An odyssey through computer science

Readings: `Syllabus', `Resources', and Sections 1.1, 2.1, and 2.2..

Our goal

What's this all about?

To understand the

• scope,
• techniques, and
• contributions

Helpful resources

CS staff:
Carl Burch, core instructor
Kirk Yenerall, lab/CTW instructor

Web page:

Textbook

Lectures:
Web notes and questions
Your questions!

Classwork:
Due Mondays
Collaborate!
Cluster help
Start early!

Classmates:

Alice	Bob	Carrie	Krunch	Eve	Spot

Programming experience

But I know everything already!

Carrie's in the minority.

For those with programming experience: a self-study track!

• Exercises at own pace
• TA will supervise
• Interesting projects

Definition

Enough preliminaries! What is computer science?

Computer science seeks to answer:

Computers

But computer science should be about computers!

Computing science would be a better name.

But computers are essential tools to problem-solving.

• fast
• reliable (usually)
• correct (hopefully)

CS circles

Let's look at the ``circles'' of CS.

• Theory
• Systems
• Industry
• Artificial intelligence
• Programming languages

Limbo!

First circle: Theory

What are the fastest ways to solve particular problems?

• Mathematical approach
• Looks for
  • fast methods (algorithms)
  • lower bounds (complexity)
• Overlaps with discrete math

Second circle: Systems

How can we build better problem-solving tools?

• Emphasis on engineering
• Examines
  • Computers (hardware engineering)
  • Software (software engineering)
• Overlaps with electrical engineering

Third circle: Industry

How can we build better programs?

• Looks for
  • reliability and cost-effectiveness (software engineering)
  • usability (human-computer interaction)
• Overlaps with social sciences

Fourth circle: Artificial intelligence

How can we behave `intelligently' automatically?

• Facets: learning, understanding, planning
• Overlaps with psychology and robotics

Fifth circle: Programming languages

How can we best represent procedure?

• Looks for how to incorporate aspects into programming languages
  • security
  • parallelism
  • other features
• Overlaps with logic

Curiouser and curiouser!

The plan

We're covering all that?

Table 1: Tentative schedule of topic coverage

Session	Material
1	Prologue
2	:
3	Programming
4	:
5	:
6	:
7	Recursion
8	:
9	Internet
10	:
11	:
12	Algorithms
13	:
14	:
15	Cryptography
16	TBA / Quiz
17	Evaluation / Epilogue

This is very tentative!

Questions

If you ever feel yourself getting lost...

Don't make me do all the work!

What is your problem?

If computer science is about solving problems...
What is a problem?

Problems

A problem is a set of questions with well-defined answers.

Examples

Examples of problems:

• What is 6x9?
• Who killed JFK?
• Which is the way to Emerald City?

Non-examples:

• What is the answer to life, the universe, and everything?
• What is truth?
• Who is John Galt?

Input and output

For a set of questions, a problem's input identifies the question to be answered.

The output is the answer to the question.

Example:

Problem ADDITION:
Input: two numbers x and y.
Output: the sum x+y.

A problem instance is a particular question from the set: ``What is 6 + 9?''

More example problems

You mean we're going to study arithmetic?

Our problems won't always be obviously mathematical.

Example:

Problem CHESS:
Input: a configuration of the board.
Output: a move for white guaranteeing a win.

Example input:

     Q - - - - - - -
     - - - - K - - R  boldface = black
     - - - P - - - -  roman = red
     - - - P - - - -  P = pawn
     - - - - P - P -  R = rook
     - - - - - P - -  K = king
     - - - - - - - -  Q = queen
     - R - K - - - -

Algorithms

An algorithm is a method for solving a problem that

• always finds an answer
• is always correct

Example: an algorithm for ADDITION

    111
    1999
  +  125
  ------
    2124

Another example

Think of algorithms for PRIMALITY.

Problem PRIMALITY:
Input: a number n.
Output: true if n is prime, false if not.

Here are two algorithms. Each is written in pseudocode, a recipe-like mixture of blank space, English, and math.

First algorithm:

Algorithm Prime-Test-Exhaustive(n):
for each i from 2 to n-1, do:
  if i divides n, then:
    output false.
    stop.
  end of if
end of loop
output true.
stop.

Second algorithm:

Algorithm Prime-Test-All(n):
for each integer i from 2 to sqrt(n, do:
  if i divides n, then:
    output false.
    stop.
  end of if
end of loop
output true.
stop.

Another example

Problem MISSING-CARD:
Input: a number n.
Output: true if n is prime, false if not.

We choose to represent the following algorithm as a flowchart, a pictoral representation of how we move through the algorithm.

• An oval has a START or STOP instruction.
• A rectangle contains a simple instruction (and has one outgoing arrow).
• A diamond contains a decision (and has two outgoing arrows).

Conclusion

We look forward to working
with you this month!

Tomorrow:
self-paced (``experienced'') students to Baker 140
beginner students: Scaife 125 (here)