Introduction to Data Structures
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Introduction to Data Structures

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Questions and Answers

What is data?

Quantities, characters, or symbols on which operations are performed by a computer.

When does data become information?

When data is arranged in a systematic way, it gets a structure and becomes meaningful.

What is a data structure?

The systematic way to organize data so that it can be used efficiently.

Which of the following is an example of a primitive data structure?

<p>Integer</p> Signup and view all the answers

Which one of the following is an example of a dynamic data structure?

<p>Linked List</p> Signup and view all the answers

What is the main characteristic of non-linear data structures?

<p>Data elements are not arranged sequentially or linearly.</p> Signup and view all the answers

Match the following data structures with their classification.

<p>Array = Primitive Data Structure Linked List = Dynamic Data Structure Tree = Non-linear Data Structure Stack = Linear Data Structure</p> Signup and view all the answers

What operations can be performed on data structures?

<p>Traversal, Search, Insertion, Deletion, Sort, Merge.</p> Signup and view all the answers

A collection of data with a fixed size is called a ______ data structure.

<p>Static</p> Signup and view all the answers

To perform frequent searches, a ______ search tree is preferred.

<p>Binary</p> Signup and view all the answers

Study Notes

What is Data

  • Data can be quantities, characters, or symbols that are processed by a computer.
  • Data is stored in external memory.
  • Data can be transmitted in the form of electrical signals.

When Data Becomes Information

  • Data becomes information when it is arranged in a systematic way and becomes meaningful.
  • Meaningful data is called information.

Data Structure Defined

  • A data structure is a systematic way of organizing data for efficient use.
  • It is a group of data elements stored together under one name.
  • Example: arrays.
  • It is also referred to as "Abstract Data Type (ADT)."
  • ADT is a type (or class) for objects whose behavior is defined by a set of values and a set of operations.

Classifications of Data Structures

  • Data structures can be classified into two categories:
    • Primitive data structures: Storing the value of only one data type.
    • Non-primitive data structures: Storing the value of more than one data type.

Physical Data Structures

  • Actual implementations of data structures in memory.
  • Examples:
    • Array - fixed-size collection of elements of same data type, accessed with index
    • Linked list - dynamic collection of nodes, each containing data and reference to next node, offers efficient insertions and deletions.

Logical Data Structures

  • Logical implementation of data over physical memory.
  • Examples:
    • Stack - LIFO (Last-In, First-Out) structure, operations: push, pop, peek
    • Queue - FIFO (First-In, First-Out) structure, operations: enqueue, dequeue, peek
    • Tree - hierarchical data structure, often used for searching and sorting, relationship between nodes: parent-child, ancestors-descendants

Static vs. Dynamic Data Structures

  • Static data structures: Have a fixed size and can store a limited amount of data. Example: array.
  • Dynamic data structures: Can modify their size during operations and store a variable amount of data. Example: linked list.

Linear Data Structures

  • Data elements are arranged sequentially or linearly.
  • Each element is attached to its previous element and the next adjacent element.
  • Single level is involved.
  • Easy to implement because computer memory is arranged in a linear way.
  • Examples: array, stack, queue, linked list.

Non-Linear Data Structures

  • Data elements are not arranged sequentially or linearly.
  • Hierarchical multiple levels are involved.
  • Complex to implement.
  • Utilize computer memory efficiently compared to linear data structures.
  • Examples: trees and graphs.

Data Structure Operations

  • Different operations can be performed for data manipulation in every data structure:
    • Traversal: Accessing each record (or node) exactly once.
    • Search: Finding the location of the desired node with a given key value or conditions.
    • Insertion: Adding a new node (or record,) to the structure.
    • Deletion: Removing a node (or record) from the structure.
    • Sort: Arranging all data items in a particular order.
    • Merge: Combining the data items of two different sorted lists into a single sorted list.

How to Choose a Data Structure

  • The choice of an appropriate data structure depends on the following factors:
    • Based on the operations to be performed:
      • For insertion and deletion - linked list
      • For indexing - array
    • Based on the time complexity of the operations:
      • For frequent searches - binary search tree
    • Based on the space complexity of the operations:
      • To store a lot of data - array
    • Based on the amount of memory to be used:
      • To store a lot of data using less memory - linked list

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Introduction.pdf

Description

This quiz covers the fundamental concepts of data and data structures. Learn how data transforms into information, the definition of data structures, and their classifications. Test your understanding of both primitive and non-primitive data structures.

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