Quantcast
Viewing all 39796 articles
Browse latest View live

weak test cases in TOWFL???

i haven't solved the TWOFL problem, but i have read an accepted code from one other, and i found that his code can't pass the my test case (TLE). I generated the input for my test case by the following code (you can change the variable n,m higher than 200 as i set) https://ideone.com/GBwbq5

i tested 3 submissions got 100 points: https://www.codechef.com/viewsolution/18867726https://www.codechef.com/viewsolution/18868162https://www.codechef.com/viewsolution/18868334 in Codeforces by "Custom Invocation" and all of them got TLE with my test case i realize that the time complexity of the first out of 3 submission above can goes up to (n.m)^2

By the way, where is the editorial for June Challenge 2018?


FFT - Editorial

PROBLEM LINK:

Practice
Contest

Author:Denis Anishchenko
Tester:Hasan Jaddouh
Editorialist:Sarv Shakti Singh

Difficulty: Medium

Prerequisites: Combinatorics

Problem: You have a bunch of cycles, each containing some nodes. For each node, starting from the node, travel across the cycle until you reach the same node. Now, you have an array A of N elements, which means that the ith node occurs A[i] times after applying each operation. You need to tell how many ways are there to form those cycles that are consistent with array A.

Explanation: Let's clear up the problem statement given on the contest page. Gritukan writes a permutation P of N numbers such that, for each node i, visit P[i], then P[P[i]], and repeat this until you reach i again. Now, this guarantees that the permutation has each node in a cycle exactly once. Proof?

  1. Each node is a part of a cycle, otherwise we will never reach the start node again.
  2. Each node is part of a cycle exactly once, since we can move to only one node from a current node.(Just think about it!)

We need to find how many such permutations occur, given how many times a node has been visited in Gritukan's scheme.

Graphically looking, any permutation would result in a bunch of different sized isolated cycles. Talking about just one cycle having p nodes, obviously each node of that cycle will occur p times in Gritukan's scheme (once for each time the algorithm starts for every node). Hence, if A[i]=p, that means node i is a part of a cycle of size p. Now, keeping that in mind, let us prove one fact that for a valid permutation to occur, in the array A, p will occur k*p times where k is any arbitrary positive integer(otherwise, there will always be some number of nodes less than p left that cannot be satisfied). Hence, for a valid permutation to occur, the only condition is each number p present in the array A must be k*p times in the array.

Now, all the concept behind this problem is over. It all comes down to the math: You have to form ki cycles of pi nodes each, such that the total number of times pi occurs, mi=ki.pi. This can be given by the formula: $\prod \frac{\left(^{m_i}C_{p_i}.\left(p_i-1\right)\right).\left(^{m_i-p_i}C_{p_i}.\left(p_i-1\right)\right).\left(^{m_i-2p_i}C_{p_i}.\left(p_i-1\right)\right)...\left(^{p_i}C_{p_i}.\left(p_i-1\right)\right)}{k_i!}$ where nCr means $\frac{n!}{r!.(n-r)!}$.

We select p nodes from m nodes in mCp ways, arrange them in a cycle by p-1 ways, then repeat it again, until all nodes are put in a cycle. At last we divide by k!, because each cycle is identical.

For my solution, I have broken down the formula to this: $\prod \frac{1}{k_i!}.\frac{1}{p_i^{k_i}}.\left( \frac{p_i!}{0!}.\frac{2p_i!}{i!}.\frac{3p_i!}{2i!}...\frac{m_i!}{m_i-p_i!} \right)$

Complexity and Implementation: Computation of how many times each number comes in array A can be done in linear time. Then, we iterate over each pi and get mi. Then, loop through mi to pi at a decrement of pi, and calculate the answer. Although nested loop, the complexity of this actually of the order O(N). Since, at max, we will have to iterate from mi to 1, at decrement 1. However, the sum of mi over A is actually N.

We will be actually computing the value of all the factorials%MOD beforehand, along with their inverses, for constant time access. This build operation will take at most 106 operations.

editorialist's solution

AUTHOR'S AND TESTER'S SOLUTIONS:

Author's solution can be found here.
Tester's solution can be found here.

compiler shows wrong answer even though program works

Hello. I am new to this site so please forgive any newbie mistakes I made, but why is the compiler showing me "Wrong Answer", even though my code is right. What might be wrong?

Here is my code: #include<stdio.h> int main() { int T,M,B; scanf("%d",&T); while(T--) { scanf("%d %d",&M,&B); while(B > 0) { if(M == B) break; M = (M > B)?(M-B):((B = (B-M))+(2*M)); } printf("%d\n", (M+B)); } return 0; }Note: Before modifying to this, I used if-else but it was showing Time Limit Exceed. And this code runs fine on my gcc compiler (version same as in codechef).

Output is correct but getting wrong answer during submission.

http://discuss.codechef.com/problems/ERROR

include<stdio.h>

include<string.h>

int main() { int i,t; scanf("%d",&t); for(i=1;i<=t;i++) { int len,j,k,l,flag=0,count1=0,count2=0,count3=0;; char num1[100001]; char num2[3]; char sample1[3]={'1', '0', '1'}; char sample2[3]={'0', '1', '0'}; scanf("%s", num1); len=strlen(num1); for(j=0;j<len-2;j++) {

        for(k=j;k<=j+2;k++)
        {
            num2[count1]=num1[k];
            count1++;
        }
        for(l=0;l<3;l++)
        {
            if(num2[l]==sample1[l])
            count2+=1;
        }
        for(l=0;l<3;l++)
        {
            if(num2[l]==sample2[l])
            count3+=1;
        }
        if(count2==3)
        {
            flag=1;
            break;
        }
        else if(count2==3)
        {
            flag=2;
            break;
        }
        count1=0,count2=0,count3=0;
    }
    if(flag==1 || flag==2)
    printf("GOOD");
    else
    printf("BAD");
    printf("\n");
}

return 0; }

TWOFL RunTime Error in Java

So when I was trying to do TWOFL question I don't know I was getting RunTimeError for some of the cases and only in subtasks 2 and 3. So I wonder whether this is because of big values. Then somehow in my program I made all value as 1 and traversed it for n=1000 and m=1000. Clearly on my PC I got an error of StackOverFlow. I thought may be my program is going in an infinite recursion so I tried more and couldn't find why is this happening. Then I thought of looking at one of the accepted codes in CPP and changing it into Java. Still it was giving RunTimeError on same cases. Then I looked at others code of Java and many were getting the same error and hence I was sure that this is only with Java who is doing in recursive fashion.

And finally I found this:
http://codeforces.com/blog/entry/166
http://codeforces.com/blog/entry/166

I hope this will help you.

Thanks

WRKWAYS - Editorial

Problem Link

Practice

Contest

Author:Noszály Áron

Tester:Misha Chorniy

Editorialist:Bhuvnesh Jain

Difficulty

MEDIUM

Prerequisites

Factroisation, Combinatorics

Problem

You are given $N$ workers and each of them has a deadline to complete the work, given by $d_i$ for $i^{th}$ worker. Each worker completes the work in $1$ day and on each day at most $1$ worker can work. You need to decide to the array containing the deadline for every worker such that the number of ways in which the workers can decide to work is $C$ and $d_n$ is minimised. Also, the array of deadlines should be sorted.

Explanation

Before proceeding towards the solution, we need to find the number of ways in which workers can decide to work for a given array $d_1 ≤ d_2 ≤ \cdots ≤ d_n$.

Consider the case for $n ≤ 3$. Let $d_1 = x, d_2 = y, d_3 = z$. We have the following dynammic programming solution

$$dp[x] = x$$

$$dp[x][y] = dp[x] * (y - x) + dp[x-1] * x = xy - x^2 + x^2 - x$$

$$dp[x][y] = xy - x = (y-1) * dp[x]$$

$$dp[x][y][z] = dp[x][y] * (z - y) + dp[x][y-1] * (y - x) + dp[x-1][y-1] * x$$ $$dp[x][y][z] = (xy - x)(z - y) + (xy - 2x)(y - x) + (xy - 2x - y + 2)x$$ $$dp[x][y][z] = (xyz - xz - 2xy + 2x) = (z - 2) * (xy - x)$$ $$dp[x][y][z] = (z - 2) * dp[x][y]$$

Using the above observations, it is clear that number of ways is $\prod_{i=1}^{i=n} {(d_i - i + 1)}$. We can even prove it combinatorially. The first person has $d_1$ choices, the second one has $(d_2 - 1)$ choices and so on. By the principle of multiplication, the number of ways comes out to be same.

Note the above solution clearly points out that $d_i >= i$. Thus for $C = 1$, the array is $(1, 2, 3, 4, \cdots)$.

Thus, the problem now reduces to finding an array $d_1 ≤ d_2 ≤ \cdots ≤ d_n$ such that $\prod_{i=1}^{i=n} {(d_i - i + 1)} = C$ and $d_n$ is minimised.

Instead of finding $d_1, d_2 \cdots d_n$, we will find sorted array, $d_1, (d_2-1), \cdots, (d_n-n+1)$, such that product of this sequence is $C$ and later add back $(i - 1)$ to every term to ensure that sequence is increasing.

Subtask 1: N ≤ 10, C ≤ 100

We can use dynamic programming based solution for this subtask. Let $dp[N][C]$ denote the minimised value of $d_n$ for which the sequence $d_1, d_2, \cdots, d_n$ has number of ways as $C$. The transitions are simple. Let $dp[N][C] = x$. So, we need to find the minimum value for the sequence with $(N - 1)$ terms and product as $(C/x)$. The possible candidates are the divisors of $(C/x)$. So, we try all possible candidates and update our answer whether or not it is possible to form an array with the tried candidate. Once, the dynamic programming table is built, we can simply backtrack it to print the answer.

The time compleixty of the above approach is $O(N * {\sigma_{0}{(C)}}^2)$, where $\sigma_{0}{(C)}$ denotes the number of divisors of $C$.

For details, you can refer to author's solution for the above approach.

Subtask 2, 3: N ≤ ${10}^6$, C ≤ ${10}^9$

We may see that for optimal answer, the sequence $d_1, (d_2-1), \cdots, (d_n-n+1)$, looks like the following for large $n$:

[zero or more numbers greater than 1] [bunch of ones] [zeros or more numbers greater than 1]

Outline of proof for above claim: Basically we want to show that if we have a solution that is not in the above form, then there's a solution of the above form which has the same last element. We achieve this by moving the blocks of non $1$ elements as a unit, in this part, we will use the monotonicity of array $d$ as an argument to show that the blocks are indeed movable and don't break anything.

The above form is important because increasing $N$ actually just pushes more ones into the middle (if there were a better way to distribute the numbers we would have used it earlier). So to solve, we calculate the optimal sequence for smaller $N$ and then extend the "bunch of ones" in the middle.

In the worst case the above method's complexity is $O(N + (\text{number of prime factors of C}) * {\sigma_{0}{(C)}}^2)$. Because the number of prime factors in the range of ${10}^9$ is $30$ in the worst case and the number of divisors is $1000$ in the worst case, this gives around $3 * {10}^7$ operations per test case.

For more details, you can refer to the setter's or tester's solution below.

Editorialist Solution: Based on solutions by contestants in the contest (Greedy approach)

We will first store all the factors of $C$. Now, we traverse the factors one by one and check if we can form an array $d_1, (d_2-1), \cdots, (d_n-n+1)$, such that the last element is given factor. Is yes, we simply update the answer. Below is the pseudo-code for checking whether we can find an array with the last element as given factor $x$.


    # facts store the factors of C.
    # facts[idx] = x

    def check(idx):
        ptr = n
        prod = c
        while ptr > 0:
            while prod % facts[idx] != 0
                idx -= 1
            prod /= facts[idx]
            ans[ptr] = facts[idx] + ptr - 1
            ptr -= 1
            if idx != len(facts)-1 and facts[idx] == (facts[idx+1] - 1):
                idx += 1
            if idx == 0 or prod == 1:
                break
        return (prod == 1)

Let us analyse the above pseudo-code. We first try to greedily find the first largest factor of the remaining product. At first step it will be $facts[idx] = x$, the number we want to check. Since in final array we want $d_{(i-1)} ≤ d_i$ and we are finding array $(d_i - i + 1)$, the previous term can now contain a possible larger factor only if it is greater than the previous factor by $1$. The last condition just checks that if the product has become 1, then we know the trivial answer or if the factor to be considered is $1$, the product will remain same. Below is an example iteration of the above for $N = 8$ and $C = 36$. Let the factor to be checked is $x = 2$.

$$\text{facts} = {1, 2, 3, 4, 6, 9, 12, 18, 36}$$

$$\text{Step 1} = {\cdots, 2}$$

$$\text{Step 2} = {\cdots, 3, 2}$$

$$\text{Step 3} = {\cdots, 3, 3, 2}$$

$$\text{Step 4} = {\cdots, 2, 3, 3, 2}$$

Since the prod now becomes $1$ we break. To build the required array we add the offsets $(i - 1)$ to the array.

Thus, required array is $(1, 2, 3, 4, 6, 8, 9, 9)$. Note that this may or may not be the optimal solution. It just shows how we check if a given factor can form the series if it is the last term in the sequence.

The time complexity of the above approach will be $O(\sigma_{0}{(C)} * \log{C} + N)$. This is because, for every factor, the checking will take $O(\log{C})$ step in the worst case as "prod" variable will decrease by a factor of atleast $2$ in each iteration. The second term, $O(N)$, is for building the complete sequence containing the initial trivial part of $(1, 2, 3, \cdots)$ and printing the answer. The space complexity will be $O(N + sqrt(C))$.

Once, you are clear with the above idea, you can see the editorialist implementation below for help.

Feel free to share your approach, if it was somewhat different.

Time Complexity

$O(N + (\text{number of prime factors of C}) * {\sigma_{0}{(C)}}^2)$ or $O(\sigma_{0}{(C)} * \log{C} + N)$

Space Complexity

$O(sqrt(C) + 1000 * sqrt(C) + N)$, where $1000$ denotes the value of small $N$ used by author to solve problem by dynamic programming.

AUTHOR'S AND TESTER'S SOLUTIONS:

Author's solution can be found here.

Tester's solution can be found here.

Editorialist's solution can be found here.

a good set solve ?

okay, so I used two way to do this problem, first is using a custom fibonacci where instead of f(a) = f( a - 1 ) + f( a -2 ), I turned it into f(a) = f(a - 1 ) + f( a - 2 ) + 1, this should make sure that it meets the requirements, and it did, albeit only for the first subtask, next I used a method that will definitely meet the requirement, by having the output like this, e.g input 1, outputs 1 input 2, outputs 1 11 input 3, outputs 1 11 111 input 4, outputs 1 11 111 1111 if the outputs are like this, there should be no way that the output don't meet the requirements, and yet I got WA for both subtask...weird anyways, here is my submission

100% attendance laddus

Has anyone received the laddus for 100% participation between March '17-Feb '18?


my code is running on ide but here it is not working.help me out??

package javaapplication1; import java.util.*;

class JavaApplication1 {

public static void main(String[] args) {
    Scanner sc=new Scanner(System.in);
    int t=sc.nextInt();
   while(t-->0) {
       int n=sc.nextInt();
       int arr[]=new int[n];
       for(int i=0;i<arr.length;i++)
       {
           arr[i]=sc.nextInt();

       }
       Arrays.sort(arr);
       int min=arr[1]-arr[0];
       for(int i=0;i<arr.length-1;i++)
       {
           int c=arr[i+1]-arr[i];
           if(c<=min)
           {
               min=c;
           }
       }
       System.out.println(min);

    }

}

}

Akhil and colored balls, wrong example ?

ok, so in problem link umm, it said that "BWBW" is the only solution, but I finds out that "BWWW" can be the answe too, ok, let's break it down "WBWB" and "BWBW", all of them are different so hammington distance is 4, "WBBB" and "BWBW" have hammington distance of 3, pos 1, 2, and 4, total of 7, and for "BWWW", "WBWB" and "BWWW" have hammington distance 3, and "WBBB" and "BWWW" have hamington distance of 4...which equals 7, now there has become two answers...also, there is another constraint which says lexicographically smallest arangement...hmm, does that matter and I have been stupid ? ( anyways I don't understand what lexicographically smallest arangement means )

need help in the string length function

here is my code to find out the length of the string.

include <stdio.h>

include <stdlib.h>

int main()
{
char st[ ]="hithere";
printf("\a");
int i;
i=len(st);
printf("%s",st);
printf("\a%d",i);
return 0;
}
int len(char s)
{
int l=0;
while(
s != '\0');
{

 l++;        
 s++;

}

return (l);
}

cant figure out the problem please help. (making in codeblocks)

100% scholarship in CCDSAP based on JUNE Challenge results

How I will get my 100% scholarship in CCDSAP on getting highest score in JUNE Challenge 2018 in my institute?

Majin Vegeta - Quick Code

I have written My Code in Java , it is working properly with exit code 0 , in my IntelliJ IDE , but while submitting here , I get an Runtime error - NZEC .

import java.util.Scanner;
public class Main {

public static void main(String[] args) {

    long N = 100000;
    int primeFactor[] = new int[100000];

    Scanner scan = new Scanner(System.in);
    int t = scan.nextInt();

    for(int i = 0; i<t ; i++ ) {


        for(int k = 0;k<N;k++) {
            primeFactor[k] = 0;
        }


        int n = scan.nextInt();
        int m = scan.nextInt();

        for(int j = 2 ; j < N ; j++) {
            if(primeFactor[j] == 0) {
                for(int e = j ; e < N ; e+=j ) primeFactor[e]++;
            }
        }
        int sum = 0;
        for(int s = n; s < m ; s++ ) {
            sum += primeFactor[s];
        }
        System.out.println(sum);

      }

 }

}

Needed Help in TWOFL problem ? Getting WA answer except 3 test Cases.. plz plz

My Approach is same As mentioned in editorial :-

  1. create component for same type
  2. create edges for different component
  3. use union find (dsu) concept

I am not able to find out any Test case where my code is giving WA answer.. plz someOne provide any test case for my code is not giving right answer

solution link:- link


Output ScreenShot:-Image may be NSFW.
Clik here to view.
alt text

Most used method to find LCA

Since there are many ways to find LCA(lowest common ancestor) with different preprocessing and query time, and almost each one is able to pass the time limit in general case, I was wondering which method is generally used among competitive programmers. I mean there must be one among them which is having a slight edge over the others in terms of code length, etc., and is widely used.

So my question is that which technique to find LCA is mostly used in competitive programming.


reverse a doubly linked list in a group of given size

can anyone please correct my code because it is not working and i am not able to solve....

 #include<iostream>
 #include<cstdlib>
 #include<algorithm>
 #include<string>
 #include<vector>

 using namespace std;

struct node
{
   int info;
  node *next;
   node *prev;
};

void add(node **start,int data)
{
   struct node *tmp = new node;

  tmp->next = (*start);
  tmp->prev = NULL;
  tmp->info = data;

  if((*start)!=NULL)
  {
    (*start)->prev = tmp;
  }

  (*start) = tmp;
  }

 struct node *reverse_kth(node *start,int k)
 {
   int i=0;

    node *pre=NULL,*curr=(start);
    while(curr!=NULL && i<k-1)
    {
        pre=curr->prev;
        curr->prev=curr->next;
        curr->next=pre;
        curr=curr->prev;
        i++;
    }

    if(curr!=NULL)
    {
        curr->next=reverse_kth(curr->prev,k);
        curr->next->prev=curr;
    }
  return pre->prev;
 }

  void print(node *p)
 {
   while(p!=NULL)
  {
      cout<<p->info<<"<->";
      p=p->next;
  }
   cout<<"NULL\n";
 }

int main()
{
  struct node *a=NULL;

  add(&a,2);
  add(&a,4);
  add(&a,8);
  add(&a,10);

  int k=2;

  cout<<"list before reversing : ";
  print(a);

  a=reverse_kth(a,k);

  cout<<"list after reversing : ";
  print(a);

  return 0;
}

BINSHFFL - Editorial

Problem Link

Practice

Contest

Author:Noszály Áron

Tester:Misha Chorniy

Editorialist:Bhuvnesh Jain

Difficulty

EASY

Prerequisites

BFS/Floyd Warshall, Observations

Problem

You are to convert number $A$ to number $B$ using the following operation in the minimum number of steps:

  • Write A as a binary number with arbitrary number of leading zeros (possibly none)
  • Shuffle the binary digits of the A in an arbitrary order. Call it $A'$
  • The output is $(A' + 1)$. Let us call this number as $X$.

Remember the notation of $A'$ and $X$ as it is used everywhere in the editorial.

Explanation

Subtask 1: A, B ≤ 128

The problem asks to minimise the number of steps to go from $A$ to $B$. Generally, these type of problems can be easily modelled as a graph and perform BFS to find the answer. Here is a general idea:

Let us model each step as an edge from initial number to final number with an edge of some cost. So, the path with the smallest weight from source to destination is the required answer and also gives us a way to achieve the transition.

In this problem, we can just do what the operations ask us to do. Just all possible shuffling of the digits of A in binary representation and consider only those ones which give end result within the desired range ([0, 128]). Let us call this number as $X$. Add an edge of weight $1$ from $A$ to $X$. Build the complete graph based on all possible transitions. Make sure that this graph will be directed one as transforming from $A$ to $X$ might not be the same as transforming from $X$ to $A$ due to the last operation which adds $1$ to the result. Once, we have the directed graph, we can simply perform any all pair shortest path algorithm like BFS, Floyd Warshall (or Dynamic Programming as a graph is directed) and precalculate the answer for all possible cases. Once, the answers are precalculated, each test case can be answered in constant complexity. For more details, one can refer to the editorialist solution below.

The maximum number of edges from a number $A$ emerging out will be $7! = 5040$ in the worst case, but in practice, it will be quite less. The number of vertices in the graph will be $128$. Using Floyd Warshall algorithm the precomputation can be achieved in $O(128^3)$, i.e. $O(A^3)$. This is enough to solve this subtask.

Subtask 2: A, B ≤ ${10}^{18}$

The constraints in this subtask are quite large and the number of test cases also suggest we need a logarithmic approach. This leads us to write $A$ and $B$ in binary representation and finding some observations to proceed with the solution.

Let us first simplify the approach by trying to convert $A$ to $(B-1)$ as in the end $1$ would be added as part of the last operation.

We can see that in one step we can shuffle the digits of $A$ in such a manner that an extra $1$ is introduced in the binary representation of the newly formed number. This can be done by simply shuffling the digits to contain binary digit $1$ from the ${2}^{nd}$ position. For example: Let $A = 3$. In binary representation $A = 011$. We can shuffle the digits as $A' = 110$. On adding $1$, we get $X = 111$, i.e. $X = 7$. Thus, we can introduce a binary digit $1$ in one step.

Also, we can decrease any number of binary digit $1$ from $A$. This can be done by easily placing the required in the number of $1$ in towards the end, followed by a $0$ and then placing the digits in any order we like. For example: Let $A = 13$, i.e. $A = 1101$ in binary representation. Say we want to decrease one binary digit $1$, we can arrange the digits as $A' = 1011$. On adding $1$, we get $X = 1100$. If we wanted to decrease two binary digit $1$, we can arrange the digits as $A' = 0111$. On adding $1$, we get $X = 1000$. Thus, we decrease any number of binary digit $1$ in one step.

With the above 2 scenarios, the following is the algorithm-

  1. Find the number of ones in the binary representation of $A$ and $(B - 1)$. Let us denote then by $OA$ and $OB$
  2. If $OA > OB$, then we can achieve the operation in $2$ steps. First decreasing the number of ones in the first step and then rearranging the digits in another step.
  3. If $OA <= OB$, then we need $(OB - OA)$ steps to first make the number of ones equal (see decrease operation takes place at one step each). Finally, we can arrange the digits to achieve the desired number.

The only corner case is as follows:

  1. If $B$ is $0$ then, we can't achieve the desired state whatever the value of $A$ is. Since we are adding $1$ in the last step we are guaranteed to have atleast one binary digit $1$ in binary representation. Thus the answer for this case is $-1$.
  2. If $B$ is $1$ then, we can achieve the desired state only if $A = 0$, in one step. In another case, it is impossible as even though decreasing the number of binary digit $1$, the end result would be a number greater than $1$. So the answer is $1$ if $A = 0$, else $-1$.

The number of ones in binary representation can be calculated using the below pseudo-code:


    def count_ones(integer x):
        ones = 0
        while x > 0:
            if x % 2 == 1:
                ones += 1
            x /= 2
        return ones

Feel free to share your approach, if it was somewhat different.

Time Complexity

$O(\log{A} + \log{B})$ per test case.

Space Complexity

$O(1)$

AUTHOR'S AND TESTER'S SOLUTIONS:

Author's solution can be found here. (It will pass subtask 1 only and uses dynammic programming approach)

Tester's solution can be found here.

Editorialist's solution for subtask 1 can be found here.

Editorialist's solution for full problem can be found here.

WA in MARBLES

If there is + or -sign in ahead of a variable, then what does it means??

New Server

We at Blancode have take an initiative to bring all the coders from the world under one roof.

A Discord community to share , discuss , learn and grow.

here is link :https://discord.gg/3886gu

Thanks to @puneetrai04 for making this server.

Note:we have strict rules if any one will try to ask any type of problem on server he/she will be thrown out of it

Viewing all 39796 articles
Browse latest View live


<script src="https://jsc.adskeeper.com/r/s/rssing.com.1596347.js" async> </script>