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| No Art-sense |
Few places to begin with when considering to know more about computer science
Principal areas of study within Computer Science include artificial intelligence,computer systems and networks, security, database systems, human computer interaction, vision and graphics, numerical analysis, programming languages, software engineering, bioinforma
ics and theory of computing.
computer science is a study of the theory, experimentation, and engineering that form the basis for the design and use of computers. It is the scientific and practical approach to computation and its applications and It is the systematic study of the feasibility, structure, expression, and mechanization of the methodical procedures (or algorithms) that underlie the acquisition, representation, processing, storage, communication of, and access to information. An alternate, more succinct definition of computer science is the study of automating algorithmic processes that scale. A computer scientist specializes in the theory of computation and the design of computational systems.[1]
Its fields can be divided into a variety of theoretical and practical disciplines. Some fields, such as computational complexity theory (which explores the fundamental properties of computational and intractable problems), are highly abstract, while fields such as computer graphics emphasize real-world visual applications. Still other fields focus on challenges in implementing computation. For example, programming language theory considers various approaches to the description of computation, while the study of computer programming itself investigates various aspects of the use of programming language and complex systems. Human–computer interaction considers the challenges in making computers and computations useful, usable, anduniversally accessible to humans.
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| Victor Grafix What computer is all about |
- Computer science is a discipline that spans theory and practice. It requires thinking both in abstract terms and in concrete terms. The practical side of computing can be seen everywhere. Nowadays, practically everyone is a computer user, and many people are even computer programmers. Getting computers to do what you want them to do requires intensive hands-on experience. But computer science can be seen on a higher level, as a science of problem solving. Computer scientists must be adept at modeling and analyzing problems. They must also be able to design solutions and verify that they are correct. Problem solving requires precision, creativity, and careful reasoning.Computer science also has strong connections to other disciplines. Many problems in science, engineering, health care, business, and other areas can be solved effectively with computers, but finding a solution requires both computer science expertise and knowledge of the particular application domain. Thus, computer scientists often become proficient in other subjects.Finally, computer science has a wide range of specialties. These include computer architecture, software systems, graphics, artificial intelligence, computational science, and software engineering. Drawing from a common core of computer science knowledge, each specialty area focuses on particular challenges.
- Computer Science is practiced by mathematicians, scientists and engineers. Mathematics, the origins of Computer Science, provides reason and logic. Science provides the methodology for learning and refinement. Engineering provides the techniques for building hardware and software.Finally, and most importantly, computer scientists are computer scientists because it is fun. (Not to mention lucrative career opportunities!)
- Another definition from http://www.csab.org/comp_sci_profession.htmlComputer Science: The Profession
Computer science is a discipline that involves the understanding and design of computers and computational processes. In its most general form it is concerned with the understanding of information transfer and transformation. Particular interest is placed on making processes efficient and endowing them with some form of intelligence. The discipline ranges from theoretical studies of algorithms to practical problems of implementation in terms of computational hardware and software.
A central focus is on processes for handling and manipulating information. Thus, the discipline spans both advancing the fundamental understanding of algorithms and information processes in general as well as the practical design of efficient reliable software and hardware to meet given specifications. Computer science is a young discipline that is evolving rapidly from its beginnings in the 1940's. As such it includes theoretical studies, experimental methods, and engineering design all in one discipline. This differs radically from most physical sciences that separate the understanding and advancement of the science from the applications of the science in fields of engineering design and implementation. In computer science there is an inherent intermingling of the theoretical concepts of computability and algorithmic efficiency with the modern practical advancements in electronics that continue to stimulate advances in the discipline. It is this close interaction of the theoretical and design aspects of the field that binds them together into a single discipline.
Because of the rapid evolution it is difficult to provide a complete list of computer science areas. Yet it is clear that some of the crucial areas are theory, algorithms and data structures, programming methodology and languages, and computer elements and architecture. Other areas include software engineering, artificial intelligence, computer networking and communication, database systems, parallel computation, distributed computation, computer-human interaction, computer graphics, operating systems, and numerical and symbolic computation.
A professional computer scientist must have a firm foundation in the crucial areas of the field and will most likely have an in-depth knowledge in one or more of the other areas of the discipline, depending upon the person's particular area of practice. Thus, a well educated computer scientist should be able to apply the fundamental concepts and techniques of computation, algorithms, and computer design to a specific design problem. The work includes detailing of specifications, analysis of the problem, and provides a design that functions as desired, has satisfactory performance, is reliable and maintainable, and meets desired cost criteria. Clearly, the computer scientist must not only have sufficient training in the computer science areas to be able to accomplish such tasks, but must also have a firm understanding in areas of mathematics and science, as well as a broad education in liberal studies to provide a basis for understanding the societal implications of the work being performed.
- From Mississippi State UniversityComputer Science is the study of principles, applications, and technologies of computing and computers. It involves the study of data and data structures and the algorithms to process these structures; of principles of computer architecture-both hardware and software; of problem-solving and design methodologies; of computer-related topics such as numerical analysis, operations research, and artificial intelligence; and of language design, structure, and translation technique. Computer Science provides a foundation of knowledge for students with career objectives in a wide range of computing and computer-related professions.
- From http://www2.cs.unb.ca/ Problem solving.The study of efficient and effective software development techniques.
Team work and communication skills.
An interest in applying technology to problems in a wide variety of disciplines.
- http://www.cs.umr.edu/csdept/career/what_is_cs.htmlComputer Science is concerned with information in much the same sense that physics is concerned with energy; it is devoted to the representation, storage, manipulation and presentation of information.
Computer Science is concerned with "the study of symbol-manipulating machines, with communication between man and machine and with the application of these machines".
Major areas of Computer Science include:
1. Operating Systems--concerned with the development and structure of complex programs which facilitate man-machine communications.
2. Computational Science--the analysis of numerical methods for solving mathematical problems with a computer.
3. Programming Languages--the study of the design and properties of languages by which humans communicate with computers.
4. Architecture--the study and use of mathematical logic to design electronic circuits.
5. Intelligent Systems--concerned with means by which computers may perform tasks which might be characterized as "intelligent" if performed by humans.
6. Automata Theory--an abstract study of computers and their capabilities.
7. Information Storage and Retrieval--the study of methods for storing a vast amount of data in a computer and methods for searching and retrieving this data.
8. Software Engineering--the study of tools and techniques for software design, development, testing and maintenance.
- Another way to view any science is to look at the methods used within that science. In some sense these methods are similar in many (most?) sciences, but they can take on different characteristics in each discipline. Four important methods used in the study of computer science are:
- invention --- formulation of new algorithmic and new architectural paradigms
- design --- software engineering uses design principles to build complex systems to solve computational problems
- analysis --- certainly a major focus within computer science is the analysis and evaluation of software, algorithms and architecture.
- experimentation --- use of experiments to reveal computing principles is an important method of scientific investigation within computer science.
Is Computer Science Science?
Computer science meets every criterion for being a science, but it has a
self-inflicted credibility problem.
What is your profession?
Computer science.
Oh? Is that a science?
Sure, it is the science of information
processes and their interactions
with the world.
I’ll accept that what you do is technology;
but not science. Science deals
with fundamental laws of
nature. Computers are manmade.
Their principles come
from other fields such as physics
and electronics engineering.
Hold on. There are many
natural information processes.
Computers are tools to implement,
study, and predict them.
In the U.S. alone, nearly 200
academic departments recognize
this; some have been granting CS
degrees for 40 years.
They all partake of a mass delusion.
The pioneers of your field genuinely
believed in the 1950s that
their new field was science. They
were mistaken. There is no computer
science. Computer art, yes. Computer
technology, yes. But no science.
The modern term, Information
Technology, is closer to the truth.
I don’t accept your statements
about my field and my degree.
Do you mind if we take a closer
look? Let’s examine the accepted criteria for science and see how
computing stacks up.
I’m listening.
Common Understandings
of Science
Our field was called computer
science from its
beginnings in the 1950s.
Over the next four decades, we
accumulated a set of principles
that extended beyond its original
mathematical foundations to
include computational science,
systems, engineering, and design.
The 1989 report, Computing as a
Discipline, defined the field as:
“The discipline of computing
is the systematic study of algorithmic
processes that describe
and transform information:
their theory, analysis,
design, efficiency, implementation,
and application.
The fundamental
question underlying all of
computing is, ‘What can
be (efficiently) automated?’”
[3, p. 12]
Science, engineering,
and mathematics combine
into a unique and
potent blend in our field.
Some of our activities are
primarily science—for example,
experimental algorithms, experimental
computer science, and
computational science. Some are
primarily engineering—for example,
design, development, software
engineering, and computer
engineering. Some are primarily
mathematics—for example, computational
complexity, mathematical
software, and numerical
analysis.
The Profession of IT
The objection that computing is not a science because it studies
man-made objects (technologies) is a red herring. Computer science
studies information processes both artificial and natural.
principles. In 1989, we used the
term “computing” instead of
“computer science, mathematics,
and engineering.” Today, computing science, engineering,
mathematics, art, and all their
combinations are grouped under
the heading “computer science.”
The scientific
paradigm, which
dates back to
Francis Bacon, is
the process of
forming hypotheses and testing
them through
experiments; successful hypotheses
become models that explain and
predict phenomena in the world.
Computing science follows this
paradigm in studying information
processes. The European synonym
for computer science—informatics—more clearly suggests the
field is about information
processes, not computers.
The lexicographers offer two
additional distinctions. One is
between pure and applied science;
pure science focuses on knowledge for its own sake and applied
focuses on knowledge of demonstrable utility. The other is
between inexact (qualitative) and
exact (quantitative) science; exact
science deals with prediction and
verification by observation, measurement, and experiment.
Computing research is rife
with examples of the scientific
paradigm. Cognition researchers,
for example, hypothesize that
much intelligent behavior is the
result of information processes in
brains and nervous systems;
they build
systems that
implement
hypothesized
information
processes and
compare them
with the real
thing. The computers in these studies are tools to
test the hypothesis; successful systems can be deployed immediately. Software engineering
researchers hypothesize models
for how programming is done
and how defects arise; through
testing they seek to understand
which models work well and how
to use them to create better programs with fewer defects. Experimental algorithmicists study the
performance of real algorithms on
real data sets and formulate models to predict their time and storage requirements; they may one
day produce a more accurate theory than Big-O-Calculus and
include a theory of locality. The
nascent Human-Computer Interaction (HCI) field is examining
the ways in which human information processes interact with
automated processes.
By these definitions, computing
qualifies as an exact science. It
studies information processes,
which occur naturally in the physical world; computer scientists work
with an accepted, systematized
body of knowledge; much computer science is applied; and computer science is used for prediction
and verification.
The objection that computing
is not a science because it studies
man-made objects (technologies)
is a red herring. Computer science studies information
processes both artificial and natural. It helps other fields study
theirs too. Physicists explain particle behavior with quantum
information processes—some of
which, like entanglement, are
quite strange—and verify their
theories with computer simulation experiments. Bioinformaticians explain DNA as encoded
biological information and study
how transcription enzymes read
and act on it; computer models
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