"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
"
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
Data Scientist
Coding
+4 more
🧠 Want an expert answer to a question? Saving questions lets us know what content to make next.
"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
"WITH ActiveUsersYesterday AS (
SELECT DISTINCT user_id
FROM user_activity
WHERE activity_date = CAST(GETDATE() - 1 AS DATE)
),
VideoCallUsersYesterday AS (
SELECT DISTINCT user_id
FROM video_calls
WHERE call_date = CAST(GETDATE() - 1 AS DATE)
)
SELECT
(CAST(COUNT(DISTINCT v.userid) AS FLOAT) / NULLIF(COUNT(DISTINCT a.userid), 0)) * 100 AS percentagevideocall_users
FROM
ActiveUsersYesterday a
LEFT JOIN
VideoCallUsersYesterday v ON a.userid = v.userid;"
Bala G. - "WITH ActiveUsersYesterday AS (
SELECT DISTINCT user_id
FROM user_activity
WHERE activity_date = CAST(GETDATE() - 1 AS DATE)
),
VideoCallUsersYesterday AS (
SELECT DISTINCT user_id
FROM video_calls
WHERE call_date = CAST(GETDATE() - 1 AS DATE)
)
SELECT
(CAST(COUNT(DISTINCT v.userid) AS FLOAT) / NULLIF(COUNT(DISTINCT a.userid), 0)) * 100 AS percentagevideocall_users
FROM
ActiveUsersYesterday a
LEFT JOIN
VideoCallUsersYesterday v ON a.userid = v.userid;"See full answer
"Use a representative of each, e.g. sort the string and add it to the value of a hashmap> where we put all the words that belong to the same anagram together."
Gaston B. - "Use a representative of each, e.g. sort the string and add it to the value of a hashmap> where we put all the words that belong to the same anagram together."See full answer
"we can use two pointer + set like maintain i,j and also insert jth character to set like while set size is equal to our window j-i+1 then maximize our answer and increase jth pointer till last index"
Kishor J. - "we can use two pointer + set like maintain i,j and also insert jth character to set like while set size is equal to our window j-i+1 then maximize our answer and increase jth pointer till last index"See full answer
"#inplace reversal without inbuilt functions
def reverseString(s):
chars = list(s)
l, r = 0, len(s)-1
while l < r:
chars[l],chars[r] = chars[r],chars[l]
l += 1
r -= 1
reversed = "".join(chars)
return reversed
"
Anonymous Possum - "#inplace reversal without inbuilt functions
def reverseString(s):
chars = list(s)
l, r = 0, len(s)-1
while l < r:
chars[l],chars[r] = chars[r],chars[l]
l += 1
r -= 1
reversed = "".join(chars)
return reversed
"See full answer
"def is_valid(s: str) -> bool:
stack = []
closeToOpen = { ")" : "(", "]" : "[", "}" : "{" }
for c in s:
if c in closeToOpen:
if stack and stack[-1] == closeToOpen[c]:
stack.pop()
else:
return False
else:
stack.append(c)
return True if not stack else False
debug your code below
print(is_valid("()[]"))
`"
Anonymous Roadrunner - "def is_valid(s: str) -> bool:
stack = []
closeToOpen = { ")" : "(", "]" : "[", "}" : "{" }
for c in s:
if c in closeToOpen:
if stack and stack[-1] == closeToOpen[c]:
stack.pop()
else:
return False
else:
stack.append(c)
return True if not stack else False
debug your code below
print(is_valid("()[]"))
`"See full answer
"
import java.io.*;
import java.util.*;
class Solution {
static boolean canFinish(int n, int prerequisites) {
List> adjMatrix = new ArrayList();
for(int i = 0; i ());
}
for(int[] pre : prerequisites) {
adjMatrix.get(pre[1]).add(pre[0]);
}
boolean[] visited = new boolean[n];
boolean[] path = new boolean[n];
for(int i"
Basil A. - "
import java.io.*;
import java.util.*;
class Solution {
static boolean canFinish(int n, int prerequisites) {
List> adjMatrix = new ArrayList();
for(int i = 0; i ());
}
for(int[] pre : prerequisites) {
adjMatrix.get(pre[1]).add(pre[0]);
}
boolean[] visited = new boolean[n];
boolean[] path = new boolean[n];
for(int i"See full answer
"Initialize left pointer: Set a left pointer left to 0.
Iterate through the array: Iterate through the array from left to right.
If the current element is not 0, swap it with the element at the left pointer and increment left.
Time complexity: O(n). The loop iterates through the entire array once, making it linear time.
Space complexity: O(1). The algorithm operates in-place, modifying the input array directly without using additional data structures.
"
Avon T. - "Initialize left pointer: Set a left pointer left to 0.
Iterate through the array: Iterate through the array from left to right.
If the current element is not 0, swap it with the element at the left pointer and increment left.
Time complexity: O(n). The loop iterates through the entire array once, making it linear time.
Space complexity: O(1). The algorithm operates in-place, modifying the input array directly without using additional data structures.
"See full answer
"\# Definition for a binary tree node.
class TreeNode:
def init(self, val=0, left=None, right=None):
self.val = val
self.left = left
self.right = right
class Solution:
def maxPathSum(self, root: TreeNode) -> int:
self.max_sum = float('-inf')"
Jerry O. - "\# Definition for a binary tree node.
class TreeNode:
def init(self, val=0, left=None, right=None):
self.val = val
self.left = left
self.right = right
class Solution:
def maxPathSum(self, root: TreeNode) -> int:
self.max_sum = float('-inf')"See full answer