Representation Techniques for Logical Spaces

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Stanley McDonald
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1 Representation Techniques for Logical Spaces Mr. Wasim Khan Women's Polytechnic College,Indore Mr. Dharmendra Gupta CDGI,Indore Abstract: Computer machine is executed through instruction and rules, every location available in a memory has their own map features through which data could be operated at that places. For proper functioning and applicability of system programs and sequence different data structure has been created, which provides easy and well defined execution and operation of data evaluated at different stages and by different operations. Here in the propose paper logical structure and features of data structures has been presented. DATA-STRUCTRE Definition: There are two basic ways of representing such linear structure[1] in memory. One is to have the linear relationship between the elements represented by means of sequential memory locations, and the other is to have the liner relationship between the elements represented by means of pointers of links. NON LINEAR DATA STRUCTURE: A data structure is said to be non linear if its elements containing a hierarchical relationship between elements. Significance of data structure: Data structure +Algorithms=programs Data structure are the building blocks of a program Data structure is a logical or mathematical model of a particular organization of a data. TYPES OF DATA STRUCTURE: Hence the selection of a particular data structure[2] that best suits the requirement is most important step in the program design Data structures are classified as either linear or non linear LINEAR DATA STRUCTARE: A data structure is said to be linear it its elements form a sequence, or a linear list Operations on data structure: (a) Traversal processing each element in the list. (b) Search Finding the location of the element with a given value or the record with given key. (c) Insertion adding a new element to the list. (d) Deletion removing an element from the list. (e) Sorting arranging the elements in some type of order.

2 (f) Merging (g) Updation combining two lists into a single list. store, modify and delete element in the list. Data structure Stack :- A stack also called last in first out (LIFO) system[3], is a linear list in which insertion and deletion can take place only one end, called top. This structure is similar in its operation to a stack of dishes on a spring system. Application of stack: 1array representation 2 function call 3 expression evaluation 4 quick sort 5 recursion Application areas: use for solving functions, String reversing Queue :- A queue also called first in first out (FIFO) system, is a linear list in which deletion can take place only at one end of the list, the front of the list and insertion can take place only at the other end called the list the rear of the list [4]. This structure is same way as a line of people waiting at a bus stop, railway reservation, light bill submission, etc. Application of Queue: Array definition:- Array is collection of homogeneous data elements. Linear Array is the simplest type of data structure. Linear Array means a list of a finite number [2,3] of similar data elements. Linear Array are called one Dimensional Array because each element in such an array in a collection of similar data elements where each elements is referenced by two subscripts. (Such arrays are called matrices in mathematics, and tables in business Applications.) Limitations of Array:- Array are data structure fixed size insertion & deletion involve re-shuffling of Array elements thus Array manipulation is time consuming & inefficient to overcome These drawbacks linked list are used. Application: Uses for storing static positioned data Link List:- A link list or one way list is a linear collection of data elements, called nodes, where linear order is given by means of pointers. That is each node is divided into two parts the first part contains the information of the elements and the second part called link field contains the address of the next node in the list. 1 Array representation 2 time sharing multi user operating system 3 job queue Application: uses in software flow designing and printer routines. Array:- Array are usually easy to traverse, search, and sort, they are frequently used to store relatively Permanent collection of data. If the size of the structure and the data in the structure are constantly changing, then the Array may not be useful we can use linked list as data structure. In show fig schematic diagram of a linked list with u nodes each node divided in to parts the left part contain am entire record of date items(name, Add, ) the right part contain Address of the next node, the pointer of the last node contains a special value called the null pointer Insertion into a linked list:

3 Let list be com linked last with successive nodes A and B [5] show in Fig. Suppose a node N is to be inserted into the list between node A and B. (2) A circular header list is a header list where the last nodes contain the address of header node. Two way list:- Deletion from a linked list: Let list be a linked [6] list with node N between node A and node B as below show Fig. Suppose node N is to be deleted from the linked list In one way list there is only one way that the list can be traversed. We can traverse the list in only one direction. A new list structure called two-way list which can be traversed in two directions. In the usual forward direction from the beginning of the list to the end of the list to the beginning. A two way list is a linear collection of data element, called modes where each node N is divided into three parts: 1) An information field INFO which contains the data of N 2) A pointer field FROW which contains the location of the next Node in the list. 3) A pointer field BACK which contains the location of the preceding node of in the list. Header linked list:- A header linked list is a linked list which always contains a special node called the header node at the beginning of the list. Header linked list is two types:- (1) A grounded header list is a header list where the last Node contains the null pointer. Application: use for dynamic accessing. Provides flexible accesses of memory locations, eliminates problems of fragmentation

4 Graph:- Is a non liner data structure in the graph hierarchy relationship between elements. A graph G consists of two things: 1) A set V of elements called nodes (vertices) 2) A set E of edges. Graph indicates G = (V, E) Where V = set of vertices (v1, v2, v3 vn) E = set of edges (e, e2, e3.en) Definition:- A graph G = (V, E) consists of a set of object v= (v1, v2, v3,.vn ) Whose element are called vertices (Nodes) and on another set E= (e, e2, e3.en) whose elements are called edges. Simple graph:- A graph that has neither self loops nor parallel edges is called a simple graph. Undirected graph:- A graph is undirected when all edges no assigned a direction. Directed graph:- A directed graph G also called a diagraph of graph is the same as multigraph except that each edges e in G is assigned a direction. Regular graph:- A graph G in which all vertices are of equal degree is called regular graph. Null graph:- A graph having no edges is called a null graph. Weighted graph:- A weighted graph is a graph in which all edges are assigned a weight (length). Shortest path:- Shortest path between any two given vertices of weighted graph is defined as a path of minimum weight. Graph search method:- Breadth first search (BFS):here all the attached nodes of the starting node is first traversed and the process is repeated in a same sequence as prior done to get complete traversing. Depth first search (DFS): Here the depth of a node is evaluated from starting to end and the same process is evaluated to get complete traversing result. Application: Uses for accessing and searching data from different locations of main memories. Tree: - A connected graph having no circuit is called a tree. A tree is a connected undirected graph with no simple circuit. Properties of tree:- 1. a graph is a tree if and if there is one and only one path between every pairs of Vertices. 2. A tree T with N vertices has N-1 edges. 3. Each tree is graph but not every graph is tree. Binary Tree:- A binary tree is defined as a tree in which there is exactly one vertex of degree two and each of the remaining vertexes is of degree one or three. Complete Binary tree:- A tree in which all the levels are completed at all respect. Traversing of Binary tree:- 1. Preorder- a) Process the root R b) Traverse the left c) Traverse the right

5 2. Inorder a) Traverse the left b) Process the root R c) Traverse the right [3] Sinha, R. & Zobel, J. (2004), Cacheconscious sorting of large sets of strings with dynamic tries, ACM Jour. of Exp. Algorithmics 9(1.5). [4] PLDS210/objects.html#objects [5] [6] ctures/lect1/lect1.html 3 Postorder a) Traverse the left b) Traverse the right sub tree of R in c) Process the root R Binary search tree:- Suppose T is a binary tree. Then T is a called binary search tree if each node N of T has the following Properties: The value at N is greater than every value in the left sub tree of N and is less than every value in the right sub tree of N. Tree: use for storing data in tree structure like Drives of a operating system. Conclusion: Here in the paper, different data structure is briefly discussed and presented to get their signature values and understand their logics for execution. A data structure are key components in design and implementation process,because memory mapping and their values are organized and only accessed through data values,by address and accessing mechanisms. References: [1] C. C. Charlton and P. H. Leng. Editors: two for the price of one. Software Practice and Experience, 11:195{202, [2] Computer Science 15 Homepage, Brown University. /cs015.

Data Structure. IBPS SO (IT- Officer) Exam 2017

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