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VisuAlgo: Visualising Data Structures and Algorithms through Animation http://t.co/81sfSY8x84 http://t.co/kfTWGwS5H9

160+ Algorithm & Data Structure Problems using C++ Data Structure and Algorithms Problems | Current Status| Stats || :------------: | :----------: || Total Problems | 166 | LinkedList Problems | Problem | Solution || :------------ | :----------: || Find the nth node of linked list from last. | nthToLastNode.cpp || Add numbers where each digit of the number is represented by node of a linkedlist. Give output as a linked list. | add two numbers lists.cpp || Swap nodes of a linkedlist without swapping data. | swapNodesWithoutSwappingData.cpp || Reverse a linked list, iteratively and recursively | reverseLinkedListIterAndRecurse.cpp || Given a linked list, reverse alternate nodes and append at the end. | reverseAlternateNodes.cpp || Only given a node pointer, delete the node from the linked list. | deleteNode.cpp || Delete the entire linkedlist. | deleteLinkedlist.cpp || Print middle node of linkedlist without iterating twice. | printMiddleNode.cpp | | Detecting and removing a cycle in linkedlist.| floyedCycleDetection.cpp || Determine if a linked list is a pallindrome. | listPallindrome.cpp || Insert data in a sorted linked list.| insertInASortedLinkedList.cpp || Determine the intersection(merging) point of two given linked list.| findIntersectionPointOfLists.cpp || Clone a linkedlist which has next and an random pointer, Space Complexity - O(1). | cloneListWithRandomPtr.cpp || Given a sorted linked list with duplicates, remove duplicates in one iteration. | removeDuplicatesFromSortedList.cpp | | Using Floyd's cycle finding algorithm, detect if a linkedlist contain cycle, if it does contain cycle, remove the loop | floyedCycleDetection.cpp || Sort a linked list using merge sort | mergesort.cpp || Given a singly linked list L 0 -> L 1 -> … -> L n-1 -> L n . Rearrange the nodes in the list (in place) so that the new formed list is : L 0 -> L n -> L 1 -> L n-1 -> L 2 -> L n-2 .... | rearrange_list.cpp | Include Include contains single header implementation of data structures and some algorithms. | Data Structure/Algorithm | Implementation || :------------: | :----------: || Generic Macros and Algorithms like swap, random number generation | generic.h || Generic Stack Implementation | stack.h || Generic Queue Implementation | queue.h || Generic List Implementation | list.h || Binary Search Tree Implementation | binarySearchTree.h || Quick Sort Implementation | quickSort.h || Merge Sort Implementation | mergeSort.h || Selection Sort Implementation | selectionSort.h || Bubble Sort Implementation | bubbleSort.h || Linux Kernel Double LinkedList Implementation | double linked list.h || Generic Graph Implementation (Adjacency List) | graph.h || Heap Sort Implementation | heap_sort.h || My own string library implementation | pstring.h pstring.cpp | Bit Manipulation Problems | Problem | Solution || :------------ | :----------: || Determine if a number is a power of 2. | power of 2.cpp || Add two binary number represented as string. | addBin.cpp || Determine the next power of 2 for a given number. | next power of 2.cpp || Using bit manipulation determine if a number is multiple of 3. | multipleof 3.cpp || Determine endianess of the machine, print a number in reverse Endianess. | reverseEndianness.cpp || Find the parity of given number. | findparity.cpp || Implement fast multiplication of a number to 7 using bit manipulation. | multiply by 7.cpp || Reverse bits of unsigned integer (two methods - Reversing bit by bit & divide and conquer). | reverseBitsOfAnInteger.cpp || Small function to determine position of right most set bit in a given integer.| right most set bit.cpp | |Given a vector of numbers, only one number occurs odd number of times, find the number.| findodd one out.cpp || Given two integers, determine if their sum would be interger overflow.| integerOverflow.cpp || How many bit flip operation would require to convert number A to B. | countNumberOfBitFlips.cpp || Given a number x and two positions (from right side) in binary representation of x, write a function that swaps n right bits at given two positions and returns the result. It is also given that the two sets of bits do not overlap.| swapSetOfBits.cpp || Add two numbers without using any arithmetic operators | addition without operators.cpp ||Louise and Richard play a game. They have a counter set to N. Louise gets the first turn and the turns alternate thereafter. In the game, they perform the following operations: If N is not a power of 2, reduce the counter by the largest power of 2 less than N. If N is a power of 2, reduce the counter by half of N. The resultant value is the new N which is again used for subsequent operations.The game ends when the counter reduces to 1, i.e., N == 1, and the last person to make a valid move wins. Given N, your task is to find the winner of the game. If they set counter to 1, Richard wins, because its Louise' turn and she cannot make a move. Input Format : -The first line contains an integer T, the number of testcases. T lines follow. Each line contains N, the initial number set in the counter. | counter game.cpp ||Determine if two integers are of opposite signs.| checkopposite signs.cpp ||Swap two bits at position p and q of a given integer.| swapBits.cpp ||Check if a number is power of 4. | checkif power of_4.cpp | Cracking the coding interview problems | Problem | Solution || :------------ | :----------: || Problem 1-1 : Edition 6: Write an algorithm to determine whether a string has unique characters or not. Can we do it without using addtional data structures? | 1-1-hasUniqueChars.cpp || Problem 1-2 : Edition 5: Reverse a string when you are a pass a null terminated C string.| 1-2-edi5-reverseString.cpp || Problem 1-2 : Edition 6: Given two strings, determine if one is permutation of other.| 1-2-perm-strings.cpp || Problem 1-3 : Edition 5: Write an algorithm to remove duplicate chars from a string.| 1-3-edi5-removeDuplicates.cpp || Problem 1-3 : Edition 6: URLify: Replace all the spaces in a string with '%20'. Preferebly Inplace | 1-3-URLify.cpp || Problem 1-4 : Edition 6: Given a string, write a function to check if it is a permutation of a pallindrome.| 1-4-pallindrome-permutations.cpp || Problem 1-5 : Edition 6: There are three possible edits that can be performed on a string - Insert a char, Delete a char, Replace a char. Given two strings, determine if they are one or 0 edit away.| 1-5-one-edit-away.cpp || Problem 1-6: Implement a method to perform basic string compression. Example string aabcccccaaa should be compressed to a2b1c5a3 , however if compressed string is bigger than original string, return original string| 1-6-string-compression.cpp || Problem 1-7: Rotate the matrix clockwise( & anticlockwise) by 90 degrees| 1-7-matrix-rotation.cpp || Problem 1-8: Write an algorithm such that if an element of MxN matrix is 0, its entire row and column is set to 0. | 1-8-zero-matrix.cpp || Problem 1-9: Given two strings s1 and s2, determine s2 is rotation of s1 using only one call to a function which checks whether one string is rotation of another.| 1-9-string-rotation.cpp || Problem 2-1: Remove duplicates from an unsorted linked list. What if no temporary buffer is allowed.| 2-1-remove-dups.cpp || Problem 2-2: Determine k th node from the last of a singly linked list. (Iterative and Recursive Approaches) | 2-2-kthToLast.cpp || Problem 2-3: Implement an algorithm to delete a node in the middle of a singly linked list | 2-3-delete-middle-node.cpp || Problem 2-4: Partition a linked list around a value x, all the nodes smaller than x come before all the nodes greater than equal to x | 2-4-partition.cpp || Problem 2-5: You have two numberse represented by a linked list where each node contains a single digit. The digits are stored in reversed order, such that 1's digits are at the head of the list. Write a function that adds the two numbers and returns the sum as a linked list.Example: Input: ( 7 --> 1 --> 6 ) + ( 5 --> 9 --> 2 ) that is 617 + 295 Output: ( 2 --> 1 --> 9 ) i.e. 912. FOLLOW UP : Suppose the lists are stored in forward order, Repeat the above problem. Input: ( 6 --> 1 --> 7 ) + ( 2 --> 9 --> 5 ) i.e. 617 + 295 Output: ( 9 --> 1 --> 2 ) i.e. 912. Implement it recursively and iteratively. | 2-5-add-lists.cpp || Problem 2-6: Determine if linked list is palindrome( 2 iterative and one recursive approach | 2-6-palindrome.cpp || Problem 2-7: Determine if two singly linked list intersect, if yes, return the intersecting node. The intersection is defined based on reference not on values| 2-7-intersection.cpp || Problem 2-8: Detect if the linked list have a loop, Find the start node of the loop and remove the loop| 2-8-loop-detection.cpp Dynamic Programming Problems | Problem | Solution || :------------ | :----------: || N th Fibonacci term using different memoization techniques | fibonacci.cpp || Longest Common Subsequence Problem | lcs.cpp || Maximum Value Contigous Subsequence Problem wiki | max subsequence.cpp || Catalan number - Count the number of possible Binary Search Trees with n keys | catalannumber.cpp || Calculate the number of unique paths from source origin (0, 0) to destination (m-1, n-1) in a m x n grid. You can only move either in down or right direction.| unique_paths.cpp | Tree Problems | Problem | Solution || :------------ | :----------: ||Iterative Level order traversal of Tree using queue | levelOrderTraversalIterative.cpp ||Recursive Level order traveral of Tree | levelOrderTraversalRecursive.cpp ||ZigZag Traversal of Tree | zigZagTraversal.cpp ||Predecessor and Successor of a given node in Binary Search Tree | predecessorSuccessor.cpp ||Given values of two nodes in a Binary Search Tree, find the Lowest Common Ancestor (LCA). Assume that both the values exist in the tree.| [lowest-common-ancestor.cpp] (tree problems/lowest-common-ancestor.cpp)||Given a binary tree (unlike binary search tree), find the Lowest Common Ancestor (LCA).| lowest-common-ancestor-binary-tree.cpp ||Given a binary tree, print out all of its root-to-leaf paths one per line.| printAllRootToLeafPath.cpp |Determine if a tree is sum tree. A SumTree is a Binary Tree where the value of a node is equal to sum of the nodes present in its left subtree and right subtree. An empty tree is SumTree and sum of an empty tree can be considered as 0. A leaf node is also considered as SumTree.| sumTree.cpp ||Convert a tree to sumTree, such that each node is sum of left and right subtree of the original tree.| convert to sum tree.cpp|| Convert a sorted array to balanced binary search tree.| sortedArrayToBST.cpp || Given a binary tree, generate sum of each vertical column.| verticalSum.cpp || Given a binary tree and key, node with key exists in tree. Find all the ancestors of the node with key, ancestor here are the nodes which are in straight path from node to root.| node ancestors in root path.cpp || Given a binary tree and key, return the level of the node with key. Root is at level 1, and if node with key does not exists in tree, return 0| level of node.cpp || Given a binary tree, find all the paths from root to nodes, whose sum is k. | k sum paths.cpp || Given a binary tree, print its nodes level by level in reverse order. i.e. all nodes present at last level should be printed first followed by nodes of second-last level and so on.. All nodes for any level should be printed from left to right. | reverseLevelOrderTraversal.cpp || Invert a binary tree, recursively and iteratively.| invert a tree.cpp || Given a Binary Search Tree, find ceil and floor of a given key in it. If the given key lie in the BST, then both floor and ceil is equal to that key, else ceil is equal to next greater key (if any) in the BST and floor is equal to previous greater key (if any) in the BST | floor ceil bst.cpp || Find kth smallest element in a binary search tree | kth_smallest.cpp | String Problems | Problem | Solution || :------------ | :----------: || Implementation of Robin-Karp algorithm for string search | robinKarpStringMatching.cpp || Find next permutation of a given string, ie. rearrange the given string sucht a way that is next lexicographically greater string than given string | next permutation.cpp || Implementation of Z algorithm for pattern matching | z.cpp || Test cases for self created string library | pstringtest.cpp | Common Data Structure and logic problems | Problem | Solution || :------------ | :----------: || Print the contents of matrix in a spiral order | matrix spiral print.cpp | Given a M x N matrix, rotate it by R rotations anticlockwise, and show the resulting matrix. | rotate matrix.cpp || Rotate an array by r elements ( left or right ) | arrayrotation.cpp | Given an array of repeating/non-repeating intergeres, determine the first non-repeating int in this array | first non repeating int.cpp || In Quantumland, there are n cities numbered from 1 to n. Here, c i denotes the i th city. There are n−1 roads in Quantumland. Here, c i and c i+1 have a bidirectional road between them for each i < n.There is a rumor that Flatland is going to attack Quantumland, and the queen wants to keep her land safe. The road between c i and c i+1 is safe if there is a guard in c i or c i+1 . The queen has already placed a few guards in some of the cities, but she is not sure if they are enough to keep the roads safe. She wants to know the minimum number of new guards she needs to hire. See comments in solution for input/output details. | savequantamland.cpp || You are given an integer N. Find the digits in this number that exactly divide N (division that leaves 0 as remainder) and display their count. For N=24, there are 2 digits (2 & 4). Both of these digits exactly divide 24. So our answer is 2. See more details in header comment of the solution file. | findDigits.cpp || Encrypt and then decrypts a text using Caeser Cipher. | caeser cipher.cpp || Encrypt and then decrypts a text using Vigenère cipher. | vigenerecipher.cpp || Generate binary numbers between 1 to N efficiently. | n binary.cpp || Implement power function | powerfunction.cpp | Math Problems | Problem | Solution || :------------ | :----------: || Print all the permutations of a string. Example: Permutations of ABC are ABC, ACB, BCA, BAC, CAB, CBA | string permutations.cpp || Euclidean algorithm to find greatest common divisor of two numbers. (Iterative and recursive)| gcd.cpp || Implement pow(x,y) using divide and conquer approach. Try implementing it in O(logn)| pow.cpp || Calculate factorial of large number, say 100 (it will have 158 digits) | factorialof large num.cpp || Generate all possible words from a number entered on a traditional mobile keypad | phone_digits.cpp | Stack Problems | Problem | Solution || :------------ | :----------: || We have series of n daily price quotes for a stock. We need to calculate span of stock's price for all n days. Span for ith day is defined as maximum number of consecutive days, for which the price of the stock was less than or equal to ith day. For stock quotes {100, 60, 70, 65, 80, 85} span will be {1, 1, 2, 1, 4, 5}. Span for day 1 is always 1, now for day 2 stock is at 60, and there is no day befor it when stock was less than 60. So span remains 1. For day 3, the stock is priced at 70, so its span is 2, as previous day it was 60, and so on. | stock span problem.cpp || Given an infix expression, convert it to postfix expression, Example (A+B)*C --> AB+C* | infix to postfix.cpp || Given a string containing just the characters '(', ')', '{', '}', '[' and ']', determine if the input string is valid.The brackets must close in the correct order, "()" and "()[]{}" are all valid but "(]" and "([)]" are not.| valid_parenthesis.cpp | Sort and Search Problems | Problem | Solution || :------------ | :----------: || Given a sorted vector, return first index of the occurrence of a value in vector, if number does not exist, return -1 | first occurrence binary search.cpp || Find the first repeating element in an array of integers. Given an array of integers, find the first repeating element in it. We need to find the element that occurs more than once and whose index of first occurrence is smallest.| firstRepeatingElement.cpp || Given a list of unsorted integers, A={a 1 ,a 2 ,…,a N }, Find the pair of elements that have the smallest absolute difference between them? If there are multiple pairs, find them all.| closestnumbers.cpp || Given a sorted array, determine index of fixed point in this array. If array does not have a fixed point return -1. An array has a fixed point when index of the element is same as index i.e. i == arr[i], Expected time complexity O(logn)| fixedPoint.cpp || Find the maximum element in an array which is first increasing and then decreasing. Input: arr[] = {8, 10, 20, 80, 100, 200, 400, 500, 3, 2, 1}, output : 500. Array may be strictly increasing or decreasing as well. ExpectedTime complexity is O(logn).| findMaximum.cpp || Given an array of positive and/or negative integers, find a pair in the array whose sum is closest to 0.| findClosestPairToZero.cpp || Numeros, the Artist, had two lists A and B, such that B was a permutation of A. Numeros was very proud of these lists. Unfortunately, while transporting them from one exhibition to another, some numbers were left out of A. Can you find the missing numbers? Notes: If a number occurs multiple times in the lists, you must ensure that the frequency of that number in both lists is the same. If that is not the case, then it is also a missing number. You have to print all the missing numbers in ascending order. Print each missing number once, even if it is missing multiple times. The difference between maximum and minimum number in B is less than or equal to 100. . There will be four lines of input: n - the size of the first list, This is followed by n space-separated integers that make up the first list. m - the size of the second list. This is followed by m space-separated integers that make up the second list. Output the missing numbers in ascending order.| missingNumbers.cpp || Find the closest pair from two sorted arrays. Given two sorted arrays and a number x, find the pair whose sum is closest to x and the pair has an element from each array. We are given two arrays ar1[0…m-1] and ar2[0..n-1] and a number x, we need to find the pair ar1[i] + ar2[j] such that absolute value of (ar1[i] + ar2[j] – x) is minimum.| closestPairSorted.cpp || Given an array A of n elements, find three indices i, j and k such that A[i]^2 + A[j]^2 = A[K]^2. O(n2) time complexity and O(1) space complexity | squareSum.cpp || Given an unsorted array arr[0..n-1] of size n, find the minimum length subarray arr[s..e] such that sorting this subarray makes the whole array sorted. | minLengthUnsortedArray.cpp || Find the missing number in Arithmetic Progression | missingNumber2.cpp || Find the common elements in 3 sorted vectors | commonIn3Arrays.cpp || Find all the pairs with a given sum in an unsorted array/vector | find pairs with sum.cpp || Given an array, find peak element in it. A peak element is an element that is greater than its neighbors.| peakelement.cpp || Given a sorted array of distinct non-negative integers, find smallest missing element in it.| smallest missing.cpp || Move all zeros in the vector to the end | movezeros.cpp | Graph Problems | Problem | Solution || :------------ | :----------: || Depth First Traversal of a Graph | dfsDemo.cpp || Breadth First Traversal of a Graph | bfsDemo.cpp || calculate the shortest distance from the start position (Node S) to all of the other nodes in the graph using Dijkstra algorithm. | dijkstra-shortest-reach.cpp || Calculate total weight of Minimum Spanning Tree of a given graph ( sum of weights of edges which forms MST) using Prim's algorithm | primsMST.cpp || Print Minimum Spanning Tree( MST ) of a given graph using Kruskal's algorithm.| kruskalMST.cpp || Create a program to generate a Huffman encoding for each character as a table.| huffman_encoding.cpp | Greedy Problems | Problem | Solution || :------------ | :----------: || Given two integer arrays, A and B, each containing N integers. You are free to permute the order of the elements in the arrays. Is there an permutation A', B' possible of A and B, such that, A' i +B' i ≥ K for all i, where A' i denotes the i th element in the array A' and B' i denotes i th element in the array B'.| two arrays.cpp ||John is taking orders. The i th order is placed by the i th customer at t i time and it takes d i time to procees. What is the order in which the customers will get their orders? (see more details in solutions's comments)| ordersorder.cpp | Leet code Problems | Problem | Solution || :------------ | :----------: || Given a sorted integer array without duplicates, return the summary of its ranges. For example, given [0,1,2,4,5,7], return ["0->2","4->5","7"].| summary ranges.cpp || Given a 2D matrix, with following properties Integers in each row are sorted in ascending from left to right. Integers in each column are sorted in ascending from top to bottom. search2DII.cpp || Given an unsorted integer array, find the first missing positive integer.Example: [1,2,0] should return 3 and [3,4,-1,1] should return 2. Expected time complexity O(n) and solution should use constant space| firstMissingPositiveNum.cpp ||Given an unsorted array of integers, find the length of the longest consecutive elements sequence. For example: Given [100, 4, 200, 1, 3, 2]. The longest consecutive elements sequence is [1, 2, 3, 4]. Return its length: 4. Algorithm should run in O(n) complexity.| longestConsecutiveSeq.cpp ||Given two sorted integer arrays nums1 and nums2, merge nums2 into nums1 as one sorted array.You may assume that nums1 has enough space (size that is greater or equal to m + n) to hold additional elements from nums2. The number of elements initialized in nums1 and nums2 are m and n respectively.| mergeArrays.cpp |Given an array of non-negative integers, you are initially positioned at the first index of the array. Each element in the array represents your maximum jump length at that position. Determine if you are able to reach the last index. For example: A = [2,3,1,1,4], return true. A = [3,2,1,0,4], return false. | jumpGame.cpp ||Given a positive integer, return its corresponding column title as appear in an Excel sheet. For example 1 -> A, 2 -> B,...26 -> Z, 27 -> AA, 28 -> AB, ...705 -> AAC | excelColSheetTitle.cpp ||Given an array nums, write a function to move all 0's to the end of it while maintaining the relative order of the non-zero elements. For example, given nums = [0, 1, 0, 3, 12], after calling your function, nums should be [1, 3, 12, 0, 0].| moveZeroes.cpp ||Given an array of integers, find if the array contains any duplicates. Function should return true if any value appears at least twice in the array, and it should return false if every element is distinct.| containsDuplicate.cpp || Given a list, rotate the list to the right by k places, where k is non-negative. For example: Given 1->2->3->4->5->NULL and k = 2, return 4->5->1->2->3->NULL | rotateList.cpp || Given two words word1 and word2, find the minimum number of steps required to convert word1 to word2. (each operation is counted as 1 step.). You have the following 3 operations permitted on a word: Insert a character Delete a character. Replace a character .| editDistance.cpp ||Given a binary tree, Populate each next pointer to point to its next right node. If there is no next right node, the next pointer should be set to NULL. Initially, all next pointers are set to NULL.You may only use constant extra space.You may assume that it is a perfect binary tree (ie, all leaves are at the same level, and every parent has two children).| connectNextPointers.cpp ||Given n pairs of parentheses, write a function to generate all combinations of well-formed parentheses. For example, given n = 3, a solution set is *"((()))", "(()())", "(())()", "()(())", "()()()"*| generateparenthesis.cpp ||Given an array containing n distinct numbers taken from 0, 1, 2, ..., n, find the one that is missing from the array.For example, Given nums = [0, 1, 3] return 2.| missing number.cpp ||Suppose a sorted array is rotated at some pivot unknown to you beforehand. (i.e., 0 1 2 4 5 6 7 might become 4 5 6 7 0 1 2). Find the minimum element. You may assume no duplicate exists in the array.| findmin rotated.cpp ||Given an array S of n integers, find three integers in S such that the sum is closest to a given number, target. Return the sum of the three integers. You may assume that each input would have exactly one solution.| threeSumClosest.cpp ||Given n non-negative integers a 1 , a 2 , ..., a n , where each represents a point at coordinate (i, a i ). n vertical lines are drawn such that the two endpoints of line i is at (i, a i ) and (i, 0). Find two lines, which together with x-axis forms a container, such that the container contains the most water. Note: You may not slant the container.| maxArea.cpp || Given a binary tree containing digits from 0-9 only, each root-to-leaf path could represent a number. An example is the root-to-leaf path 1->2->3 which represents the number 123. Find the total sum of all root-to-leaf numbers. Example in solution comments | sumRootToLeafNumbers.cpp || Say you have an array for which the ith element is the price of a given stock on day i. If you were only permitted to complete at most one transaction (ie, buy one and sell one share of the stock), design an algorithm to find the maximum profit.| maxProfitStock.cpp || Given a m x n grid filled with non-negative numbers, find a path from top left to bottom right which minimizes the sum of all numbers along its path. Note: You can only move either down or right at any point in time.| minPath.cpp || Count the number of prime numbers less than a non-negative number, n.| countPrimes.cpp || Find all possible combinations of k numbers that add up to a number n, given that only numbers from 1 to 9 can be used and each combination should be a unique set of numbers. Ensure that numbers within the set are sorted in ascending order. Example : for k = 3, n = 9 result would be [[1,2,6], [1,3,5], [2,3,4]], similarly for k = 3, n = 7, result would be [[1,2,4]]. | combinationSum3.cpp || Given a non-negative integer num, repeatedly add all its digits until the result has only one digit. For example: Given num = 38, the process is like: 3 + 8 = 11, 1 + 1 = 2. Since 2 has only one digit, return it. Follow up: Could you do it without any loop/recursion in O(1) runtime?| addDigits.cpp || Given a matrix with cell values 0 or 1. Find the length of the shortest path from (a1, b1) to (a2, b2), such that path can only be constructed through cells which have value 1 and you can only travel in 4 possible directions, i.e. left, right, up and down.| shortestpath maze.cpp || The Hamming distance between two integers is the number of positions at which the corresponding bits are different. Given two integers x and y, calculate the Hamming distance.| hammingdistance.cpp || Given two binary trees and imagine that when you put one of them to cover the other, some nodes of the two trees are overlapped while the others are not. You need to merge them into a new binary tree. The merge rule is that if two nodes overlap, then sum node values up as the new value of the merged node. Otherwise, the NOT null node will be used as the node of new tree.| merge trees.cpp || Write a function that takes a string as input and reverse only the vowels of a string.| reversevowels.cpp || Given a string, sort it in decreasing order based on the frequency of characters.For example: Input: cccbbbbaa Output: bbbcccaa | sortCharByFrequency.cpp ||Product of Array Except Self. Given an array of n integers where n > 1, nums, return an array output such that output[i] is equal to the product of all the elements of nums except nums[i].| product except self.cpp ||Given a sorted array, remove duplicates in place and return the new length. It doesn't matter what is in array beyond the unique elements size. Expected O(1) space and O(n) time complexity.| remove_duplicates.cpp | To restore the repository download the bundle wget https://archive.org/download/github.com-mandliya-algorithms_and_data_structures_-_2018-01-11_22-54-36/mandliya-algorithms_and_data_structures_-_2018-01-11_22-54-36.bundle and run: git clone mandliya-algorithms_and_data_structures_-_2018-01-11_22-54-36.bundle Source: https://github.com/mandliya/algorithms_and_data_structures Uploader: mandliya Upload date: 2018-01-11

Integrating knowledge from multiple sources is an important aspect of automated reasoning systems. In the first part of this series of papers, we presented a uniform declarative framework, based on annotated logics, for amalgamating multiple knowledge bases when these knowledge bases (possibly) contain inconsistencies, uncertainties, and non-monotonic modes of negation. We showed that annotated logics may be used, with some modifications, to mediate between different knowledge bases. The multiple knowledge bases are amalgamated by embedding the individual knowledge bases into a lattice. In this paper, we briefly describe an SLD-resolution-based proof procedure that is sound and complete w.r.t. our declarative semantics. We will then develop an OLDT-resolution-based query processing procedure, MULTI_OLDT, that satisfies two important properties: (1) efficient reuse of previous computations is achieved by maintaining a tablewe describe the structure of this table, and show that table operations can be efficiently executed, and (2) approximate, interruptable query answering is achieved, i.e., it is possible to obtain an intermediate, approximate answer from the QPP by interrupting it at any point in time during its execution. The design of the MULTI_OLDT procedure will include the development of run-time algorithms to incrementally and efficiently update the table.

Integrating knowledge from multiple sources is an important aspect of automated reasoning systems. In the first part of this series of papers, we presented a uniform declarative framework, based on annotated logics, for amalgamating multiple knowledge bases when these knowledge bases (possibly) contain inconsistencies, uncertainties, and non-monotonic modes of negation. We showed that annotated logics may be used, with some modifications, to mediate between different knowledge bases. The multiple knowledge bases are amalgamated by embedding the individual knowledge bases into a lattice. In this paper, we briefly describe an SLD-resolution-based proof procedure that is sound and complete w.r.t. our declarative semantics. We will then develop an OLDT-resolution-based query processing procedure, MULTI_OLDT, that satisfies two important properties: (1) efficient reuse of previous computations is achieved by maintaining a tablewe describe the structure of this table, and show that table operations can be efficiently executed, and (2) approximate, interruptable query answering is achieved, i.e., it is possible to obtain an intermediate, approximate answer from the QPP by interrupting it at any point in time during its execution. The design of the MULTI_OLDT procedure will include the development of run-time algorithms to incrementally and efficiently update the table.

Learn Data Structures and Algorithms with Golang is a practical guide for developers looking to deepen their understanding of core computer science concepts using the Go programming language. Through hands-on examples and clear explanations, this book helps you implement efficient algorithms and master essential data structures to write faster, more scalable code in Go.

Learn Data Structures and Algorithms with Golang is a practical guide for developers looking to deepen their understanding of core computer science concepts using the Go programming language. Through hands-on examples and clear explanations, this book helps you implement efficient algorithms and master essential data structures to write faster, more scalable code in Go.

The Outline of the course was as follows: 1) Computational geometry; 2) Geometrical problems related to robotics; 3) Heuristics for finding approximations for Steiner minimum trees; 4) The grid file as a data structure suited for geometrical computation; 5) Different schemes for representing three-dimensional objects; 6) Visibility problems that occur in VLSI design; 7) Algorithms for point location, convex hull and the maxima of a set of vectors in two and three dimensions; and 8) Merging heaps and some unsolved problems.

The Outline of the course was as follows: 1) Computational geometry; 2) Geometrical problems related to robotics; 3) Heuristics for finding approximations for Steiner minimum trees; 4) The grid file as a data structure suited for geometrical computation; 5) Different schemes for representing three-dimensional objects; 6) Visibility problems that occur in VLSI design; 7) Algorithms for point location, convex hull and the maxima of a set of vectors in two and three dimensions; and 8) Merging heaps and some unsolved problems.

The Outline of the course was as follows: 1) Computational geometry; 2) Geometrical problems related to robotics; 3) Heuristics for finding approximations for Steiner minimum trees; 4) The grid file as a data structure suited for geometrical computation; 5) Different schemes for representing three-dimensional objects; 6) Visibility problems that occur in VLSI design; 7) Algorithms for point location, convex hull and the maxima of a set of vectors in two and three dimensions; and 8) Merging heaps and some unsolved problems.

Matroids are discrete mathematical structures that appear in a variety of applications. They are structures for which greedy algorithm gives an optimal solution, and when interested characterize such problems as minimum weight maximum cardinality bipartite matching. In this paper we study a class of combinatorial problems from a matroid point of view. Consider a matroid of rank n in which each element has a real-valued cost and one of d 1 colors. A class of matroid intersection problems is studied in which one of the matroids is a partition matroid that specifies that base have 9 sub k elements of color j, for j = 12 =1, 2, ..., d. Relationships are characterized among the solutions to the family of problems generated when the vector (q sub 1, q sub,... q sub d) is allowed to range over all values that sum to n. A fast algorithm is given for solving such matroid intersection problems when d is small. A characterization is presented for how the solution changes when one element changes in cost. Data structures are given for updating the solution on-line each time the cost of an arbitrary matroid element is modified. Efficient update algorithms are given for maintaining a color-constrained minimum spanning tree in either a general or a planar graph. An application for the techniques to finding a minimum spanning tree with several degree-constrained vertices is described.

A description of the discrete-pattern matching process is presented with the key elements described. Six data structure approaches and related search algorithms are presented. Twelve programs were coded to implement five out of the six structures/algorithms using packed and unpacked approaches on a CYBER 74. Runs were made with twelve different data files using Fortran, English, and random text. The effect of the number of patterns in the data structure and the expected incidence in the text were included. The best data structures/algorithms were a finite state automata and an alternate/successor linked list. (Author)

Trimester 2, 2022/2023

Trimester 2, 2022/2023

Inroduction to Data structures and Algorithms || Deepali Srivastava

In this Learning Data Structures and Algorithms video training course, Rod Stephens will teach you how to analyze and implement common algorithms used in data processing. This course is designed for the absolute beginner, meaning no previous programming experience is required. You will start by learning about the complexity theory, then jump into learning about numerical algorithms, including randomizing arrays, prime factorization, and numerical integration. From there, Rod will teach you about linked lists, such as singly linked lists, sorted, and doubly linked lists. This video tutorial also covers arrays, stacks and queues, and sorting. You will also learn about searching, hash tables, recursion, and backtracking algorithms. Finally, you will cover trees, balanced trees, decision trees, and network algorithms. Once you have completed this video training course, you will be fully capable of analyzing and implementing algorithms, as well as be able to select the best algorithm for various situations. Working files are included, allowing you to follow along with the author throughout the lessons.

Trimester 2 - 2019/2020

Trimester 1 - 2017/2018

Trimester 1 - 2017/2018

This report contains two independent papers on range searching. A range search retrieves from a file all records which conjunctively satisfy a set of range requirements for the keys; that is, each key must lie in some specified range. Range searching arises in many applications, such as data base management and statistical computing. The first paper in this report, 'A survey of algorithms and data structures for range searching' by J. L. Bentley and J. H. Friedman, describes the known 'logical structures' which can be used for range searching and then discusses the implementation of those structures in different storage media. This paper is slanted towards the practitioner. The second paper, 'Efficient worst-case data structures for range searching' by J. L. Bentley and H. A. Maurer, is more theoretical. Two new classes of data structures are proposed for range searching, establishing bounds on the asymptotic complexity of the problem. (Author)

To facilitate flexible and efficient structural bioinformatics analyses, new functionality for three-dimensional structure processing and analysis has been introduced into PyCogent -- a popular feature-rich framework for sequence-based bioinformatics, but one which has lacked equally powerful tools for handling stuctural/coordinate-based data. Extensible Python modules have been developed, which provide object-oriented abstractions (based on a hierarchical representation of macromolecules), efficient data structures (e.g. kD-trees), fast implementations of common algorithms (e.g. surface-area calculations), read/write support for Protein Data Bank-related file formats and wrappers for external command-line applications (e.g. Stride). Integration of this code into PyCogent is symbiotic, allowing sequence-based work to benefit from structure-derived data and, reciprocally, enabling structural studies to leverage PyCogent's versatile tools for phylogenetic and evolutionary analyses.

Kelvin Lau and Vincent Ngo of "Data Structures and Algorithms in Swift" show why to have these into your core knowledge list.

Kelvin Lau and Vincent Ngo of "Data Structures and Algorithms in Swift" show why to have these into your core knowledge list.

Kelvin Lau and Vincent Ngo of "Data Structures and Algorithms in Swift" show why to have these into your core knowledge list.

xxv, 833, 12 p. : 23 cm

vi, 312 pages : 28 cm

This report provides an (updated) overview of {\sl Grafalgo}, an open-source library of graph algorithms and the data structures used to implement them. The programs in this library were originally written to support a graduate class in advanced data structures and algorithms at Washington University. Because the code's primary purpose was pedagogical, it was written to be as straightforward as possible, while still being highly efficient. Grafalgo is implemented in C++ and incorporates some features of C++11. The library is available on an open-source basis and may be downloaded from https://code.google.com/p/grafalgo/. Source code documentation is at www.arl.wustl.edu/\textasciitilde jst/doc/grafalgo. While not designed as production code, the library is suitable for use in larger systems, so long as its limitations are understood. The readability of the code also makes it relatively straightforward to extend it for other purposes.

This report provides an (updated) overview of {\sl Grafalgo}, an open-source library of graph algorithms and the data structures used to implement them. The programs in this library were originally written to support a graduate class in advanced data structures and algorithms at Washington University. Because the code's primary purpose was pedagogical, it was written to be as straightforward as possible, while still being highly efficient. Grafalgo is implemented in C++ and incorporates some features of C++11. The library is available on an open-source basis and may be downloaded from https://code.google.com/p/grafalgo/. Source code documentation is at www.arl.wustl.edu/\textasciitilde jst/doc/grafalgo. While not designed as production code, the library is suitable for use in larger systems, so long as its limitations are understood. The readability of the code also makes it relatively straightforward to extend it for other purposes.

Trimester 3 - 2016 / 2017

Although large amounts of programming knowledge are available to human programmers in the form of books and articles, very little of this knowledge is available in a form suitable for use by a machine in performing programming tasks automatically. The principal goal of the research reported here is the explication of programming knowledge to a sufficient level of detail that it can be used effectively by a machine. The programming task considered in this experiment is that of constructing concrete implementations of abstract algorithms in the domain of symbolic programming. Knowledge about several aspects of symbolic programming has been expressed as a collection of four hundred refinement rules. The rules deal primarily with collections and mappings and ways of manipulating such structures, including several enumeration, sorting and searching techniques. The principal representation techniques covered include the representation of sets as linked lists and arrays (both ordered and unordered), and the representation of mappings as tables, sets of pairs, property list markings, and inverted mappings (indexed by range element). In addition to these general constructs, many low-level programming details are covered (such as the use of variables to store values).

Dr. Dobb's Essential books on algorithms and data structures: Contributors: Cormen, Thomas H. Introduction to algorithms Amsbury, Wayne, 1935- Data structures Horowitz, Ellis. Fundamentals of data structure Plum, Thomas, 1943- Reliable data structures in C Weiss, Mark Allen. Data structures and Algorithm Analysis in C Flamig, Bryan. Practical data structures in C++ Korsh, James F., 1938- Data structures, algorithms and program style using C

Tri 2 2018/2019

Tri 2 2018/2019

TRI 2, 2019/2020

TRI 2, 2019/2020

TRI 2, 2019/2020

TRI 2, 2019/2020

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Multi-adaptive Galerkin methods are extensions of the standard continuous and discontinuous Galerkin methods for the numerical solution of initial value problems for ordinary or partial differential equations. In particular, the multi-adaptive methods allow individual and adaptive time steps to be used for different components or in different regions of space. We present algorithms for efficient multi-adaptive time-stepping, including the recursive construction of time slabs and adaptive time step selection. We also present data structures for efficient storage and interpolation of the multi-adaptive solution. The efficiency of the proposed algorithms and data structures is demonstrated for a series of benchmark problems.

Multi-adaptive Galerkin methods are extensions of the standard continuous and discontinuous Galerkin methods for the numerical solution of initial value problems for ordinary or partial differential equations. In particular, the multi-adaptive methods allow individual and adaptive time steps to be used for different components or in different regions of space. We present algorithms for efficient multi-adaptive time-stepping, including the recursive construction of time slabs and adaptive time step selection. We also present data structures for efficient storage and interpolation of the multi-adaptive solution. The efficiency of the proposed algorithms and data structures is demonstrated for a series of benchmark problems.

Trimester 2 - 2015 / 2016

Includes bibliographies

Includes bibliographies

Trimester 1 - 2019/2020

Trimester 1 - 2019/2020

Jacinta Catherine Richardson http://linux.conf.au/schedule/presentation/69/ Data structures and algorithms are essential tools in the developer's toolkit, yet it is an area that is too easy to get behind in. The essential algorithms you learned whenever you did Computer Science probably included: 1. Shortest path and tree (and graph) traversals - depth-first, breadth first, cycle management 2. Sorting - quick sort, bubble sort, merge sort, binary sort 3. Searching - binary trees, B-trees, B+trees, red-black trees 4. Specific problems - knapsack problem, painters algorithm, decision trees 5. Algorithm tecniques - divide and conquer, backtracking, creating NFAs You might also have learned the Fast Fourier Transform (FFT) and the Convolution theorem. For data structures you might have learned: 1. Matrices 2. Linked lists 3. Hashing 4. Singular Value Decomposition (SVD) from Linear Algebra This talk will overview some of the more interesting parts of the above (such as the FFT, convolution theorem, and SVD) before providing an overview of some of the more interesting algorithms developed in the last 16 years.

Learn Data Structures And Algorithms For Free 📈

Learn Data Structures And Algorithms For Free 📈