"public class BoggleBoard {
public static List findWords(char board, Set dictionary) {
int rows = board.length;
int cols = board[0].length;
boolean visited = new booleanrows;
int directions = {{1,0}, {-1,0}, {0,1}, {0,-1}};
List result = new ArrayList();
for(int i=0; i<rows; i++) {
for(int j=0; j<cols; j++) {
dfs(board, visited, i, j, dictionary, "", result, dire"
Aniket G. - "public class BoggleBoard {
public static List findWords(char board, Set dictionary) {
int rows = board.length;
int cols = board[0].length;
boolean visited = new booleanrows;
int directions = {{1,0}, {-1,0}, {0,1}, {0,-1}};
List result = new ArrayList();
for(int i=0; i<rows; i++) {
for(int j=0; j<cols; j++) {
dfs(board, visited, i, j, dictionary, "", result, dire"See full answer
"filter function usually exists in some high level programming that adopt FP paradigm.
It taks a sequence of items and a predicate function, and returns (conceptually) a subset of the items that satisfy the predicate.
Adopt this kind of operation (filter, map, reduce, take, pairwise ...) can help writting
cleaner code, and reduce the usage of mutable part in the program, lower the
possibility of making human mistake.
Take Python for example (although const-ness is not exists in Python),
assu"
Weida H. - "filter function usually exists in some high level programming that adopt FP paradigm.
It taks a sequence of items and a predicate function, and returns (conceptually) a subset of the items that satisfy the predicate.
Adopt this kind of operation (filter, map, reduce, take, pairwise ...) can help writting
cleaner code, and reduce the usage of mutable part in the program, lower the
possibility of making human mistake.
Take Python for example (although const-ness is not exists in Python),
assu"See full answer
"let str = 'this is a test of programs';
let obj={};
for (let s of str )
obj[s]?(obj[s]=obj[s]+1):(obj[s]=1)
console.log(JSON.stringify(obj))"
Anonymous Emu - "let str = 'this is a test of programs';
let obj={};
for (let s of str )
obj[s]?(obj[s]=obj[s]+1):(obj[s]=1)
console.log(JSON.stringify(obj))"See full answer
"function constructTree(n, matrix) {
let parent = [];
let child = [];
let root = null;
for (let i = 0; i < n; i++) {
for (let j = 0; j < n; j++) {
if (matrixi === 1) {
parent.push(i);
child.push(j);
}
}
}
for (let i = 0; i < n; i++) {
if (parent.indexOf(i) === -1) {
root = i;
}
}
let node = new Node(root);
for (let i = 0; i < n; i++) {
if (i !== root) {
constructTreeUtil(node, parent[i], child[i]);
}
}
return node;
}"
Ugo C. - "function constructTree(n, matrix) {
let parent = [];
let child = [];
let root = null;
for (let i = 0; i < n; i++) {
for (let j = 0; j < n; j++) {
if (matrixi === 1) {
parent.push(i);
child.push(j);
}
}
}
for (let i = 0; i < n; i++) {
if (parent.indexOf(i) === -1) {
root = i;
}
}
let node = new Node(root);
for (let i = 0; i < n; i++) {
if (i !== root) {
constructTreeUtil(node, parent[i], child[i]);
}
}
return node;
}"See full answer
"import java.util.*;
public class NetworkTopology {
public int topologytype(int N, int M, int[] input3, int[] input4) {
if (M != N - 1 && M != N) return -1; // Fast check for invalid cases
int[] degree = new int[N + 1]; // Degree of each node (1-based indexing)
// Build the degree array
for (int i = 0; i < M; i++) {
degree[input3[i]]++;
degree[input4[i]]++;
}
// Check for Bus Topology
boolean isBus = (M"
Alessandro R. - "import java.util.*;
public class NetworkTopology {
public int topologytype(int N, int M, int[] input3, int[] input4) {
if (M != N - 1 && M != N) return -1; // Fast check for invalid cases
int[] degree = new int[N + 1]; // Degree of each node (1-based indexing)
// Build the degree array
for (int i = 0; i < M; i++) {
degree[input3[i]]++;
degree[input4[i]]++;
}
// Check for Bus Topology
boolean isBus = (M"See full answer
"
import pandas as pd
from datetime import datetime
def findfastestlike(log: pd.DataFrame) -> pd.DataFrame:
log=log.sortvalues(['userid','timestamp'])
#get the prev event, time by user
log['prevevent'] = log.groupby('userid')['event'].shift(1)
log['prevtimestamp'] = log.groupby('userid')['timestamp'].shift(1)
True only on rows where the previous event was a login
and the current event is a like
log['loginlike'] = (log['prevevent'] == 'log"
Sean L. - "
import pandas as pd
from datetime import datetime
def findfastestlike(log: pd.DataFrame) -> pd.DataFrame:
log=log.sortvalues(['userid','timestamp'])
#get the prev event, time by user
log['prevevent'] = log.groupby('userid')['event'].shift(1)
log['prevtimestamp'] = log.groupby('userid')['timestamp'].shift(1)
True only on rows where the previous event was a login
and the current event is a like
log['loginlike'] = (log['prevevent'] == 'log"See full answer
"The height of a binary tree is the maximum number of edges from the root node to any leaf node. To calculate the height of a binary tree, we can use a recursive approach. The basic idea is to compare the heights of the left and right subtrees of the root node, and return the maximum of them plus one."
Prashant Y. - "The height of a binary tree is the maximum number of edges from the root node to any leaf node. To calculate the height of a binary tree, we can use a recursive approach. The basic idea is to compare the heights of the left and right subtrees of the root node, and return the maximum of them plus one."See full answer