Data Structures

Data Structures is a subject which teaches us different ways of organizing data and storing in a computer so that it can be used efficiently. In data structure basically the algorithms are created which could be converted on formulated into any language thus handling vast data. Different kinds of data structures are required for different kinds of applications, and few of them are highly specialized to perform specific tasks. For example, compiler implementations usually use hash tables to look up identifiers, while B-trees are particularly well-suited for implementation of databases. Some of the various methodologies are discussed below: 

Searching :  When we store vast amount of data in computer we need some effective search criteria so that the individual record could be retrieved efficiently within seconds. Some of the search algorithms which can be used are as follows:

 a) Sequential Search

 b) Binary Search: this search is better if we have an array containing values either in ascending form or descending form.

Sorting :  In the earlier days, when magnetic tape storage was used before modern data-bases, Sorting was the most common operation performed by the computers. Updating a”Database” was generally done by sorting transactions and merging them with a master file. Even today Sorting is important for presentation of data extracted from the databases: most of the managers prefer getting the reports is some or the other sorted manner. Different sorting algorithms available are:

 a) Bubble Sort

 b) Selection Sort

 c) Insertion Sort

Pointers : A pointer is a variable that holds a memory address, usually the location of another variable. With the help of pointers we can do dynamic memory allocation. We need not to specify the length if an array beforehand. Some of the applications of pointers are:-    Single Linked Lists, Circular Linked Lists, Double Linked Lists etc.

 

 

 

 

 

 

 

 

 

 

Graph Theory : 

Graph data structure can be useful in representing various data for e.g. Each node could represent a city and edges connecting the nodes could represent roads. It can also be used to represent a computer network where nodes denote the workstations and edges represent the network connection. Graphs have so many applications in the computer science and mathematics that various algorithms have been written to perform the standard graph operations such as finding the shortest path between nodes of a graph and searching the graph. Representation of a graph: 

 

 

 

 

 

 

 

Run Time Calculations

Run time Calculation helps to determine the best case, average case, and the worst case memory usage or running time of a particular algorithm. This helps the algorithm designers to predict the behaviour of their algorithm and to determine which algorithm they must use.