"from collections import deque
def updateword(words, startword, end_word):
if end_word not in words:
return None # Early exit if end_word is not in the dictionary
queue = deque([(start_word, 0)]) # (word, steps)
visited = set([start_word]) # Keep track of visited words
while queue:
word, steps = queue.popleft()
if word == end_word:
return steps # Found the target word, return steps
for i in range(len(word)):
"
叶 路. - "from collections import deque
def updateword(words, startword, end_word):
if end_word not in words:
return None # Early exit if end_word is not in the dictionary
queue = deque([(start_word, 0)]) # (word, steps)
visited = set([start_word]) # Keep track of visited words
while queue:
word, steps = queue.popleft()
if word == end_word:
return steps # Found the target word, return steps
for i in range(len(word)):
"See full answer
"Sorted the array and stored the minimum difference in a variable and then traversed the array for the pairs having minimum difference"
Aashka C. - "Sorted the array and stored the minimum difference in a variable and then traversed the array for the pairs having minimum difference"See full answer
"Reversing a linked list is a very popular question. We have two approaches to reverse the linked list: Iterative approach and recursion approach.
Iterative approach (JavaScript)
function reverseLL(head){
if(head === null) return head;
let prv = null;
let next = null;
let cur = head;
while(cur){
next = cur.next; //backup
cur.next = prv;
prv = cur;
cur = next;
}
head = prv;
return head;
}
Recursion Approach (JS)
function reverseLLByRecursion("
Satyam S. - "Reversing a linked list is a very popular question. We have two approaches to reverse the linked list: Iterative approach and recursion approach.
Iterative approach (JavaScript)
function reverseLL(head){
if(head === null) return head;
let prv = null;
let next = null;
let cur = head;
while(cur){
next = cur.next; //backup
cur.next = prv;
prv = cur;
cur = next;
}
head = prv;
return head;
}
Recursion Approach (JS)
function reverseLLByRecursion("See full answer
"I would assume that this is similar to an intervals question. Meeting Rooms II (https://www.lintcode.com/problem/919/?fromId=203&_from=collection) on Leetcode seems like the closest comparison, it's a premium question so I linked Lintcode.
I'm assuming that we also need to just return the minimum number of cars used. You need to sort for the most optimal solution, so you're constrained by an O(nlogn) time complexity. So any sorting solution could work (using a heap, sorting the array input arra"
Sohum S. - "I would assume that this is similar to an intervals question. Meeting Rooms II (https://www.lintcode.com/problem/919/?fromId=203&_from=collection) on Leetcode seems like the closest comparison, it's a premium question so I linked Lintcode.
I'm assuming that we also need to just return the minimum number of cars used. You need to sort for the most optimal solution, so you're constrained by an O(nlogn) time complexity. So any sorting solution could work (using a heap, sorting the array input arra"See full answer
"2 Approaches:
1) The more intuitive approach is doing a multi-source BFS from all cats and storing the distance of closest cats. Then do a dfs/bfs from rat to bread.
Time Complexity: O(mn + 4^L) where L is path length, worst case L could be mn
Space Complexity: O(m*n)
2) The first approach should be fine for interviews. But if they ask to optimize it further, you can use Binary Search. Problems like "Finding max of min distance" or "Finding min of max" could be usually solved by BS.
"
Karan K. - "2 Approaches:
1) The more intuitive approach is doing a multi-source BFS from all cats and storing the distance of closest cats. Then do a dfs/bfs from rat to bread.
Time Complexity: O(mn + 4^L) where L is path length, worst case L could be mn
Space Complexity: O(m*n)
2) The first approach should be fine for interviews. But if they ask to optimize it further, you can use Binary Search. Problems like "Finding max of min distance" or "Finding min of max" could be usually solved by BS.
"See full answer
"It was like say we have a library A which has a library B as a dependency and so on, how would we determine in the dependency chain that whether there is a circular depedency?"
Chris R. - "It was like say we have a library A which has a library B as a dependency and so on, how would we determine in the dependency chain that whether there is a circular depedency?"See full answer
"public static boolean isPalindrome(String str){
boolean flag = true;
int len = str.length()-1;
int j = len;
for(int i=0;i<=len/2;i++){
if(str.charAt(i)!=str.charAt(j--)){
flag = false;
break;
}
}
return flag;
}"
Sravanthi M. - "public static boolean isPalindrome(String str){
boolean flag = true;
int len = str.length()-1;
int j = len;
for(int i=0;i<=len/2;i++){
if(str.charAt(i)!=str.charAt(j--)){
flag = false;
break;
}
}
return flag;
}"See full answer
"Used Recursive approach to traverse the binary search tree and sum the values of the nodes that fall within the specified range [low, high]"
Srikant V. - "Used Recursive approach to traverse the binary search tree and sum the values of the nodes that fall within the specified range [low, high]"See full answer
"I firstly discuss the brute force approach in O(n^2) time complexity , than i moved to O(nlogn) tine complexity than i discussed the O(n) time complexity and O(n) space complexity . But interviewer want more optimised solution , in O(n) time complexity without using extra space ,
The solution wants O(1) space complexity i have to do changes in same array without using any space . This method is something like i have to place positive values to its original position by swapping and rest negativ"
Anni P. - "I firstly discuss the brute force approach in O(n^2) time complexity , than i moved to O(nlogn) tine complexity than i discussed the O(n) time complexity and O(n) space complexity . But interviewer want more optimised solution , in O(n) time complexity without using extra space ,
The solution wants O(1) space complexity i have to do changes in same array without using any space . This method is something like i have to place positive values to its original position by swapping and rest negativ"See full answer
"
Compare alternate houses i.e for each house starting from the third, calculate the maximum money that can be stolen up to that house by choosing between:
Skipping the current house and taking the maximum money stolen up to the previous house.
Robbing the current house and adding its value to the maximum money stolen up to the house two steps back.
package main
import (
"fmt"
)
// rob function calculates the maximum money a robber can steal
func maxRob(nums []int) int {
ln"
VContaineers - "
Compare alternate houses i.e for each house starting from the third, calculate the maximum money that can be stolen up to that house by choosing between:
Skipping the current house and taking the maximum money stolen up to the previous house.
Robbing the current house and adding its value to the maximum money stolen up to the house two steps back.
package main
import (
"fmt"
)
// rob function calculates the maximum money a robber can steal
func maxRob(nums []int) int {
ln"See full answer
"Batch Packing Problem
In Amazon’s massive warehouse inventory, there are different types of products. You are given an array products of size n, where products[i] represents the number of items of product type i. These products need to be packed into batches for shipping.
The batch packing must adhere to the following conditions:
No two items in the same batch can be of the same product type.
The number of items packed in the current batch must be strictly greater than the number pack"
Anonymous Goat - "Batch Packing Problem
In Amazon’s massive warehouse inventory, there are different types of products. You are given an array products of size n, where products[i] represents the number of items of product type i. These products need to be packed into batches for shipping.
The batch packing must adhere to the following conditions:
No two items in the same batch can be of the same product type.
The number of items packed in the current batch must be strictly greater than the number pack"See full answer
"find total sum. assign that to rightsum
traverse from left to right: keep updating left sum and right sum, when they match return the index.
else if you reach end return -1 or not found"
Rahul J. - "find total sum. assign that to rightsum
traverse from left to right: keep updating left sum and right sum, when they match return the index.
else if you reach end return -1 or not found"See full answer
"Given a Binary Tree, the task is to find its vertical traversal starting from the leftmost level to the rightmost level. If multiple nodes pass through a vertical line, they should be printed as they appear in the level order traversal of the tree.
The idea is to traverse the tree using dfs and maintain a hashmap to store nodes at each horizontal distance (HD) from the root. Starting with an HD of 0 at the root, the HD is decremented for left children and incremented for right children. As we"
Anonymous Mongoose - "Given a Binary Tree, the task is to find its vertical traversal starting from the leftmost level to the rightmost level. If multiple nodes pass through a vertical line, they should be printed as they appear in the level order traversal of the tree.
The idea is to traverse the tree using dfs and maintain a hashmap to store nodes at each horizontal distance (HD) from the root. Starting with an HD of 0 at the root, the HD is decremented for left children and incremented for right children. As we"See full answer
"We can use dictionary to store cache items so that our read / write operations will be O(1).
Each time we read or update an existing record, we have to ensure the item is moved to the back of the cache. This will allow us to evict the first item in the cache whenever the cache is full and we need to add new records also making our eviction O(1)
Instead of normal dictionary, we will use ordered dictionary to store cache items. This will allow us to efficiently move items to back of the cache a"
Alfred O. - "We can use dictionary to store cache items so that our read / write operations will be O(1).
Each time we read or update an existing record, we have to ensure the item is moved to the back of the cache. This will allow us to evict the first item in the cache whenever the cache is full and we need to add new records also making our eviction O(1)
Instead of normal dictionary, we will use ordered dictionary to store cache items. This will allow us to efficiently move items to back of the cache a"See full answer
"Question: An array of n integers is given, and a positive integer k, where k << n. k indicates that the absolute difference between each element's current index (icurrent) and the index in the sorted array (isorted) is less than k (|icurr - isorted| < k).
Sort the given array.
The most common solution is with a Heap:
def solution(arr, k):
min_heap = []
result = []
for i in range(len(arr))
heapq.heappush(min_heap, arr[i])
"
Guilherme M. - "Question: An array of n integers is given, and a positive integer k, where k << n. k indicates that the absolute difference between each element's current index (icurrent) and the index in the sorted array (isorted) is less than k (|icurr - isorted| < k).
Sort the given array.
The most common solution is with a Heap:
def solution(arr, k):
min_heap = []
result = []
for i in range(len(arr))
heapq.heappush(min_heap, arr[i])
"See full answer