IT 265 Data Structures for Problem Solving
Data Structures and Methods

9/20/2014
Phase 5

Contents Executive Summary 4 Phase 1 4 Phase 2 4 Phase 3 4 Phase 4 4 Phase 5 5 Section 1: Lists, Stacks, and Queues 6 Stacks 6 Queues 10 Section 2: Hashing, Heaps and Trees 14 Section 3: Sorting Algorithms 20 Insertion sort 20 Bubble Sort 20 Selection sort 21 Section 4: Searching 22 Array 22 Linked Lists 23 Section 5: Recursion 30 References 33

Executive Summary
Phase 1 A list is a collection of items in which the items have a position (Weiss, 2010). A linked list allows data to be input or removed easily because each of the data items in the list is connected to its neighbor by a pointer that can be quickly and easily modified to accommodate new or removed items (CTU M.U.S.E. 2014). The Phase 1 portion of this document will be demonstrating the implementation of Stacks and Queues.
Phase 2 Hash tables can be viewed as an array of lists and are used to speed up a search for data by creating a situation that does not require the search to start at the beginning and go through every item. The identifying value is the key and the associated record is the data, thus a hash table is a collection of (key, value) pairs.
Phase 3
In order to efficiently use a database, the data must be stored in some sort of order. There are a number of different sorting algorithms; a programmer would choose which one to use depending on the amount and type of data being sorted. Insertion sort, Bubble sort, and Selection sort are described with examples.
Phase 4 A binary tree, is a node-based data structure where each node has a comparable key (and an associated value) and satisfies the restriction that the key in any node is larger than the keys in all nodes in that node's left subtree and smaller than the keys in all nodes in