8,325 research outputs found
Does OO sync with the way we think?
Given that corrective-maintenance costs already dominate the software life cycle and look set to increase significantly, reliability in the form of reducing such costs should be the most important software improvement goal. Yet the results are not promising when we review recent corrective-maintenance data for big systems in general and for OO in particular-possibly because of mismatches between the OO paradigm and how we think
Modules program structures and the structuring of operating systems
In this paper some views are presented on the way in which complex systems, such as Operating Systems and the programs to be interfaced with them can be constructed, and how such systems may become heavily library oriented. Although such systems have a dynamic nature, all interfacing within and among modules can be checked statically. It will be shown that the concepts presented are equally valid for single user systems, multi-programming systems and even distributed systems. The ideas have been spurred by the implementation of a modular version of Pascal and a supporting Operating System, currently nearing completion at Twente University of Technology, The Netherlands
Ada as an implementation language for knowledge based systems
Debates about the selection of programming languages often produce cultural collisions that are not easily resolved. This is especially true in the case of Ada and knowledge based programming. The construction of programming tools provides a desirable alternative for resolving the conflict
Lisp, Jazz, Aikido -- Three Expressions of a Single Essence
The relation between Science (what we can explain) and Art (what we can't)
has long been acknowledged and while every science contains an artistic part,
every art form also needs a bit of science. Among all scientific disciplines,
programming holds a special place for two reasons. First, the artistic part is
not only undeniable but also essential. Second, and much like in a purely
artistic discipline, the act of programming is driven partly by the notion of
aesthetics: the pleasure we have in creating beautiful things. Even though the
importance of aesthetics in the act of programming is now unquestioned, more
could still be written on the subject. The field called "psychology of
programming" focuses on the cognitive aspects of the activity, with the goal of
improving the productivity of programmers. While many scientists have
emphasized their concern for aesthetics and the impact it has on their
activity, few computer scientists have actually written about their thought
process while programming. What makes us like or dislike such and such language
or paradigm? Why do we shape our programs the way we do? By answering these
questions from the angle of aesthetics, we may be able to shed some new light
on the art of programming. Starting from the assumption that aesthetics is an
inherently transversal dimension, it should be possible for every programmer to
find the same aesthetic driving force in every creative activity they
undertake, not just programming, and in doing so, get deeper insight on why and
how they do things the way they do. On the other hand, because our aesthetic
sensitivities are so personal, all we can really do is relate our own
experiences and share it with others, in the hope that it will inspire them to
do the same. My personal life has been revolving around three major creative
activities, of equal importance: programming in Lisp, playing Jazz music, and
practicing Aikido. But why so many of them, why so different ones, and why
these specifically? By introspecting my personal aesthetic sensitivities, I
eventually realized that my tastes in the scientific, artistic, and physical
domains are all motivated by the same driving forces, hence unifying Lisp,
Jazz, and Aikido as three expressions of a single essence, not so different
after all. Lisp, Jazz, and Aikido are governed by a limited set of rules which
remain simple and unobtrusive. Conforming to them is a pleasure. Because Lisp,
Jazz, and Aikido are inherently introspective disciplines, they also invite you
to transgress the rules in order to find your own. Breaking the rules is fun.
Finally, if Lisp, Jazz, and Aikido unify so many paradigms, styles, or
techniques, it is not by mere accumulation but because they live at the
meta-level and let you reinvent them. Working at the meta-level is an
enlightening experience. Understand your aesthetic sensitivities and you may
gain considerable insight on your own psychology of programming. Mine is
perhaps common to most lispers. Perhaps also common to other programming
communities, but that, is for the reader to decide..
Adapting to Computer Science
Although I am not an engineer who adapted himself to computer science but a mathematician who did so, I am familiar enough with the development, concepts, and activities of this new discipline to venture an opinion of what must be adapted to in it.
Computer and Information Science is known as Informatics on the European continent. It was born as a distinct discipline barely a generation ago. As a fresh young discipline, it is an effervescent mixture of formal theory, empirical applications, and pragmatic design. Mathematics was just such an effervescent mixture in western culture from the renaissance to the middle of the twentieth century. It was then that the dynamic effect of high speed, electronic, general purpose computers accelerated the generalization of the meaning of the word computation This caused the early computer science to recruit not only mathematicians but also philosophers (especially logicians), linguists, psychologists, even economists, as well as physicists, and a variety of engineers.
Thus we are, perforce, discussing the changes and adaptations of individuals to disciplines, and especially of people in one discipline to another. As we all know, the very word discipline indicates that there is an initial special effort by an individual to force himself or herself to change. The change involves adaptation of one\u27s perceptions to a special way of viewing certain aspects of the - world, and also one\u27s behavior in order to produce special results. For example we are familiar with the enormous prosthetic devices that physicists have added to their natural sensors and perceptors in order to perceive minute particles and to smash atoms in order to do so (at, we might add, enormous expense, and enormous stretching of computational activity). We are also familiar with the enormously intricate prosthetic devices mathematicians added to their computational effectors, the general symbol manipulators, called computers
EOS: A project to investigate the design and construction of real-time distributed embedded operating systems
The EOS project is investigating the design and construction of a family of real-time distributed embedded operating systems for reliable, distributed aerospace applications. Using the real-time programming techniques developed in co-operation with NASA in earlier research, the project staff is building a kernel for a multiple processor networked system. The first six months of the grant included a study of scheduling in an object-oriented system, the design philosophy of the kernel, and the architectural overview of the operating system. In this report, the operating system and kernel concepts are described. An environment for the experiments has been built and several of the key concepts of the system have been prototyped. The kernel and operating system is intended to support future experimental studies in multiprocessing, load-balancing, routing, software fault-tolerance, distributed data base design, and real-time processing
Simple algebraic data types for C
ADT is a simple tool in the spirit of Lex and Yacc that makes algebraic data types and a restricted form of pattern matching on those data types as found in SML available in C programs. ADT adds runtime checks, which make C programs written with the aid of ADT less likely to dereference a NULL pointer. The runtime tests may consume a significant amount of CPU time; hence they can be switched off once the program is suitably debugged
Teaching programming with computational and informational thinking
Computers are the dominant technology of the early 21st century: pretty well all aspects of economic, social and personal life are now unthinkable without them. In turn, computer hardware is controlled by software, that is, codes written in programming languages. Programming, the construction of software, is thus a fundamental activity, in which millions of people are engaged worldwide, and the teaching of programming is long established in international secondary and higher education. Yet, going on 70 years after the first computers were built, there is no well-established pedagogy for teaching programming.
There has certainly been no shortage of approaches. However, these have often been driven by fashion, an enthusiastic amateurism or a wish to follow best industrial practice, which, while appropriate for mature professionals, is poorly suited to novice programmers. Much of the difficulty lies in the very close relationship between problem solving and programming. Once a problem is well characterised it is relatively straightforward to realise a solution in software. However, teaching problem solving is, if anything, less well understood than teaching programming.
Problem solving seems to be a creative, holistic, dialectical, multi-dimensional, iterative process. While there are well established techniques for analysing problems, arbitrary problems cannot be solved by rote, by mechanically applying techniques in some prescribed linear order. Furthermore, historically, approaches to teaching programming have failed to account for this complexity in problem solving, focusing strongly on programming itself and, if at all, only partially and superficially exploring problem solving.
Recently, an integrated approach to problem solving and programming called Computational Thinking (CT) (Wing, 2006) has gained considerable currency. CT has the enormous advantage over prior approaches of strongly emphasising problem solving and of making explicit core techniques. Nonetheless, there is still a tendency to view CT as prescriptive rather than creative, engendering scholastic arguments about the nature and status of CT techniques. Programming at heart is concerned with processing information but many accounts of CT emphasise processing over information rather than seeing then as intimately related.
In this paper, while acknowledging and building on the strengths of CT, I argue that understanding the form and structure of information should be primary in any pedagogy of programming
Programming language trends : an empirical study
Predicting the evolution of software engineering technology trends is a dubious proposition. The recent evolution of software technology is a prime example; it is fast paced and affected by many factors, which are themselves driven by a wide range of sources. This dissertation is part of a long term project intended to analyze software engineering technology trends and how they evolve. Basically, the following questions will be answered: How to watch, predict, adapt to, and affect software engineering trends?
In this dissertation, one field of software engineering, programming languages, will be discussed. After reviewing the history of a group of programming languages, it shows that two kinds of factors, intrinsic factors and extrinsic factors, could affect the evolution of a programming language. Intrinsic factors are the factors that can be used to describe the general desigu criteria of programming languages. Extrinsic factors are the factors that are not directly related to the general attributes of programming languages, but still can affect their evolution. In order to describe the relationship of these factors and how they affect programming language trends, these factors need to be quantified. A score has been assigued to each factor for every programming language. By collecting historical data, a data warehouse has been established, which stores the value of each factor for every programming language. The programming language trends are described and evaluated by using these data.
Empirical research attempts to capture observed behaviors by empirical laws. In this dissertation, statistical methods are used to describe historical programming language trends and predict the evolution of the future trends. Several statistics models are constructed to describe the relationships among these factors. Canonical correlation is used to do the factor analysis. Multivariate multiple regression method has been used to construct the statistics models for programming language trends. After statistics models are constructed to describe the historical programming language trends, they are extended to do tentative prediction for future trends. The models are validated by comparing the predictive data and the actual data
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