This outline is also available in PDF.
Held: Tuesday, May 11, 2010
Summary:
We begin to conclude our introduction to CS by looking beyond this
course to what kinds of topics computer scientists often study.
Related Pages:
Notes:
Overview:
- What is CS?
- Subfields of CS.
- Related Disciplines.
- We started the course with this question.
- We therefore start to end the class with a similar question.
- I've given you a simple definition:
Computer science is the study of algorithms and data.
- We've seen a bit what an algorithm is and what data are.
- But how do we study them?
- How have we studied them in this course?
- In late April and early May 2008, the SIGCSE (Special Interest Group
in Computer Science Education) listserve had an interesting discussion
about the definition of CS, spurred, in part, by a comment on the role
of Calculus in CS and ABET's decision to remove the Calculus requirement.
- ABET is the engineering accrediting board
- I particularly like the following message.
From: Michael Feldman
Subject: Re: [SIGCSE-members] CS definitions
Date: May 3, 2008 6:18:28 PM CDT
To: SIGCSE-members
Computing Curricula 2005 was developed by a joint task force of members
from The Association for Computing Machinery (ACM), The Association for
Information Systems (AIS), and The IEEE Computer Society (IEEE-CS).
Here's the definition of Computer Science that appears in CC 2005, in
the overview document at
http://www.acm.org/education/curric_vols/CC2005-March06Final.pdf:
"Computer science spans a wide range, from its theoretical and
algorithmic foundations to cutting-edge developments in robotics,
computer vision, intelligent systems, bioinformatics, and other exciting
areas.
"We can think of the work of computer scientists as falling into three
categories.
"-- They design and implement software. Computer scientists take on
challenging programming jobs. They also supervise other programmers,
keeping them aware of new approaches.
"-- They devise new ways to use computers. Progress in the CS areas of
networking, database, and human-computer-interface enabled the
development of the World Wide Web. Now CS researchers are working with
scientists from other fields to make robots become practical and
intelligent aides, to use databases to create new knowledge, and to use
computers to help decipher the secrets of our DNA.
"-- They develop effective ways to solve computing problems. For
example, computer scientists develop the best possible ways to store
information in databases, send data over networks, and display complex
images. Their theoretical background allows them to determine the best
performance possible, and tstudy of algorithms helps them to develop new
approaches that provide better performance."
I also think the CSAB definition at
http://www.csab.org/comp_sci_profession.html
bears repeating:
"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."
Let me pull out and emphasize one part of the 3rd paragraph, because (in
my opinion) it's really the nub of the profession and consequently of
our responsibility as educators:
"[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."
If that's not a clear, crisp, understandable, effective definition of
our profession, I don't know what is.
Mike Feldman
- In part, the ways in which we study algorithms lead to different
subfields of computer science. The domains we study also lead
to different classes of algorithms.
- Computer scientists who emphasize
organization and architecture
study the ways in which algorithms and data may be implemented
in hardware and the implications of particular implementations.
- Example: Representing integers and adding integers.
- Grinnell's course: CSC 211
- Computer scientists who emphasize operating systems study
algorithms and data representations that permit programs to use
the common resources (file system, processor, mouse, etc.)
- Example: Dining philosophers problem.
- Grinnell's course: CSC 213
- Computer scientists who emphasize software engineering
look at the design of large computer applications. They may consider
process, program segmentation, team aspects, or even social
aspects.
- Example: Waterfall vs. Agile
- Grinnell's courses: CSC 323/335
- Computer scientists who emphasize artificial intelligence
look for ways to either model the way the brain works or to build
alternate simulations.
- Example: Genetic programming.
- Grinnell's course: CSC 261
- Computer scientists who emphasize algorithms tend to
look for interesting problems for which to design algorithms. They
also investigate general algorithm design strategies and prove
things about the characteristics of problems and algorithms.
- Example: Lower-bound on the running time of a sorting algorithm.
- Example: The traveling salesman problem.
- Grinnell's' course: CSC 301
- Computer scientists who emphasize programming languages look
at the design of the languages in which we express algorithms.
- Example: Paradigms
- Grinnell's course: CSC 302
- CSC 362 considers who we implement these languages.
- Computer scientists who emphasize theory consider
models of computation and the limits of these models.
- Example: The halting problem.
- Example: The Church-Turing thesis.
- Grinnell's course: CSC 341
- Computer scientists who emphasize computer graphics write
algorithms related to that problem domain.
- Example: Ray tracing.
- Grinnell's course: Special Topics
- Computer scientists who emphasize human-computer interaction
consider the relationship of the programs we write to the people
who use them.
- Example: Menu ordering.
- Grinnell's course: Special Topics
- Computer scientists who emphasize databases look carefully
at the models for representing and accessing large amounts of data.
- Example: Relations
- Grinnell's course: Special Topics
- Computer scientists across the board consider social and
societal implications of computing, although some focus more on
this area than others. (And yes, some make it their specialization,
and we still consider them computer scientists.)
- And that's just some of them.
- There are many fields that are like computer science, but differ a bit.
- Here are some variants that you may hear.
- Computer Engineering emphasizes the construction of computational
devices.
- Software Engineering (mentioned above) emphasizes the
construction of software, particularly processes, using some of the
approaches of the discipline of engineering.
- Informatics is either (a) a better, European, name for
CS or (b) the application of CS to a particular problem domain.
- Information Science is the study of information. It tends
to focus more on representation or the softer sides of CS.
- Computer Programming is a profession not always closely
related to CS.
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