It 265 Data Structures Phase 5 Essay

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IT 265 Data Structures for Problem Solving
Data Structures and Methods

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
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The left sub-tree contains only nodes with keys less than the parent node; the right sub-tree contains only nodes with keys greater than the parent node. BSTs are also dynamic data structures, and the size of a BST is only limited by the amount of free memory in the operating system. The main advantage of binary search trees is that it remains ordered, which provides quicker search times than many other data structures.
Phase 5 Recursion is a function that calls itself. In the function definition there is a call to that very same function. This sections gives an explanation with an example of recursion.

Section 1: Lists, Stacks, and Queues
A Linked List is a type of data structure that can be arranged in memory in a variety of ways. The list is a collection of nodes that contain data and a next link to the next node. It is easy to add and remove data from a linked list because the pointer can be easily modified to accommodate any changes. (CTU MUSE, 2010)

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Node 1 Node 2 Node 3 Node 4 null

In the case when the data files are large these lists aren’t very efficient because the data must be searched sequentially.
A Stack is an example of a Linked List. Data items are “pushed” on to the top of the stack and items removed, or “ popped” off the list from the top in a
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