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CSE 326: Data StructuresLecture #1

Introduction

Alon Halevy

Spring Quarter 2001

Today’s Outline

• Administrative Stuff• Overview of 326• Survey• Introduction to Complexity

Course Information• Instructor: Alon Halevy <alon@cs>

Office hours: Wed. 4:30-5:30, 310 Sieg Hall

• TA: Maya Rodrig <rodrig@cs>Office hours: Monday 1:30-2:30.

Meet in Sieg 226B

• TA (1/2) (and C++ expert): Nicholas Bone (bone@cs)• Sections are held in: BLD 392, EE1 031.• Text: Data Structures & Algorithm Analysis in C++,

2nd edition, by Mark Allen Weiss

Course Policies• Several written homeworks

– Due at the start of class on due date

• Several programming projects – Projects turned in electronically before 11pm on due date

• 10% penalty for 1 weekday late; afterward, NOT accepted

• Work in teams only on explicit team projects

• Grading– homework: 25%

– projects: 25%

– midterm: 20%

– final: 30%

Course Mechanics

• 326 Web page: www/education/courses/326/01sp• 326 course directory: /cse/courses/cse326• 326 mailing list: cse326@cs.washington.edu

– subscribe to the mailing list using majordomo, see homepage

• Course labs are 232 and 329 Sieg Hall– lab has NT machines w/X servers to access UNIX

• All programming projects graded on UNIX/g++

What is this Course About?

Clever ways to organize information in order to enable efficient computation

– What do we mean by clever?

– What do we mean by efficient?

Clever? Efficient?

Lists, Stacks, Queues

Heaps

Binary Search Trees

AVL Trees

Hash Tables

Graphs

Disjoint Sets

Insert

Delete

Find

Merge

Shortest Paths

Union

Data Structures Algorithms

Used Everywhere!

Mastery of this material separates you from:

Systems

TheoryGraphics

AI

Applications

• Perhaps the most important course in your CS curriculum! • Guaranteed non-obsolescence!

Anecdote #1

• N2 “pretty print” routine nearly dooms major expert system project at AT&T

– 10 MB data = 10 days (100 MIPS)

– programmer was brilliant, but he skipped 326…

Asymptotic Complexity

Our notion of efficiency:

How the running time of an algorithm scales with the size of its input– several ways to further refine:

• worst case

• average case

• amortized over a series of runs

The Apocalyptic Laptop

Seth Lloyd, SCIENCE, 31 Aug 2000

1

100000

1E+10

1E+15

1E+20

1E+25

1E+30

1E+35

1E+40

1E+45

1E+50

1E+55

1E+60

1 10 100 1000

2^N

1.2^N

N 5̂

N 3̂

5N

Big BangUltimate Laptop,

1 year1 second

1000 MIPS,

since Big Bang

1000 MIPS,

1 day

Specific Goals of the Course

• Become familiar with some of the fundamental data structures in computer science

• Improve ability to solve problems abstractly– data structures are the building blocks

• Improve ability to analyze your algorithms– prove correctness– gauge (and improve) time complexity

• Become modestly skilled with the UNIX operating system (you’ll need this in upcoming courses)

One Preliminary Hurdle

1. Recall what you learned in CSE 321 …– proofs by mathematical induction

– proofs by contradiction

– formulas for calculating sums and products of series

– recursion

Know Sec 1.1 – 1.4 of text by heart!

A Second Hurdle

• UnixExperience 1975 all over again!

– Try to login, edit, create a Makefile, and compile your favorite “hello world” program right away

– Programming Project #1 distributed Wednesday

– Bring your questions and frustrations to Section on Thursday!

A Third Hurdle: Templatesclass Set_of_ints {

public:

insert( int x );

boolean is_member( int x ); … }

template <class Obj> class Set {

public:

insert( Obj x );

boolean is_member( Obj x ); … }

Set <int> SomeNumbers;

Set <char *> SomeWords;

In Every Silver Lining, There’s a Big Dark Cloud – George Carlin

• Templates were invented 12 years ago, and still no compiler correctly implements them!

• Using templates with multiple source files tricky– See Course Web pages and TAs for best way

• MAINTAINING SANITY RULE– Write/debug first without templates

– Templatize as need

– Keep it simple!

Handy Libraries• From Weiss:

vector < int > MySafeIntArray;vector < double > MySafeFloatArray;string MySafeString;

• Like arrays and char*, but provide– bounds checking– memory management

• STL (Standard Template Library)– most of CSE 326 in a box– don’t use (unless told); we’ll be rolling our own

C++ Data StructuresOne of the all time great books in computer science:

The Art of Computer Programming (1968-1973)by Donald Knuth

Examples in assembly language (and English)!

American Scientistsays: in top 12 booksof the CENTURY!

Very little about C++ in class.

Abstract Data Types

Data Typesinteger, array,

pointers, …

Abstract Data Type (ADT)Mathematical description of an object and the set of operations on the object

Algorithmsbinary search, quicksort, …

tradeoffs!

ADT Presentation Algorithm• Present an ADT• Motivate with some applications• Repeat until it’s time to move on:

– develop a data structure and algorithms for the ADT– analyze its properties

• efficiency• correctness• limitations• ease of programming

• Contrast strengths and weaknesses

• Queue operations– create– destroy– enqueue– dequeue– is_empty

• Queue property: if x is enQed before y is enQed, then x will be deQed before y is deQedFIFO: First In First Out

First Example: Queue ADT

F E D C Benqueue dequeueG A

Applications of the Q

• Hold jobs for a printer• Store packets on network routers• Make waitlists fair• Breadth first search

Circular Array Q Data Structure

enqueue(Object x) {

Q[back] = x ;

back = (back + 1) % size }

b c d e f

Q0 size - 1

front back

dequeue() {

x = Q[front] ;

front = (front + 1) % size;

return x ; }

How test for empty list?

How to find K-th element in the queue?

What is complexity of these operations?

Limitations of this structure?

Linked List Q Data Structureb c d e f

front back

enqueue(Object x) {

back->next = new Node(x);

back = back->next; }

dequeue() {

saved = front->data;

temp = front;

front = front->next;

delete temp ;

return saved;}

What are tradeoffs?

• simplicity

• speed

• robustness

• memory usage

To Do

• Return your survey before leaving!• Sign up on the cse326 mailing list• Check out the web page• Log on to the PCs in course labs and access an

instructional UNIX server• Read Chapters 1 and 2 in the book