CS261

Data Structures

Fall 2009

Professor Timothy Budd

Why data structures

• By this point, you have learned the mechanics of coding - variables, loops, etc

• This course will help you take the next step in becoming a programming, learning higher level skills, such as abstraction, modularization, correctness, efficiency.

Administrivia

• Go over administrivia -

• Two midterms, one final

• Several programming assignments, several homeworks

• Recitations used for learning programming skills, course will deal more with concepts

More administrivia

• I’m found in KEC 3049

• OH: MWF 1:30 - 3:00 for now

• Two TA’s: they will each hold office hours as well in KEC lobby (see web page)

Textbook

• Textbook is on-line, also with links to many articles (wikipedia and so on) for further information. You should print it out

• Textbook begins with material you should already have seen - read chapters 1 to 5 immediately.

Active Learning

• This course uses a technique termed Active Learning

• We do worksheets most every day.

• Worksheets can be done in groups, helping each other

• They are gathered and recorded, but only lightly graded

Why Data Structures?

• The study of data structures is considered the cornerstone and starting point for systematic examination of computer science

• Notice I said computer science, not just programming

Ubiquitous

• Certain collection classes are found in almost every nontrivial program

• Knowing these keeps you from having to reinvent the wheel

Vocabulary

• The common data structures have well known names

• Helps provide a vocabulary that is shared by all computer professionals

Abstraction

• Data structures are one of the easiest ideas to visualize abstractly

• Abstraction is the key idea used by computer professionals to control complexity.

Information Hiding and Large Projects

• An important part of abstraction is information hiding - what details do you NOT need to know?

• Key to modern large software projects

• What does programmer A NOT need to know to use the work of programmer B?

Tools and Techniques

• The analysis of data structures provides a good vehicle to learn a variety of mathematical and other analytical techniques

• Recursion, big-Oh, counting arguments, proof of correctness

Design Pattern format

• A very useful and recent tool

• Design patterns provide a way to document proven solutions to common problems

• More importantly, provide a vocabulary

• Grew out of OO world, starting to become common everywhere else

Features of Design pattern

• Problem: Short statement of problem

• Solution: Abstract characteristics

• Forces: Reasons for using pattern

• Counter-Forces: Reasons for NOT using pattern

• Example - Façade (change in interface, not in implementation)

Questions??

• If not, then we do our first worksheet

What is O( )

int countOccurrences (double data [ ], int n, double testValue)

{ int i; int count = 0; for (i = 0; i < n; i++) { if (data[i] == testValue) count++; } return count;}

Btw, arrays and pointers are the same. More common:

int countOccurrences (double * data, int n, double testValue)

{ int i; int count = 0; for (i = 0; i < n; i++) { if (data[i] == testValue) count++; } return count;}

A loop that is not an array index. What is O( )?

int isPrime (int n) {

int i;

for (i = 2; i * i <= n; i++) {

if (0 == n % i) return 0;

}

return 1; /* 1 is true */

}

Calling a function inside another O( )?

void printPrimes (int n) {

int i;

for (i = 2; i < n; i++) {

if (isPrime(i))

printf(“Value %d is prime”, i); }

}

What is printf

• And older way to do printing (before streams).

• Don’t remember how to use it? Look in the handy pocket reference.

Nexted loop (Note, this is pseudo-code, not C)

void matMult (int [][] a, int [][] b, int [][] c) { int n = n; // assume all same size int i, j, k; for (int i = 0; i < n; i++) for (int j = 0; j < n; j++) { c[i][j] = 0; for (k = 0; k < n; k++) c[i][j] += a[i][k] * b[k][j]; }}

A more subtle loop

void selectionSort (double * storage, int n) { int p, i, indexLargest; for (p = n – 1; p > 0; p--) { indexLargest = 0; for (i = 1; i <= p; i++) { if (storage[i] > storage[indexLargest]) indexLargest = i; } if (indexlargest != position) swap(storage, indexLargest, position); } }}

What is the sum?

• What is the sum of

1 + 2 + 3 + … + (n - 1) ?

An operator you might have never seen

for (i = n; i > 0; i = i >> 1) …

What is the >> operator? Right shift. Imagine that n starts at 100. What are the values that i will go through?