The course is divided into 5 sections covering fundamental data structure concepts, arrays, stacks and queues, linked lists, trees, graphs, and searching and sorting algorithms. Students will be assessed through 5 tests and 4 programming assignments. The course aims to provide students with hands-on experience implementing various data structures and algorithms in C/C++. Key topics include arrays, linked lists, stacks, queues, trees, graphs, sorting, searching, complexity analysis, and various operations on each data structure.
17. Java data structures trees representation and traversalIntro C# Book
In this chapter we will discuss tree data structures, like trees and graphs. The abilities of these data structures are really important for the modern programming. Each of this data structures is used for building a model of real life problems, which are efficiently solved using this model.
17. Java data structures trees representation and traversalIntro C# Book
In this chapter we will discuss tree data structures, like trees and graphs. The abilities of these data structures are really important for the modern programming. Each of this data structures is used for building a model of real life problems, which are efficiently solved using this model.
Class lecture of Data Structure and Algorithms and Python.
Stack, Queue, Tree, Python, Python Code, Computer Science, Data, Data Analysis, Machine Learning, Artificial Intellegence, Deep Learning, Programming, Information Technology, Psuedocide, Tree, pseudocode, Binary Tree, Binary Search Tree, implementation, Binary search, linear search, Binary search operation, real-life example of binary search, linear search operation, real-life example of linear search, example bubble sort, sorting, insertion sort example, stack implementation, queue implementation, binary tree implementation, priority queue, binary heap, binary heap implementation, object-oriented programming, def, in BST, Binary search tree, Red-Black tree, Splay Tree, Problem-solving using Binary tree, problem-solving using BST, inorder, preorder, postorder
In this chapter we will discuss tree data structures, like trees and graphs. The abilities of these data structures are really important for the modern programming. Each of this data structures is used for building a model of real life problems, which are efficiently solved using this model. We will explain what tree data structures are and will review their main advantages and disadvantages. We will present example implementations and problems showing their practical usage. We will focus on binary trees, binary search trees and self-balancing binary search tree. We will explain what graph is, the types of graphs, how to represent a graph in the memory (graph implementation) and where graphs are used in our life and in the computer technologies. We will see where in .NET Framework self-balancing binary search trees are implemented and how to use them.
Class lecture of Data Structure and Algorithms and Python.
Stack, Queue, Tree, Python, Python Code, Computer Science, Data, Data Analysis, Machine Learning, Artificial Intellegence, Deep Learning, Programming, Information Technology, Psuedocide, Tree, pseudocode, Binary Tree, Binary Search Tree, implementation, Binary search, linear search, Binary search operation, real-life example of binary search, linear search operation, real-life example of linear search, example bubble sort, sorting, insertion sort example, stack implementation, queue implementation, binary tree implementation, priority queue, binary heap, binary heap implementation, object-oriented programming, def, in BST, Binary search tree, Red-Black tree, Splay Tree, Problem-solving using Binary tree, problem-solving using BST, inorder, preorder, postorder
In this chapter we will discuss tree data structures, like trees and graphs. The abilities of these data structures are really important for the modern programming. Each of this data structures is used for building a model of real life problems, which are efficiently solved using this model. We will explain what tree data structures are and will review their main advantages and disadvantages. We will present example implementations and problems showing their practical usage. We will focus on binary trees, binary search trees and self-balancing binary search tree. We will explain what graph is, the types of graphs, how to represent a graph in the memory (graph implementation) and where graphs are used in our life and in the computer technologies. We will see where in .NET Framework self-balancing binary search trees are implemented and how to use them.
Data Structure is a way of collecting and organising data in such a way that we can perform operations on these data in an effective way. Data Structures is about rendering data elements in terms of some relationship, for better organization and storage. For example, we have data player's name "Virat" and age 26. Here "Virat" is of String data type and 26 is of integer data type.
We can organize this data as a record like Player record. Now we can collect and store player's records in a file or database as a data structure. For example: "Dhoni" 30, "Gambhir" 31, "Sehwag" 33
In simple language, Data Structures are structures programmed to store ordered data, so that various operations can be performed on it easily.
Data Structures Multiple Choice Questions (MCQs) are designed to test an individual's understanding of the fundamental concepts, algorithms, and implementations related to organizing and storing data efficiently. These questions cover a wide range of topics within the field of data structures. Below is a description outlining the common themes addressed by MCQs in this domain:
Basic Concepts:
MCQs may cover fundamental concepts such as arrays, linked lists, stacks, and queues.
Understanding the basic properties, advantages, and disadvantages of these data structures is often assessed.
Trees and Graphs:
Questions may focus on tree structures, including binary trees, AVL trees, and B-trees.
Graph-related topics could include concepts like traversal algorithms, connectivity, and properties of directed and undirected graphs.
Hashing:
MCQs often evaluate knowledge of hashing techniques and collision resolution methods.
Understanding the principles of hash functions and their applications in data retrieval is essential.
Sorting and Searching:
Questions may cover various sorting algorithms (e.g., bubble sort, quicksort, mergesort) and their time complexities.
Searching algorithms, such as binary search and linear search, might be included in these questions.
Dynamic Programming:
MCQs may assess the understanding of dynamic programming concepts, including optimal substructure and overlapping subproblems.
Knowledge of dynamic programming techniques to solve problems efficiently may be evaluated.
Graph Algorithms:
Questions may explore graph traversal algorithms like depth-first search (DFS) and breadth-first search (BFS).
Shortest path algorithms (e.g., Dijkstra's algorithm, Bellman-Ford algorithm) and minimum spanning tree algorithms may also be covered.
Heap and Priority Queue:
MCQs may inquire about heap data structures and their applications, including priority queues.
Understanding the operations and time complexities associated with heaps is commonly tested.
Advanced Data Structures:
Questions may cover more advanced data structures such as trie, segment tree, and Fenwick tree (Binary Indexed Tree).
Knowledge of these structures and their use cases is often examined in MCQs.
Abstract Data Types (ADTs):
MCQs may assess the understanding of abstract data types like stacks, queues, and sets.
Candidates may be tested on their ability to choose appropriate ADTs based on specific requirements.
Space and Time Complexity Analysis:
Questions may evaluate the ability to analyze the time and space complexity of algorithms and data structures.
Candidates may need to compare different algorithms and choose the most efficient one for a given problem.
Applications and Real-World Scenarios:
Some MCQs may present real-world scenarios and ask candidates to identify the most suitable data structure or algorithm for solving specific problems.
These MCQs aim to assess a candidate's proficiency in understanding, implementing, and analyzing various data.
clustering,distance measures,properties,types of clustering,clustering of algorithm,comment on the k_means method,nearest neighbor clustering,partitional,
In this session you will learn:
Implement Single and Multi dimensional array
Declare and Define Functions
Call Functions by value and by reference
Implement Method Overloading
Use String data-type and String-buffer
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Course module of DS
1. PUNJAB COLLEGE OF TECHNICAL EDUCATION
LUDHIANA
Teacher Name: Sandeepjit Kaur (SJ) Class Name: MCA
Subject Name: Data Structure Max Marks:60
Subject Code: MCA-302 (N2) Total Lects Required: 50
No. of Tests: 5 No. of Assignments: 4
Instruction for candidates
1. Candidates are required to attempt one question each from sections A, B, C and D of
the question paper and the entire section E
2. Use of non-programmable scientific calculator is allowed
Section A
Basic concepts and notations, data structures and data structure operations, mathematical
notation and functions, algorithmic complexity and time space trade off. Basic data
structures such as arrays, stack and queues and their applications, linked and sequential
representation. Linked list, representation of linked list, multi linked structures.
Section B
Trees-definitions and basic concepts, linked tree representation, representations in
contiguous storage, binary trees, binary tree traversal, searching insertion and deletion in
binary trees, heap tree and heap sort algorithm, AVL trees.
Section C
Graphs and their application, sequential and linked representation of graph – adjacency
matrix, operations on graph, traversing a graph, Dijkstra’s algorithm for shortest distance,
DFS and BFS, Hashing.
Section D
Searching and sorting use of various data structures for searching and sorting, Linear and
Binary search, Insertion sort, Selection sort, Merge sort, Radix sort, Bubble sort, Quick
sort, Heap Sort.
Note: -
1. Programs are to be implemented in ‘C/C++’
2. Insertion, deletion, search and traversal operations are to be performed on all the data
structures.
References:
1. A. Tannenbaum, Y. Lanhgsam and A.J.Augenstein,”Data Structures Using C”,
Prentice Hallof India, 1990
2. Seymour Lipschultz, “ Theory and Practice of Data structures”, Mc Graw Hill, 1988.
3. E. Horowitz and S.Sahni,”Data structures with Pascal”, Galgotia, 3rd edition,
2. COURSE BREAKUP
Propose Lect. Topics Actual Assign Test
d Week No. DOD
1. Introduction to Data Structure:
• Basic concepts of data
• Problem analysis
2. Data Structure
• Types of data structures
• Data operations
3. Data Structure ( Continue…)
• Need of data structure
• Mathematical notations and functions
4. Algorithm Complexity
• Big O notation
• Time space trade off
5. Introduction to Arrays
• Memory representation of One
Dimensional array
• Location of an element at in one
dimensional array
6. Introduction to Arrays
• Memory representation of two
Dimensional array
• Location of an element at in two
dimensional array
3. 7. TUTORIAL
8. TEST 1
9. Operations on array (Continue…)
Traversing of an array
Insertion of an element in an array
o in the beginning
o at Kth location
o at the end
10. Operations on array (Continue…)
Deletion of an element from an array
o from the beginning
o from Kth location
o from the end
Merging of two arrays
11. TUTORIAL
12. TEST 2
13. Stacks & Queues:
• Basics of stacks
• Operations on stack
PUSH operation
POP operation
14. Applications of Stack
• Expression evaluation
15. Applications of Stack (Continue…)
• Polish notation
• Recursion
16. REVISION OF STACK WITH
EXAMPLES
4. 17. TEST 3
18. Introduction of Queues
• Operations on Queues
o Insertion
o Deletion
19. Queues:
o Circular Queues
o Priority Queues
20. Linked Lists:
• Singular List
• Circular List
21. REVISION OF QUEUES WITH EXAMPLES
22. Operations Performed on link list:
Insertion
o In the beginning
o At kth location
23. Insertion in Link list (Continue…)
o After a given no
o At the end
24.
FIRST HALF SYLLABUS TEST
25. Deletion in Link list
o from the beginning
o from kth location
26. Deletion in Link List
o from the end
o Searching in link list
27. More in Link List:
o Doubly Linked List
o Dynamic storage management
28. More in Link List:
o Generalized list
5. o Garbage collection
29. TUTORIAL
30. TEST 4
31. Trees:
• Definition & Concept, Basic Tree
• Binary Tree representation
32. Trees (Continue….)
• Threaded Storage representation
• Binary tree traversals
o Inorder
o Preorder
o Postorder
33. Trees (Continue….)
Searching in binary tree
34. Insertion and deletion in binary tree
35. Heap tree and heap sort
36. AVL tree
37. Graphs: introduction, sequential and linked
representation of graphs
38. Adjacency matrix, operations on graph,
traversing a graph
39. Dijkstra’s algorithm for shortest distance
40. DFS and BFS, Hashing.
41. Searching and Sorting:
• Use of various data structure for
searching & sorting
• Linear & Binary Search
42. Searching and Sorting (Continue…)
• Insertion Sort
6. • Selection Sort
43. Searching and Sorting (Continue…)
• Merge Sort
44. TEST 5
45. Searching and Sorting (Continue…)
• Radix Sort
46. Searching and Sorting (Continue…)
• Bubble Sort
47. Searching and Sorting (Continue….)
• Quick Sort
48. Searching and Sorting (Continue….)
• Heap Sort
49.
TUTORIAL
50.
FULL SYLLABUS TEST
7. ASSIGNMENT 1
Ques 1: Consider the linear Array NAME, which is stored alphabetically.
a) Suppose Daljit is to be inserted into the linear array. How many names must be
moved to new locations?
b) Suppose Gagan is to be deleted from the array. How many names must be moved
to new locations?
Ques 2: Consider the algebraic expression ( 7x + 5y ) (2a – 5b )3. Draw the corresponding
diagram for it.
Ques 3: The tree structure is given by means of level numbers. Draw the corresponding
tree diagram.
01 Student 02 Name 03 First name
02Class 03Middle name
02Rollno 03 Last name
02Father’sName 03Father’s First name
02Age 03 Father’s first name
02Address 03 father’s middle name
02 Contactno 03father’s last name
03 HouseNo
03 StrretNo
03 City
03 State
03 Pincode
8. ASSIGNMENT 2
Short Questions:
1. What is threaded Binary Tree?
2. How the height of a binary search tree effects its performance?
3. What is the different between B-Tree, B + - Tree, B * Tree
4. How heap differs from binary tree?
Long Questions:
1. For a binary Tree the in-order & post-order traversal sequences are as follows:
In order: D C K E A H B Q J I
Post order: D K E C H Q J I B A
Draw Binary Tree.
2. Write a search () function so that it not only returns the location of the element but
also return location of its parents in a binary search tree.
3. What is a thread? How it is useful? What are advantages of threading a binary
tree?
9. ASSIGNMENT 3
SHORT QUESTIONS
1. What is a Complete Binary Tree? Explain its related terminology.
2. What is the node structure of a tree (Binary)?
3. What is Tree Traversal?
LONG QUESTIONS
1. What do you mean by Binary Search Tree? Explain how deletion of a node is
performed in the Binary Search Tree.
2. Describe the Binary Tree Traversing methods with the help of proper examples.
3. Traverse the following tree in inorder, preorder and postorder. Write the
algorithm also.
A
B C
G
D E F
H
10. Practical Software Lab – III
BC-207(N2) Max Marks 100
Internal Assessment 40
External Assessment 60
Note: Program should be fully documented with sample I/O data Flow
charts should be developed wherever necessary.
Write program in C
1. To insert and delete a node in a linked list
2. To add two polynomials using linked list
3. To insert and delete a node in a circular linked list.
4. To implement a stack using arrays and linked list.
5. To implement a queue using arrays and linked list.
6. To invert a linked list.
7. To merge two arrays.
8. To solve polish expression using stacks.
9. For tower of hanoi problem using recursion.
10 .To insert and delete node in binary search tree
11. To find traversals of expressions using binary tree
12. To search an element using binary tree.
11. Presentation Topics
1. Need Of Data Structure
2. Types of data structures
3. Operations performed on data structure
4. What is structure? Difference b/w structure and union.
5. What is self referential structure?
6. What is pointer & operations performed on pointer
7. What is an array? Types of array?
8. Operations of an array.
9. Complexity of an algorithm?
10.Hotel Taj Attack (reasons)
11.Future of IT
12. WiFi
13.Advantages and Disadvantages of Internet
14. Stack and its operations
15.Applications of stack
16.Queues and its operations
17.Applications of Queues
18.Types of queues
19. Reliance telecom
20. DELL
21. RGTP (Rajiv Ghandhi Technology Park, Mohali)
22. Online Education