assignment of data structure

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• DSA Problems
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• Divide and Conquer
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Data Structures and Algorithms Problems

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• Data Structures
• Linked List
• Binary Tree
• Binary Search Tree
• Segment Tree
• Disjoint Set Union
• Fenwick Tree
• Red-Black Tree
• Advanced Data Structures

Data Structures Tutorial

Data structures are the fundamental building blocks of computer programming. They define how data is organized, stored, and manipulated within a program. Understanding data structures is very important for developing efficient and effective algorithms.

In this tutorial, we will explore the most commonly used data structures, including arrays, linked lists, stacks, queues, trees, and graphs.

What is Data Structure?

A data structure is a storage that is used to store and organize data. It is a way of arranging data on a computer so that it can be accessed and updated efficiently.

A data structure is not only used for organizing the data. It is also used for processing, retrieving, and storing data. There are different basic and advanced types of data structures that are used in almost every program or software system that has been developed. So we must have good knowledge about data structures. 

Classification of Data Structure

• Linear Data Structure :  Data structure in which data elements are arranged sequentially or linearly, where each element is attached to its previous and next adjacent elements, is called a linear data structure.  Example: Array, Stack, Queue, Linked List, etc.
• Static Data Structure:  Static data structure has a fixed memory size. It is easier to access the elements in a static data structure.  Example : array.
• Dynamic Data Structure:  In dynamic data structure, the size is not fixed. It can be randomly updated during the runtime which may be considered efficient concerning the memory (space) complexity of the code.  Example : Queue, Stack, etc.
• Non-Linear Data Structure:  Data structures where data elements are not placed sequentially or linearly are called non-linear data structures. In a non-linear data structure, we can’t traverse all the elements in a single run only.  Examples: Trees and Graphs.
• Introduction to Data Structures

Array Data Structure

Linked list data structure, 1. singly linked list:, 2. circular linked list:, 3. doubly linked list:, matrix data structure, stack data structure, queue data structure, binary tree data structure, binary search tree data structure, heap data structure, hashing data structure, graph data structure.

• Advanced Data Structure

1. Advanced Lists:

2. segment tree data structure:.

• 3. Trie Data Structure:

4. Binary Indexed Tree Data Structure:

• 5. Suffix Array and Suffix Tree:

6. AVL Tree:

7. splay tree:, 9. red-black tree:, 10. k dimensional tree:, others data structures:.

• What is Data Structure: Types, Classifications and Applications
• Common operations on various Data Structures
• Search, insert and delete in an unsorted array
• Search, insert and delete in a sorted array
• Write a program to reverse an array
• Leaders in an array
• Given an array A[] and a number x, check for pair in A[] with sum as x
• Majority Element
• Find the Number Occurring Odd Number of Times
• Largest Sum Contiguous Subarray
• Find the Missing Number
• Search an element in a sorted and pivoted array
• Merge an array of size n into another array of size m+n
• Median of two sorted arrays
• Program for array rotation
• Reversal algorithm for array rotation
• Block swap algorithm for array rotation
• Maximum sum such that no two elements are adjacent
• Sort elements by frequency | Set 1
• Count Inversions in an array

All Articles on Array Coding Practice on Array Quiz on Array Coding Practice on Array Recent Articles on Array

• Introduction to Linked List
• Linked List vs Array
• Linked List Insertion
• Linked List Deletion (Deleting a given key)
• Linked List Deletion (Deleting a key at given position)
• A Programmer’s approach of looking at Array vs. Linked List
• Find Length of a Linked List (Iterative and Recursive)
• How to write C functions that modify head pointer of a Linked List?
• Swap nodes in a linked list without swapping data
• Reverse a linked list
• Merge two sorted linked lists
• Merge Sort for Linked Lists
• Reverse a Linked List in groups of given size
• Detect and Remove Loop in a Linked List
• Add two numbers represented by linked lists | Set 1
• Rotate a Linked List
• Generic Linked List in C
• Circular Linked List Introduction and Applications,
• Circular Singly Linked List Insertion
• Circular Linked List Traversal
• Split a Circular Linked List into two halves
• Sorted insert for circular linked list
• Doubly Linked List Introduction and Insertion
• Delete a node in a Doubly Linked List
• Reverse a Doubly Linked List
• The Great Tree-List Recursion Problem.
• QuickSort on Doubly Linked List
• Merge Sort for Doubly Linked List

All Articles of Linked List Coding Practice on Linked List Recent Articles on Linked List

• Search in a row wise and column wise sorted matrix
• Print a given matrix in spiral form
• A Boolean Matrix Question
• Print unique rows in a given boolean matrix
• Maximum size square sub-matrix with all 1s
• Inplace M x N size matrix transpose | Updated
• Dynamic Programming | Set 27 (Maximum sum rectangle in a 2D matrix)
• Strassen’s Matrix Multiplication
• Create a matrix with alternating rectangles of O and X
• Print all elements in sorted order from row and column wise sorted matrix
• Given an n x n square matrix, find sum of all sub-squares of size k x k
• Count number of islands where every island is row-wise and column-wise separated
• Find a common element in all rows of a given row-wise sorted matrix

All Articles on Matrix Coding Practice on Matrix Recent Articles on Matrix.

• Introduction to Stack
• Infix to Postfix Conversion using Stack
• Evaluation of Postfix Expression
• Reverse a String using Stack
• Implement two stacks in an array
• Check for balanced parentheses in an expression
• Next Greater Element
• Reverse a stack using recursion
• Sort a stack using recursion
• The Stock Span Problem
• Design and Implement Special Stack Data Structure
• Implement Stack using Queues
• Design a stack with operations on middle element
• How to efficiently implement k stacks in a single array?

All Articles on Stack Coding Practice on Stack \ Recent Articles on Stack

• Queue Introduction and Array Implementation
• Linked List Implementation of Queue
• Applications of Queue Data Structure
• Priority Queue Introduction
• Deque (Introduction and Applications)
• Implementation of Deque using circular array
• Implement Queue using Stacks
• Find the first circular tour that visits all petrol pumps
• Maximum of all subarrays of size k
• An Interesting Method to Generate Binary Numbers from 1 to n
• How to efficiently implement k Queues in a single array?

All Articles on Queue Coding Practice on Queue Recent Articles on Queue

• Binary Tree Introduction
• Binary Tree Properties
• Types of Binary Tree
• Handshaking Lemma and Interesting Tree Properties
• Enumeration of Binary Tree
• Applications of tree data structure
• Tree Traversals
• BFS vs DFS for Binary Tree
• Level Order Tree Traversal
• Diameter of a Binary Tree
• Inorder Tree Traversal without Recursion
• Inorder Tree Traversal without recursion and without stack!
• Threaded Binary Tree
• Maximum Depth or Height of a Tree
• If you are given two traversal sequences, can you construct the binary tree?
• Clone a Binary Tree with Random Pointers
• Construct Tree from given Inorder and Preorder traversals
• Maximum width of a binary tree
• Print nodes at k distance from root
• Print Ancestors of a given node in Binary Tree
• Check if a binary tree is subtree of another binary tree
• Connect nodes at same level

All articles on Binary Tree Coding Practice on Binary Tree Recent Articles on Tree

• Search and Insert in BST
• Deletion from BST
• Minimum value in a Binary Search Tree
• Inorder predecessor and successor for a given key in BST
• Check if a binary tree is BST or not
• Lowest Common Ancestor in a Binary Search Tree.
• Inorder Successor in Binary Search Tree
• Find k-th smallest element in BST (Order Statistics in BST)
• Merge two BSTs with limited extra space
• Two nodes of a BST are swapped, correct the BST
• Floor and Ceil from a BST
• In-place conversion of Sorted DLL to Balanced BST
• Find a pair with given sum in a Balanced BST
• Total number of possible Binary Search Trees with n keys
• Merge Two Balanced Binary Search Trees
• Binary Tree to Binary Search Tree Conversion

All Articles on Binary Search Tree Coding Practice on Binary Search Tree Recent Articles on BST

• Binary Heap
• Why is Binary Heap Preferred over BST for Priority Queue?
• K’th Largest Element in an array
• Sort an almost sorted array
• Binomial Heap
• Fibonacci Heap
• Tournament Tree (Winner Tree) and Binary Heap

All Articles on Heap Coding Practice on Heap Recent Articles on Heap

• Hashing Introduction
• Separate Chaining for Collision Handling
• Open Addressing for Collision Handling
• Print a Binary Tree in Vertical Order
• Find whether an array is subset of another array
• Union and Intersection of two Linked Lists
• Find a pair with given sum
• Check if a given array contains duplicate elements within k distance from each other
• Find Itinerary from a given list of tickets
• Find number of Employees Under every Employee

All Articles on Hashing Coding Practice on Hashing Recent Articles on Hashing

• Graph and its representations
• Breadth First Traversal for a Graph
• Depth First Traversal for a Graph
• Applications of Depth First Search
• Applications of Breadth First Traversal
• Detect Cycle in a Directed Graph
• Detect Cycle in Graph using DSU
• Detect cycle in an Undirected Graph using DFS
• Longest Path in a Directed Acyclic Graph
• Topological Sorting
• Check whether a given graph is Bipartite or not
• Snake and Ladder Problem
• Minimize Cash Flow among a given set of friends who have borrowed money from each other
• Boggle (Find all possible words in a board of characters)
• Assign directions to edges so that the directed graph remains acyclic

All Articles on Graph Data Structure Coding Practice on Graph Recent Articles on Graph

• Memory efficient doubly linked list
• XOR Linked List – A Memory Efficient Doubly Linked List | Set 1
• XOR Linked List – A Memory Efficient Doubly Linked List | Set 2
• Skip List | Set 1 (Introduction)
• Self Organizing List | Set 1 (Introduction)
• Unrolled Linked List | Set 1 (Introduction)
• Segment Tree | Set 1 (Sum of given range)
• Segment Tree | Set 2 (Range Minimum Query)
• Lazy Propagation in Segment Tree
• Persistent Segment Tree | Set 1 (Introduction)

All Articles on Segment Tre

3. Trie Data Structure :

• Trie | (Insert and Search)
• Trie | (Delete)
• Longest prefix matching – A Trie based solution in Java
• How to Implement Reverse DNS Look Up Cache?
• How to Implement Forward DNS Look Up Cache?

All Articles on Trie

• Binary Indexed Tree
• Two Dimensional Binary Indexed Tree or Fenwick Tree
• Binary Indexed Tree : Range Updates and Point Queries
• Binary Indexed Tree : Range Update and Range Queries

All Articles on Binary Indexed Tree

5. Suffix Array and Suffix Tree :

• Suffix Array Introduction
• Suffix Array nLogn Algorithm
• kasai’s Algorithm for Construction of LCP array from Suffix Array
• Suffix Tree Introduction
• Ukkonen’s Suffix Tree Construction – Part 1
• Ukkonen’s Suffix Tree Construction – Part 2
• Ukkonen’s Suffix Tree Construction – Part 3
• Ukkonen’s Suffix Tree Construction – Part 4,
• Ukkonen’s Suffix Tree Construction – Part 5
• Ukkonen’s Suffix Tree Construction – Part 6
• Generalized Suffix Tree
• Build Linear Time Suffix Array using Suffix Tree
• Substring Check
• Searching All Patterns
• Longest Repeated Substring,
• Longest Common Substring, Longest Palindromic Substring

All Articles on Suffix Tree

• AVL Tree | Set 1 (Insertion)
• AVL Tree | Set 2 (Deletion)
• AVL with duplicate keys
• Splay Tree | Set 1 (Search)
• Splay Tree | Set 2 (Insert)
• B-Tree | Set 1 (Introduction)
• B-Tree | Set 2 (Insert)
• B-Tree | Set 3 (Delete)
• Red-Black Tree Introduction
• Red Black Tree Insertion.
• Red-Black Tree Deletion
• Program for Red Black Tree Insertion

All Articles on Self-Balancing BSTs

• KD Tree (Search and Insert)
• K D Tree (Find Minimum)
• K D Tree (Delete)
• Treap (A Randomized Binary Search Tree)
• Ternary Search Tree
• Interval Tree
• Implement LRU Cache
• Sort numbers stored on different machines
• Find the k most frequent words from a file
• Given a sequence of words, print all anagrams together
• Decision Trees – Fake (Counterfeit) Coin Puzzle (12 Coin Puzzle)
• Spaghetti Stack
• Data Structure for Dictionary and Spell Checker?
• Cartesian Tree
• Cartesian Tree Sorting
• Centroid Decomposition of Tree
• Gomory-Hu Tree
• Recent Articles on Advanced Data Structures.
• Commonly Asked Data Structure Interview Questions | Set 1
• A data structure for n elements and O(1) operations
• Expression Tree

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• Prof. Erik Demaine
• Dr. Jason Ku
• Prof. Justin Solomon

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• Electrical Engineering and Computer Science

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• Algorithms and Data Structures
• Theory of Computation
• Computation

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Introduction to algorithms, 6.006 introduction to algorithms, lecture 2: data structures.

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This repository is a compilation of my solutions to the Data Structures and Algorithms assignments offered by the University of California, San Diego (UCSD) and the National Research University Higher School of Economics (HSE) on Coursera. These assignments, covering material from courses 1 through 6, have all been solved using the Python.

TZhoroev/Coursera-Data_Structures_and_Algorithms

Folders and files, repository files navigation, coursera-data_structures_and_algorithms.

This repository contains my solutions to the Data Structures and Algorithms assignments offered by the University of California, San Diego (UCSD) and the National Research University Higher School of Economics (HSE) on Coursera. All of the problems from courses 1 through 6 have been solved using Python.

These solutions are intended to serve as a reference for those working on these assignments or seeking an alternative perspective on how to approach the problems. It is recommended that you try solving the assignments independently before consulting these solutions, as the best way to improve your skills is through practice. However, if you encounter difficulties or require additional guidance, these solutions are available for reference.

I hope that this repository proves to be a useful resource for your studies in data structures and algorithms.

Algorithmic Toolbox : Certificate

This online course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming.

Week 1: Welcome

• Sum of Two Digits .
• Maximum Pairwise Product .

Week 2: Algorithmic Warm-up

• Fibonacci Number
• Last Digit of a Large Fibonacci Number
• Greatest Common Divisor
• Least Common Multiple
• Fibonacci Number Again
• Last Digit of the Sum of Fibonacci Numbers Again

Week 3: Greedy Algorithms

• Money Change
• Maximum Value of the Loot
• Car Fueling
• Maximum Advertisement Revenue
• Collecting Signatures
• Maximum Number of Prizes
• Maximum Salary

Week 4: Divide and Conquer

• Binary Search
• Binary Search with Duplicates
• Majority Element
• Improving Quick Sort
• Number of Inversions
• Organizing a Lottery
• Closest Points

Week 5: Dynamic Programming I

• Money Change Again
• Primitive Calculator
• Edit Distance
• Longest Common Subsequence of Two Sequences
• Longest Common Subsequence of Three Sequences

Week 6: Dynamic Programming II

• Maximum Amount of Gold
• Partitioning Souvenirs
• Maximum Value of an Arithmetic Expression

Data Structures : Certificate

In this online course, we consider the common data structures that are used in various computational problems.

Week 1: Basic Data Structures

• Check brackets in the code
• Compute tree height
• Network packet processing simulation
• Extending stack interface
• Maximum in Sliding Window

Week 2: Priority Queues and Disjoint Sets

• Convert array into heap
• Parallel processing
• Merging tables

Week 3: Hash Tables and Hash Functions

• Hashing with chains
• Find pattern in text
• Substring equality
• Longest common substring
• Pattern matching with mismatches

Week 4: Binary Search Trees

• Binary tree traversals
• Is it a binary search tree?
• Is it a binary search tree? Hard version
• Set with range sums

Algorithms on Graphs : Certificate

In this online course, first learned what a graph is and what are some of the most important properties. Then we learned several ways to traverse graphs and how one can do useful things while traversing the graph in some order. Then we learned shortest paths algorithms — from the basic ones to those which open door for 1000000 times faster algorithms used in Google Maps and other navigational services. We finished with minimum spanning trees which are used to plan road, telephone and computer networks and also find applications in clustering and approximate algorithms.

Week 1: Decomposition of Graphs I

• Finding an Exit from a Maze
• Adding Exits to a Maze

Week 2: Decomposition of Graphs II

• Checking Consistency of CS Curriculum
• Determining an Order of Courses
• Checking Whether Any Intersection in a City is Reachable from Any Other

Week 3: Paths in Graphs I

• Computing the Minimum Number of Flight Segments
• Checking whether a Graph is Bipartite

Week 4: Paths in Graphs II

• Computing the Minimum Cost of a Flight
• Detecting Anomalies in Currency Exchange Rates
• Exchanging Money Optimally

Week 5: Minimum Spanning Trees

• Building Roads to Connect Cities

Week 6: Advanced Shortest Paths

• Friend Suggestion
• Compute Distance Faster Using Coordinates
• Compute Distance with Preprocessing
• Compute Distance with Preprocessing on Larger Road Networks
• Travelling Salesman Problem

Algorithms on Strings : Certificate

Textual information abounds in the world and on the internet. We read webpages, books, emails, and textual inquiries to conduct information searches. From the perspective of computer science, each of those are strings. Search engines employ a variety of string algorithms to make sense of all that data and improve the effectiveness of searches. In addition, a variety of search methods are used in the developing field of personalized medicine to identify mutations in the human genome that cause disease. You will master important pattern matching ideas in this online course, including attempts, suffix trees, suffix arrays, and even the Burrows-Wheeler transform.

Week 1: Suffix Trees

• Construct a Trie from a Collection of Patterns
• Implement TrieMatching
• Extend TrieMatching
• Construct the Suffix Tree of a String
• Find the Shortest Non-Shared Substring of Two Strings

Week 2: Burrows–Wheeler Transform and Suffix Arrays

• Construct the Burrows–Wheeler Transform of a String
• Reconstruct a String from its Burrows–Wheeler Transform
• Implement BetterBWMatching
• Construct the Suffix Array of a String

Week 3 & 4: Algorithmic Challenges: Suffix Arrays

• Find All Occurrences of a Pattern in a String
• Construct the Suffix Array of a Long String
• Pattern Matching with the Suffix Array
• Construct the Suffix Tree from the Suffix Array

Advanced Algorithms and Complexity : Certificate

Week 1: flows in networks.

• Evacuating People
• Assigning Airline Crews to Flights
• Stock Charts

Week 2: Linear Programming

• Infer Energy Values of Ingredients
• Optimal Diet Problem
• Online Advertisement Allocation

Week 3: NP-completeness

• Assign Frequencies to the Cells of a GSM Network
• Cleaning the Apartment
• Advertisement Budget Allocation

Week 4: Coping with NP-completeness

• Integrated Circuit Design
• Plan a Fun Party
• Reschedule the Exams

Week 5: Streaming Algorithms

• Nice vs Naughty

Genome Assembly Programming Challenge : Certificate

Week 1: Assembling phi X174 Using Overlap Graphs

• Assembling the phi X174 Genome from Error-Free Reads Using Overlap Graphs
• Assembling the phi X174 Genome from Error-Prone Reads Using Overlap Graphs

Week 2: Assembling Genomes Using de Bruijn Graphs

• Puzzle Assembly
• Finding an Eulerian Cycle in Directed Graph
• Finding a k-Universal Circular String
• Assembling the phi X174 Genome from its k-mer Composition

Week 3: Genome Assembly Faces Real Sequencing Data

• Finding a Circulation in a Network
• Selecting the Optimal k-mer Size
• Bubble Detection
• Tip Removal
• Assembling the phi X174 Genome from Error-Prone Reads using de Bruijn Graphs
• Python 61.9%

Data Structures

Arrays - ds easy problem solving (basic) max score: 10 success rate: 93.00%, 2d array - ds easy problem solving (basic) max score: 15 success rate: 93.19%, dynamic array easy problem solving (basic) max score: 15 success rate: 87.09%, left rotation easy problem solving (basic) max score: 20 success rate: 91.62%, sparse arrays medium problem solving (basic) max score: 25 success rate: 97.30%, array manipulation hard problem solving (intermediate) max score: 60 success rate: 62.33%, print the elements of a linked list easy problem solving (basic) max score: 5 success rate: 97.11%, insert a node at the tail of a linked list easy problem solving (intermediate) max score: 5 success rate: 95.31%, insert a node at the head of a linked list easy problem solving (basic) max score: 5 success rate: 98.29%, insert a node at a specific position in a linked list easy problem solving (intermediate) max score: 5 success rate: 96.93%, cookie support is required to access hackerrank.

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