Previous Year Data Structure Questions asked in AKTU

Table of Contents

Unitwise List of Questions
Visit Data Structure Units Here
Syllabus Of Data Structure
Data Structure Cheatsheet

In this page you will find unit wise collection of previous year questions asked in Dr. A P J Abdul Kalam technical university.

And this will going to help in the preparation of semester exam and secure good score. I am not giving you a guarantee of 100% score but after preparation from here you will be able to secure at least 70% marks easily.

We have covered questions and answers from all units like

Unitwise List of Questions

Below I have shared a brief note of data structure to revise the data structure concepts in one go. Also I have shared AKTU syllabus of data structure for you.

I hope this will be very helpful for you to secure good marks in semester exam and protect you from the backlogs.

Visit Data Structure Units Here

Data Structure Complete Overview

Unit -1 : Introduction to DS

Unit – 2 : Array and Linked List

Unit -3 : Searching and Sorting

Unit -4 : Graph and Tree

Unit -5 : Stacks and Queue

Syllabus Of Data Structure

Unit/Module 1 : Introduction to Data Structure

Basic Terminology, Elementary Data Organization, Built in Data Types in C.
Algorithm, Efficiency of an Algorithm, Time and Space Complexity,

Asymptotic notations: Big Oh, Big Theta and Big Omega, Time-Space trade-off. Abstract Data Types (ADT)

Unit/Module 2 : Arrays and Linked List

Array: Definition, Single and Multidimensional Arrays,

Representation of Arrays: Row Major Order, and Column Major Order, Derivation of Index Formulae for 1-D,2-D,3-D and n-D Array, Application of arrays, Sparse Matrices and their representations.

Linked lists: Array Implementation and Pointer Implementation of Singly Linked Lists, Doubly Linked List, Circularly Linked List, Operations on a Linked List. Insertion, Deletion, Traversal, Polynomial Representation and Addition Subtraction & Multiplications of Single variable & Two variables Polynomial.

Unit/Module 3 : Searching And Sorting

Searching: Concept of Searching, Sequential search, Index Sequential Search, Binary Search.
Concept of Hashing & Collision resolution Techniques used in Hashing.

Sorting: Insertion Sort, Selection, Bubble Sort, Quick Sort, Merge Sort, Heap Sort and Radix Sort.

Unit/Module 4: Graphs and Trees

Graphs: Terminology used with Graph, Data Structure for Graph Representations: Adjacency Matrices, Adjacency List, Adjacency. Graph Traversal: Depth First Search and Breadth First
Search, Connected Component, Spanning Trees,

Minimum Cost Spanning Trees: Prim’s and Kruskal algorithm. Transitive Closure and Shortest Path algorithm: Warshal Algorithm and Dijikstra Algorithm.

Unit/Module 5 : Stacks and Queue

Stacks: Abstract Data Type, Primitive Stack operations: Push & Pop, Array and Linked Implementation of Stack in C,

Application of stack: Prefix and Postfix Expressions, Evaluation of postfix expression, Iteration and Recursion- Principles of recursion, Tail recursion, Removal of recursion Problem solving using iteration and recursion with examples such as binary search, Fibonacci numbers, and Hanoi towers. Tradeoffs between iteration and recursion.

Queues: Operations on Queue: Create, Add, Delete, Full and Empty, Circular queues, Array and linked implementation of queues in C, Dequeue and Priority Queue.

Now We have seen the definition of data structure. Let’s move on next topics 🙂

Data Structure Cheatsheet

Data type:- It describes which type of value can be stored by a variable. suppose if a variable has int data type it means that that variable can only hold the integer values.

It is of two types:-

1). Primitive data type

2). non-primitive data type

For more detail, you may refer below URL.

Now let’s move on the next topics “Algorithm”

An algorithm is a finite steps solution of a problem in a human-readable format. Every algorithm has some space and time complexity which denotes how much an algorithm is efficient.

Five asymptotic notations are Big-Oh notation, Omega notation, Theta notation, little O and little omega to measure the efficiency.

I hope you got a little bit idea of an Algorithm.

Let’s jump on Unit 2 Array and Linked List.

An array is a collection of similar type of elements which is stored in contiguous memory locations. A here similar type of element means each element have the same data type.

We can denote it as

int arr[] ;

Means arr is an array in which we can only assign integer type of elements.

An array is Basically of two types:

1). One dimensional or single dimensional array

2). Multidimensional Array

Representation of an Array:

We can represent array in two ways

1). Row Major Order

LOC (A [i, j]) = base_address + W [M (i) + j] Here,

base_address = address of the first element in the array.

W = Word size means a number of bytes occupied by each element of an Array.

N = Number of rows in the array.

M = Number of columns in the array.

2). Column Major Order

LOC (A [i, j]) = base_address + W [N (j) + (i)]

Here,

base_address = address of the first element in the array.

W = Word size means a number of bytes occupied by each element of an Array.

N = Number of rows in the array.

M = Number of columns in the array.

Linked List

Linked List is a linear and dynamic data structure. It stores elements at non-contiguous memory locations.

Linked List is of different types:

1). Singly Linked List

2). Doubly Linked List

3). Circular Linked List

We have seen some basics of Array and Linked List ;

Let’s jump on Unit 3 Searching and Sorting

Searching: It is an operation to find a particular element in a list or in array.

Types of searching

Linear Search
Binary Search
Hash Search
Binary Tree Search

Sorting: It is also an operation on elements of an array or linked list to arrange it either in ascending or descending order.

Types Of Sorting

Insertion Sort
Bubble Sort
Selection Sort
Quick Sort
Merge Sort
Heap Sort
Radix Sort

I think we can wrap up here. For more detail you can follow given link

Unit 4 is Graph and Tree

Graph : A Graph is a non-linear and abstract data structure which consist of nodes and edges. A single edge connects two Vertices in graph.

We Can Traverse the node of graph by using two algorithms

BFS ( Breadth First Search)
DFS (Depth First Search)

Tree : Tree is also a non-linear data structure that consists node which is connected using edge. But in tree all node are arrange as root node, parent node and child node in hierarchical manner.

Minimum cost spanning tree : It is a subset of tree and graph in which sum of the weight to traverse each node is minimum. A tree has many number of spanning tree but not all are minimum spanning tree.

There are some algorithm to identify minimum spanning tree.

Prim’s Algorithm
Kruskal’s Algorithm

The Last 5th unit is Stack and Queue

Stack: Stack is an abstract data type which follow the LIFO ( Last In First Out) Principle.

We can perform only two operation on stack

1). PUSH

2). POP

Stacks are used to evaluate post-fix expression.

Recursion : Recursion is a process in which one function calls it self again and again for a finite time to solve a given problem.

Queue: Queue is also a abstract data type which follow FIFO(First In First Out Principle).

2 Operations can be performed on Queue

1). enqueue

2). dequeue

Enqueue means put elements in queue and dequeue means remove it from queue.

For more details and semester question answers please follow the given link.

What did you think?