the self-surprise cognitive process of creativity and equips computational creators with the ability to search for outcomes that deviate from the algorithm’s expected behavior. The predictive model of expected outcomes is based on historical trails of where the search has been and some local information about the search space. We showcase the basic steps of the algorithm via a problem solving (maze navigation) and a generative art task. What distinguishes surprise search from other forms of divergent search, such as the search for novelty, is its ability to diverge not from earlier and seen outcomes but rather from predicted and unseen points in the creative domain considered.This work has been supported in part by the FP7 Marie Curie CIG project AutoGameDesign (project no: 630665).peer-reviewe