```CHAPTER 1
CS 10051
Prefaces and Chapters 1-2
OVERVIEW OF COURSE:
1. The algorithmic foundations of computer science.
2. The hardware world.
3. The virtual machine.
4. The software world.
5. Applications.
6. Social issues.
Note these correspond to the labels on the step pyramid
on the backside of first interior page of your text.
WHAT IS COMPUTER SCIENCE?
MISCONCEPTION 1:
Computer science is the study of computers.
MISCONCEPTION 2:
Computer science is the study of how to write computer
programs.
MISCONCEPTION 3:
Computer science is the study of the uses and
applications of computers and software.
SO, HOW DO WE DEFINE
COMPUTER SCIENCE?
 Computer
science is the study of
algorithms including




1. Their formal and mathematical
properties
2. Their hardware realizations
3. Their linguistic realizations
4. Their applications
QUESTION:
What is an algorithm?
 An
algorithm is a
 well-ordered collection of
 unambiguous and
 effectively computable operations
that, when executed,
 produces a result and
 halts in a finite amount of time.
AN EXAMPLE OF A VERY SIMPLE
ALGORITHM
 1.
 2.
Lather your
hair.
 3. Rinse your
hair.
 4. Stop.
Observe:
Operations need not be
executed by a computer
only by an entity capable
of carrying out the
operations listed.
We assume that
The algorithm begins executing at the top of the list
of operations.
The "Stop" can be omitted if we assume the last
line is an implied "Stop" operation.
A well-ordered collection of
operations
The question that must be answered is:
At any point in the execution of the algorithm, do you
know what operation is to be performed next?
Well-ordered
operations:
Not well-ordered
operations:
1. Either wet your hair or
Don't assume that you can't make choices:
Well-ordered operations:
Well-ordered operations:
1. If your hair is dirty, then If your hair is dirty, then
2. Else
a. Go to bed.
Else
Go to bed.
Note: We will often omit the numbers and the letters
and assume a "top-down" reading of the operations.
Unambiguous operations
The question that must be answered is:
Does the computing entity understand what the
operation is to do?
This implies that the knowledge of the computing
entity must be considered.
For example, is the following ambiguous?
Make the pie crusts.
To an experienced cook,
Make the pie crusts.
is not ambiguous.
But, an less experienced cook may need:
Take 1 1/3 cups of flour.
Sift the flour.
Mix the sifted flour with 1/2 cup of butter
and 1/4 cup of water to make dough.
Roll the dough into two 9-inch pie crusts.
or even more detail!
Definition: An operation that is
unambiguous is called a primitive
operation (or just a primitive)
One question we will be exploring in the course is
what are the primitives of a computer.
Note that a given collection of operations may be
an algorithm with respect to one computing
agent, but not with respect to another computing
agent!!
Effectively computable operations
The question that must be answered is:
Is the computing entity capable of doing the
operation?
This assumes that the operation must first be
unambiguous- i.e. the computing agent understands
what is to be done.
Not effectively computable operations:
Write all the fractions between 0 and 1.
Add 1 to the current value of x.
that, when executed, produces a
result
The question that must be answered is:
Can the user of the algorithm observe a result
produced by the algorithm?
The result need not be a number or piece of text
It could be an alarm, signaling something is
wrong.
It could be an approximation to an answer.
It could be an error message.
halts in a finite amount of
time
The question that must be answered is:
Will the computing entity complete the operations
in a finite number of steps and stop?
Do not confuse "not finite" with "very, very large".
A failure to halt usually implies there is an infinite
loop in the collection of operations:
1. Write the number 1 on a piece of paper.
2. Add 1 to the number you just wrote and
write it on a piece of paper.
3. Repeat 2.
4. Stop.
Definition of an algorithm:
 An
algorithm is a well-ordered
collection of unambiguous and
effectively computable operations
that, when executed, produces a
result and halts in a finite amount of
time.
Note: Although I have tried to give clean cut examples to
illustrate what these new words mean, in some cases, a
collection of operations can fail for more than one reason.
RETURNING TO OUR ORGINAL
QUESTION:
HOW DO WE DEFINE COMPUTER
SCIENCE?
 Computer
science is the study of
algorithms including




1. Their formal and mathematical
properties
2. Their hardware realizations
3. Their linguistic realizations
4. Their applications
1. Their formal and
mathematical properties
 It
is not enough to develop any old
algorithm to solve a problem.
properties of an algorithm:



How efficient is it?
What kinds of resources must be used to
execute it?
How does it compare to other algorithms
that solve the same problem.
2. Their hardware realizations
 Algorithms
need not execute on machines.
All we really need are computing entities.

Anything that can compute – e.g., a human.
 But,
ultimately, most of our interest will lie
with algorithms that execute on computing
entities called "computers".
 How are these entities constructed?

The emphasis will be on the logical
construction of a computer, not the physical
construction.
3. Their linguistic realizations
 How
do we represent algorithms?
realization today, called pseudocode
and later will look at many different
realizations in various programming
languages.
 We'll even consider some of the visual
representations using graphics.
And finally:
4. Their applications
 What
are some of the many important and
popular applications of computers in
current use including:







modeling and simulation
information retrieval
numerical problem solving
telecommunications
artificial intelligence
networking
graphics
Early History of Computing
Abacus
An early device to record numeric values
We normally do not call it a computer, but a computing
device.
It is still used in parts of the world today.
This distinction between a computer and a computing
device will become clearer as we look at other aspects
of the history of computing.
source: http://www.ee.ryerson.ca:8080/~elf/abacus/intro.html
6
Napier’s Bones (or Rods)

Rods were marked with multiplication table
results.
 These were used to provide fairly simple
means of multiplying large numbers.
 On the below web site, one of the labs goes
into some details on Napier’s Bones:
http://csilluminated.jbpub.com/labs/Napier.cfm
 The honor for constructing the first calculating
machine belongs to a German called Wilhelm
Schickard . In 1623 he completed a
mechanical calculating machine based on
Napier's work.
Using the bones to compute 46732
X5
10
150
3500
30000
200000
source: http://csilluminated.jbpub.com/labs/Napier.cfm
Slide Rule

In 1614, John Napier discovered algorithms which made
it possible to perform multiplication and division using
 To avoid having to log tables, Edmund Gunter created a
number line in which the position of numbers were
proportional to their logs.
 William Oughtred soon simplified things further by
creating a slide rule with two Gunter’s lines.
 One line could “slide” in order to increment (multiply)
or decrement (divide) a value by a second value.
 The slide rule was widely in use by the end of the 17
century and remained popular for the next 300 years.
 Improvements included ability to compute powers and
roots of numbers but did not include ability to add or
subtract.
Blaise Pascal

In 1642 Blaise Pascal, a Frenchman invented a
new kind of computing device.
had ten notches, numbered '0' to '9'. When a
wheel was turned seven notches, it added 7 to
the total on the machine.
 Pascal's machine, known as the Pascaline,
 It could also subtract.
source: http://www.tased.edu.au/schools/rokebyh/curric/
infotech/stage1/assign2/pre20th.htm#schickard
Gottfried Leibnitz
 Leibnitz
machine so that it could also perform
multiplication, division and calculate
square roots.
source: http://www.tased.edu.au/schools/rokebyh/curric/
infotech/stage1/assign2/pre20th.htm#schickard
Grillet’s Pocket Calculator





One very early machine which incorporated Napier’s
ideas was that built by a French clockmaker called Grillet
in 1678.
Grillet included a set of Napier's Rods in an adaptation of
the Pascaline. It could be considered the world's first
pocket calculator.
The top section of the device consisted of 24 dials or sets
of wheels. The lower section contained a set of inverted
Napier’s Rods engraved on cylinders.
Although the device was limited, it did allow simple
operations to be performed.
It could carry out eight digit additions -- something that
would have been very useful at a time when very few
Grillet’s Machine
http://www.tased.edu.au/schools/rokebyh/curric/infotech/stage1/
assign2/pre20th.htm#schickard
Joseph Jacquard





In the late 1700s in France, Joseph Jacquard
invented a way to control the pattern on a
weaving loom used to make fabric.
Jacquard punched pattern holes into paper
cards.
The cards told the loom what to do.
Instead of a person making every change in a
pattern, the machine made the changes all by
itself.
Jacquard's machine didn't count anything. So
it wasn't a computer or even a computing
device. His ideas, however, led to many
other computing inventions later.
Jacquard Loom - A mechanical device that
influenced early computer design
Intricate textile
patterns were
prized in France in
early 1800s.
Jacquard’s loom
(1805-6) used
punched cards to
allow only some
rods to bring the
loom on each
shuttle pass.
Source:
http://65.107.211.206/technology/jacquard.html
Sheets of punched cards set the
pattern of the weave
Source: http://65.107.211.206/technology/jacquard.html
Luddites

During the 1700's and early 1800's, part of the world saw the
development of industrialization.
 Before the Industrial Revolution, manufacturing was done by
hand or simple machines.
 The Industrial Revolution caused many people to lose their
jobs.
 Groups of people known as Luddites attacked factories and
wrecked machinery in Britain between 1811 and 1816.
Ned Ludd.
 They believed that the introduction of new textile machines
in the early 1800's had caused unemployment and lowered
the textile workers' standard of living.
 Note this is similar to the way some people see that
computers today are taking the jobs of workers.
Charles Babbage



Babbage is known as the
father of modern computing
because he was the first
person to design a general
purpose computing device.
In 1822, Babbage began to
design and build a small
working model of an
automatic mechanical
calculating machine, which
he called a "difference
engine".
Example: It could find the first
30 prime numbers in two and
a half minutes.
In the Science Museum,
London
Source: http://www.sciencemuseum.org.uk/online/babbage/page3.asp
A closer look at difference engine
source: http://www.computer.org/history/development/graphics/diff_eng.jpg

Babbage continued work to produce a full scale working
Difference Engine for 10 years, but in 1833 he lost interest
because he had a "better idea"--the construction of what
today would be described as a general-purpose, fully
program-controlled, automatic mechanical digital computer.

Babbage called his machine an "analytical engine".

He designed, but was unable to build, this Analytical Engine
(1856) which had many of the characteristics of today’s
computers:
an input device – punched card reader
an output device – a typewriter
memory – rods which when rotated into position “stored”
a number
control unit – punched cards with instructions encoded as
with the Jacquard loom
The machine was to operate automatically, by steam
power, and would require only one attendant.
source: http://www.sciencemuseum.org.uk/on-line/babbage/page5.asp
Some call Babbage’s analytic engine the first
computer, but, as it was not built by him, most
people place that honor elsewhere.

Babbage's analytical engine contained all the
basic elements of an automatic computer-storage, working memory, a system for moving
between the two, an input device and an output
device.
 But Babbage lacked funding to build the
machine so Babbage's computer was never
completed.
Babbage designed a printer, also, that has just
been built at the Science Museum in London4,000 working parts!
source: http://news.bbc.co.uk/1/hi/sci/tech/710950.stm

Ada Byron Lovelace was a close
friend of Babbage.
 Ada thought so much of
Babbage's analytical engine that
she translated a previous work
 Because of the detailed
work, she has been called the
inventor of computer
programming.
Today, on behalf
of her work in
computing, a
programming
named after her.
source:http://www.pbs.org/teachersource/mathline/concepts/
womeninmath/activity2.shtm
7
Herman Hollerith





In 1886, Herman Hollerith invented a machine known as
the Automatic Tabulating Machine, to count how many
people lived in the United States.
This machine was needed because the census was taking
far too long.
His idea was based on Jacquard's loom. Hollerith used
holes punched in cards. The holes stood for facts about a
person; such as age, address, or his type of work. The
cards could hold up to 240 pieces of information.
Hollerith also invented a machine, a tabulator, to select
special cards from the millions.
To find out how many people lived in Pennsylvania, the
machine would select only the cards punched with a
Pennsylvania hole. Hollerith's punched cards made it
possible to count and keep records on over 60 million
people.
Hollerith Tabulator
Hollerith founded the
Tabulating Machine
Company.
In 1924, the name of
the company was
changed to
International
Corporation (IBM).
This is the 1890
version used in
tabulating the 1890
federal census.
Source: http://www.columbia.edu/acis/history/hollerith.html
Punched cards
The punched card
used by the Hollerith
Tabulator for the
1890 US census.
The punched card
was standardized in
1928:
It was the primary input
media of data processing
and computing from 1928
until the mid-1970s and
was still in use in voting
machines in the 2000 USA
presidential election.
source: http://www.columbia.edu/acis/history/hollerith.html
History of Hardware
Harvard Mark I, ENIAC, UNIVAC I,
ABC and others

These are the names of some of the early
computers that launched a new era in
mathematics, physics, engineering and
economics initially and, subsequently, almost
every area has been impacted by computers.
 The early computers were huge physically and
very limited by today’s standards.
First Generation Hardware
(1951-1959) – Major
characteristics
Vacuum Tubes
Large, not very reliable, generated a lot of heat
Magnetic Drum Storage
Card Readers & Magnetic Tape Drives
Development of these sequential auxiliary storage
devices
8
ABC built by Professor John Atanasoff and a
graduate student, Clifford Berry, at Iowa State
University between 1939 and 1942.

Special purpose
computer and was
not truly
programmable.
 The instructions to
the machine were
entered by buttons.
 Input: Punched
paper tape
 Output: Punched
cards
Source: www.cs.iastate.edu/jva/images/abc-1942.gif
Mark I designed by Howard Aiken and Grace
Hopper at Harvard University in 1939-1944.
Contains more than 750,000
components, is 50 feet long, 8 feet
tall, and weighs approximately 5
tons
Instructions were pre-punched on
paper tape
Input was by punched cards
Output was displayed on an electric typewriter.
Could carry out addition, subtraction, multiplication,
division and reference to previous results.
Still exists in the Computer Science Building at Harvard
University and can be turned on and run!
Source: http://www.digidome.nl/howard_h__aiken.htm
Zuse’s Machines, Z1-Z4 built by Konrad Zuse in
Berlin, Germany, 1938 – 1944 (all destroyed
supposedly in the Berlin bombings)
If these machines did exist as described by Zuse
after the war, they were the first computers.
Rebuilt model of Z3 housed in Deutsches Technik
Museum, Berlin
Input: from a numeric, decimal,
20 digit keyboard
Output: Numbers displayed with
lamps, 4 decimal digits with
decimal point
Programmed via a punch tape
Multiplication 3 seconds,
division 3 seconds, addition 0.7 seconds.
Used a 600 relay numeric unit,
1600 relay storage unit
Computer vs computing device
 Most,
but not all, people claim a computer
must be




 If
Digital
Programmable
Electronic
General purpose
any characteristic is missing, at best,
you have a computing device.
Mauchly and Eckert or Zuse – built
the first computer



Many claim the ENIAC was the first computer as
there was proof that it did exist.
John Mauchly envisioned the ENIAC. He was a
professor of Physics at Ursinus College. In 1943 he
attended a workshop at Penn were, he saw a
machine calculating firing tables. Mauchly realized
that he could build an electronic machine that could
be much faster.
J. Presper Eckert solved the engineering challenges.
The chief challenge was tube reliability. Eckert was
able to get good reliability by running the tubes at 1/4
power.
ENIAC – (Electrical Numerical Integrator And
Calculator), built by Presper Eckert and John
Mauchly at Moore School of Engineering,
University of Pennsylvania, 1941-46
Often called the
first computer (that
was electronic,
programmable,
general purpose
and digital).
ENIAC






18,000 vacuum tubes and weighed 30 tons
Duration of an average run without some failure
was only a few hours, although it was predicted
to not run at all!
When it ran, the lights in Philadelphia dimmed!
ENIAC Stored a maximum of twenty 10-digit
decimal numbers.
Output: Punched cards, lights
Eniac’s Vacuum Tubes
Photo taken at Computer Science History Museum, San Jose, CA,
by Dr. Robert Walker on VLSI Trip to Silicon Valley.
A vacuum tube similar
to those used in the
earliest computers.
Source: http://www.cs.virginia.edu/brochure/images/mus_024.jpg
ENIAC
Programming required rewiring of the machine,
Source: http://ftp.arl.army.mil/ftp/historic-computers/
UNIVAC – first commercial
computer





On March 31, 1951, the Census Bureau
accepted delivery of the first UNIVAC computer.
The final cost was close to one million dollars.
Forty-six UNIVAC computers were built for both
Remington Rand became the first American
manufacturer of a commercial computer
system.
Their first non-government contract was for
General Electric in Louisville, Kentucky, who
used the UNIVAC computer for a payroll
application.
UNIVAC’s prediction ignored

A 1952 UNIVAC made history by predicting the
election of Dwight D. Eisenhower as US
president before the polls closed.
 The results were not immediately reported by
Walter Cronkite because they were not
believed to be accurate.
Stevenson was the front-runner in all the
advance opinion polls, but by 8:30 p.m. on the
East Coast, well before polls were closed in the
Western states, UNIVAC projected 100-to-1
odds that Dwight D. Eisenhower would win by
a landslide, which is in fact what happened.
1952 election night
source: http://www.cedmagic.com/history/univac-cronkite.html
Whirlwind at MIT - 1952
 The
first digital computer capable of
displaying real time text and graphics on
a large oscilloscope screen.
Bouncing
ball
displayed on
screen
Second Generation Hardware
(1959-1965) - Characteristics
Transistor
Replaced vacuum tube, fast, small, durable, cheap
Magnetic Cores
Replaced magnetic drums, information available
instantly
Magnetic Disks
Replaced magnetic tape, data can be accessed directly
9
A Typical Computing Environment in 1960 –
UNIVAC 1107 at Case Institute of
Technology
source: http://www.fourmilab.ch/documents/univac/case1107.html

1961-
The true purpose of computers is finally
realized in 1961, when a MIT student, Steve
Russell, created the first computer game –
Spacewar on a DEC PDP-1- a minicomputer
200 hours to program!
http://www.nersc.gov/~deboni/Computer.history/GAM.PDP-1/
Father of Graphics- Ivan Sutherland
Ph.D.
Thesis, 1963, MIT :
Sketchpad: The First Interactive Computer Graphics
Package on TX-2 (forerunner of DEC machines).
TX-2 was a giant machine for the day:







320 kilobytes of memory, about twice the
capacity of the biggest commercial machines
magnetic tape storage,
an on-line typewriter,
the first Xerox printer,
paper tape for program input,
a light pen for drawing,
a nine inch CRT (i.e. display screen) !
Light Pen Input
System," used the light pen to create engineering drawings
directly on the CRT.
1964 CDC
Control Data
Corporation
CDC 6600 at U of
Texas, 1964-68
Cost: \$2,000,000+
Kept in dustfree
room behind
locked doors
source: http://www.computerhistory.org/timeline/timeline.php?
timeline_category=cmptr
CDC 6600 – University of Texas - 1964
Workstations
were available
to only a few.
use punched
cards handed
in through a
window
Source: http://ed-thelen.org/comp-hist/vs-cdc-6600.jpg
A sampling of 1960-1965 circuit boards:
Photo taken at Computer Science History Museum, San Jose, CA,
by Dr. Robert Walker on VLSI Trip to Silicon Valley
Third Generation Hardware (19651971)
Integrated Circuits
Replaced circuit boards, smaller, cheaper, faster, more
reliable.
Transistors
Now used for memory construction
Terminal
An input/output device with a keyboard and screen
By 1968 you could buy a 1.3 MHz CPU with half a megabyte
of RAM and 100 megabyte hard drive for a mere US\$1.6 million.
10
PDP I – first of the minicomputers to be used
by many universities.
The PDP-40, a popular 3rd generation
minicomputer in the early 1970’s
The DEC-10 was popular at a lot of large universities.
Photo taken at Computer Science History Museum, San Jose, CA,
by Dr. Robert Walker on VLSI Trip to Silicon Valley
Dumb terminals or workstations were used to tie into the
mainframes:
Photo taken at Computer Science History Museum, San Jose, CA,
by Dr. Robert Walker on VLSI Trip to Silicon Valley
Fourth Generation Hardware
(1971-?)
Large-scale Integration
PCs, the Commercial Market, Workstations
Personal Computers were developed as new companies
like Apple and Atari came into being. Workstations
emerged.
11
Personal Computers were
Introduced around 1977
Photo of early PCs taken at Computer Science History Museum
In San Jose, CA, by Dr. Robert Walker on Trip to Silicon Valley
Typical prices on early PCs

Contrary to
popular
belief today,
these were
not cheap –
the IBM
5100 in mid
1970s.
Memory BASIC
16K
\$8,975
32K
\$11,975
APL
\$9,975
\$12,975
Both
\$10,975
\$13,975
48K
\$14,975
\$15,975
\$16,975
64K
\$17,975
\$18,975
\$19,975
Note that \$1 in 1975 would be equal to \$3.76 today so
multiply these by ~3.8! For this price comparison
see http://www.westegg.com/inflation/
VAX 780 – Early Math-CS computer
at KSU, obtained in1982.
Photo taken at Computer Science History Museum, San Jose, CA,
by Dr. Robert Walker on VLSI Trip to Silicon Valley
Dumb terminals were used for some input with these
machines and line printers were used for output:
Photo taken at Computer Science History Museum, San Jose, CA,
by Dr. Robert Walker on VLSI Trip to Silicon Valley
Parallel Computing and
Networking
Parallel Computing
Computers rely on interconnected central processing
units that increase processing speed.
Networking
With the Ethernet small computers could be connected
and share resources. File servers connected PCs in
the late 1980s.
ARPANET and LANs  Internet
12
There are many different kinds of parallel
machines – this is one type

A parallel computer must be capable of working
on one task even though many individual
computers are tied together.
 Lucidor is a distributed memory computer (a
cluster) from HP. It consists of 74 HP servers
and 16 HP workstations. Peak: 7.2 GFLOPs
GFLOP =
one billion
decimal
number
operations/
second
source:http://www.pdc.kth.se/compresc/machines/lucidor.html
Cray Machines Are Another Type of
Parallel Machine –Cray 1
Photo taken at Computer Science History Museum, San Jose, CA,
by Dr. Robert Walker on VLSI Trip to Silicon Valley
Cray 2
Photo taken at Computer Science History Museum, San Jose, CA,
by Dr. Robert Walker on VLSI Trip to Silicon Valley
Another Earlier Parallel Computer at the
University of Illinois was the Illiac IV
Photo taken at Computer Science History Museum, San Jose, CA,
by Dr. Robert Walker on VLSI Trip to Silicon Valley
Another View of the Illiac IV
Photo taken at Computer Science History Museum, San Jose, CA,
by Dr. Robert Walker on VLSI Trip to Silicon Valley
CM-2 Connection Machine
Interesting fact: The lights are there only for show!
The IBM 360 (late ’60s) console
Photo taken at Computer Science History Museum, San Jose, CA,
by Dr. Robert Walker on VLSI Trip to Silicon Valley
A History of the Web - Let’s Be Precise

Late 1960s – the ARPANET was conceived as a
network of computers in which packets of information
(i.e. data) could be transmitted between various
computers via telephone lines or higher speed
dedicated data lines.

ARPA was the Advanced Research Projects Agency.

This allowed remote logins to computers (using
telnet), the ability to transfer files between computers
(using ftp = file transfer protocol), and e-mail.

Many people now say it was designed for the
military, but that was newspaper hype.
 The purpose of the ARPANET was to allow the
sharing of National Science Foundation (NSF)
research project information between
researchers.
 In 1972, there were 29 nodes (i.e. computer
sites that were interconnected).
 CS program at KSU was earliest node in Ohio
(~1982).
The ARPANET Introduced the
Internet Protocol
To move data from computer A to computer B:
Break the data up into packets of information.
 Each packet carries the IP (Internet Protocol) address of
computer B which consists of 4 numbers.
envelope is shipped along to another computer using a
recipe called a routing algorithm.
 At no time are A and B necessarily physically connected
(unless they are adjacent nodes on the network).
 The different packets will not necessarily follow the same
route.
 At computer B, the packets are reassembled into the
document.
 A packet is typically in the 40 – 1500 byte range
(1 byte = 1 character)

Docu
Document
ment
X at A
Packet-based
transmission of
a document
from Computer
A to Computer
B
Note: If one
computer fails,
the document
still may be
transmitted.
Packet X-1
for B
Computer C
Packet X-2
for B
Computer F
Packet X-3
for B
Computer E
Computer D
Computer B
Computer G
Document
X at B
Tracing the Route Your Packets Take

Traceroute is a tool that traces the route your
packets take.
 Ping is a tool that tells you whether or not a web
site is up.
 Ping Plotter (http://www.pingplotter.com/) is a
tool that graphically shows you the route your
packets take.
 It was free, but can be used for 30 days
without a subscription of \$0.99 a month today.
 Interesting to see how your packets travel!
One Ping Plotter Trace to www.weather.com
A Trace to KSU
If you watch these interactively you’ll see the route changes.
Internet to World Wide Web

The Internet is a collection of computers using the
internet protocol to transmit information
 The World Wide Web is a multimedia environment
invented by Tim Berners-Lee, in 1990.
 Was a physicist at CERN (the European
Organization for Nuclear Research).
 Wrote the first web browser (WorldWideWeb) and
the software for the first web server.
 Invented both the HTML markup language in which
many web pages are written and the HTTP protocol
used to request and transmit web pages between
web servers and web browsers
Growth in WWW

Number of Unique Web Sites
The number of Web sites, adjusted to account for sites
1998: 2,636,000
1999: 4,662,000
2000: 7,128,000
2001: 8,443,000
2002: 8,712,000

A Web site is defined as a distinct location on the Internet,
identified by an IP address, that returns a response code of 200
and a Web page in response to an HTTP request for the root
page. The Web site consists of all interlinked Web pages

Statistics provided by OCLC Online Computer Library Center,
Inc., Office of Research
Active Internet Users by Major
Country
Average Web Usage in U.S.
More Than Half of People in U.S. and
Global Usage – Includes All Countries Monitored :
~20 countries accounting an estimated 90% of all
Internet users
For a more complete list see:
http://www.clickz.com/stats/big_picture/geographics/article.php/
5911_151151
From the “Computer Industry Almanac”

Worldwide Internet Population 2004: 934 million

Projection for 2005: 1.07 billion

Projection for 2006: 1.21 billion

Projection for 2007: 1.35 billion
For more details for individual countries see:
http://www.clickz.com/stats/sectors/geographics/
article.php/%205911_151151
Negative Properties of WW







Uneven capabilities of user’s browsers and other
software
 i.e. plug-ins differ widely and can interact with
each other in strange ways.
No central control – therefore, unregulated and
somewhat uncensored.
Anonymity of site owners.
Contrary to popular belief, it is not free.
Device independent – but not all hardware acts
the same.
Uneven bandwidth – number of bits that can be
transmitted per second.
Be Cautious and Critical
 There
is a famous New Yorker cartoon:
Cartoon by Peter Steiner reproduced from page 61 of July 5, 1993
issue of The New Yorker, (Vol.69 (LXIX) no. 20).
Brief Mention of History of
Theory
We’ll study this more later
Alan Turing
Turing Machine, Artificial Intelligence Testing

Much of the early work on computers was theoretical
and done by mathematicians.
 Alan Turing, and others, studied the questions “What
tasks can be computed?” and “What is a computer?” His
abstract model, called the Turing Machine, is of great
interest in studying these questions.
 Another big questions was, and still is, “Are machines
intelligent?”
 Alan Turing devised a test, now known as The Turing
Test (1950), to answer this question.
 We’ll delve into these issues a little later in the course.
History of Software
Again, we will go deeper into
these topics later
First Generation Software
(1951-1959) -we’ll see more on these
topics later
Machine Language
Computer programs were written in binary (1s and 0s)
Assembly Languages and translators
Programs were written in languages that mimicked
machine language and were then translated into
machine language
Programmers begin to specialize
Programmers divide into application programmers and
systems programmers.
13
Systems vs Applications

Computer scientists that design programs and
systems for other computer scientists to use are
called systems computer scientists.

Computer scientists that design programs and
systems for non-computer scientists to use are
called application computer scientists.
Second Generation Software
(1959-1965)
High Level Languages
Use English-like statements and made programming
easier:
Fortran, COBOL, Lisp.
High-Level
Languages
Assembly
Language
Machine
Languag
e
14
Third Generation Software (19651971)

Systems Software Developed



utility programs,
language translators,
and the operating system, which decides which
programs to run and when.

Separation between Users and Hardware
 Computer programmers now created
programs to be used by people who did not
know how to program
15
Third Generation Software (19651971)
Application Package
Systems Software
High-Level Languages
Assembly Language
Machine Language
16
Fourth Generation Software (19711989)
Structured Programming
Pascal, C
New Application Software for Users
systems
17
Fifth Generation Software (1990present)
Microsoft
The Windows operating system, and other Microsoft
application programs dominate the market
Object-Oriented Design
Based on a hierarchy of data objects (i.e. Java, C++)
World Wide Web
Allows easy global communication through the Internet
New Users
Today’s user can “get by” with little computer knowledge
18
Computing as a Tool
Programmer / User
Systems Programmer
(builds tools)
Applications Programmer
(uses tools)
Domain-Specific Programs
User with No
Computer Background
20
Computing as a Discipline

What can be (efficiently) Automated?

Four Necessary Skills
1.
2.
3.
4.
Algorithmic Thinking
Representation
Programming
Design
21
Some Systems Areas of
Computer Science
 Study
of Algorithms and Data Structures
 Programming Languages
 Architecture
 Operating Systems
 Software Methodology and Engineering
 Human-Computer Communication
 Systems Programming
23
Some Application Areas of
Computer Science
 Numerical
and Symbolic Computation
 Databases and Information Retrieval
 Artificial Intelligence and Robotics
 Graphics
 Organizational Informatics
 Bioinformatics
 Multimedia
 Game development
24
Some other disciplines sharing some ground
with computer science
 Computer
engineering
 Electrical engineering
 Computational physics
 Computational chemistry
 Computational biology (or bioinformatics)
Hot off the presses
What field has…
• …the best-rated job, and 5 of the top 10
highest paid, highest growth jobs?
• …shown strong job growth in the face of
outsourcing?
• …a looming severe shortage in college
Computer Science!
This slide and the rest of the slides in this presentation were collated from SIGCSE
announcements and displayed at the Gettysburg College Department of Computer Science
website. Individual sources are given on the last slide.
•
Software engineers top the list of
best jobs according to a Money
magazine and Salary.com survey based
on “strong growth prospects, average
pay of \$80,500 and potential for
creativity”. [1]

5 computing jobs are in the top 10 salary jobs from
the Bureau of Labor Statistics’ list of the 30 fastest
growing jobs through 2014. [2]
1. Computer systems software engineer: \$81,140
2. Computer applications software engineer: \$76,310
6. Computer systems analyst: \$67,520
9. Network systems and data communication analyst:
\$61,250
Salaries are given as mean annual salaries over all
regions.
• In April 2006, more Americans were employed in IT
than at any time in the nation’s history. [3]
• In May 2004, “U.S. IT employment was
17% higher than in 1999
5% higher than in 2000 and
showing an 8% growth in the [following] year …
The compound annual growth rate of IT wages has been
about 4% since 1999 while inflation has been just 2% per
year
… Such growth rates swamp predictions of the outsourcing
job loss in the U.S., which most studies estimate to be 2% to
3% per year for the next decade.” [4]
• “According to the National Science Foundation, the need
for science and engineering graduates will grow 26%,
or by 1.25 million, between now and 2012.
The number of jobs requiring technical training is growing at
five times the rate of other occupations. And U.S. schools are
nowhere near meeting the demand, according to multiple
studies.” [5]
• The percentage of college freshmen listing computer
science as their probable major fell 70% between 2000
and 2004. [6]
[1] Wulfhorst, Ellen. Reuters.com, Apr. 12, 2006.
http://www.salary.com/careers/layoutscripts/crel_display.asp?tab=cre&cat=nocat&ser=Ser387&part=Par615
[2] Morsch, Laura. CareerBuilders.com, Jan. 27, 2006.
http://www.cnn.com/2006/US/Careers/01/26/cb.top.jobs.pay/index.html
[3] Chabrow, Eric. InformationWeek.com, Apr. 18, 2006.
http://www.informationweek.com/showArticle.jhtml?articleID=185303797
[4] Patterson, David. President’s Letter: Restoring the Popularity of
Computer Science, Communications of the ACM, Sept. 2005, Vol. 48, No. 9
[5] Deagon, Brian. Investor’s Business Daily, May 12, 2006.
http://www.investors.com/editorial/IBDArticles.asp?artsec=24&issue=20060512&view=1
[6] Robb, Drew. ComputerWorld.com, July 17, 2006.
http://computerworld.com/action/article.do?command=printArticleBasic&articleId=112364
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