History Of Computer Science Research Articles

Fine-Grained Multithreading for the Multifrontal $QR$ Factorization of Sparse Matrices

The advent of multicore processors represents a disruptive event in the history of computer science as conventional parallel programming paradigms are proving incapable of fully exploiting their potential for concurrent computations. The need for different or new programming models clearly arises from recent studies which identify fine-granularity and dynamic execution as the keys to achieving high efficiency on multicore systems. This work presents an approach to the parallelization of the multifrontal method for the $QR$ factorization of sparse matrices specifically designed for multicore based systems. High efficiency is achieved through a fine-grained partitioning of data and a dynamic scheduling of computational tasks relying on a dataflow parallel programming model. Experimental results show that an implementation of the proposed approach achieves higher performance and better scalability than existing equivalent software.

Evaluating Question Answering Over Linked Data

The availability of large amounts of open, distributed and structured semantic data on the web has no precedent in the history of computer science. In recent years, there have been important advances in semantic search and question answering over RDF data. In particular, natural language interfaces to online semantic data have the advantage that they can exploit the expressive power of Semantic Web data models and query languages, while at the same time hiding their complexity from the user. However, despite the increasing interest in this area, there are no evaluations so far that systematically evaluate this kind of systems, in contrast to traditional question answering and search interfaces to document spaces. To address this gap, we have set up a series of evaluation challenges for question answering over linked data. The main goal of the challenge was to get insight into the strengths, capabilities and current shortcomings of question answering systems as interfaces to query linked data sources, as well as benchmarking how these interaction paradigms can deal with the fact that the amount of RDF data available on the web is very large and heterogeneous with respect to the vocabularies and schemas used. Here we report on the results from the first and second of such evaluation campaigns. We also discuss how the second evaluation addressed some of the issues and limitations which arose from the first one, as well as the open issues to be addressed in future competitions.

Consideration Of The Question "What Is Computation" Considered Harmful

The thinking of Professors Newell, Perlis, and Simon on the subject of “What is Computer Science?” was clarified In their famous Letter in Science [2]: their statement that “computer science is the study of computers” should be read in the context of the discussion that asserts that “Phenomena breed sciences” and their reference to “the varied, rich, complex phenomena surrounding computers.” The subsequent history of computer science and computing more generally at CMU to this day, strongly supports the continued viability of this definition.

Approximating Optimal Binary Decision Trees

We give a (ln n+1)-approximation for the decision tree (DT) problem. An instance of DT is a set of m binary tests T=(T 1,…,T m ) and a set of n items X=(X 1,…,X n ). The goal is to output a binary tree where each internal node is a test, each leaf is an item and the total external path length of the tree is minimized. Total external path length is the sum of the depths of all the leaves in the tree. DT has a long history in computer science with applications ranging from medical diagnosis to experiment design. It also generalizes the problem of finding optimal average-case search strategies in partially ordered sets which includes several alphabetic tree problems. Our work decreases the previous best upper bound on the approximation ratio by a constant factor. We provide a new analysis of the greedy algorithm that uses a simple accounting scheme to spread the cost of a tree among pairs of items split at a particular node. We conclude by showing that our upper bound also holds for the DT problem with weighted tests.

Creating wiki communities in blended learning environment and the creation of the Moodle new Wiki

The Wiki is one of the basic tools for collaborating online, gathering, sharing and organising knowledge. Wikipedia is an overwhelming proof of that. Introducing the wiki as a learning tool is, however, not an easy task. This paper explains a case of introduction of wikis into a course that succeeded and that helped to contribute to improve one of the tools more used in education worldwide: Moodle. The teachers of the subject 'Computer science history and ethics' of the UPC have been applying collaborative learning techniques since 1994. On 2004, inspired by the social constructionist paradigm, they started using Wiki and Moodle to create learning communities during the last five semesters. This article will discuss which strategies where adopted and the quantitative and qualitative results obtained. To accomplish their objectives, the teachers of ASAI have developed a new Wiki module (nWiki) for Moodle; this module implements an innovative grading feature. The nWiki has been accepted by the Moodle FOSS community as the new Wiki official module in Moodle 2.0 upcoming version. This article is about pedagogical principles, the use of Wiki as a collaborative tool and how fulfilling specific needs can benefit a whole community through the open source paradigm.

Theory research at Google

Through the history of Computer Science, new technologies have emerged and generated fundamental problems of interest to theoretical computer scientists. From the era of telecommunications to computing and now, the Internet and the web, there are many such examples. This article is derived from the emergence of web search and associated technologies, and focuses on the problems of research interest to theoretical computer scientists that arise, in particular at Google.

Nineteen eighty-four unplugged [history of computer science

Big Brother knew a thing or two about using technology as a tool of oppression. The author investigates on how have the systems described in 'nineteen eighty-four' evolved into the 21st Century and whether George Orwell could have written a more accurate vision of the future had he known about the advancements in computer science occurring in 1948.

Colossus: the secrets of Bletchley Park's codebreaking computers

The American ENIAC is customarily regarded as the first electronic computer. In this fascinating volume, Jack Copeland rewrites the history of computer science, arguing that in reality Colossus--the giant computer built in Bletchley Park by the British secret service during World War II--predates ENIAC by two years. Until very recently, much about the Colossus machine was shrouded in secrecy, largely because the code-breaking algorithms employed during World War II remained in use by the British security services until a short time ago. Copeland has brought together memoirs of veterans of Bletchley Park--the top-secret headquarters of Britain's secret service--and others who draw on the wealth of declassified information to illuminate the crucial role Colossus played during World War II. A must read for anyone curious about code-breaking or World War II espionage, Colossus offers a fascinating insider's account of the world's first giant computer, the great-great-grandfather of the massive computers used today by the CIA and the National Security Agency.

"Numeri e Macchine"

Considering a historical perspective may be not only, in Knuth's witty words [?], "one of the ways to help make computer science respectable," but also a valuable tool for education purposes. After outlining the main reasons for teaching the history of computing, in this paper we present a virtual museum on the subject, addressed to Italian students, developed in a cooperative project engaging both university and school teachers. It is meant first of all as an opportunity to experiment a learning environment suitable to explore the cultural roots of computer science, especially in the school ages. We are now planning classroom experiences to assess this tool, as well as proposing it in a curricular course on the history of computer science for training secondary school teachers.

Social issues of Computer Science in the "Methods of Teaching Computer Science in the High School" course

This paper discusses social issues of Computer Science in the context of the preparation of high school Computer Science teachers. Specifically, it focuses on the importance of addressing social issues in the Methods of Teaching Computer Science in the High School course and illustrates the actual teaching, in the course, of the following three social issues of Computer Science: ethics, diversity, and history of Computer Science.

Editorial: Ontology Challenges: A Thumbnail Historical Perspective

Rarely in the history of computer science has there been an idea that was so obviously right and that has failed for so long to deliver on its promise. In its simplest form, this idea can be phrased as follows: People use hierarchically organized knowledge about domain objects and relations as a major ingredient of their intelligent behavior. Thus, one might reason abductively, if we equip computers with this kind of knowledge and appropriate processing algorithms, we should get intelligent behavior. The earliest history of artificial intelligence concentrated on the processing algorithms. But, after many unexpected difficulties, research turned more and more toward the knowledge part of the knowledge plus reasoning algorithms framework. Yet, paradoxically, even though large amounts of knowledge have been amassed in some areas, notably medical informatics, and even though knowledge structures have been studied for over 35 years, the expected big breakthrough toward computational intelligence has not happened. This leaves us with the initially mentioned paradox: Why has an idea that is so obviously right not led to the expected results? In 1968, Quillian (Quillian 1968) published his famous semantic network paper. His network was essentially an electronic representation of a dictionary of real-world terms. Using that dictionary and spreading activation reasoning, Quillian’s program was able to generate simple natural language expressions of stored semantic relationships. Given the extremely limited hardware (in today’s view) that Quillian had available, his achievement was a major milestone that inspired research in semantic networks (Woods 1975; Lehmann 1992; Sowa 1991), cognitive psychology (Collins and Quillian 1969; Collins and Loftus 1975; Anderson 1983) and a field that was to become known as knowledge representation (Brachman and Schmolze 1985; Cercone and McCalla 1987; Sowa 2000).

EBusiness and geophysics

While many claims and promises of the dot-com boom have come and gone, the boom did initiate a tremendous amount of network and software innovation, and did push the Internet into mainstream business. One example of Internet innovation is the Java programming language, which was designed specifically with networking in mind and is capable of dealing with security and parallel distributed computing issues while maintaining portability. Java has seen the most rapid explosion in number of developers in the history of computer science: three million developers in five years.

Teaching the history of computer science

Students who are truly interested in computer science would enjoy learning about those programmers who went before them, and how they overcame their difficulties.

Using & Re-using Archive Information for Multimedia Applications: The Virtual Museum of Italian Computer Science History

The quality of content is a key attribute for assessing the globalquality of a museum application. Unfortunately, producing good content,especially in multimedia digital form, is expensive and time-consuming.One way to reduce the costs without sacrificing quality is to exploitthe concept of information reuse. The idea is to use (portions of) thesame multimedia material in different applications, possibly adapting itfor different contexts, for different categories of users, and fordifferent delivery channels (e.g., on-line and off-line). Informationreuse does not come free. To be effective, it requires a well-organizedenvironment in which information can be easily stored, inspected,retrieved, and adapted for different purposes. This paper describes theapproach adopted in the project ``The Virtual Museum of Italian ComputerScience History'', funded by the Italian National Council of Research(CNR). In this project, all the digital material (documents, images,video interviews, etc.) is stored in a digital archive based on amultimedia database with a WWW front-end. The archive is designed forspecialists only: members of the editorial board of the project;researchers in the history of science; application developers (whoare looking for interesting content to include in their CD-ROMs or Websites). Each research group involved in the project extracted andadapted from the digital archive the multimedia material needed to builda different hypermedia application in two ``versions'' – WWW andCD-ROM. These applications, both on-line and off-line, strongly reuse(portions of) the digital archive content, but organize and present itwith a totally different style, to address the needs of non-specialists(e.g., people who have some interest, or curiosity, in the history ofItalian computer science).

Have we witnessed a real-life Turing Test?

Did Deep Blue ace the Turing Test? Did it do much more? It seems that the IBM creation not only beat the reigning chess World Champion Gary Kasparov, but also took a large step, in some people's eyes, toward true artificial intelligence. For AI professionals, a computer defeating a human in chess is probably neither surprising nor really significant. After all, they contend, chess can be described in terms of a nondeterministic alternating Turing machine. Despite the enormous number of possible positions and available moves, the task does not present a challenging theoretical AI problem of NP completeness. There are many well-developed AI strategies that limit the search for the best move to an analysis of the most promising positions. Therefore, the progress in logical and numerical methods of AI and a computer's computational speed and available memory made the computer's victory inevitable. Deep Blue's victory, then, was attributable to its ability to analyze 200 million positions per second and a refined algorithm that accounted for positional-in addition to material-advantage. In summary, most AI professionals conclude that the computer won by brute force, rather than a sophisticated or original strategy. What most AI experts have overlooked, though, is another aspect of the match, which may signify a milestone in the history of computer science: for the first time, a computer seems to have passed the Turing Test.

On the history of computer science, computer engineering, and computer technology development in Slovakia

The history of computer developments in Czechoslovakia spans the period from the end of World War II until recent times, when the country split into two: the Czech Republic and Slovakia. This is an account of those developments. When the area was one country, the story includes information about the entire national picture, but we have, in this article, put particular emphasis on those events occurring in Slovakia.

Regular Expressions for Program Computations

In brief history of computer science, no single article has attracted more attention nor stirred more controversy than a seemingly innocuous 1968 letter to editor (of Communications of ACM) by Edsger Dijkstra [3], titled Goto Statement Considered Harmful. We were just emerging from Fortran era, when programming had not yet been thought of as an art or even a craft. A diagram of program flowlines, what came to be called a flowchart, would very nearly resemble a plate of spaghetti go to here and this, then go to there and that. Programs were held together with baling wire, little thought being given to their organizational structure. Dijkstra argued that an unbridled use of goto was heart of problem. In his opening sentence, he asserts that the quality of programmers is a decreasing function of density of goto statements in programs produce. He would later argue for elimination of goto statement altogether. At time, nothing could have been more controversial. Many programmers argued that some algorithms were impossible (or at very least, unnatural) to implement without use of goto. But new programming languages were on horizon (e.g., Pascal particularly), offering such structural constituents as do, until, then else, and case statements, whereby one could organize a program into successive levels of refinement, giving some credence to Dijkstra claim. Proponents of Dijkstra discipline of programming began to use a cryptic (at time) and somewhat obscure result of Corrado I3ohm and Giuseppe Jacopini [1] as justification for their optimism and enthusiasm. In effect, their work seemed to indicate that any algorithm could be written as a structuredprogram [2], i.e., as a program involving only repetition (whether of while do or repeat until variety), selection (typically characterized by if then else construct) and sequence of (possibly compound) statements, these three constructs perhaps being nested one within other to an arbitrary depth, down to level of elementary processes of assignment, input, and output. And most importantly, there was seen to be nb need whatsoever of employing harmful goto But Bohm-Jacopini result was not all that clearly understood at time. Even Dijkstra himself stated only that they seem to have proved logical superfluousness of goto statement. For it happens that it is not all that easy to give a totally convincing proof in elementary terms. We take up just such a challenge in this survey. We use opportunity to introduce reader to a modern software engineering framework for investigation, using topics that are important to a contemporary computer science research area known as software metrics, and we further employ an algebra of regular expressions, as most commonly encountered in theory of automata, all toward offering a modified form of now-classical Bohm-Jacopini result, and thus achieving a presentation blending new with old.

Out of their minds: the lives and discoveries of 15 great computer scientists

From the Publisher: Imagine being able to ask Newton about falling apples or Euclid about his personal vision of geometry. In Out of their Minds, readers will hear the Newtons and Euclids of the computer age as they talk about their discoveries in information technology that have changed forever the way we live, work, and think about the world. Based on interviews by freelance writer Cathy Lazere and the expertise of computer scientist Dennis Shasha, Out of their Minds introduces readers to fifteen of the planet's foremost computer scientists, including eight winners of the Turing Award, computing's Nobel Prize. The scientists reveal themselves in fascinating anecdotes about their early inspirations and influences, their contributions to computer science, and their thoughts on its explosive future. These are the programmers whose work helps architects walk through virtual buldings, engineers manage factories, and cartoonists animate movie monsters. These are the mathematicians who invented many of the problem-solving techniques, languages, and architectures that enable the computer to extend the reaches of human insight. Some were inventors from their earliest years-designing spitball catapults, contributing satire to Mad magazine, and rearranging the periodic table of chemical compounds. Others were renegades or musicians. Along the path to adulthood and discovery, these explorers grappled with bureaucracies, political persecution, and academic dogma. Their lives span the 50-year history of computer science. To help explain the work of these pioneers, Shasha and Lazere fill in the historical background and distill the extraordinary discoveries of these thinkers into everyday conceptsthat nonscientists can readily understand. Detailed technical points are set off in boxes for perusal by readers wishing deeper explanations. In the final chapters Shasha and Lazere explore two intriguing questions: Is there a set of shared traits or experiences that characterizes the scientists out of whose minds computers came? How might the content of this book differ if it were to be written twenty-five years from now, in 2020? Dennis Shasha is a professor of computer science at New York University's Courant Institute of Mathematical Sciences. His previous books include Database Tuning: A Principled Approach, and two mathematical detective stories, The Puzzling Adventures of Dr. Ecco, and Codes, Puzzles, and Conspiracy. Cathy Lazere is a freelance writer who specializes in international corporate finance and technology. She has worked as an editor at McGraw-Hill and Business International, a division of the Economist Group. Ms. Lazere holds a B.A. from Yale and an M.B.A. from New York University.

GRIN: The History of a Laboratory

Together with Grenoble, Paris, Toulouse, and Nantes, Nancy was one of the first French universities in which computer science appeared 30 years ago. The history of computer science in each French university has its own particular character. Through such a history (1960-1975) one can understand a certain number of general phenomena.

Applying software process models to the full lifecycle is premature

Applying software process models to the full lifecycle is premature