Computer Science: An Overview Tenth Edition by J. Glenn …cc.ee.ntu.edu.tw/~farn/courses/BCC/NTUEE/slides/ch00… · · 2014-02-26Copyright © 2008 Pearson Education, Inc. Publishing

Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley

Computer Science: An Overview

Tenth Edition

by

J. Glenn Brookshear

Chapter 0:

Introduction

Presentation files modified by Farn Wang

Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 0-2

Chapter 0: Introduction

• 0.1 The Role of Algorithms

• 0.2 The Origins of Computing Machines

• 0.3 The Science of Algorithms

• 0.4 Abstraction

• 0.5 An Outline of Our Study

• 0.6 Social Repercussions


Terminology

• Algorithm: A set of steps that defines how

a task is performed

• Program: A representation of an algorithm

• Programming: The process of developing

a program

• Software: Programs and algorithms

• Hardware: Equipment


• Select a deck of 10 black and a deck of 10

red cards.

• Put them face down.

• Shuffle the cards in the two decks.

• Pick a red card if the audience want red.

• Pick a black card otherwise.

A magic trick


• Select a deck of 10 black and a deck of 10

red cards.

• Put them face down.

• Bend the red deck slightly concave.

• Bend the black deck slightly convex.

• Shuffle the cards in the two decks.

• Pick a concave card if the audience want

red.

• Pick a convex card otherwise.

An algorithm for a magic trick


History of Algorithms

• The study of algorithms was originally a

subject in mathematics.

• Early examples of algorithms

– Long division algorithm

– Euclidean Algorithm

• Gödel's Incompleteness Theorem: Some

problems cannot be solved by algorithms.


The Euclidean algorithm


Origins of Computing Machines

• Early computing devices

– Abacus: positions of beads represent numbers

• Only a storage device

• needs operation by human




– Gear-based machines (1600s-1800s)

• Positions of gears represent numbers

• Blaise Pascal (for additions)

• Wilhelm Leibniz (for the selection of a few operations)

• Charles Babbage

– differential engine (a prototype),

– analytical engine (truly programmable, never built)

– program, programmer




– Augusta Ada King, Countess of Lovelace

– 10 December 1815 – 27 November 1852

– The daughter of poet Lord Byron

– Programmer of Babbage’s Analytical

Engine

– Author of a paper describing how to write

programs for various operations.

– The first known programmer in the history.

– US Ministry of Defense defined a

language called Ada.


Early Data Storage

• Punched cards

– First used in Jacquard Loom (1801) to store

patterns for weaving cloth

– Storage of programs in Babbage’s Analytical

Engine

– Hollerith’s machine for US 1890 census

• IBM

– Popular through the 1970’s

• Gear positions


Early Computers

• Based on mechanical relays

– 1940: Stibitz at AT&T Bell Laboratories

– 1944: Mark I: Howard Aiken and IBM at Harvard


Early Computers

• Based on vacuum tubes

– 1937-1941: Atanasoff-Berry at Iowa State

– 1940s: Colossus: secret German code-breaker

– 1940s: ENIAC: Mauchly & Eckert at U. of Penn.

Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 14

The War in North Africa, WWII


Pacific war

- from a computational perspective

Japan radio communication was

deciphered by US with electronic

computing technology.

• Battle of the coral sea (May 4–8, 1942)

• Battle of Midway (June 4-7, 1942)

• 聯合艦隊司令山本五十六擊落(April 18,

1943)

• Bougainville Island

15


Battle of Midway

- from a computational perspective

Deciphered information

• A Japanese decoy fleet to Dutch Harbor, Alaska,

June 3, 1942

• Target: AF Midway

• Time of the battle

– in-time repair of carrier Yorktown

• The composition of the Japanese fleet

– Throughout the battle, Japanese did not know how many US

carriers there were.

16


Battle of Midway, June 4, 1942

加賀號（Kaga）

赤城號（Akagi）

蒼龍號（Soryu）

飛龍號（Horyu）

Enterprise

Hornet

Yorktown



蒼龍號

閃避轟炸中


Battle of Midway, June 4, 1942 加賀號（Kaga）

赤城號（Akagi）

蒼龍號（Soryu）

飛龍號（Horyu）



飛龍號燃燒中


The 1st Modern Computer

ENIAC

• arguable

• general-purpose functional computer

• In University of Pennsylvania

• Only hardware and programs

• The computers ? Men or machines ?

21


Downsizing of modern computers

• Transistors

– William Shockley, John Bardeen, Walter

Brattain (AT&T Bell Lab.)

• IC, Integrated Circuits

– Jack Kilby, Robert Noyce

0-22


Downsizing of modern computers

• Moore’s law

– half cost in 18

months

– double density,

speed in 18

months

0-23

Gordon Moore

co-founder of Intel


Personal Computers

• First used by hobbyists

– Apple computer

– motherboard + keyboard + monitor

• IBM introduced the PC in 1981.

– Accepted by business

– Became the standard hardware design for

most desktop computers

– Most PCs use software from Microsoft


Confluence of

computing & communication

Computing

• PDA

• notepad

• GPS

• sensors

• smartphone

0-25

Communication

• Internet

• emails,

• browsers

• search engines

• social groups


Computing & Communications

on the history

茉莉花革命

0-26

佔領華爾街


Computing & Communications

on the history

0-27

• Profit from hardware 1960-1980

• Profit from software 1980-2000

• Profit from data 2000-2010

• Profit from traffic & services 2010-?

Google, Youtube, Facebook, ….

Now the big brother is coming back to haunt

us.


Computer Science

• The science of algorithms

• Draws from other subjects, including

– Mathematics

– Engineering

– Philosophy

– Business Administration

– Psychology


Central Questions of Computer

Science

• Which problems can be solved by algorithmic processes?

• How can algorithm discovery be made easier?

• How can techniques of representing and communicating algorithms be improved?

• How can characteristics of different algorithms be analyzed and compared?


Central Questions of Computer

Science (continued)

• How can algorithms be used to manipulate information?

• How can algorithms be applied to produce intelligent behavior?

• How does the application of algorithms affect society?


The central role of algorithms in

computer science


Algorithms – application of

• Common algorithms for various

applications

– sorting, searching, string matching, query

processing, logic analysis, graph algorithms,

genetic programming, neural networks, …

• Techniques to adapt existing algorithms

• Efficiency enhancement

0-32


Algorithms – analysis of

• Computation time ?

– average-case

– worst-case

– probabilistic analysis

• Space requirement ?

• How many messages ?

• Complexities with respect to input sizes

0-33


Algorithms – discovery of

• Can a problem be solved with existing

algorithms ?

– One algorithm ?

– A combination of algorithms ?

• New algorithms needed ?

• Information/knowledge representation ?

– data structure ?

• Do the algorithms meet the goal ?

– specification, verification, testing ? 0-34


Algorithms – representation of

• Meeting the various styles of reasoning.

– flowcharts

– natural languages

– case analysis

– scenarios

– rule sets

• Supporting strutural reasoning

• Revealing logic errors

0-35


Algorithms – communication of

• Conveying of unambiguous ideas

• Enhancing comprehensibility

• Automation of

– specification reviewing

– algorithm analysis

– collaborative authoring and development

– testing

– verification

0-36


Algorithms – execution of

How does a computer execute your program ?

• Programming language design

– the basic computation primitives

– the pseudo machines

• Compilation

– optimization of instruction orders

– multithread – workload

decomposition/distribution

• Linking/loading

• Scheduling

0-37


Algorithms – limitations of

• Computability

– What problems can be solved with algorithms ?

• Intractability

– What cost do we pay for the algorithms ?

– space complexities

– time complexities

– message complexities

• Near optimal approximations

0-38


Abstraction

• Abstraction:

– The distinction between the external

properties of an entity and the details of the

entity’s internal composition

• Abstract tool:

– A “component” that can be used without

concern for the component’s internal

properties

– OO: C++, Java,


Outline of Our Study

• Chapter 1: Data Storage

• Chapter 2: Data Manipulation

• Chapter 3: Operating Systems

• Chapter 4: Networks and the Internet

• Chapter 5: Algorithms

• Chapter 6: Programming Languages


Outline of Our Study (continued)

• Chapter 7: Software Engineering

• Chapter 8: Data Abstractions

• Chapter 9: Database Systems

• Chapter 10: Computer Graphics

• Chapter 11: Artificial Intelligence

• Chapter 12: Theory of Computation


• Principles of right and wrong

• Assumes individuals are acting as free

moral agents to make choices to guide

their behavior

Ethics


Ethical Theories

• Consequence based (utilitarianism):

What leads to the greatest benefit?

• Duty based:

What are my intrinsic obligations?

• Contract based:

What contracts must I honor?

• Character based (Plato & Aristotle):

Who do I want to be?


• Redistribution of decision-making rights,

power, and other resources.

Example: IT makes it possible for millions of

people to download video files, weakening

the exclusive rights of movie studios to

control distribution for their own profit.

• Creation of new opportunities to commit

crimes.

Example: E-mail creates the conditions for

extensive “phishing” or online con games

designed to defraud ordinary citizens.

Why ethical issues in computer

science ?


Social Repercussions

• Advances in computer science raise new

questions.

– In law: Questions of rights and liabilities

– In government: Questions of regulation

– In the work place: Questions of

professionalism

– In society: Questions of social behavior


Social Repurcussions

- Google example

• Google search: compliance to individual

government’s policy ?

• YouTube: liability for file distribution of

users?

• Google Books: copyright ?

• Google Maps: collection of peoples’

whereabout ?

0-46


• Using systems to increase efficiency, and causing layoffs and personal hardships

• jobless recovery ?

• Using systems to monitor employee e-mail to protect valuable assets, but decreasing employee privacy

• Monitoring employee use of the Internet at work, decreasing employee privacy

• Using huge databases to aggregate consumer information, reducing the costs of granting credit, but increasing the chance of losing personal data to criminals, terrorists, or others

Dilemmas （王士元）


• Privacy: Claim of individuals to be left alone,

free from surveillance or interference from

other individuals, organizations, or the state.

The claim to be able to control information

about yourself

• Fair information practices

Privacy & freedom (I/III)


• Privacy

• Fair information practices: Set of principles

governing the collection and use of

information on the basis of U.S. and

European privacy laws

http://www.ftc.gov/reports/privacy3/fairinfo.shtm

Federal Trade Commission

Privacy & freedom (II/III)






Over the past quarter century, government agencies in the

United States, Canada, and Europe have studied the

manner in which entities collect and use personal

information -- their "information practices" -- and the

safeguards required to assure those practices are fair and

provide adequate privacy protection.

The result has been a series of reports, guidelines, and model

codes that represent widely-accepted principles

concerning fair information practices.

Fair information practices (I/II)





Common to all of these documents are five core principles

of privacy protection:

(1) Notice/Awareness;

(2) Choice/Consent;

(3) Access/Participation;

(4) Integrity/Security; and

(5) Enforcement/Redress.

Fair information practices (II/II)



• DPMA and ACM Codes of Conduct

http://www.acm.org/constitution/code.html • Geographic Information System Professionals

Code of Ethics • General federal privacy laws:

Freedom of Information Act, 1966 Privacy Act of 1974

Electronic Communications Privacy Act of 1986 Computer Matching and Privacy Protection Act of

1988 Computer Security Act of 1987 Federal Managers Financial Integrity Act of 1982

Ethics codes & privacy laws


Other issues

• Intellectual properties

• Accountability, liability, & control

• Quality

– System errors and data quality

– Life issues

• equity (computer-literate vs. illiterate)

• access

• boundaries

Documents

Computer Science: An Overview Tenth Edition by J. Glenn …cc.ee.ntu.edu.tw/~farn/courses/BCC/NTUEE/slides/ch00… · · 2014-02-26Copyright © 2008 Pearson Education, Inc. Publishing