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# Find minimum number of coins that make a given value Dynamic programming

### Minimum number of coins that make a given valu

• g Algorithms. There is a list of coin C (c1, c2, Cn) is given and a value V is also given. Now the problem is to use the
• imum number of coins. The
• imum number of coins. The
• imum number of coins required to get 11. We'll also assume that there are unlimited supply of coins. We're going to use dynamic program

This is indeed the minimum number of coins required to get 11. We'll also assume that there are unlimited supply of coins. We're going to use dynamic programming to solve this problem. We'll use a 2D array dp[n][total + 1] where n is the number of different denominations of coins that we have. For our example, we'll need dp After finding the minimum number of coins use the Backtracking Technique to track down the coins used, to make the sum equals to X. In backtracking, traverse the array and choose a coin which is smaller than the current sum such that dp [current_sum] equals to dp [current_sum - chosen_coin]+1. Store the chosen coin in an array

### Find minimum number of coins that make a given value

1. imum number of coins required to make change of amount j
2. imum possible number of coins we can use. If the value at any array [i-k] + 1 is lesser than the existing value at array [i], replace the value at array [i] with the one at array [i-k] +1
3. imum number of coins the sum of which is S (we can use as many coins of one type as we want), or report that it's not possible to select coins in such a way that they sum up to S. Example: Given coins with values 1, 3, and 5. And the sum S is 11

Given coins of certain denominations and a total, how many minimum coins would you need to make this total.https://github.com/mission-peace/interview/blob/ma.. The order of coins doesn't matter. For example, for N = 4 and S = {1,2,3}, there are four solutions: {1,1,1,1}, {1,1,2}, {2,2}, {1,3}. So output should be 4. For N = 10 and S = {2, 5, 3, 6}, there are five solutions: {2,2,2,2,2}, {2,2,3,3}, {2,2,6}, {2,3,5} and {5,5}. So the output should be 5 Find minimum number of coins (using Dynamic Programming) | GeeksforGeeks - YouTube. Watch later. Share. Copy link. Info. Shopping. Tap to unmute. If playback doesn't begin shortly, try restarting.

Example 1: Suppose you are given the coins 1 cent, 5 cents, and 10 cents with N = 8 cents, what are the total number of combinations of the coins you can arrange to obtain 8 cents. Input: N=8 Coins : 1, 5, 10 Output: 2 Explanation: 1 way: 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 = 8 cents. 2 way: 1 + 1 + 1 + 5 = 8 cents Your dynamic programming algorithm is basically correct (except for the bug that @janos found). That's a good start. You've declared the function as static, which is an improvement over your previous questions.However, it's private, which makes the function not so useful.I'm not a fan of the final keywords for the parameters, as they add noise without adding much protection As the programmer of a vending machine controller your are required to compute the minimum number of coins that make up the required change to give back to customers. An efficient solution to this problem takes a dynamic programming approach, starting off computing the number of coins required for a 1 cent change, then for 2 cents, then for 3 cents, until reaching the required change and each time making use of the prior computed number of coins. Write a program containing the functio

### dynamic-programming - Minimum Number of Coins to Get Total

1. ith state of dp : dp [i] : Minimum number of coins required to sum to i cents. In this approach, we move from the base case to the desired value of the sum. base dp =0 , where for 0 cents of value we need 0 coins. Initially, we will fill the dp [] array with INT_MAX and dp =0 as for 0 cents we need 0 coins
2. g - Coin Change Problem. August 31, 2019 June 27, 2015 by Sumit Jain. Objective: Given a set of coins and amount, Write an algorithm to find out how many ways we can make the change of the amount using the coins given. This is another problem in which i will show you the advantage of Dynamic program
3. imum number of coins up to 19, and I have a feeling that you actually want it for 20. In which case you would need:
4. ations in Indian currency, i.e., we have an infinite supply of { 1, 2, 5, 10, 20, 50, 100, 500, 1000} valued coins/notes, what is the
5. When there isn't a value of 1, the function will give an answer of the best number of coins under the price. def find_change(coins, money): coins = sorted(coins, reverse=True) coincount = 0 for coin in coins: while money >= coin: money = money - coin coincount += 1 return coincoun

What is the minimum number of coins need to change 9 cents? To solve this problem using Dynamic Programming, the first thing we have to do is finding right recurrences for this problem. We can see that the minimum number of coins need to change 9 cents is the minimum of coins that we need to change 3(= 9-6) or 4(= 9-5) or 8(= 9-1). So we. Coin Change Problem: Minimum number of coins Dynamic Programming - YouTube. Get Grammarly. www.grammarly.com

Minimum number of coins. To find the min. no. of coins for amount Rs. 6 we have to take the value from C[p] array. So, minimum coins required to make change for amount Rs. 6 = C = 2. Coins in the optimal solution. To know the coins selected to make the change we will use the S[p] array Step 1: Set a = A Step 2: If a > 0 then Print d[S[a. Dynamic Programming - Coin In a Line Game Problem. August 31, 2019 May 8, 2016 by Sumit Jain. Objective: In this game, which we will call the coins-in-a-line game, an even number, n, of coins, of various denominations from various countries, are placed in a line. Two players, who we will call Alice and Bob, take turns removing one of the coins from either end of the remaining line of coins. Dynamic Programming A dime plus the minimum number of coins to make change for \(11 - 10 = 1\) cent (1) Either option 1 or 3 will give us a total of two coins which is the minimum number of coins for 11 cents. Figure 4: Minimum Number of Coins Needed to Make Change ¶ Figure 5: Three Options to Consider for the Minimum Number of Coins for Eleven Cents ¶ Listing 8 is a dynamic programming. This is classic dynamic programming problem to find minimum number of coins to make a change. This problem has been featured in interview rounds of Amazon, Morgan Stanley, Paytm, Samsung etc. Problem statement: Given a value P, you have to make change for P cents, given that you have infinite supply of each of C { C 1, C 2, ,C n} valued coins Write a program to find the minimum number of coins required to match the given amount value. Example You have coins 1, 5, 7, 9, 11. Calculate minimum number of coins required for any input amount 250. Example: AMount 6 will require 2 coins (1, 5). Amount 25 will require 3 coins (5, 9, 11). This question was asked in the coding round of Byju's interview. You can use Dynamic programming.

Given an infinite supply of coins of values: {C1, C2 Cn} and a sum. Find minimum number of coins that can represent the sum. Java solution to find minimum number of coins using dynamic programming. Java visualization is provided in algorithm visualization section. Example 1:values: {2, 5, 3} sum = 5Then 5 can be represented as: 2 + 3 = 2 coins5 = 1 coin Therefore, minimum number of coins. Find minimum number of coins which result in a given sum We are given few denominations of coins, we can use each denomination as many number of times as we want and arrive to a given sum of money. For e.g. we are given denominations 1, 3, 5, 6, 7 and we have to arrive to 100 rupees Find Complete Code at GeeksforGeeks Article: http://www.geeksforgeeks.org/greedy-algorithm-to-find-minimum-number-of-coins/Practice Problem Online Judge: htt..

### dynamic programming - Minimum number of coins for a given

Coin change is the problem of finding the number of ways to make change for a target amount given a set of denominations. It is assumed that there is an unlimited supply of coins for each denomination. An example will be finding change for target amount 4 using change of 1,2,3 for which the solutions are (1,1,1,1), (2,2), (1,1,2), (1,3). As you. In this problem, we will use a greedy algorithm to find the minimum number of coins/ notes that could makeup to the given sum. For this we will take under consideration all the valid coins or notes i.e. denominations of { 1, 2, 5, 10, 20, 50 , 100, 200 , 500 ,2000 } Dynamic Programming Solution to the Coin Changing Problem (1) Characterize the Structure of an Optimal Solution. The Coin Changing problem exhibits opti- mal substructure in the following manner. Consider any optimal solution to making change for n cents using coins of denominations d 1;d 2;:::;d k. Now consider breaking that solution into two di erent pieces along any coin boundary. Suppose.

We will only concentrate on computing the number of coins. We will later recreate the solution. Let C[p] be the minimum number of coins needed to make change for p cents. Let x be the value of the rst coin used in the optimal solution. Then C[p] = 1+C[p x] . Problem:We don't knowx. Answer:We will try all possiblexand take the minimum. C[p. Write a method to compute the smallest number of coins to make up the given amount. If the amount cannot be made up by any combination of the given coins, return -1. For example: Given [2, 5, 10] and amount=6, the method should return -1. Given [1, 2, 5] and amount=7, the method should return 2. Java Solution 1 - Dynamic Programming (Looking Backward) The solution one use a 2-D array for DP. Maximum Value Contiguous Subsequence. Given a sequence of n real numbers A(1) A(n), determine a contiguous subsequence A(i) A(j) for which the sum of elements in the subsequence is maximized. Making Change. You are given n types of coin denominations of values v(1) v(2) v(n) (all integers). Assume v(1) = 1, so you can always make.

Finding n th Finobacci number in O(log n) Note: The method described here for finding the n th Fibonacci number using dynamic programming runs in O(n) time. There is still a better method to find F(n), when n become as large as 10 18 ( as F(n) can be very huge, all we want is to find the F(N)%MOD , for a given MOD ) I also want to share Michal's amazing answer on Dynamic Programming from Quora. Imagine you have a collection of N wines placed next to each other on a shelf. For simplicity, let's number the wines from left to right as they are standing on the shelf with integers from 1 to N, respectively.The price of the i th wine is pi. (prices of different wines can be different)

### Generate a combination of minimum coins that sums to a

Also, maximum number of coins that can be used for a particular denomination d i = N/d i. So, if we run a loop from 0 to N/d i for i th denomination and consider all values in that range, then we can consider the remaining denominations for other values. Continuing in this fashion, we can find both the solutions - minimum no of coins and. You are given an integer array coins representing coins of different denominations and an integer amount representing a total amount of money.. Return the fewest number of coins that you need to make up that amount.If that amount of money cannot be made up by any combination of the coins, return -1.. You may assume that you have an infinite number of each kind of coin Given a value V and array coins[] of size M, the task is to make the change for V cents, given that you have an infinite supply of each of coins{coins 1, coins 2 coins m} valued coins.Find the minimum number of coins to make the change. If not possible to make change then output -1. Example 1: Input: V = 30, M = 3, coins[] = {25, 10, 5} Output: 2 Explanation: Use one 25 cent coin and one. I can now run a script to find the minimum amount of change for \$120. print minimum_bills_to_make_change(120) 2. If you are learning Dynamic Programming from your computer science and algorithms courses like me, I hope you find this article useful. I hope to see you on Twitter. I am KoderDojo. Best Wishes We then give a formal characterization of dynamic programming under certainty, followed by an in-depth example dealing with optimal capacity expansion. Other topics covered in the chapter include the discounting of future returns, the relationship between dynamic-programming problems and shortest paths in networks, an example of a continuous-state-space problem, and an introduction to dynamic.

### Minimum Coin Change Problem TutorialHorizo

Explanation: Dynamic programming calculates the value of a subproblem only once, while other methods that don't take advantage of the overlapping subproblems property may calculate the value of the same subproblem several times. So, dynamic programming saves the time of recalculation and takes far less time as compared to other methods that don't take advantage of the overlapping. You are given coins of different denominations and a total amount of money. Write a function to compute the number of combinations that make up that amount. You may assume that you have infinite number of each kind of coin. Example 1: Input: amount = 5, coins = [1, 2, 5] Output: 4 Explanation: there are four ways to make up the amount: 5=5 5=2+2+1 5=2+1+1+1 5=1+1+1+1+1 Example 2: Input: amount. The change-making problem addresses the question of finding the minimum number of coins (of certain denominations) that add up to a given amount of money. It is a special case of the integer knapsack problem, and has applications wider than just currency.. It is also the most common variation of the coin change problem, a general case of partition in which, given the available denominations of. The value of each coin is already given. Can you determine the number of ways of making change for a particular number of units using the given types of coins? Example: If you have 3 types of coins, and the value of each type is given as 1,2,3 respectively, you can make change for 4 units in four ways

It is simple - for each coin j, V j ≤i, look at the minimum number of coins found for the i-V j sum (we have already found it previously). Let this number be m . If m+1 is less than the minimum number of coins already found for current sum i , then we write the new result for it 8.2/CoinChangingRevisited 333 8.1),fn isgivenintermsofsmallersubproblemsfn−1andfn−2.Theparam- eteristhesubscript. Inthissection,tocomputetheminimumnumberof coins. Dynamic programming is breaking down a problem into smaller sub-problems, solving each sub-problem and storing the solutions to each of these sub-problems in an array (or similar data structure) so each sub-problem is only calculated once. It is both a mathematical optimisation method and a computer programming method. Optimisation problems seek the maximum or minimum solution Dynamic programming with tabulation. As an alternative, we can use tabulation and start by filling up the memo table. Note that the order of computation matters: to compute the value memo[i][j], the values of memo[i+1][j] and memo[i][j-1] must first be known Platform to practice programming problems. Solve company interview questions and improve your coding intellec

### Dynamic Programming: Examples, Common Problems, and Solution

The algorithm should return an array C where C[i] is the number of coins of value V[i] to return as change and m the minimum number of coins it took. You must return exact change so . The objective is to minimize the number of coins returned or: a) Describe and give pseudocode for a dynamic programming algorithm to find the minimum number of coins to make change for A. b) What is the. Given a set of positive integers, and a value sum, determine if there is a subset of the given set with sum equal to given sum. Coin Change Problem (Total number of ways to get the denomination of coins, coming soon) Given an unlimited supply of coins of given denominations, find the total number of distinct ways to get a desired change Step 3 (the crux of the problem): Now, we want to begin populating our table. As with all dynamic programming solutions, at each step, we will make use of our solutions to previous sub-problems Given an amount and the denominations of coins available, determine how many ways change can be made for amount. There is a limitless supply of each coin type. Example. There are ways to make change for : , , and . Function Description. Complete the getWays function in the editor below. getWays has the following parameter(s) This is Step 4 of the dynamic programming paradigm in which we construct an optimal solution from computed information. The array s[i, j] can be used to extract the actual sequence. The basic idea is to keep a split marker in s[i, j] that indicates what is the best split, that is, what value of k leads to the minimum value of m[i, j]

### N coins problem with sum equal to S - Dynamic programmin

Coin change-making problem: Given an unlimited supply of coins of given denominations, find the minimum number of coins required to get the desired change Introduction of Dynamic Programming. Dynamic Programming is the most powerful design technique for solving optimization problems. Divide & Conquer algorithm partition the problem into disjoint subproblems solve the subproblems recursively and then combine their solution to solve the original problems Let's take the price table given above and find the optimal revenue for each length. After finding the solution of the problem, let's code the solution. Code for Rod cutting problem. Let's look at the top-down dynamic programming code first. Top Down Code for Rod Cutting. We need the cost array (c) and the length of the rod (n) to begin with, so we will start our function with these two - TOP. Dynamic Programming Dynamic programming is a useful mathematical technique for making a sequence of in- terrelated decisions. It provides a systematic procedure for determining the optimal com-bination of decisions. In contrast to linear programming, there does not exist a standard mathematical for-mulation of the dynamic programming problem. Rather, dynamic programming is a gen-eral. Objective: Given two string sequences, write an algorithm to find the length of longest subsequence present in both of them. These kind of dynamic programming questions are very famous in the interviews like Amazon, Microsoft, Oracle and many more. What is Longest Common Subsequence: A longest subsequence is a sequence that appears in the same relative order, but not necessarily contiguous(not.

Let's start by having the values of the coins in an array in reverse sorted order i.e., coins = [20, 10, 5, 1]. Now if we have to make a value of n using these coins, then we will check for the first element in the array (greedy choice) and if it is greater than n, we will move to the next element, otherwise take it Topcoder is a crowdsourcing marketplace that connects businesses with hard-to-find expertise. The Topcoder Community includes more than one million of the world's top designers, developers, data scientists, and algorithmists. Global enterprises and startups alike use Topcoder to accelerate innovation, solve challenging problems, and tap into specialized skills on demand The rest of the answers gave a pretty representative sample of dynamic programming questions and you can always find more online (ex. LeetCode or GeeksForGeeks). Keep in mind that these are all great problems for learning dynamic programming, but. In this dynamic programming problem we have n items each with an associated weight and value (benefit or profit). The objective is to fill the knapsack with items such that we have a maximum profit without crossing the weight limit of the knapsack. Since this is a 0 1 knapsack problem hence we can either take an entire item or reject it completely. We can not break an item and fill the. Coin Change Medium Accuracy: 47.19% Submissions: 18943 Points: 4 Given a value N, find the number of ways to make change for N cents, if we have infinite supply of each of S = { S 1 , S 2 ,. , S M } valued coins

### Coin Changing Minimum Number of Coins Dynamic programming

You are given n types of coin denominations of values v1 < v2 < < vn (all integers). Assume v1 = 1, so you can always make change for any integer amount of money C. You want to make change for C amount of money with as few coins as possible. We will solve this using Dynamic Programming. Let M(i, c) denote the minimum number of coins needed to make a change for c when we are allowed only. Solving with Dynamic Programming. The problem already shows optimal substructure and overlapping sub-problems.. r(i) = maximum revenue achieved by applying 0, 1,.(i-1) cuts respectively to a rod

The coin problem (also referred to as the Frobenius coin problem or Frobenius problem, after the mathematician Ferdinand Frobenius) is a mathematical problem that asks for the largest monetary amount that cannot be obtained using only coins of specified denominations. For example, the largest amount that cannot be obtained using only coins of 3 and 5 units is 7 units Dynamic programming is both a mathematical optimization method and a computer programming method. The method was developed by Richard Bellman in the 1950s and has found applications in numerous fields, from aerospace engineering to economics.. In both contexts it refers to simplifying a complicated problem by breaking it down into simpler sub-problems in a recursive manner ip a fair coin ten times. Find the probability of the following events. [Total: 5 points] (a) The number of heads and the number of tails are equal. [1 point] Solution: There must be 5 tails and 5 heads. There are 10 5 ways to pick 5 heads out of 10 coins ips, and a total of 210 head/tail sequences (of length 10). Therefore the probability of 5. should provide insight into the scope of integer-programming applications and give some indication of why many practitioners feel that the integer-programming model is one of the most important models in management science. Second, we consider basic approaches that have been developed for solving integer and mixed-integer programming problems. 9.1 SOME INTEGER-PROGRAMMING MODELS Integer.

Dynamic Programming — Predictable and Preparable. One of the reasons why I personally believe that DP questions might not be the best way to test engineering ability is that they're predictable and easy to pattern match. They allow us to filter much more for preparedness as opposed to engineering ability. These questions typically seem pretty complex on the outside, and might give you an. CodeChef - A Platform for Aspiring Programmers. CodeChef was created as a platform to help programmers make it big in the world of algorithms, computer programming, and programming contests.At CodeChef we work hard to revive the geek in you by hosting a programming contest at the start of the month and two smaller programming challenges at the middle and end of the month Output of program: If the minimum occurs two or more times in the array then the index at which it occurs first is printed or minimum value at the smallest index. You can modify the code to print the largest index at which the minimum occurs. You can also store all indices at which the minimum occurs in the array Maximum values, returned as a scalar, vector, matrix, or multidimensional array. size(M,dim) is 1 , while the sizes of all other dimensions match the size of the corresponding dimension in A , unless size(A,dim) is 0 [LeetCode - Dynamic Programming] Coin Change. Coin Change You are given coins of different denominations and a total amount of money amount. Write a function to compute the fewest number of coins that you need to make up that amount. If that amount of money cannot be made up by any combination of the coins, return -1. Example 1: coins = [1, 2, 5], amount = 11 return 3 (11 = 5 + 5 + 1) Example.

[Coin Change Problem] By using the dynamic programming method, look. for a combination of the minimum coin change that can be formed from a nominal amount of 284 using banknotes with a nominal value of 1, 5, 10, 25, 50 and 100 The amount can be written as (59+1),(50+10),(30+30) or (20+40). Consider a function howmany(amt) that finds the minimum number of coins required to make an amount amt. If howmany(amt) is called, it finds the minimum of howmany(59), howmany(50), howmany(30) and howmany(20), adds 1 to the result and gives this as the value of the function. This. Dynamic Programming : Given an infinite supply of coins of denominations {20,10,5,1}, find out total number of way to make change of given amount 'n' ! with the given set of coins?: make-change ( cents coins -- ways ) members [ ] inv-sort-with ! Sort coins in descending order. recursive-count ; From the listener: USE: rosetta.coins ( scratchpad ) 100 { 25 10 5 1 } make-change . 242 ( scratchpad ) 100000 { 100 50 25 10 5 1 } make-change . 13398445413854501 This algorithm is slow. A test machine needed 1 minute to run 100000 { 100 50 25 10 5.  ### Coin Change DP-7 - GeeksforGeek

2.7. Mathematical optimization: finding minima of functions¶. Authors: Gaël Varoquaux. Mathematical optimization deals with the problem of finding numerically minimums (or maximums or zeros) of a function. In this context, the function is called cost function, or objective function, or energy.. Here, we are interested in using scipy.optimize for black-box optimization: we do not rely on the. Give a dynamic-programming solution to the 0-1 the order of the items when sorted by increasing weight is the same as their order when sorted by decreasing value. Give an efficient algorithm to find an optimal solution to this variant of the knapsack problem, and argue that your algorithm is correct. 17.2-4. Professor Midas drives an automobile from Newark to Reno along Interstate 80. His. Data Structures - Dynamic Programming. Dynamic programming approach is similar to divide and conquer in breaking down the problem into smaller and yet smaller possible sub-problems. But unlike, divide and conquer, these sub-problems are not solved independently. Rather, results of these smaller sub-problems are remembered and used for similar. To find maximum and minimum values in an array in Java you can use one of the following options-Iterate the array and look for the maximum and minimum values. See example. You can also write a recursive method to recursively go through the array to find maximum and minimum values in an array. See example Adding three numbers is equivalent to adding the first two numbers, and then adding these two numbers again. (Note, in Matlab, a function can be called without all the arguments. The nargin function tells the computer how many values were specified. Thus add_numbers(1) would have an nargin of 1; add_numbers(1,1) would have an nargin of 2; add.

### Find minimum number of coins (using Dynamic Programming

Making change: You are given n types of coins with values v 1;:::;v n and a cost C. You may assume v 1 = 1 so that it is always possible to make any cost. Give an algorithm for nding the smallest number of coins required to sum to C exactly. For example, assume you coins of values 1, 5, and 10. Then the smallest number of coins to make 26 is 4: 2 coins of value 10, 1 coin of value 5, and 1. Counting Coins. This problem is to count to a desired value by choosing the least possible coins and the greedy approach forces the algorithm to pick the largest possible coin. If we are provided coins of ₹ 1, 2, 5 and 10 and we are asked to count ₹ 18 then the greedy procedure will be −. 1 − Select one ₹ 10 coin, the remaining count is Give the number of recursive calls used by mcCarthy() you must completely fill up your tank. Assume that you start with a full tank and that the d[i] are integers. Use dynamic programming to find a minimum cost sequence of stops. Unix diff. The Unix diff program compares two files line-by-line and prints out places where they differ. Write a program Diff.java that reads in two files. The dynamic programming of Richard Bellman is an alternative to the calculus of variations. Extrema. The A sufficient condition for a minimum is given in the section Variations and sufficient condition for a minimum . Example. In order to illustrate this process, consider the problem of finding the extremal function y = f (x) , which is the shortest curve that connects two points (x 1, y 1.   The problem of finding the maximum of a prefix of an array (which changes) is a standard problem that can be solved by many different data structures. For instance we can use a Segment tree or a Fenwick tree Given an `M × N` matrix, calculate the maximum sum submatrix of size `k × k` in it in `O(M × N)` time. For example, consider the following `5 × 5` matrix Note: Excel times are fractional values, which explains the long decimal values. The IF function acts like a filter. Only time values associated with TRUE make it through the filter, other values are replaced with FALSE. The IF function delivers this array directly to the MIN function, returns the minimum value in the array. FALSE values are. C Program to Find Largest Number Using Dynamic Memory Allocation In this example, you will learn to find the largest number entered by the user in a dynamically allocated memory. To understand this example, you should have the knowledge of the following C programming topics The Coin Change problem is the problem of finding the number of ways of making changes for a particular amount of cents, , using a given set of denominations . It is a general case of Integer Partition, and can be solved with dynamic programming   Consider an example. Let's say we flipped a coin 100 times and observed 52 heads and 48 tails. We want to come up with a model that will predict the number of heads we'll get if we kept flipping another 100 times. Formalising the problem a bit, let's think about the number of heads obtained from 100 coin flips. Given that You are given a string s of lower case english alphabets. You can choose any two characters in the string and replace all the occurences of the first character with the second character and replace all the occurences of the second character with the first character. Your aim is to find the lexicographically smallest string that can be obtained by doing this operation at most once. Example 1. C++ Program to Find Largest Element of an Array. This program takes n number of element from user (where, n is specified by user) and stores data in an array. Then, this program displays the largest element of that array using loops

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