Data Structures and Algorithms
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    Data

    Data is a collection of numbers, alphabets, and symbols combined to represent information. A computer accepts the raw data as input and produces improved data as output after processing it.

    • Atomic data:

      Atomic data are the non-decomposable entity. For example, an integer value 111 or a character value “J” cannot be further divided.

    • Composite data:

      It is a composition of several atomic data and it can be further divided into atomic data. For example, the Date of birth (05/07/1995) can be separated into three atomic values. The first one gives the day of the month, the second one gives the month and the last is the year.

    Data Types

    A data type is a set of values and a set of operations defined on those values.

    Example: int age; [age can hold, integer type of data]

    Every programming language has a method for declaring a set of variables of a particular type.

     

    Abstract Data Types (ADT)

    ADT in programming language means a user-defined extension to the native data types available in the programming language.

    It consists of:

    • A set of values
    • A set of operations

    In ADT, the implementation details remain hidden from the user. ADT is widely referred to as object-based programming.

     

    Data Structure

    The data structure indicates the following things:

    • Organization of data
    • Associativity among data elements
    • Accessing methods
    • Operations on data
    • Processing alternatives for data

    The data structure deals with the representation of data considering not only the elements stored but also their relationship with each other.

    A well-suited data structure must be chosen so that the relationship between data elements can be expressed. A data structure is an instance of an ADT.

     

    Types of Data Structures

    • Primitive data structures:

      The primitive data structures are primitive data types. The int, char, float, double, and pointer are the primitive data structures that can hold a single value.

    • Non-primitive data structures:

      The non-primitive data structure is divided into two types:

      • Linear:

        Elements are arranged sequentially is known as Linear data structure. A one-to-one relationship can be handled by the linear data structure. Arrays, Linked lists, Stacks, and Queues are examples of Linear data structures.

      • Non-linear:

        All one-to-many, many-to-one, and many-to-many relationships are handled by Non-linear data structures. Trees, graphs, and tables are examples of Non-linear data structures.

     

    Operations on Data Structures

    The common operations performed on data structures are:

    • Traversing:

      A data structure is accessing each element and accessing only once.

    • Searching:

      Finding the location of elements within the given data structure.

    • Insertion:

      Adding the new element in a data structure.

    • Update:

      Update the element, i.e. replace the element with another element.

    • Deletion:

      Removing the element from the data structure.

    • Sorting:

      Arranging the elements of a data structure either in an ascending or descending order.