1. E-mail: ravi93@gmail.edu
CS 315 Data Structures
B. Ravikumar
Office: 116 I Darwin Hall
Phone:
Course Web site:

2. Textbook for the course:
Data Structures and Algorithm Analysis in C++
by Mark Allen Weiss
Class time
Lecture:
T Th 10:45 to 12 noon, Darwin Hall 102
Lab:
F 9 to 11:50 AM, Darwin Hall # 25

3. Data Structures – informal definition
How to store data sets in memory so that the computation(s) can be solved easily, efficiently etc.
Some typical issues:
preprocessing vs. updating
trade-offs between operations
interaction between algorithm and data structure

4. Course Goals Learn to use fundamental data structures:
arrays, linked lists, stacks and queues
hash table
priority queue – binary heap and others
binary trees, binary search trees, AVL trees
quad-trees, skip-lists
Improve your skill in programming in c++
recursion, classes, algorithm implementation
design solutions using different data structures

5. Course Goals Analytical and experimental analysis
quantitative reasoning about the performance of algorithms (time, storage, network, bandwidth etc.)
comparing different data structures
Applications
image storage and manipulation
image and data compression
sorting and searching
spelling checking, backtracking
packet routing in a network
geometric problems 5

6. Goals for today’s lecture
Course outline
Course work
lab assignments
projects
tests, final exam
quiz and class participation (new)
If any time left, start discussing recursion.

7. Data Structures – key to software design
Data structures play a key role in every type of software.
Data structure deals with how to organize the data in the memory while solving a problem in order to reduce
overall running time of a program
response time (for queries)
memory requirements
Cost model for data access - array access, pointers

8. Abstract Data Structure (ADT), supported operations
Dictionary
search
insert primary operations
Delete
deleteMin
Range search
Successor secondary operations
Merge
Priority queue
Insert
Merge, split etc. Secondary operations
primary operations

9. Linear data structures
key properties of the (1-d) array:
a sequence of items are stored in consecutive memory locations.
array provides a constant time access to k-th element for any k.
(access the element by: Element[k].)

10. Linear data structures
inserting at the end is easy.
if the current size is s, then we can add x at the end using the single instruction:
Element[s++] = x;
deleting at the end is also easy.
inserting or deleting at any other position is expensive.
searching for a key is expensive (unless sorted).
Expensive means the number of operations ~ size of the array. 10

11. Images stored in 2-dim arrays
We will work on 2-d arrays by manipulating images:
Each pixel is represented by a blue value, a red value and a green value (any color is a combination of these colors).
(255, 255, 255) represents white,
(255, 0, ) represents red etc.
pic(i , j)-> Blue represents the blue component of the i-th row, j-th column pixel of pic and so on.
Some basic operations on images:
open, read, write
rotate, copy a sub-image
filter (remove blemishes)
extract features (identify where buildings are in an aerial photograph)