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Data Structures using C

This is the collection of Sikkim Manipal University (SMU) question and answers for Data Structures using C. It will help to prepare your examination. All question paper are classified as per semester, subject code and question type of Part A, Part B and Part C with multiple choice options as same as actual examination. SMU question papers includes year 2022, 2021, 2020 Sem I, II, III, IV, V, VI examinations of all subjects.

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Course Name        MCA (Master of Computer Application)

Subject Code       MC0068 (Data Structures using C)

Get Questions        PART - A    PART - B    PART - C

Data Structures using C Syllabus.

Part 1: Arrays, Pointers and Structures
Introduction; Definition and concept of an Array: Array Used in „C‟ Language, Single – Dimensional Arrays (One Dimensional Array), Two Dimensional Arrays. [Matrix]; Pointers; Declaring a pointer variable,: Pointer Operators; Pointers and Arrays; Pointers used in function; Pointers used in an Array; Structures: Declaration of structure, Initialization of structure, Processing of Structure, Structure used with an Array.

Part 2 Overview of Data Structures
Introduction: What is a Data Structure?, Definition of data structure, The Abstract Level, The Application Level, Implementation Level; Data Types and Structured Data Type: Common Structures, Abstract Data Types, Properties of Abstract Data Types, Generic Abstract Data Types, Programming with Abstract Data Types; Pre and Post Conditions: Preconditions, Post conditions, Checking Pre & Post Conditions, Implementation Checks Preconditions; Linear Data Structure: The Array Data Structure, Using an Array and Lists as a Data Structure, Elementary Data Structures; What the application needs ?;
Implementation methods; Non Linear Data Structures: Trees, Binary Tree, Hash Tables.

Part 3: Overview of Stack
Introduction; Operations of Stack;Insert / Push operation; Delete/pop operation; Display; Stack implementation using arrays; Applications of stack; Stacks using structures; Sample C programs to represents the Stack Implementation.

Part 4: Overview of Queues
Introduction; Queues and its Operations; Different types of queues: Ordinary queue, Disadvantage of ordinary queue, Double ended queue (Deque), Circular queue; Sample C programs to represents the Queue Implementation.

Part 5: Linked Lists
Introduction; Linear list; Linked list: Typical basic linked-list operations, Singly-Linked Lists; Circular singly linked list: Insert a node at the front end, Insert a node at the rear end, Delete a node from the front end, Delete a node from the rear end; Doubly linked lists: Insert a node at the front end, Insert a node at the rear end, Delete a node from the front end.

Part 6 : Trees
Introduction; Overview of Tree Concept; Binary tree: Strictly binary tree, Complete binary tree, Almost complete binary tree, Storage representation of a binary tree; Various operations on binary trees using linked representation: Insertion Operation, Traversals;
Binary search tree (BST): Insertion Operation, Searching, Other operations, To find maximum value in a tree BST, To find minimum value in a BST, Height of tree, Count nodes in a tree, Count leaves in a tree, Delete a node from the tree.

Part 7: Graphs
Introduction; Overview of Graphs; Adjacency lists & Adjacency Matrix: Adjacency lists, Adjacency Matrix; Depth – First Traversal; Breadth – First Traversal; Spanning Trees.

Part 8: Searching Methods
Introduction; Basics Searching Techniques; Algorithmic Notation: Sequential Search [Linear search], Binary Search; Illustration of C programmes.

Part 9: Sorting Methods
Introduction; Overview of Sorting Methods; How do you sort?; Evaluating a Sorting Algorithms: Stability on Sorting algorithm; Internal Sorting: Insertion Sort, Bubble Sort, Selection Sort, Shell Sort, Quick Sort, Tree Sort; External Sorts: Merge Sort, 2-Way Merge Sort.

Part 10: Advanced Topics in Trees and Their Applications
Introduction; Analyzing the BST Search Algorithm; Inserting Nodes into a BST; The Order of Insertion Determines the BST's Topology; Deleting Nodes from a BST; Traversing the Nodes of a BST: Preorder Traversal, Inorder Traversal, Postorder Traversal; The Cost of Recursion; Binary Search Trees in the Real-World; Big-O Notation: Application of Big-O notation to algorithm analysis; Big- and Big-:Properties of the sets O(f(n)) and (f(n)), Other useful mathematical formulae; Height Balanced Trees: AVL Trees, Red-Black Trees, Lemma, Insertion into a red-black tree, Deletions from a Red-Black tree; The A-A tree; AVL Trees: Definition, Worst case height of an AVL tree with n Nodes; The Binary Heap: Definition, Insertions into a Binary Heap, Deletions from a Binary Heap, Analysis of Insertion Algorithm, Build Heap -- building a tree from a collection of forests.

Part 11: Minimum Spanning Trees and Algorithms
Introduction; Spanning Trees: Minimum spanning trees, Why minimum spanning trees; How to find minimum Spanning Tree?: Lemma; Kruskal's Algorithm; Prim's algorithm; Finding Shortest Paths using BFS; Relaxation; Dijkstra Algorithm; Bellman-Ford Algorithm; Single-source shortest paths in Directed Acyclic Graph (DAG); Floyd Warshall and Variants:Transitive Hull, MiniMax Distance, MaxiMin Distance, Safest Path; Other Graphs: Graph Transpose Problem, Euler Cycle, Euler Path, Topological Sort Problem, Strongly Connected Components problem.

Part 12: Graphs and their Applications – I
Introduction to Graphs; Representation; Examples of Graph Problems: Telecommunication, Sample Problem: Riding The Fences, Knight moves, Overfencing; Terminology; Directed Graph; Paths; Graph Representation: Edge List, Adjacency Matrix, Adjacency List, Implicit Representation; Connectedness; Sub graphs; Special Graphs: Rooted tree, Forest, Complete Graph, Bipartite Graph; Uninformed Search: Breadth-first search, Uniform-cost search, Depth-first search, Depth-limited search , Iterative deepening search, Bidirectional search.

Part 13: Graphs and their Applications – II
Introduction; Depth First Search (DFS) Algorithm: Sample Problem: n Queens [Traditional], Depth First Search (DFS) Implementation, Complexity; Breadth First Search (BFS): Sample Problem: Knight Cover [Traditional], Breadth First Search (BFS) Implementation, Complexity; Depth First with Iterative Deepening (DF-ID): Complexity; Comparison of DFS, BFS & DFS+ID; Sample Problems: Super-prime Rib, Betsy's Tour , Udder Travel , Desert Crossing, Addition Chains; Informed Search: Best First Search, A* Search; An Application of Graph; Amortized Analysis: Aggregate Analysis, The potential method, Properties of the Potential Function, The Dynamic Hash Table, A Dynamic Hash Table that both expands and contracts.

Part 14: Splay Trees (Self-adjusting Search Trees)
Introduction; Splay Trees; Access lemma; Balance Theorem; Strong Access Lemma;  Static Optimality Theorem ; Static Finger Theorem; Other Theorems : Working Set Theorem, Sequential Access Theorem, Dynamic Finger Theorem, Dynamic Optimality Conjecture, Insertion, Join, Deletion.

Part 15: File Structures
Introduction; Logical or Physical Organization and Data Independence; A language for describing file structures; Basic terminology; Sequential files; Inverted files; Index-sequential files; Multi-lists; Cellular multi-lists; Ring structures; Threaded lists; Trees; Scatter storage or hash addressing; Clustered files; B - Tree File Organization; B- Tree Index Files; Dynamic Hashing: How does it work?.

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