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Data Structures

This resource provides an introduction to data structures, including their definition, types, and operations. Learn how data structures can help organize and access data efficiently, and understand the importance of abstract data types.

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Data Structures

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  1. Data Structure is a way of collecting and organising data in such a way that we can perform operations on these data in an effective way. Data structure is formerly defined to be a triplet (D,F,A) Where, D -> set of data objects F ->is a set of functions A->Axioms(set of rules to implement functions) Example: integer data type D =(0,+-(1),+-(2)...) F=(+,-,*,/,%) A=set of binary arithmetic's rules to perform addition,subtraction,division,multiplication and module operations. Data Structures Visit for more Learning Resources

  2. Need for Data Structure • Data structures are important way of organizing data in a computer • It has a different way of storing and organizing data so that it can be used efficiently. • It helps us to understand relationship of one data element with other • It helps to store a data in logical order. • It stores a data that may grow and shrink dynamically over a time and allows efficient access.

  3. Abstract data type • Abstract data type is defined in term of its data items or its associated operations rather than by its implementation. • It is just mathematical model which specifies “logical properties” and “operations” of the data type. • It simply tells us “what “ has to be done.It doesn't tell “how” do do it. • Advantages: • Abstraction • Encapsulation • Generalization

  4. Classification of data structures

  5. PRIMITIVE DATASTRUCTURE • The primitive data structures are the basic data types that are available in most of the programming languages. • The primitive data structures are used to represent single values. • Example: • Integer, character, string, Boolean

  6. NON-PRIMITIVE DATASTRUCTURE • The data structure that are derived from primary data structure is known as non-Primitive data structure. • These data types are used to store group of values. • Example: • Arrays, Structure, Union, linked list, Stacks, Queue etc.

  7. LINEAR DATA STRUCTURES: • In linear data structure the elements are stored in sequential order. The linear data structures are • Array: Array is a collection of data of same data type stored in consecutive memory location and is referred by common name • Linked list: Linked list is a collection of data of same data type but the data items need not be stored in consecutive memory locations. • Stack: A stack is a Last-In-First-Out linear data structure in which insertion and deletion takes place at only one end called the top of the stack. • Queue: A Queue is a First in First-Out Linear data structure in which insertions takes place one end called the rear and the deletions takes place at one end called the Front.

  8. NON-LINEAR DATA STRUCTURE: Elements are stored based on the hierarchical relationship among the data. The following are some of the Non-Linear data structure Trees: • Trees are used to represent data that has some hierarchical relationship among the data elements. Graph: • Graph is used to represent data that has relationship between pair of elements not necessarily hierarchical in nature. For example electrical and communication networks, airline routes, flow chart, graphs for planning projects.

  9. Operation on data structure. • Insertion: Adding new element in the data structure • Deletion: It is removing data from data structure • Searching: It is finding location of a data in within a given data structure. • Sorting: It is arranging of data in some logical order. • Traversing: A data structure is accessing each data only once. • Merging: It is combining of two similar data structures. For more detail contact us

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