Visualisation techniques for users and designers of layout algorithms

Visualisation systems consisting of a set of components through which data and interaction commands flow have been explored by a number of researchers. Such hybrid and multistage algorithms can be used to reduce overall computation time, and to provide views of the data that show intermediate results and the outputs of complementary algorithms. In this paper we present work on expanding the range and variety of such components, with two new techniques for analysing and controlling the performance of visualisation processes. While the techniques presented are quite different, they are unified within HIVE: a visualisation system based upon a data-flow model and visual programming. Embodied within this system is a framework for weaving together our visualisation components to better afford insight into data and also deepen understanding of the process of the data's visualisation. We describe the new components and offer short case studies of their application. We demonstrate that both analysts and visualisation designers can benefit from a rich set of components and integrated tools for profiling performance

ATS displays: A reasoning visualization tool for expert systems

Reasoning visualization is a useful tool that can help users better understand the inherently non-sequential logic of an expert system. While this is desirable in most all expert system applications, it is especially so for such critical systems as those destined for space-based operations. A hierarchical view of the expert system reasoning process and some characteristics of these various levels is presented. Also presented are Abstract Time Slice (ATS) displays, a tool to visualize the plethora of interrelated information available at the host inferencing language level of reasoning. The usefulness of this tool is illustrated with some examples from a prototype potable water expert system for possible use aboard Space Station Freedom

Teaching Parallel Computing to Freshmen

Parallelism is the future of computing and computer science and should therefore be at the heart of the CS curriculum. Instead of continuing along the evolutionary path by introducing parallel computation “top down” (first in special junior-senior level courses), we are taking a radical approach and introducing parallelism at the earliest possible stages of instruction. Specifically, we are developing a completely new freshman-level course on data structures that integrates parallel computation naturally, and retains the emphasis on laboratory instruction. This will help to steer our curriculum as expeditiously as possible toward parallel computing. Our approach is novel in three distinct and essential ways. First, we will teach parallel computing to freshmen in a course designed from beginning to end to do so. Second, we will motivate the course with examples from scientific computation. Third, we use multimedia and visualization as instructional aids. We have two primary objectives: to begin a reform of our undergraduate curriculum with an laboratory-based freshman course on parallel computation, and to produce tools and methodologies that improve student understanding of the basic principles of parallel computing. Parallelism is the future of computing and computer science and should therefore be at the heart of the CS curriculum. Instead of continuing along the evolutionary path by introducing parallel computation “top down” (first in special junior-senior level courses), we are taking a radical approach and introducing parallelism at the earliest possible stages of instruction. Specifically, we are developing a completely new freshman-level course on data structures that integrates parallel computation naturally, and retains the emphasis on laboratory instruction. This will help to steer our curriculum as expeditiously as possible toward parallel computing. Our approach is novel in three distinct and essential ways. First, we will teach parallel computing to freshmen in a course designed from beginning to end to do so. Second, we will motivate the course with examples from scientific computation. Third, we use multimedia and visualization as instructional aids. We have two primary objectives: to begin a reform of our undergraduate curriculum with an laboratory-based freshman course on parallel computation, and to produce tools and methodologies that improve student understanding of the basic principles of parallel computing

Проблемите в обучението на начинаещите програмисти и възможности за тяхното преодоляване

Доклад, поместен в сборника на Националната конференция "Образованието в информационното общество", Пловдив, май, 2011 г.Начинаещите програмисти намират въведението в програмирането за доста трудно. Множеството от нови знания, които трябва да бъдат усвоени, действат демотивиращо. На по-късен етап от обучението се регистрира наличие на пропуски в познанията относно основните алгоритмични конструкции и парадигми. Представя се една възможност за повишаване на способностите за решаване на задачи чрез среда за анимирано представяне на алгоритми.Асоциация "Развитие на информационното общество", Институт по математика и информатика при БАН, Пловдивски университе

CHR^vis: Syntax and Semantics

The work in the paper presents an animation extension (CHR^{vis}) to Constraint Handling Rules (CHR). Visualizations have always helped programmers understand data and debug programs. A picture is worth a thousand words. It can help identify where a problem is or show how something works. It can even illustrate a relation that was not clear otherwise. CHR^{vis} aims at embedding animation and visualization features into CHR programs. It thus enables users, while executing programs, to have such executions animated. The paper aims at providing the operational semantics for CHR^{vis}. The correctness of CHR^{vis} programs is also discussed

DART: DECLARATIVELY RENDERING 2D SKETCHES IN CANVAS

Dart is a recent programming language for the web browser. It features structured programming through traditional class-based syntax, metaprogramming via mirror-based reflection and scriptable rendering of 2D shapes with the Canvas API. This project explores Dart as a potential host for a domain-specific language (DSL) to produce figures, like those found in entry-level programming books. The goal is for instructors or book authors to generate figures such as the ones that appear in a typical CS1/CS2 text book. Figures from the book are analyzed and a library for rendering them declaratively is developed. Dart was able to provide a convenient API even though not having advanced metaprogramming capability built-in

ALMA versus DDD

To be a debugger is a good thing! Since the very beginning of the programming activity, debuggers are the most important and widely used tools after editors and compilers; we completely recognize their importance for software development and testing. Debuggers work at machine level, after the compilation of the source program; they deal with assembly, or binary-code, and are mainly data structure inspectors. Alma is a program animator based on its abstract representation. The main idea is to show the algorithm being implemented by the program, independently from the language used to implement it. To say that ALMA is a debugger, with no value added, is not true! ALMA is a source code inspector but it deals with programming concepts instead of machine code. This makes possible to understand the source program at a conceptual level, and not only to fix run time errors. In this paper we compare our visualizer/animator system, ALMA, with one of the most well-known and used debuggers, the graphical version of GDB, the DDD program. The aim of the paper is twofold: the immediate objective is to prove that ALMA provides new features that are not usually offered by debuggers; the main contribution is to recall the concepts of debugger and animator, and clarify the role of both tools in the field of program understanding, or program comprehension.FC

Automatic generation of language-based tools

Many tools can be automatically derived from formal language definitions, such as compilers/interpreters, editors, analyzers, visualizers/animators, etc. Some examples of language-based tools generated automatically by the LISA system are described in the paper. In addition the specification of an algorithm animator and program visualizer, Alma, generated from an extended LISA input-grammar is discussed; LISA principles and code are reused in Alma implementation.GRICES - MCTE