Contents: CS2

From

Introduction (needs to be written)

Contents 1 Data Structures and Abstract Data Types 2 Introduction to Computability and Complexity 3 Algorithms 4 Preliminaries of Data Organization 5 ADTs and Data Structures 5.1 Linear Structures 5.2 Trees 5.3 Graphs 5.4 Un-ordered Collections

Data Structures and Abstract Data Types

A data structure is a means of organizing data in a computer’s memory to try to optimize either the memory needed or the time to access the data. This brings up the classic trade-off in Computer Science: the trade-off between Time and Space. In most situations today, it seems that we are primarily interested in minimizing the Time aspect. But, given smaller and smaller devices that increasingly do more (think of the evolution of the cell phone), minimizing the Space aspect can be important also.

There is sometimes a difference made between a data structure and an abstract data type (ADT). An ADT describes the public interface of a data structure: the type of data and the valid operations on the data. An ADT, however, does not consider an implementation, and this is the essential difference.

Introduction to Computability and Complexity

• Overview of computability and complexity
  
• Asymptotic Measures
  
• Emperical Measures
  

Algorithms

• Overview of Algorithms and Psuedocode
  
• Seaching
  
• Sorting
  

Preliminaries of Data Organization

• Memory Allocation
  
• Primitive Structures
  
• Concept of an Element (Node)
  
• Abstract Data Types
  

ADTs and Data Structures

Linear Structures

• Overview of Linear Abstract Data Types
• Stacks
  
• Queues
  
• Lists
  

Trees

• Binary Trees
  
• Binary Search Trees
  
• AVL Trees
  
• Red-Black Trees
  
• Splay Trees
  
• Heaps
  
• B-Trees
  

Graphs

• Overview of Graphs ADTs
  
• Graph representation methods
  
• Common Graph Algorithms
  

Un-ordered Collections

• Sets
  
• Maps and Dictionaries
  
• Hash Tables