1. COP3530- Data Structures Introduction
Dr. Ron Eaglin

2. Objectives Understand and describe field of Data Structures
Explain why data structures are important in IT and Computer Science.
Understand pre-requisites to learning data structures.
Understand the outcomes of the data structures course.

3. What are Data Structures?
Data Structure: A particular way of organizing data in a computer so it can be used efficiently
Primitive – Bit, Integer, Float, String
Complex – Array, List, Tree, Hash, Graph

4. Abstract Data Types
An Abstract Data Type is defined by its behavior – not its implementation
Data Structures are concrete implementations of abstract data types.
We will define the Abstract Data Types by their Interface and discuss implementation strategies

5. Why Data Structures?
Everything stored in a computer is stored as a Data Structure
Memory
Hard Drive
Other
Goals of Data Structures
Storage Efficiency
Computational Efficiency
Retrieval Efficiency
Search Efficiency

6. Importance of Data Structures
Most of the biggie tech companies like Microsoft focus mainly on data structures. It appears as if data structures is the only thing that they expect from a graduate.
I ask interview questions about data structures because on my team the developers design, implement and manipulate complex data structures all day every day.
Anyone who's been a developer in the last 30 years should know basic data structures like single/double linked lists, binary trees or graphs.

7. But Why are they Important?
Building blocks of more complex systems
Used in development of algorithms and algorithmic efficiency
Fundamental to all computer systems

8. What do you need to know? Basic computer programming skills Will learn
Creating and calling functions
Accepting user input, generate output
Control structures (if/then, switch)
Loops and iteration (for/next, while)
Assignment and operations (+, -, *, /, ^, …)
Will learn
Objects
Pointers

9. Outcomes
1. Describe both complex and simple data structures. 2. Select the correct data structure and algorithm to solve specific problems. 3. Implement data structures and algorithms in computer code. 4. Analyze the performance of algorithms and data structures. 

10. Data Structures Arrays Lists (Queues and Stacks)
Trees (AVL, Binary Tree, other)
Hash Tables
Graphs

11. Algorithms
Searching
Sorting
Traversal
Applications

12. Efficiency Analyzing efficiency Scalability of algorithms
Notations of efficiciency

13. Objectives Understand and describe field of Data Structures
Explain why data structures are important in IT and Computer Science.
Understand pre-requisites to learning data structures.
Understand the outcomes of the data structures course.