Job Saarnee

# Top 99+ Most Important Question with Solution of Data Structure | All Study Material

## Top 99+ Most Important Question with Solution of Data Structure

In computer science, a data structure is a particular way of storing and organizing data in a computer’s memory so that it can be used efficiently. Data may organized in many different ways, the logical or mathematical model of a particular organization of data is called data structure.

### Syllabus brief

Unit 1: Introduction:

Â Basic Terminology: Elementary Data Organisation, 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). 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 Matrix and their representations. Linked List: Array Implementation and Pointer Implementation of SinglyÂ  Linked Lists , Doubly Linked List, Circularly Linked List, Operations on a Linked List. Insertion, Deletion, Traversal, Polynomial Representation and
Addition Subtraction and Multiplications of Single Variable and Two variables Polynomial.

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### Unit 2:

Stacks:Â Abstract Data Types, Primitive Stack Operations: Push and Pop, Array and Linked Implementation of Stack in C, Application of Stack: Prefix and Post fix Expressions , Evaluation of post fix expression, Iteration and Recursion- Principle of recursion, Tail recursion, removal of recursion, Problem solvingÂ  using iteration and recursion with examples such as binary search, Fibonacci numbers and Hanoi towers. Trade offsÂ between iteration and recursion.

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

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Unit 3:

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

Sorting: Insertion sort, selection, Bubble sort, Quick sort, Merge sort, Heap sort and Radix sort.

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Unit 4:

Graphs: Terminology used with Graphs, Data Structure for Graph Representations: Adjacency Matrix, Adjacency List, Adjacency. Graph Traversal: Depth first search and Breadth first search, Connected Component, Spanning trees, Minimum Cost spanning tree: Prims and Kruskal algorithm. Transitive Closure and Shortest Path algorithm: Warshal and Dijikstra Algorithm.

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Unit 5:

Trees: Basic terminology used with Tree, Binary tree representation: Array representation and pointed(Linked list) representation, Binary search tree, Strictly binary tree, Complete binary tree. An extended binary trees, Tree traversal algorithms: In order, Pre order and Post order, Constructing binary tree from given traversal, operation of insertion,
deletion, searching and Modification of data in Binary search, Threaded binary trees, Huffman coding using binary tree. Concept and basic operation for AVL tree, B.tree and Binary heaps.

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