CIS 269 - Data Structures

1. Implement and manipulate defined composite data types and structures, classes.
2. Design, develop, modularize, test, validate, and document program solutions to business and scientific information processing problems using top-down design, data structure, and file handling tools.
3. Describe and code various sort and search algorithms. 
4. Execute performance analysis and determine relative timing complexity (Bit Oh Notation) relating to the sort and search algorithms, discuss advantages and disadvantages of the above. 
5. Describe and code various complex algorithms with memory management components, classes, and pointers.
6. Code a breadth first and depth first algorithm.
7. Use, create, and extend templates.
8. Read/write to multiple file handles and streams in a program.
9. Use a source control system such as GitHub to manage source code.

1. Software Engineering Concepts and Theory
2. Review of C++    
   1. Classes, types and declarations
   2. Operators
   3. Control flow statements
   4. Pointers – single and multi-level indirection
   5. Functions – including function pointers
   6. Inheritance, overloading
   7. Abstract classes
   8. Streams and file handles.   
3. Stacks and Queues    
   1. Add an element to a stack or queue
   2. Delete an element from a stack or queue
   3. Use a circular array to simulate a stack or queue
   4. Simulate a stack or queue using a linked list
   5. Stack overflow   
4. Recursion    
   1. Divide and conquer
   2. Backtracking
   3. Removal of
5. Dynamic Abstract Data Structures    
   1. Linked lists– singly and doubly listed
   2. Trees        
      1. Binary
      2. Binary search trees
      3. AVL trees (balanced)   
6. Sort and Search Algorithms    
   1. Quick sort
   2. Merge sort
   3. Heap sort
   4. Radix sort
   5. Hash tables
   6. Introduction to Big O notation and analysis
7. Memory Management    
   1. Destructor calling order
   2. Memory leaks
   3. Garbage collection
8. Hash Tables    
   1. Hash functions
   2. Types of hash tables
   3. Addressing schemes
   4. Analysis of complexity   
9. Templates    
   1. Creating a template
   2. Extending an existing template   
10. Graphs, Trees and Networks    
    1. Adjacency matrix
    2. Depth-first and breadth-first search
    3. Shortest path algorithm